Method of transmitting data from an ultrasound system to a data processing device

Abstract

The present disclosure relates to a method for transmitting data from an ultrasonic system to a data processing device. In a method for transmitting data from an ultrasonic system having at least one ultrasonic transmitter and an ultrasonic receiver to a data processing device via a vehicle data bus, a predefined signal profile feature is extracted from an echo signal received from the at least one ultrasonic receiver of the ultrasonic system. Echo signal data representing the signal profile feature extracted from the echo signal is created. The echo signal data is transmitted from the ultrasonic system to the data processing device via the vehicle data bus.

Description

[0001] This patent application is a divisional application 202410041314.X of Chinese invention patent application No. 201880035869.6, entitled "Method for transmitting data from an ultrasonic system to a data processing device via a vehicle data bus", which entered the national phase of the PCT international application filed on May 16, 2018, with application number PCT / EP2018 / 062808. Technical Field

[0002] This invention relates to a method for transmitting data from an ultrasonic system having at least one ultrasonic transmitter and an ultrasonic receiver to a data processing device via a vehicle data bus (a unidirectional or bidirectional single-wire, double-wire, or more-wire data bus, which may be differential). In particular, this invention relates to a method for classifying echo signals from an ultrasonic system in a vehicle for data compression and transmitting the compressed data from the ultrasonic system to the data processing device. Background Technology

[0003] Ultrasonic systems have been used in vehicles for environmental identification for some time. In this system, at least one ultrasonic transmitter emits an ultrasonic burst signal, which is received by at least one ultrasonic receiver after being reflected by an obstacle (typically an object). The ultrasonic transmitter / receiver primarily employs a so-called ultrasonic transducer, which functions as a transmitter in the first phase of a polling interval and as an ultrasonic receiver in a subsequent second phase of the polling interval.

[0004] In recent years, the demand for identifying obstacles or objects in a vehicle environment using ultrasonic systems has steadily increased. While in the past it may have been sufficient to know that an obstacle is a certain distance from the vehicle, efforts are now being made to reconstruct the types of obstacles in the vehicle environment based on echo signal variation curves.

[0005] However, this increases the amount of data that needs to be transmitted between the vehicle's ultrasonic system and data processing equipment. However, the data buses conventionally used in vehicles, especially for cost reasons, have only a limited maximum data transfer rate.

[0006] Therefore, the focus has shifted to reducing the amount of data to be transmitted. This is sometimes accomplished through obstacle object recognition (with corresponding confidence information regarding the reliability of obstacle recognition), as described, for example, in DE 10 2008 042640A1. Other examples of ultrasound systems with the potential to reduce data transmission can be found in DE 10 2005 024 716 A1 and DE 10 2012 207 164 A1.

[0007] It is desirable to increasingly transmit actual measurement signals from ultrasonic sensors to a central computer system, where this data, along with data from other ultrasonic sensor systems and / or other types of sensor systems (e.g., radar systems), is further processed into a so-called environmental map through sensor fusion. Therefore, it is desirable to perform object recognition not within the ultrasonic sensor system itself, but first through this sensor fusion within the computer system, to avoid data loss, thereby reducing the probability of erroneous information and consequently incorrect decisions, and mitigating the risk of accidents. However, at the same time, the transmission bandwidth of the available sensor data bus is limited. Replacement of sensor data buses should be avoided, as they have already proven their value in the field. Therefore, it is desirable not to increase the amount of data to be transmitted. In short: the information content of the data and its relevance to obstacle recognition (i.e., object recognition) later running in the computer system must be increased, without excessively increasing the data rate, or better yet, without increasing the data rate at all. On the contrary, it is preferable to even reduce the data rate requirements to allow for the data rate capacity used to transmit the status data and self-test information of the ultrasonic sensor system to the computer system, which is mandatory in the context of Functional Safety (FuSi). The invention presented in this paper solves this problem.

[0008] Various methods for processing ultrasonic sensor signals are known in the prior art.

[0009] For example, WO-A-2012 / 016 834 discloses a method for evaluating echo signals used in vehicle environment detection. This document proposes transmitting a measurement signal with a pre-given encoding and shape, and searching for and determining the components of the measurement signal in the received signal by means of correlation with the measurement signal. A threshold is then used to evaluate the correlation level (rather than the level of the echo signal envelope).

[0010] DE-A-4 433 957 discloses periodically radiating ultrasonic pulses for obstacle identification and inferring the location of obstacles from the propagation time, wherein residual echoes that are correlated in multiple measurement cycles are amplified in time during the assessment, while uncorrelated residual echoes are suppressed.

[0011] DE-A-10 2012 015 967 discloses a method for decoding a received signal received by an ultrasonic sensor of a motor vehicle, wherein the transmitted signal of the ultrasonic sensor is transmitted in an encoded manner, and the received signal is correlated with a reference signal for decoding, wherein before correlating the received signal with the reference signal, the frequency shift of the received signal relative to the transmitted signal is determined, and the received signal is correlated with the transmitted signal, which serves as a reference signal, having shifted by the determined frequency shift in its frequency direction, wherein the received signal is subjected to a Fourier transform for determining the frequency shift, and the frequency shift is determined based on the result of the Fourier transform.

[0012] DE-A-10 2011 085 286 discloses a method for detecting the environment around a vehicle using ultrasound, wherein ultrasonic pulses are emitted and ultrasonic echoes reflected by an object are detected, and the detection range is subdivided into at least two distance ranges, wherein ultrasonic pulses used for the detection within the respective distance ranges are emitted independently of each other and encoded with different frequencies.

[0013] WO-A-2014 / 108300 discloses an apparatus and method for detecting the environment by means of a signal converter and an evaluation unit, wherein a signal received from the environment, having a first impulse response length at a first moment during a measurement period and a larger second impulse response length at a later moment within the same measurement period, is filtered depending on the propagation time.

[0014] However, the technical teachings of the aforementioned patents are all derived from the idea that the identification of obstacles (objects) detected by the ultrasonic sensor is already performed within the ultrasonic sensor itself, and then the object data is transmitted only after the object has been identified. However, in this case, the synergistic effect when using multiple ultrasonic transmitters is lost.

[0015] DE-A-197 07 651, DE-A-10 2010 044 993, DE-A-10 2012 200 017, DE-A-102013 015402 and EP-A-2 455 779 disclose various methods for (partially) processing signals from ultrasonic sensors and subsequently transmitting those signals. Summary of the Invention

[0016] The objective of this invention is to further improve the level of data compression in a vehicle's ultrasonic system without compromising the reliability of obstacle and obstacle type identification. Another objective is to further reduce the bus bandwidth required to transmit measurement data from the ultrasonic sensor system to the computer system, or to improve the efficiency of data transmission.

[0017] To address these tasks, this invention proposes a method for transmitting data via a vehicle data bus from an ultrasonic system having at least one ultrasonic transmitter and an ultrasonic receiver to a data processing device, wherein—a pre-defined signal variation curve feature is extracted from the echo signal received from at least one ultrasonic receiver of the ultrasonic system.

[0018] - Identify the signal change curve objects in the echo signal based on a set of extracted signal change curve features.

[0019] - Assign each identified signal variation curve object to one of a plurality of pre-given signal variation curve object categories, each of which is specified by an identifier.

[0020] - For each identified signal variation curve object, at least one object parameter describing the signal variation curve object is determined, wherein the at least one object parameter is the occurrence time of the signal variation curve object relative to a reference time, the time range of the signal variation curve object, the time distance from a preceding or subsequent signal variation curve object in the echo signal, and / or the size, height, and particularly the maximum height of the signal variation curve object, the moment of the height of the signal variation curve object within its time range, and particularly the moment of the maximum height, and / or the size of the area of ​​the echo signal segment belonging to the signal variation curve object, and particularly the size of the portion of the area of ​​the echo signal segment belonging to the signal variation curve object that is above a threshold or above a threshold signal variation curve, and wherein the echo signal segment belonging to the signal variation curve object can be reconstructed from an identifier for the signal variation curve object category and one or more object parameters determined for the signal variation curve object, and

[0021] - The ultrasonic system transmits the identifier and one or more object parameters via the vehicle data bus for the identified signal change curve object, as echo signal segment data representing the echo signal segment of the signal change curve object, to identify obstacles and / or the distance of the obstacle to at least one ultrasonic receiver or one of the ultrasonic receivers of the ultrasonic system.

[0022] In this context, the basic idea of ​​the invention includes identifying potential correlation structures in the measurement signal and compressing the measurement signal by transmitting only a small amount of data about the identified potential correlation structures, rather than the measurement signal itself. If necessary, after reconstructing the measurement signal into a reconstructed measurement signal in the computer system, the actual identification of the object, such as an obstacle in a parking process, is performed. Typically, in this computer system, multiple compressed measurement signals from multiple ultrasonic sensor systems are combined (and decompressed if necessary). Therefore, the invention specifically relates to compressing data by identifying structures in the measurement signal.

[0023] Therefore, according to the proposal of the present invention, the echo signal is examined to determine whether there are definite, pre-given signal variation curve characteristics so that data representing these signal variation curve characteristics can be subsequently transmitted, wherein further conclusions can then be drawn from these echo signal data in the vehicle's data processing device. For example, the echo signal can be regenerated or, if the same signal variation curve characteristics appearing at staggered times when necessary are repeatedly identified, obstacles, the type of obstacles, changes in the distance from the vehicle to the obstacles, etc., can be inferred. In this case, it is important to shift the task of identifying obstacles from the ultrasonic system to the data processing device, which reduces the "intelligence" requirements on the components of the ultrasonic system, thereby consequently reducing the amount of data to be transmitted from the ultrasonic system to the data processing device, since the echo signal data is actually analyzed in the data processing device to determine which obstacle is in the vehicle's environment and how the obstacle changes within the vehicle's environment (especially regarding the distance from the obstacle to the vehicle).

[0024] According to the present invention, the received echo signal is checked to determine whether it contains a defined predefined signal variation curve feature. One or more of these signal variation curve features define a specific signal variation curve, which is hereinafter referred to as a signal variation curve object. Multiple object categories exist, and the identified signal variation curve object is now assigned to one of these object categories. Each object category is equipped with an identifier. Furthermore, according to the present invention, at least one object parameter is determined, which further describes or characterizes the identified signal variation curve object. Possible object parameters include, for example:

[0025] - The occurrence time of the signal change curve object relative to the reference time,

[0026] -The time range of the signal change curve object.

[0027] - The time distance from the preceding or subsequent signal change curve object in the echo signal, and / or - the size, height, and particularly the maximum height of the signal change curve object.

[0028] -The signal change curve object's height at moments within its time range, and particularly the moment of maximum height, and / or

[0029] or

[0030] - The size of the area (integral) of the echo signal segment belonging to the object of the signal change curve, and - in particular, the size of the portion of the area (integral) of the echo signal segment belonging to the object of the signal change curve that is above the threshold or above the threshold signal change curve.

[0031] The echo signal segment belonging to the signal variation curve object can be reconstructed in the data processing device using an identifier for the category of the signal variation curve object and one or more object parameters determined for the signal variation curve object. In this way, echo signal segments based on the identified signal variation curve object can now be transmitted to the data processing device in a compressed manner (i.e., using significantly less data), the echo signal segment itself being transmitted to the data processing device via its (digital) sampled values. According to the invention, the so-called echo signal segment data is transmitted, which includes at least an identifier for the category of the signal variation curve object and at least one object parameter describing the signal variation curve object. Other data can also be transmitted together if necessary, as will be discussed later.

[0032] In a suitable embodiment of the invention, the ultrasonic system is provided to have a plurality of ultrasonic transmitters and a plurality of ultrasonic receivers, and to transmit echo signal segment data representing signal change curve objects identified from a plurality of echo signals received in a pre-given time window to the data processing device via the vehicle data bus for the purpose of identifying obstacles and / or the distance of obstacles to at least one ultrasonic receiver or one of the ultrasonic receivers of the ultrasonic system.

[0033] As described above, in addition to the identifier of the signal change curve object category and the one or more object parameters, other data can be transmitted as echo signal segment data. Advantageously, in this case, it can be specified that, in addition to the echo signal segment data, confidence values ​​assigned to the corresponding identified signal change curve objects are also transmitted from the ultrasonic measuring device to the data processing device via the vehicle data bus.

[0034] According to the present invention, the search for signal change curve features in the echo signal is suitably a pre-given combination of one or more of the following: local extrema and occurrence times of the echo signal above or below a threshold; absolute extrema of the echo signal above or below a threshold, along with their occurrence times; absolute extrema of the echo signal above or below a threshold, along with their occurrence times; saddle points of the echo signal above or below a threshold, along with their occurrence times; exceeding a threshold or the threshold or exceeding a threshold signal or the threshold signal along with their exceeding time when the signal level of the echo signal becomes larger; and / or falling below a threshold or the threshold or below a threshold signal or the threshold signal along with their falling time when the signal level of the echo signal becomes smaller; or a pre-given combination of one or more of the above signal change curve features occurring sequentially in chronological order.

[0035] Preferably, the signal variation curve characteristics or the object parameters may further include: whether, when, and how the received echo signal is modulated, more precisely, for example, at a monotonically increasing or strictly monotonically increasing frequency (positive linear frequency modulation), for example, at a monotonically decreasing or strictly monotonically decreasing frequency (negative linear frequency modulation), or for example, at a constant frequency (non-linear frequency modulation). In this context, reference is made to DE-B-10 2017 123 049, DE-B-10 2017 123 051, DE-B-10 2017 123 052, and DE-B-10 2017 123 050, the contents of which are incorporated herein by reference into the subject matter of this invention.

[0036] Other frequency modulation methods, or other modulation methods in general, can also be applied. In this paper, modulation of the ultrasonic signal is provided, for example, through various types of coding. Anti-Doppler coding is advantageously employed. Generally speaking, the coding can be understood as a pre-given wavelet, the time average of which may in particular be non-zero.

[0037] In another advantageous embodiment of the invention, the ultrasonic system comprises multiple ultrasonic transmitters that transmit ultrasonic signals with different modulations. The echo signal segment data transmitted by the ultrasonic receiver further includes modulation identifiers of the received echo signals, and, based on the modulation identifiers, the data processing device determines from which ultrasonic transmitter the ultrasonic transmitted signal, which has been received as an echo signal or echo signal component, is transmitted as an echo signal or echo signal component, and the ultrasonic receiver transmits echo signal segment data about the echo signal or echo signal component to the data processing device.

[0038] The advantage of the method according to the invention lies particularly in that the ultrasonic system has multiple ultrasonic transmitters and multiple ultrasonic receivers, wherein echo signal data representing signal variation curve features extracted separately from multiple echo signals received within a pre-defined time window is transmitted to the data processing device via the vehicle data bus. The data processing device then receives echo signal data describing the echo signals received by the multiple ultrasonic receivers or the signal variation curve features detected in these echo signals within a pre-defined measurement time window. For example, if adjacently arranged ultrasonic receivers receive similar echo signals, these can be used for obstacle classification. It has been found that determining the type of obstacle based on multiple compressed echo signals from multiple ultrasonic receivers is significantly more efficient than first individually examining each echo signal from each ultrasonic receiver to infer the type of obstacle and then comparing the obtained knowledge about the obstacle type with each other if necessary.

[0039] Therefore, in the method according to the invention, the feature vector that generates the echo signal can be described as containing the characteristics of the signal variation curve and the corresponding time in the variation curve of the echo signal. Thus, the feature vector describes the various segments of the echo signal and the events within the echo signal, without yet performing obstacle recognition, etc.

[0040] According to the invention, an envelope signal may be formed from the echo signal, which is a part of the feature vector, or a part of the envelope signal may be a component of the feature vector. It is also possible to convolve the received echo signal with the associated ultrasonic transmission signal, i.e., with the ultrasonic signal received as an echo signal after reflection, thereby forming a correlated signal whose features may be a part of the feature vector.

[0041] The echo signal data describing the characteristics of the signal variation curve can advantageously include parametric data. In this case, the parametric data is preferably a timestamp indicating when the characteristic or a feature appears in the echo signal variation curve. The time reference (i.e., reference time) of the timestamp is arbitrary, but is predefined for a system consisting of an ultrasound system and data processing equipment. Another parameter may be the amplitude and / or extension of the segment of the echo signal describing the characteristics of the signal variation curve. It should be noted that the term "amplitude" in the following text should be understood generally and, for example, for the (current) signal level and / or the peak value of the signal.

[0042] On the one hand, the compression of data to be transmitted via the data bus between the ultrasound system and the data processing device, implemented according to the present invention, reduces the data bus load, thereby reducing the stringency of EMV requirements. On the other hand, idle data bus capacity is provided during the reception time of the echo signal, which can then be used to transmit control commands from the data processing device to the ultrasound system and to transmit status information and other data of the ultrasound system to the data processing device. In this case, it is advantageous to prioritize the data to be transmitted, ensuring that security-related data is transmitted first, thereby avoiding unnecessary downtime for echo signal data.

[0043] According to an advantageous embodiment of the invention, the ultrasonic system may include a plurality of ultrasonic transmitters and a plurality of ultrasonic receivers, and transmit echo signal data, representing the characteristics of signal change curves extracted from a plurality of echo signals received within a pre-given time window, to the data processing device via the vehicle data bus.

[0044] According to an advantageous embodiment of the invention, in addition to the echo signal data, confidence values ​​assigned to the corresponding extracted signal change curve features are also transmitted from the ultrasonic measuring device to the data processing device via the vehicle data bus.

[0045] According to another advantageous embodiment of the invention, the signal variation curve features can be defined as the simultaneous occurrence of local extrema of the echo signal, the simultaneous occurrence of absolute extrema of the echo signal, the simultaneous occurrence of saddle points of the echo signal, threshold overshoot occurring when the signal level of the echo signal increases along with the overshoot time, and / or below-threshold and below-threshold occurring when the signal level of the echo signal decreases. However, the signal variation curve features can also be a temporal sequence (with a pre-defined order) of multiple of the aforementioned signal variation curve features.

[0046] Furthermore, according to an advantageous embodiment of the invention, the signal variation curve characteristics may further include: whether, when, and how the received echo signal is modulated, more specifically, for example, at a monotonically increasing frequency (positive linear frequency modulation), for example, at a monotonically decreasing frequency (negative linear frequency modulation), or for example, at a constant frequency (non-linear frequency modulation).

[0047] According to another advantageous embodiment of the invention, the ultrasonic system may be configured such that a plurality of ultrasonic transmitters transmit modulated ultrasonic signals, and the source of which ultrasonic transmitter transmitted the ultrasonic signal as an echo signal or an echo signal component received by the ultrasonic receiver may be determined based on the modulation of the echo signal.

[0048] Therefore, this invention provides a method for transmitting sensor data from a sensor to a computer system. Particularly suitable is the use of this method in vehicles to transmit data of ultrasonic received signals from an ultrasonic receiver (hereinafter referred to as an ultrasonic sensor) to a control device (as a computer system or data processing device). According to a variation of the invention, an ultrasonic burst pulse is first generated and emitted into free space, typically in the environment of a vehicle. In this case, the ultrasonic burst pulse consists of multiple sound pulses that follow each other at ultrasonic frequencies. The ultrasonic burst pulse is formed by the oscillation and subsequent cessation of a mechanical oscillator. The emitted ultrasonic burst is then reflected by an object (e.g., an obstacle) and received as an ultrasonic signal by a receiver, and converted into a received signal. Particularly preferred is that the ultrasonic transmitter and ultrasonic receiver are identical, and thus referred to hereinafter as a transducer, which operates alternately as both an ultrasonic transmitter and an ultrasonic receiver. However, the principles explained below can also be applied to separate receivers and transmitters.

[0049] The ultrasonic sensor is assigned a signal processing unit that analyzes the received signal for pre-defined or pre-specified signal variation curve characteristics to minimize the amount of data required to describe the echo signal variation curve. Therefore, the ultrasonic sensor's signal processing unit can be said to compress the received signal to produce compressed data, i.e., characteristic echo signal data. This information is then transmitted to the computer system in a compressed manner. This data transmission minimizes EMV load and allows the ultrasonic sensor's status data for system fault identification to be transmitted to the computer system at regular intervals via the data bus between the ultrasonic sensor and the computer system.

[0050] It has proven advantageous to prioritize data transmissions via the data bus. In this case, notifying the computer system of safety-critical faults in the sensor (exemplarily, the ultrasonic sensor herein) has the highest priority, as these faults have a high probability of affecting the validity of the ultrasonic sensor's measurement data. This data is sent from the ultrasonic system to the computer system. Requesting the computer system to perform a safety-related self-test has the second highest priority. Such instructions are sent from the computer system to the ultrasonic system. Data from the ultrasonic sensor itself has the third highest priority, as additional latency is not permitted. All other data has a lower priority for transmission via the data bus.

[0051] Particularly advantageous is a method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle (comprising transmitting an ultrasonic burst pulse having a start 57 and an end 56, and receiving an ultrasonic signal for at least a reception time T starting from the end 56 of the ultrasonic burst pulse). E The system (including the formation of a received signal and the transmission of compressed data to the computer system via a data bus, particularly a single-wire data bus) is configured such that data transmission 54 from the sensor to the computer system begins with a start command 53 from the computer system to the sensor via the data bus and before the end 56 of transmitting the ultrasonic burst pulse, or after the start command 53 from the computer system to the sensor via the data bus and before the start 57 of transmitting the ultrasonic burst pulse. Then, transmission 54 continues periodically after the start command 53 until the end of data transmission 58. This end of data transmission 58 is then time-time-located at reception time T. E After it ended.

[0052] As a first step in data compression, another variation of the proposed method specifies the formation of a feature vector signal from the received signal. Such a feature vector signal can include multiple analog and digital data signals. Therefore, the feature vector signal represents a more or less complex data / signal structure; in its simplest case, the feature vector signal can be understood as a vector signal composed of multiple sub-signals.

[0053] For example, it might be meaningful to form the first-order and / or higher-order time derivatives of the received signal or to form single or multiple integrals of the received signal, which are then sub-signals within the eigenvector signal.

[0054] An envelope signal can also be formed, which is a sub-signal within the feature vector signal.

[0055] Furthermore, it may be meaningful to convolve the received signal with the emitted ultrasonic signal to form a correlation signal, which could then be a sub-signal within the eigenvector signal. In this case, on the one hand, this signal could be used as the emitted ultrasonic signal that was used to control the transmitter's actuator, or on the other hand, for example, as a signal that was measured on the transmitter and thus better corresponds to the actual radiated sound wave.

[0056] Finally, it may be meaningful to detect the presence of predetermined signal variation curve features using a matched filter and to form matched filter signals for corresponding signal variation curve features among some of these predetermined features. In this case, the matched filter should be understood as a filter that optimizes the signal-to-noise ratio (SNR). Predefined signal variation curve features should be identified in the interfered echo signal. The terms "correlation filter," "signal matched filter (SAF)," or simply "matched filter" are also frequently used in this literature. The matched filter is used to optimally determine the presence (detection) of the amplitude and / or location of a known signal shape, i.e., the presence of predetermined signal variation curve features, and also in the presence of interference (parameter estimation), such as signals from other ultrasonic transmitters, and / or in the presence of ground echoes.

[0057] Then, the matched filter signal is preferably a sub-signal within the eigenvector signal.

[0058] Specific events can be notified in other sub-signals of the characteristic vector signal. In the sense of this invention, these events are also signal variation curve features. Therefore, signal variation curve features include not only specific signal shapes such as rectangular pulses, wavelets, or wave trains, but also prominent points in the variation curve of the received signal and / or in the variation curve of the signal derived from the received signal, such as envelope signals that can be obtained, for example, by filtering from the received signal.

[0059] Another signal, which may be a sub-signal of the feature vector signal, can, for example, detect whether the envelope of the received signal, i.e., the envelope signal, intersects with a pre-given first threshold.

[0060] Another signal, which may be a sub-signal of the feature vector signal, may, for example, detect whether the envelope of the received signal, i.e., the envelope signal, rises and intersects with a pre-given second threshold, which may be the same as the first threshold.

[0061] Another signal, which may be a sub-signal of the feature vector signal, may, for example, detect whether the envelope of the received signal, i.e., the envelope signal, intersects with a pre-given third threshold, which may be the same as the first threshold.

[0062] Another signal, which may be a sub-signal of the feature vector signal, may, for example, detect whether the envelope of the received signal, i.e., the envelope signal, has a maximum value greater than a fourth threshold, which may be the same as the threshold mentioned above.

[0063] Another signal, which may be a sub-signal of the feature vector signal, can, for example, detect whether the envelope of the received signal, i.e., the envelope signal, has a minimum value greater than a fifth threshold, which may be the same as the aforementioned threshold. In this case, it is preferable to evaluate whether at least one preceding maximum value of the envelope has a minimum distance to the minimum value to avoid detecting noise. Other filtering may be considered at this time. It can also be checked whether the time interval between the minimum value and the preceding maximum value is greater than a first time minimum distance. The satisfaction of these conditions respectively sets a flag or signal, which is itself preferably a sub-signal of the feature vector signal.

[0064] Similarly, it should be checked in a similar manner whether the temporal distance and amplitude-measured distance of other signal variation curve characteristics meet certain authenticity requirements, such as minimum temporal distance and / or minimum amplitude distance. Other analog, binary, or digital sub-signals can also be derived from these checks, thereby further increasing the dimensionality of the eigenvector signal.

[0065] If necessary, the eigenvector signal can be converted into a salient eigenvector signal during the saliency enhancement stage. However, practice has shown that this is not necessary, at least for current requirements.

[0066] According to a variation of the method of the present invention, based on the feature vector signal or the salient feature vector signal, signal change curve features are identified within the received signal and the signal change curve features are classified into identified signal change curve feature categories.

[0067] If, for example, the amplitude of the output signal of the matched filter, and therefore the amplitude of the sub-signals of the characteristic vector signal, is higher than a sixth threshold specific to the matched filter if necessary, the signal variation curve feature for which the matched filter was designed can be considered identified. In this case, other parameters are preferably also considered. For example, if an ultrasonic burst pulse with an increasing frequency (referred to as positive linear frequency modulation) is transmitted during the burst pulse, an echo with such modulation characteristics is also expected. If the signal shape of the envelope (e.g., the triangular signal shape of the envelope) locally matches the expected signal shape in time, but the modulation characteristics are inconsistent, then it is not an echo from the transmitter, but rather an interference signal that may come from another ultrasonic transmitter or from beyond the range of operation. In this respect, the system can then distinguish between the intrinsic echo and the extrinsic echo, thereby assigning the same signal shape to two different signal variation curve features, namely the intrinsic echo and the extrinsic echo. In this case, the transmission of the intrinsic echo is preferably preferred over the transmission of the extrinsic echo, because the former is generally related to security, while the latter is generally not related to security.

[0068] Typically, at least one signal change curve feature parameter is assigned to each identified signal change curve feature, or at least one signal change curve feature parameter is determined for that signal change curve feature. Preferably, this is a timestamp indicating when the feature appears in the echo signal. In this case, the timestamp may, for example, relate to the time start point of the signal change curve feature in the received signal, the time end point of the signal change curve feature, or the time position of the time centroid of the signal change curve feature, etc. Other signal change curve feature parameters such as amplitude, extension, etc., may also be considered. Thus, in a variation of the proposed method, at least one assigned signal change curve feature parameter having at least one identified signal change curve feature category is transmitted, which is a time value and indicates a time position suitable from which the time since the transmission of the previous ultrasonic burst pulse can be inferred. Preferably, the determined distance of objects (e.g., obstacles) around the vehicle environment is then determined based on the time value thus determined and transmitted.

[0069] Finally, the identified signal change curve feature categories are transmitted first, preferably along with the assigned signal change curve feature parameters. This transmission can also be performed using more complex data structures. For example, it could be considered to first transmit the timestamps of identified safety-related signal change curve features (e.g., identified obstacles), and then transmit the identified signal change curve feature categories of safety-related signal objects. This further reduces latency.

[0070] According to a variation of the method of the present invention, one variation includes at least determining a chirp-up value as an assigned signal variation curve characteristic parameter, said assigned signal variation curve characteristic parameter indicating whether the identified signal variation curve characteristic is an echo of an ultrasonic transmitted burst pulse having positive chirp-up, negative chirp-up, or nonlinear chirp-up characteristics. "Positive chirp-up" refers to an increase in frequency within the received signal variation curve characteristic. "Negative chirp-down" refers to a decrease in frequency within the received signal variation curve characteristic. "Non-chirp" refers to a substantially constant frequency within the received signal variation curve characteristic.

[0071] According to a variation of the method of the invention, a confidence signal (confidence value Konfidenzwert) can also be formed, for example, by forming a correlation between a received signal or a signal derived from the received signal and a reference signal, the reference signal being, for example, the ultrasonic transmission signal or another anticipated wavelet. The confidence signal is then typically a sub-signal of the eigenvector signal.

[0072] In another variation of this method, a phase signal is also formed on this basis, which describes, for example, the phase shift of the received signal or a signal formed from the received signal (e.g., a confidence signal) relative to a reference signal (e.g., the ultrasonic transmission signal and / or another reference signal).

[0073] Similarly, in another variation of the proposed method, a phase position confidence signal can be formed by establishing a correlation between the phase signal or a signal derived from the phase signal and a reference signal, and the phase position confidence signal can be used as a sub-signal of the eigenvector signal.

[0074] Then, when evaluating the eigenvector signal, it is meaningful to compare the phase position confidence signal with one or more thresholds to generate a discretized phase position confidence signal, which itself can become part of the eigenvector signal.

[0075] In a variation of the proposed method, the evaluation of the feature vector signal and / or the salient feature vector signal can be performed such that one or more distance values ​​are formed between the feature vector signal and one or more prototype values ​​of the signal change curve features for identifiable signal change curve feature categories. Such distance values ​​can be Boolean values, binary values, discrete values, digital values, or analog values. Preferably, all distance values ​​are logically connected to each other in a nonlinear function. Thus, in the case of a positive linear frequency modulated (LFM) echo with a triangular shape expected, a received negative LFM echo with a triangular shape can be discarded. This discarding is a nonlinear process.

[0076] Conversely, the triangles in the received signal may form differently. This primarily involves the amplitude of the triangles in the received signal. If the amplitude in the received signal is large enough, then, for example, the matched filter assigned to the triangular signal provides a signal above a pre-given seventh threshold. Thus, in this case, for example, the signal change curve feature identified by the signal change curve feature category (triangular signal) can be assigned to the transcendental moment. In this case, the distance value between the feature vector signal and the prototype (here, the seventh threshold) is lower than one or more predetermined binary, digital, or analog distance values ​​(here, 0 = intersection).

[0077] In another variation of this method, at least one category of signal variation curve features is a wavelet, which is estimated and thus detected by an estimation device (e.g., a matched filter) and / or an estimation method (e.g., an estimation program running in a digital signal processor). The term "wavelet" refers to a function that can be used as the basis for continuous or discrete wavelet transforms. The word is a revival of the French "ondelette," meaning "wavelet," translated into Chinese partly literally ("onde" -> "wave") and partly phonetically ("-lette" -> "small"). The term "wavelet" was coined in the 1980s in geophysics (Jean Morlet, Alex Grossman) for functions that generalize the short-time Fourier transform, but since the late 1980s it has only been used in its currently common meaning. In the 1990s, a true wavelet boom ensued, thanks to Ingrid Daubechies' (1988) discovery of compact, continuous (differentiable to any order) and orthogonal wavelets, and the development of the Fast Wavelet Transform (FWT) algorithm by Stéphane Mallat and Yves Meyer (1989) using MultiResolution Analysis (MRA).

[0078] Unlike the sine and cosine functions of the Fourier transform, the most commonly used wavelets exhibit locality not only in the frequency spectrum but also in the time domain. Here, "locality" is understood in the sense of small dispersion. The probability density is the square of the normalized absolute value of the observed function or its Fourier transform. In this case, similar to Heisenberg's uncertainty principle, the product of the two variances is always greater than a constant. Due to this limitation, pioneering theories of discrete wavelet transforms emerged in function analysis: the Paley-Wiener theory (Raymond Paley, Norbert Wiener) and the Calderón-Zygmund theory (Alberto Calderón, Antoni Zygmund) corresponding to continuous wavelet transforms.

[0079] Although the integral of a wavelet function is always 0 in professional applications, wavelet functions are typically presented as outgoing (decrease) wavelets (i.e., 2 wavelets = ondelet = wavelet). However, for the purposes of this invention, wavelets with integrals other than 0 are also permitted. Rectangular and triangular wavelets are exemplified below.

[0080] Important examples of wavelets with zero integrals are the Haar wavelet (Alfred Haar 1909), the Daubechies wavelet named after Ingrid Daubechies (circa 1990), the Coiflet wavelet also constructed by Ingrid Daubechies, and the theoretically more important Meyer wavelet (Yves Meyer, circa 1988).

[0081] For wavelets existing in spaces of arbitrary dimensions, tensor products of one-dimensional wavelet bases are mostly used. Due to the fractal properties of the two scalar equations in the MRA, most wavelets have complex shapes, with most lacking closed shapes. This is particularly important because the eigenvector signals mentioned above are multidimensional, thus allowing the use of multidimensional wavelets for signal object recognition.

[0082] Therefore, a particular variation of the proposed method is to use multidimensional wavelets with more than two dimensions for signal object recognition. Specifically, it is suggested to use appropriate matched filters to recognize such wavelets with more than two dimensions, so as to supplement the feature vector signal with other sub-signals suitable for the recognition if necessary.

[0083] A particularly suitable wavelet, especially for the envelope signal, is a triangular wavelet. This triangular wavelet is characterized by its start time, a wavelet amplitude that linearly increases in time to its maximum amplitude after the start time, and a wavelet amplitude that linearly decreases in time to one end of the triangular wavelet after its maximum amplitude.

[0084] Another particularly suitable wavelet is the rectangular wavelet, which, in the context of this invention, also includes the trapezoidal wavelet. The rectangular wavelet is characterized by the following: at the start time, the wavelet amplitude increases with a first time slope until the first stationary time. After the first stationary time, the wavelet amplitude continues at a second slope until the second stationary time. After the second stationary time, the wavelet amplitude decreases with a third time slope until the end of the time interval. In this case, the absolute value of the second time slope is less than 10% of the absolute value of the first time slope and less than 10% of the absolute value of the third time slope.

[0085] Instead of the wavelets described above, other two-dimensional wavelets, such as the sinusoidal half-wave wavelet, can also be used, which also have non-zero integrals.

[0086] When using wavelets, it is recommended to use the time shift of the wavelet involved in the signal change curve feature as a signal change curve feature parameter, for example, by correlating and / or detecting the moment when the output level of a matched filter suitable for detecting the wavelet in question exceeds the identified signal change curve feature or a predefined threshold of the wavelet. Preferably, the envelope and / or phase signal and / or confidence signal of the received signal are evaluated.

[0087] Another possible characteristic parameter of the signal variation curve that can be determined is the time compression or expansion of the wavelet involved in the identified signal variation curve feature. Similarly, the amplitude of the wavelet of the identified signal variation curve feature can be determined.

[0088] In the development of the proposed method disclosed herein, it has been recognized that it is advantageous to transmit data of the identified signal variation curve features of the very fast-arriving echo from the sensor to the computer system first, and then transmit subsequent data of the subsequently identified signal variation curve features. Preferably, in this case, at least the category of the identified signal variation curve feature and a timestamp should always be transmitted, the timestamp preferably indicating when the signal variation curve feature re-arrives at the sensor. Within the scope of the identification process, scores can be assigned to different signal variation curve features considered for the segment of the received signal, these scores indicating what probability is assigned to the presence of the signal variation curve feature according to the estimation algorithm used. In the simplest case, such scores are binary. However, preferably they are complex numbers, real numbers, or integers. If multiple signal variation curve features have high score values, it is meaningful in some cases to also transmit data of the identified signal variation curve features with lower score values. In order for the computer system to process correctly, in this case, not only the data of the identified signal variation curve features and the timestamp for the corresponding signal variation curve feature should be transmitted, but also the determined score values ​​should be transmitted. Therefore, in this case, a list of hypotheses consisting of the identified signal change curve features, their time positions, and additional assigned scores is transmitted to the computer system.

[0089] Preferably, data of the identified signal change curve feature categories and the data assigned to them (e.g., the timestamp and score of the corresponding identified signal change curve feature category) are transmitted according to the FIFO principle, i.e., the assigned signal change curve feature parameters. This ensures that data of the reflection closest to the object is always transmitted first, and thus the safety-critical situation of the vehicle-obstacle collision is handled according to probability priority.

[0090] In addition to transmitting measurement data, the fault status of the sensor can also be transmitted. If the sensor is determined to be defective by a self-testing device and previously transmitted data may potentially contain errors, this can also be reported at the receiving time T. E This occurs during the process. This ensures that the computer system can acquire knowledge about changes in the measurement data assessment as early as possible, and can discard or process these changes differently. This is particularly important for emergency braking systems, as emergency braking is a safety-critical intervention that is only permitted if the underlying data has a corresponding confidence value. Therefore, in contrast, the transmission of the measurement data, i.e., the transmission of data on identified signal change curve characteristic categories and / or the transmission of an assigned signal change curve characteristic parameter, is postponed and thus given a lower priority. Of course, if a sensor malfunctions, transmission can be considered to be suspended. However, in some cases, it appears that a malfunction may have occurred, but this is uncertain. In such cases, transmission is instructed to continue. Therefore, the transmission of sensor safety-critical faults is preferably determined to have a higher priority.

[0091] In addition to the wavelet with a zero integral value already described and signal segments with integral values ​​other than zero, additionally referred to herein as wavelets, a specific moment in the variation curve of the received signal can also be understood, in the sense of this invention, as a signal variation curve feature, which can be used for data compression and can be transmitted in place of the sampled values ​​of the received signal. These subsets of the possible set of signal variation curve features are hereinafter referred to as signal moments. Therefore, the signal moment, in the sense of this invention, is a special form of the signal variation curve feature.

[0092] The first possible signal change curve point and therefore the characteristic of the signal change curve is the intersection of the amplitude of the envelope signal 1 and the amplitude of the threshold signal SW in the rising direction.

[0093] The second possible signal change curve point and therefore the signal change curve feature is the intersection of the amplitude of the envelope signal 1 and the amplitude of the threshold signal SW in the falling direction.

[0094] The third possible signal change curve point and therefore the characteristic of the signal change curve is the maximum value of the amplitude of the envelope signal 1 above the amplitude of the threshold signal SW.

[0095] The fourth possible signal change curve point and therefore the signal change curve characteristic is the minimum value of the amplitude of the envelope signal 1 above the amplitude of the threshold signal SW.

[0096] It may be meaningful if necessary to use a threshold signal specific to the signal moment type for these four exemplary signal moment types and other types of signal moments.

[0097] The time series characteristics of signal variation curves are typically not arbitrary. For example, if a triangular wavelet is expected in an envelope signal 1 with sufficient amplitude, then, in addition to the corresponding minimum level at the output of a matched filter suitable for detecting such a triangular wavelet, time-related parameters exceeding that minimum level at the output of the matched filter can also be expected:

[0098] 1. The occurrence of the first possible signal change curve point where the amplitude of the envelope signal 1 intersects with the amplitude of the threshold signal SW in the rising direction, and the subsequent time sequence...

[0099] 2. The appearance of a third possible signal change curve point with the maximum amplitude of envelope signal 1 above the amplitude of threshold signal SW, and the subsequent time sequence...

[0100] 3. The appearance of a second possible signal change curve point where the amplitude of envelope signal 1 intersects with the amplitude of threshold signal SW in the descending direction.

[0101] Furthermore, exceeding the minimum level at the output of the matched filter is another example of a fifth possible signal change curve point, and therefore another possible signal change curve feature.

[0102] The resulting groupings and time series of the identified signal variation curve features can be identified, for example, by a Veterbi decoder, as predefined expected groupings or time series of signal variation curve features, and thus can represent the signal variation curve features again. Therefore, the sixth possible signal variation curve point, and thus the signal variation curve feature, is such a predefined grouping and / or time series of other signal variation curve features.

[0103] If a grouping or time series of such signal variation curve features is identified, it is preferable to perform the transmission of the identified combined signal variation curve feature category and at least one assigned signal variation curve feature parameter, rather than the transmission of individual signal variation curve features, as this saves a significant amount of data bus capacity. It is possible that both are transmitted. In this case, data of the signal variation curve feature category is transmitted, which is a predefined time series and / or grouping of other signal variation curve features. For compression purposes, it is advantageous not to transmit at least one signal variation curve feature category of at least one of these other signal variation curve features.

[0104] The temporal grouping of signal variation curve features exists particularly when the time intervals between these signal variation curve features do not exceed a predefined distance. In the example mentioned above, the signal propagation time in the matched filter should be considered. Typically, the matched filter is allowed to be slower than the comparator. Therefore, the transformation of the output signal of the matched filter should have a fixed temporal relationship with the occurrence time of the relevant signal.

[0105] Particularly preferably, data transmission in the vehicle is carried out via a bidirectional single-wire data bus. In this case, the return line is preferably ensured by the vehicle body. Sensor data is preferably transmitted to the computer system in a current-modulated manner. Data for controlling the sensor is preferably transmitted to the sensor via the computer system in a voltage-modulated manner. According to the invention, the use of a PSI5 data bus and / or a DSI3 data bus is particularly suitable for the data transmission. Furthermore, it has been recognized that it is particularly advantageous to transmit data to the computer system at a transmission rate of >200 kbit / s and to transmit data from the computer system to the at least one sensor at a transmission rate of >10 kbit / s, preferably 20 kbit / s. Furthermore, it has been recognized that the data transmission from the sensor to the computer system should be modulated onto the data bus using a transmit current, the current intensity of which should be less than 50 mA, preferably less than 5 mA, and preferably less than 2.5 mA. For these operating values, these buses must be adapted accordingly. However, the basic principle remains.

[0106] To perform the above method, a computer system is required that has a data interface to the data bus, preferably to the single-wire data bus, and that the computer system supports the decompression of such compressed data. However, typically the computer system does not perform complete decompression, but rather, for example, only evaluates the timestamp and the identified signal variation curve characteristics. The sensor required to perform one of the above methods has at least one transmitter and at least one receiver for generating a received signal, and they may also be combined as one or more transducers. Furthermore, the sensor has at least a device for processing and compressing the received signal and a data interface for transmitting data to the computer system via the data bus, preferably via the single-wire data bus. For the compression, the device for compression preferably has at least one of the following sub-devices: a matched filter, a comparator, a threshold signal generating device for generating one or more threshold signals SW, a comparator, a differentiator for forming a derivative, an integrator for forming an integral signal, other filters, an envelope former for generating an envelope signal from the received signal, and a correlation filter for comparing the received signal or a signal derived from the received signal with a reference signal. Attached Figure Description

[0107] The invention will now be explained in more detail with reference to embodiments and the accompanying drawings. Specifically:

[0108] Figure 1 The principle flow of signal compression and transmission is shown.

[0109] Figure 2 The principle process of signal compression and transmission is shown in more detail.

[0110] Figure 3 Part (a) shows the typical ultrasound echo signal and its routine assessment.

[0111] Figure 3 Part (b) shows a typical ultrasound echo signal and its evaluation, where amplitudes are transmitted together.

[0112] Figure 3 Section (c) shows the ultrasonic echo signal, which includes the linear frequency modulation direction.

[0113] Figure 3 Section (d) illustrates the situation where unidentified signal components are discarded. Figure 3 The signal object (triangular signal) identified in part (c) of the signal,

[0114] Figure 4a This illustrates a conventional transmission that is not subject to protection.

[0115] Figure 4b This illustrates the unprotected transmission of data analyzed after the complete reception of the ultrasonic echo.

[0116] Figure 4c This illustrates a protected transmission of compressed data, where, in this example, the symbols of the basic signal objects are essentially uncompressed according to existing technology.

[0117] Figure 5 This illustrates a protected transmission of compressed data, where, in this example, the symbol of the basic signal object is compressed into the symbol of the signal object.

[0118] Figure 6 The transmission of compressed data requiring protection is illustrated, in which, in this example, the symbols of the basic signal objects are compressed into symbols of the signal objects, and not only the envelope signal but also the confidence signal is evaluated.

[0119] As explained above, the prior art's technical teachings all stem from the idea that the identification of an object in front of a vehicle is performed within the ultrasonic sensor, and then the object data is transmitted only after the object has been identified. However, since the synergistic effect is lost when using multiple ultrasonic transmitters in this case, it has been recognized within the scope of this invention that it is meaningless to transmit only the echo data of the ultrasonic sensor itself, without transmitting all the data.

[0120] Furthermore, the central computer system can advantageously evaluate data from multiple preferred sensors. However, this requires data compression, unlike in the prior art, for transmission via a data bus with lower bandwidth. This can create a synergistic effect. For example, consider a vehicle with more than one ultrasonic sensor. To distinguish between the two sensors, it would be meaningful for them to transmit using different codes. However, contrary to the prior art, both sensors should now detect the ultrasonic echoes from the two ultrasonic sensors and transmit them to the central computer system with appropriate compression, where the ultrasonic received signals are reconstructed and fused. Obstacles (objects in the environment) are identified only after this reconstruction (decompression). Moreover, this also enables the further fusion of ultrasonic sensor data with data from other sensor systems (e.g., radar).

[0121] This invention proposes a method for transmitting sensor data from a sensor to a computer system. Particularly suitable is this method for transmitting ultrasonic received signal data from an ultrasonic sensor to a control device serving as a computer system in a vehicle. Figure 1 To explain this method, according to the proposed method, an ultrasonic burst pulse is first generated and emitted into free space, typically in the environment of the vehicle. Figure 1 Step α). In this case, the ultrasonic burst pulse consists of multiple sound pulses that follow each other at ultrasonic frequencies. The ultrasonic burst pulse is generated by a mechanical oscillator in the ultrasonic transmitter or ultrasonic transducer slowly starting and stopping. The ultrasonic burst pulse thus emitted by the exemplary ultrasonic transducer is then reflected by objects in the vehicle environment and received as an ultrasonic signal by the ultrasonic receiver or the ultrasonic transducer itself, and converted into an electrical received signal ( Figure 1Step β). Particularly preferably, the ultrasonic transmitter is the same as the ultrasonic receiver, and is thus referred to hereinafter as a transducer, which is an electroacoustic component that operates alternately as an ultrasonic transmitter and ultrasonic receiver and therefore as an ultrasonic sensor. However, the principle explained below can also be applied to separate receivers and transmitters. A signal processing unit is present in the proposed ultrasonic sensor, which now analyzes and compresses the electrically received signal (hereinafter referred to as the "received signal") corresponding to the ultrasonic received signal. Figure 1 Step γ) is performed to minimize necessary data transmission (the amount of data to be transmitted) and create free space for, for example, the transmission of status messages and other control commands from the control computer to the signal processing unit or ultrasonic sensor system. Subsequently, the compressed electrical received signal is transmitted to the computer system ( Figure 1 Step δ).

[0122] Therefore, the method is used, particularly in vehicles, to transmit sensor data, especially ultrasonic sensor data, from a sensor to a computer system. This is preceded by the emission of an ultrasonic burst pulse (…). Figure 1 Step α) and the reception of ultrasonic signals and the formation of electrically received signals ( Figure 1 Step β). Following this, data compression of the received signal is performed by detecting preferably at least two or three or more predetermined characteristics in the received signal. Figure 1 Step γ) to produce compressed data ( Figure 1 Step γ). Preferably, by sampling ( Figure 2 Step γa, which is further subdivided into, for example, five sub-steps, converts the electrical received signal into a sampled received signal, which consists of a time-discrete stream of sampled values. In this case, typically, a sampling time can be assigned as a timestamp for each sampled value. The compression can be performed, for example, by wavelet transform (…). Figure 2Step γb). For this purpose, the received ultrasound signal, in the form of the sampled received signal, is compared with a predetermined basic signal shape (referred to above as a signal feature) by forming a correlation integral (see also Wikipedia for this term) between the predetermined basic signal shape and the sampled received signal, the basic signal shape being stored, for example, in a library. The time series of the basic signal shape in the received signal accordingly forms a signal object, which is assigned to one of a plurality of signal object categories. By forming the correlation integral, the spectral value belonging to that signal object category is determined accordingly for each of these signal object categories. Since this occurs continuously, the spectral values ​​themselves represent a time-discrete stream of instantaneous spectral values, where a timestamp can be assigned to each spectral value. A mathematically equivalent alternative is to use a matched-filter for each predetermined signal object category (basic signal shape). Since multiple signal object categories are typically used, and these categories may also undergo different time spreads (see also "Wavelet Analysis"), this typically yields a multidimensional vector of spectral values ​​for different signal object categories and a discrete-time stream of their respective time spreads, with a timestamp assigned to each of these multidimensional vectors. Each of these multidimensional vectors is a so-called eigenvector. Therefore, it is a discrete-time stream of eigenvectors. Preferably, a timestamp is assigned to each of these eigenvectors (…). Figure 2 Step γb).

[0123] Thus, the time dimension is also obtained through continuous time displacement. This can further supplement the eigenvectors of the spectral values ​​with past values ​​or values ​​dependent on those past values, such as time integrals or derivatives or filtered values ​​of one or more of these values. This can further increase the dimension of these eigenvectors within the eigenvector data stream. Therefore, to keep the workload small as described below, it is meaningful to limit the extraction of the eigenvectors from the sampled received signal of the ultrasonic sensor to a few signal object categories. Thus, for example, a matched filter can then be used to continuously monitor the occurrence of these signal object categories in the received signal.

[0124] As particularly simple signal object categories, this paper can specifically categorize them, for example, as isosceles triangles and bimodal structures. In this case, the signal object category typically consists of a pre-given vector of spectral coefficients, i.e., pre-given eigenvector values.

[0125] To determine the correlation of the spectral coefficients of the eigenvectors of an ultrasonic echo signal, the absolute value of the distance between the elements of these characteristics, i.e., the vector of instantaneous spectral coefficients (eigenvectors), and at least one combination of these characteristics (prototypes) having the form of a signal object category is determined, whereby the signal object category is represented by a pre-given eigenvector (prototype or prototype vector) from a library of pre-given signal object category vectors. Figure 2 Step γd). Preferably, the spectral coefficients of the feature vector are normalized before being correlated with the prototype ( Figure 2 Step γc). The distance determined when this distance is determined can, for example, consist of the sum of all differences between each spectral coefficient of the pre-given feature vector (prototype or prototype vector) of the corresponding prototype and the corresponding normalized spectral coefficient of the current feature vector of the ultrasonic echo signal. The Euclidean distance will be formed by the square root of the sum of the squares of the sum of the squares of each spectral coefficient of the pre-given feature vector (prototype or prototype vector) of the prototype and the corresponding normalized spectral coefficient of the current feature vector of the ultrasonic echo signal. However, this distance formation is usually too tedious. Other distance formation methods can be considered. Thus, a sign can be assigned to each pre-given feature vector (prototype or prototype vector) before normalization, and parameters such as distance value and / or amplitude can also be assigned if necessary. If the distance thus determined is below a first threshold and it is the minimum distance between the current feature vector value and one of the pre-given feature vector values ​​(prototype vector or prototype vector value), its sign is continued as the identified prototype. This produces a pair consisting of the timestamps of the identified prototype and the current feature vector. Then preferably, the data ( Figure 2 Step δ) – here the determined symbol most representative of the identified prototype – and the transmission of, for example, the distance and occurrence time (timestamp) to the computer system, only occurs if the absolute value of the distance is below the first threshold and the identified prototype is the one to be transmitted. It is possible that, for example, prototypes not to be identified are stored for noise, i.e., those without reflections. This data is irrelevant to obstacle identification and therefore should not be transmitted if necessary. Therefore, if the absolute value of the distance determined between the current feature vector value and the pre-given feature vector value (the value of the prototype or prototype vector) is below the first threshold ( Figure 2 The prototype is identified by step γe.

[0126] Therefore, it is preferable not to transmit the ultrasonic echo signal itself, but only to transmit the symbols of the identified typical time-varying curves within the echo signal and a sequence of timestamps belonging to these curves within a defined time period. Figure 2Step δ). Then, preferably for each identified signal object, only the symbol of the identified signal shape prototype, its parameters (e.g., the amplitude and / or time spread of the envelope), and the time reference point (timestamp) at which the signal shape prototype appears are transmitted as the identified signal object. The transmission of individual sample values ​​or the moment when the threshold is exceeded by the envelope of the sampled received signal is cancelled. In this way, the selection of the relevant prototype results in a large amount of data compression and a reduction in the required bus bandwidth.

[0127] Therefore, the presence of a combination of characteristics is quantitatively detected by forming an estimate (here, for example, the inverse distance between representatives of signal object categories in the form of a pre-given feature vector (prototype or prototype vector), and then compressed data is transmitted to the computer system if the absolute value of the estimate (e.g., the inverse distance) is greater than a second threshold or the inverse estimate is less than a first threshold. Therefore, the signal processing unit of the ultrasonic sensor compresses the received signal to produce compressed data. The ultrasonic sensor then transmits this compressed data, preferably only the encoding (symbol) of the prototype identified in this way, its amplitude and / or time extension, and the time of occurrence (timestamp) to the computer system. Thus, EMV burden is minimized by transmitting data via the data bus between the ultrasonic sensor and the computer system, and other data, such as the status data of the ultrasonic sensor used for system fault identification, can be transmitted to the computer system via the data bus between the ultrasonic sensor and the computer system within time intervals, which improves latency.

[0128] As indicated within the scope of this invention, data should be transmitted preferentially via the data bus. In this case, notifications of safety-critical faults of the sensor (i.e., the ultrasonic sensor in this case) to the computer system have the highest priority, as they have a high probability of affecting the validity of the ultrasonic sensor's measurement data. This data is sent from the sensor to the computer system. Requests from the computer system to perform safety-related self-tests have the second highest priority. Such commands are sent from the computer system to the sensor. Data from the ultrasonic sensor itself has the third highest priority, as additional latency is not permitted. All other data has (even) a lower priority in relation to its transmission via the data bus.

[0129] Particularly advantageously, the method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle, has the following characteristics:

[0130] -Emit an ultrasonic burst pulse, having a start (57) and an end (56) for transmitting the ultrasonic burst pulse.

[0131] - Receive the ultrasonic signal and receive it for at least the time (T) from the end of the transmission of the ultrasonic burst pulse train (56). E )

[0132] Internally formed received signal, and

[0133] - The compressed data is transmitted to the computer system via a data bus, particularly a single-wire data bus, and the data transmission (54) from the sensor to the computer system is initiated by a start command (53) from the computer system via the data bus to the sensor and prior to the end (56) of the transmission of the ultrasonic burst pulse, or after a start command (53) from the computer system via the data bus to the sensor and prior to the start (57) of the transmission of the ultrasonic burst pulse, wherein the transmission (54) is then periodically continued after the start command (53) until the end of the data transmission (58), the end of which is time-time-located at the reception time (T). E After the end of ).

[0134] Therefore, as a first step in data compression, another variation of the proposed method specifies the formation of a feature vector signal (a stream of feature vectors with n feature vector values, where n is the dimension of the feature vectors) from the received signal. Such a feature vector signal can include multiple analog and digital data signals. Thus, the feature vector signal represents a time series of data / signal structures that are more or less complex; in its simplest case, the feature vector signal can be understood as a vector signal composed of multiple sub-signals.

[0135] For example, it may be meaningful to form the first and / or higher-order time derivatives of the received signal or to form one or more integrals of the received signal, which are sub-signals within the eigenvector signal.

[0136] It is also possible to form an envelope signal of the received signal, and then the envelope signal is a sub-signal within the feature vector signal.

[0137] Furthermore, it may be meaningful to convolve the received signal with the emitted ultrasonic signal to form a correlation signal, which could then be a sub-signal within the eigenvector signal. In this case, on the one hand, this signal could be used as the emitted ultrasonic signal that was used to control the transmitter's actuator, or on the other hand, for example, as a signal that was measured on the transmitter and thus better corresponds to the actual radiated sound wave.

[0138] Finally, it may be meaningful to use a matched filter to detect the presence of a predetermined signal object and to form matched filter signals for some of the corresponding signal objects. In this case, the matched filter should be understood as a filter that optimizes the signal-to-noise ratio (SNR). The predefined signal objects should be identified in the interfered ultrasound received signal. The terms "correlation filter," "signal matched filter (SAF)," or simply "fitting filter" are also frequently used in this literature. The matched filter is used to optimally determine the presence (detection) of a known signal shape, i.e., the presence of a predetermined signal object, even in the presence of interference (parameter estimation). This interference can be, for example, signals from other ultrasound transmitters and / or ground echoes.

[0139] Then, the output signal of the matched filter is preferably a sub-signal within the eigenvector signal.

[0140] The determined events can be signaled in individual sub-signals of the characteristic vector signal. In the sense of this invention, these events are signal fundamental objects. Therefore, signal fundamental objects do not include signal shapes of other shapes such as rectangular pulses, wavelets, or wave trains, but rather include prominent points in the variation curve of the received signal and / or in the variation curve of the signal derived from the received signal, such as, for example, the derived envelope signal that can be obtained by filtering from the received signal.

[0141] Another signal, which could be a sub-signal of the feature vector signal, can, for example, probe the envelope of the received signal, i.e., whether the envelope signal intersects with a pre-given third threshold. Therefore, this is a signal that signals the presence of a fundamental signal object in the received signal and thus signals the presence of the feature vector signal.

[0142] Another signal, which could be a sub-signal of the feature vector signal, can, for example, detect the envelope of the received signal, i.e., whether the envelope signal rises to intersect with a pre-given fourth threshold, which may be the same as the third threshold. Therefore, this is a signal that notifies the presence of a signal fundamental object in the received signal and thus notifies the presence of the feature vector signal.

[0143] Another signal, which could be a sub-signal of the feature vector signal, can, for example, detect whether the envelope of the received signal, i.e., whether the envelope signal droops and intersects with a pre-given fifth threshold, which may be the same as the third or fourth threshold. Therefore, this is a signal that notifies the presence of a signal fundamental object in the received signal and thus notifies the presence of the feature vector signal.

[0144] Another signal, which could be a sub-signal of the feature vector signal, can, for example, probe the envelope of the received signal, i.e., whether the envelope signal has a maximum value above a sixth threshold, which can be the same as the third to fifth thresholds mentioned above. Therefore, this is a signal that notifies the presence of a basic signal object in the received signal and thus notifies the presence of the feature vector signal.

[0145] Another signal, which could be a sub-signal of the feature vector signal, can, for example, probe the envelope of the received signal, i.e., whether the envelope signal has a minimum value above a seventh threshold, which can be the same as the third to sixth thresholds mentioned above. Therefore, this is a signal that notifies the presence of a signal fundamental object in the received signal and thus notifies the presence of the feature vector signal.

[0146] In this case, it is preferable to evaluate whether at least one preceding maximum value of the envelope has a minimum distance to the minimum value to avoid detecting noise. Other filtering methods may be considered. It can also be checked whether the time interval between the minimum value and the preceding maximum value is greater than a first time minimum distance. The satisfaction of these conditions sets a flag or signal, which is preferably a sub-signal of the feature vector signal itself.

[0147] Similarly, the temporal and amplitude-measured distances of other signal objects should be checked in a similar manner to ensure they meet certain authenticity requirements, such as adherence to minimum temporal and / or minimum amplitude distances. Other analog, binary, or digital sub-signals can also be derived from these checks, thereby further increasing the dimensionality of the eigenvector signal.

[0148] If necessary, the eigenvector signal can be converted into a salient eigenvector signal during the saliency enhancement stage, for example, through linear mapping or through a higher-order matrix polynomial. However, practice has shown that this is not necessary, at least for the current requirements.

[0149] According to the proposed method, based on the feature vector signal or the salient feature vector signal, signal objects are identified within the received signal and the signal objects are classified into the identified signal object category.

[0150] If, for example, the amplitude of the output signal of the matched filter, and therefore the amplitude of the sub-signals of the eigenvector signal, is above a threshold (e.g., an eighth) specific to the matched filter, then the signal object for which the matched filter is designed to detect can be considered identified. In this case, other parameters are preferably also considered. For example, if an ultrasonic burst pulse with an increasing frequency (so-called positive linear frequency modulation) is transmitted during the burst pulse, then an echo with this modulation characteristic is also expected. If the signal shape of the envelope (e.g., the triangular signal shape of the envelope) is locally consistent with the expected signal shape in time but not with the modulation characteristic, then it is not an echo from the transmitter, but rather an interference signal that may come from another ultrasonic transmitter or from an interference signal beyond the range of action. In this respect, the system can then distinguish between intrinsic echoes and imported echoes, thereby assigning the same signal shape to two different signal objects, namely intrinsic echoes and imported echoes. In this case, the transmission of the intrinsic echo from the sensor to the computer system via the data bus is preferably preferred over the transmission of the imported echo, because the former is generally related to security, while the second echo type is generally not related to security.

[0151] Typically, during the identification process, at least one signal object parameter is assigned to or determined for each identified signal object. Preferably, this is a timestamp indicating when the object was received. In this case, the timestamp may, for example, relate to the time start point of the signal object in the received signal, the time end point of the signal object, the time length of the signal object, or the time position of the time centroid of the signal object. Other signal object parameters such as amplitude, extension, etc., may also be considered. Thus, in a variation of the proposed method, at least one assigned signal object parameter with a symbol for at least one signal object category to which the at least one identified signal object belongs is transmitted. The signal object parameter is preferably a time value as a timestamp and indicates a time position suitable from which the time since the previous ultrasonic burst pulse emission can be inferred. Preferably, the distance to the object is then determined based on the time value thus determined and transmitted.

[0152] Finally, the identified signal object categories are transmitted first, preferably along with the assigned signal object parameters, in the form of timestamped symbols. This transmission can also be performed using more complex data structures (Records). For example, it could be considered to first transmit the time of the identified safety-related signal object (e.g., an identified obstacle), and then transmit the identified signal object category of the safety-related signal object. This further reduces latency.

[0153] In one variant, the proposed method includes at least determining a linear frequency modulation (LFM) value as an assigned signal object parameter, which indicates whether the identified signal object is an echo of an ultrasonic transmission burst pulse exhibiting positive, negative, or nonlinear frequency modulation characteristics. "Positive LFM" refers to an increase in frequency within the received signal object. "Negative LFM" refers to a decrease in frequency within the received signal object. "Nonlinear frequency modulation" refers to a substantially constant frequency within the received signal object.

[0154] Therefore, in a variation of this method, a confidence signal can also be formed by generating a correlation, for example, by generating a time-continuous or time-discrete correlation integral between a received signal or a signal derived from the received signal in place of the received signal and a reference signal, such as the ultrasonic emission signal or another anticipated wavelet. The confidence signal is then typically a sub-signal of the eigenvector signal, i.e., a component of the eigenvector consisting of a sequence of vector sample values ​​(eigenvector values).

[0155] In another variation of this method, a phase signal is further formed, which describes, for example, the phase shift of the received signal or a signal formed from the received signal (e.g., a confidence signal) relative to a reference signal (e.g., the ultrasonic emission signal and / or another type of reference signal). This phase signal is then typically also a sub-signal of the eigenvector signal, i.e., a component of the eigenvector consisting of a sequence of vector sample values ​​(eigenvector values).

[0156] Similarly, in another variation of the proposed method, a phase position confidence signal can be formed by establishing a correlation between the phase signal or a signal derived from the phase signal and a reference signal, and this phase position confidence signal can be used as a sub-signal of the eigenvector signal. The phase position confidence signal is then typically also a sub-signal of the eigenvector signal, i.e., a component of the eigenvector consisting of a sequence of vector sample values ​​(eigenvector values).

[0157] In evaluating the eigenvector signal, it may be meaningful to compare the phase position confidence signal with one or more thresholds to generate a discretized phase position confidence signal, which itself may be a sub-signal of the eigenvector signal.

[0158] In a variation of the proposed method, the evaluation of the feature vector signal and / or the salient feature vector signal can result in forming one or more distance values ​​between the feature vector signal and one or more signal object prototype values ​​for an identifiable signal object category. Such distance values ​​can be Boolean, binary, discrete, digital, or analog values. Preferably, all distance values ​​are logically connected to each other in a nonlinear function. Thus, in the case of a triangular-shaped expected positive linear frequency modulated (FM) echo, a received triangular-shaped negative FM echo can be discarded. This discarding is a "nonlinear" process in the sense of the invention.

[0159] Conversely, the triangles in the received signal may form differently. This primarily involves the amplitude of the triangles in the received signal. If the amplitude in the received signal is large enough, then, for example, the matched filter assigned to the triangle signal provides a signal above a pre-given ninth threshold. Thus, in this case, for example, the signal object identified at the transcendental time can be assigned to the signal object category (for the triangle signal). In this case, the distance value between the feature vector signal and the prototype (here, the ninth threshold) is less than one or more predetermined binary, digital, or analog distance values ​​(here, 0 = intersection).

[0160] Within the scope of this invention, it has been recognized that it is advantageous to transmit data of identified signal objects whose echoes arrive very quickly from the sensor to the computer system first, and then transmit subsequent data of signal objects subsequently identified. Preferably, in this case, at least the category of the identified signal object and a timestamp should always be transmitted, the timestamp preferably indicating when the signal object re-arrives at the sensor. Within the scope of the identification process, scores can be assigned to different signal objects considered for the segment of the received signal, these scores indicating what probability is assigned to the presence of the signal object according to the estimation algorithm used. In the simplest case, such scores are binary. However, preferably they are complex numbers, real numbers, or integers. It can be, for example, a determined distance. If multiple signal objects have high score values, it is meaningful in some cases to also transmit data of identified signal objects with lower score values. In order for the computer system to process correctly, in this case, not only the data (symbols) of the identified signal objects and the timestamps for the corresponding signal objects should be transmitted, but also the determined score values ​​should be transmitted. In addition to transmitting only the data (symbols) of the identified signal objects and the timestamps corresponding to those symbols, the system may also transmit the data (symbols) of signal objects with a second minimum distance and their timestamps corresponding to those second maximum probability symbols. Therefore, in this case, a hypothesis list consisting of two identified signal objects, their time positions, and additionally assigned scores is transmitted to the computer system. Similarly, a hypothesis list consisting of more than two symbols for more than two identified signal objects, their time positions, and additionally assigned scores can also be transmitted to the computer system.

[0161] Preferably, data on the identified signal object category and assigned data (e.g., timestamps and scores for the corresponding identified signal object category) are transmitted according to the FIFO principle, i.e., the assigned signal object parameters. This ensures that data reflecting the closest object is always transmitted first, and thus, safety-critical situations involving vehicle-obstacle collisions are handled with probabilistic priority.

[0162] In addition to transmitting measurement data, the fault status of the sensor can also be transmitted. If the sensor determines through a self-test device that "there is a defect and the previously transmitted data may be incorrect," this can also be transmitted at the receiving time (T). EThis occurs during the period. This ensures that the computer system can acquire knowledge about changes in the measurement data assessment as early as possible, and can discard or process these changes differently. This is particularly important for emergency braking systems, as emergency braking is a safety-critical intervention that is only permitted when the underlying data has a corresponding confidence value, and is also particularly important for other driver assistance systems. Therefore, in contrast, the transmission of the measurement data, i.e., the transmission of data on the identified signal object category and / or the transmission of an assigned signal object parameter, is postponed and thus given a lower priority. Transmission can also be considered if a sensor malfunction occurs. However, it is also possible that a malfunction appears to have occurred, but its existence is uncertain. In this case, continued transmission may be indicated. Therefore, the transmission of safety-critical faults of the sensor is preferably determined to have a higher priority.

[0163] In addition to the wavelet with a zero integral value already described and signal segments with integral values ​​other than zero, additionally referred to herein as wavelets, specific locations / phases in the variation curve of the received signal can also be understood, in the sense of this invention, as signal objects that can be used for data compression and can be transmitted in place of sampled values ​​of the received signal. These subsets of the possible set of basic signal objects are hereinafter referred to as signal moments. Therefore, these points in the signal variation curve are a special form of the basic signal objects in the sense of this invention.

[0164] The first possible signal change curve point and therefore the basic signal object is the intersection of the change curve of the envelope signal (1) and the threshold signal (SW) in the rising direction.

[0165] The second possible signal change curve point and therefore the basic signal object is the intersection of the change curve of the envelope signal (1) and the threshold signal (SW) in the descent direction.

[0166] The third possible signal variation curve point and therefore the basic signal object is the local maximum or absolute maximum value of the variation curve of the envelope signal (1) above the amplitude of the thirteenth threshold signal (SW).

[0167] The fourth possible signal variation curve point and therefore the basic signal object is the local minimum or absolute minimum of the variation curve of the envelope signal (1) above the threshold signal (SW).

[0168] It may be meaningful if necessary to use the threshold signal (SW) typical of the signal basic object for these four exemplary types of signal change curve points and other types of signal change curve points.

[0169] The time series of the basic signal objects are typically not arbitrary. This is utilized according to the invention because, preferably, the basic signal objects with simple properties should not be transmitted, but rather identified patterns of the time series of these basic signal objects, which then represent the actual signal objects. For example, if a triangular wavelet is expected in an envelope signal (1) with sufficient height, then, in addition to the corresponding minimum level at the output of a matched filter suitable for detecting such a triangular wavelet, time-related parameters related to exceeding the minimum level at the output of the matched filter can also be expected.

[0170] 1. The occurrence of the first possible signal change curve point when the amplitude of the envelope signal (1) crosses the threshold signal (SW) in the rising direction, and the subsequent time...

[0171] 2. The occurrence of a second possible signal change curve point at the maximum value of the envelope signal (1) above one or the threshold signal (SW), and the subsequent time-series...

[0172] 3. The appearance of a third possible signal change curve point when the envelope signal (1) crosses with one or the threshold signal (SW) in the descent direction.

[0173] Therefore, in this example, the exemplary signal object of the triangular wavelet lies in a predefined sequence of three basic signal objects. The signal object is identified and assigned to a signal object category by means of this sequence, where this information is transmitted as a symbol of the signal object category and through parameters describing the identified signal object (e.g., specifically the time of occurrence, i.e., a timestamp). Furthermore, exceeding the minimum level at the output of the matched filter is another example of a fifth possible signal variation curve point, and thus another possible basic signal object.

[0174] The resulting groupings and time series of the identified signal fundamentals can be identified, for example, by a Veterbi decoder, as predefined expected groupings or time series of signal fundamentals, and thus can represent the signal fundamentals themselves again. Therefore, the sixth possible signal variation curve points and thus the signal fundamentals are time series of other signal fundamentals and / or such predefined groupings.

[0175] If a grouping or time series of signal object categories is identified based on the characteristics of the signal variation curve, it is preferable to perform the transmission of the symbols of the identified combined signal object categories and at least one assigned signal object parameter, rather than the transmission of individual signal basic objects, as this saves a significant amount of data bus capacity. However, it is also possible that both are transmitted. In this case, the data (symbols) of the signal object categories are transmitted, which are predefined time series and / or groups of other signal basic objects. For compression purposes, it is advantageous not to transmit at least one signal object category (symbol) of at least one of these other signal basic objects.

[0176] Time grouping of signal fundamentals exists particularly when the time intervals between these signal fundamentals do not exceed a predefined distance. In the example mentioned above, the propagation time of the signal in the matched filter should be considered. Typically, the matched filter is allowed to be slower than the comparator. Therefore, the transformation of the output signal of the matched filter should have a fixed time relationship with the occurrence time of the relevant signal.

[0177] Therefore, according to a variation of the invention, a method is proposed for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle. This method begins after transmitting an ultrasonic burst pulse and receiving an ultrasonic signal, forming a time-discrete received signal composed of a sequence of sampled values. In this case, time data (timestamps) are assigned to each sampled value. The method begins by determining at least two parameter signals from the sequence of sampled values ​​of the received signal using at least one suitable filter (e.g., a matched filter), each relating to the existence of a signal fundamental object assigned to a corresponding parameter signal. The resulting parameter signals (eigenvector signals) are also constructed as time-discrete sequences of corresponding parameter signal values ​​(eigenvector values), each parameter signal value associated with a data point (timestamp). Therefore, it is preferable to assign exactly one time data point (timestamp) to each parameter signal value (eigenvector value). These parameter signals are collectively referred to below as eigenvector signals. Thus, the eigenvector signals are constructed as time-discrete sequences of eigenvector signal values, each eigenvector signal value having n parameter signal values, which are composed of the parameter signal value and other parameter signal values, each having the same time data (timestamps). In this case, n is the dimension of each feature vector signal value, preferably the same from one feature vector value to the next. The corresponding time data (timestamp) is assigned to each feature vector signal value thus formed. Next, the time variation curve of the feature vector signal in the resulting n-dimensional phase space is evaluated, and the identified signal object is inferred based on the determined evaluation value (e.g., distance). As explained above, here, the signal object consists of a time series of basic signal objects. In this case, predefined symbols are typically assigned to the signal objects. Figuratively speaking, this involves checking whether the point pointed to by the n-dimensional feature vector signal in the n-dimensional phase space approaches a predetermined point in the n-dimensional phase space by a distance smaller than a pre-given maximum distance along its path traversing the n-dimensional phase space in a predetermined time order. Thus, the feature vector signal has a time variation curve. An evaluation value (e.g., distance) is then calculated, which may reflect, for example, the probability of the existence of a determined sequence. This evaluation value, again assigned time data (timestamp), is then compared with a threshold vector, resulting in a Boolean result, which may have a first value and a second value. If the Boolean result has the first value for the time data (timestamp), then the symbol of the signal object and the time data (timestamp) assigned to that symbol are transmitted from the sensor to the computer system. Other parameters may be transmitted if necessary, based on the identified signal object.

[0178] Particularly preferably, data transmission in the vehicle is performed via a serial, bidirectional, single-wire data bus. In this case, the electrical return line is preferably ensured by the vehicle body. Sensor data is preferably transmitted to the computer system in a current-modulated manner. Data for controlling the sensor is preferably transmitted to the sensor via the computer system in a voltage-modulated manner. According to the invention, the use of a PSI5 data bus and / or a DSI3 data bus is particularly suitable for this data transmission. Furthermore, it has been recognized that it is particularly advantageous to transmit data to the computer system at a transmission rate >200 kbps and to the at least one sensor at a transmission rate >10 kbps, preferably 20 kbps. Furthermore, it has been recognized that the data transmission from the sensor to the computer system should be modulated onto the data bus using a transmit current, the current intensity of which should be less than 50 mA, preferably less than 5 mA, and preferably less than 2.5 mA. For these operating values, these buses must be adapted accordingly. However, the basic principle remains. To perform the above method, a computer system is required that has a data interface to the data bus, preferably to the single-wire data bus, wherein the computer system supports decompression of such compressed data. However, typically the computer system does not perform complete decompression, but rather, for example, only evaluates the timestamp and the type of the identified signal object. The sensor required to perform one of the above methods has at least one transmitter and at least one receiver for generating the received signal, which may also be combined as one or more transducers. Furthermore, the sensor has at least a device for processing and compressing the received signal and a data interface for transmitting the data to the computer system via the data bus, preferably via the single-wire data bus. For the data compression, the device preferably has at least one of the following elements:

[0179] ● Matched filter,

[0180] ● Comparator,

[0181] ● A threshold signal generating device for generating one or more threshold signals (SW).

[0182] ● Differentiators used to form derivatives

[0183] • An integrator used to generate an integral signal.

[0184] Other filters,

[0185] • An envelope formler for generating an envelope signal from the received signal.

[0186] • A correlation filter used to compare the received signal or a signal derived from the received signal with a reference signal.

[0187] In a particularly simple form, the proposed method for transmitting sensor data, especially ultrasonic sensor data, from a sensor to a computer system, particularly in a vehicle, is performed as follows:

[0188] Prior to this, for example, is the transmission of an ultrasonic burst pulse and the reception of an ultrasonic signal, typically involving reflection and the formation of a time-discrete received signal consisting of a time sequence of sampled values. In this case, time data (timestamps) is assigned to each sampled value. This time data typically reflects the time of sampling. Based on this data stream, according to the invention, a first parameter signal having a first characteristic is determined from the sequence of sampled values ​​of the received signal by means of a first filter. In this case, the parameter signal is preferably again constructed as a time-discrete sequence of parameter signal values. Exactly one time data (timestamp) is again assigned to each parameter signal value. Preferably, this data corresponds to the most recent time data of the sampled value used to form the corresponding parameter signal value. Temporally in parallel with this, preferably by means of another filter assigned to another parameter signal, at least one additional parameter signal and / or the characteristic assigned to that additional parameter signal is determined from the sequence of sampled values ​​of the received signal, wherein the additional parameter signals are respectively again constructed as time-discrete sequences of additional parameter signal values. Here, the same time data (timestamps) as the corresponding parameter signal value are also assigned to each additional parameter signal value.

[0189] In the following text, the first parameter signal and the other parameter signal are collectively referred to as the parameter vector signal or the feature vector signal. Therefore, the feature vector signal represents a discrete-time sequence of feature vector signal values, which are composed of parameter signal values ​​and other parameter signal values, each having the same time data (timestamp). Thus, the corresponding time data (timestamp) can be assigned to each such formed feature vector signal value, i.e., to each parameter signal value.

[0190] Then, preferably quasi-continuously, the feature vector signal values ​​of the time data (timestamps) are compared with a threshold vector (preferably a prototype vector), simultaneously forming a Boolean result, which can have a first value and a second value. For example, one could consider comparing the absolute value of the current feature vector signal value, representing a first component of, for example, the feature vector signal value, with a threshold representing a first component of the threshold vector, and setting the Boolean result to the first value if the absolute value of the feature vector signal value is less than the threshold, and to the second value if it is not less. If the Boolean result has a first value, then it is further considered to compare the absolute value of another feature vector signal value with another threshold, such as representing another component of the feature vector signal, and the other threshold representing another component of the threshold vector, and if the absolute value of the other feature vector signal value is less than the other threshold, then the Boolean result is retained at the first value, or if it is not less, then the Boolean result is set to the second value. In this way, all other feature vector signal values ​​can be examined. Of course, other classifiers can also be considered. Comparisons can also be made with multiple different threshold vectors. These threshold vectors thus represent prototypes with a pre-given signal shape. They originate from the aforementioned library. Again, it is preferable to assign a symbol to each threshold vector.

[0191] Then, as a final step in this case, the symbol, and if necessary, the feature vector signal value and the time data (timestamp) assigned to the symbol or the feature vector signal value, are transmitted from the sensor to the computer system, if the Boolean result has a first value for the time data (timestamp).

[0192] Therefore, no other data is transmitted. Furthermore, interference is avoided through multidimensional evaluation.

[0193] Therefore, a sensor system is proposed based on this, having at least one computer system capable of performing one of the above-described methods, and at least two sensors also capable of performing one of the above-described methods, such that the at least two sensors can communicate with the computer system through signal object identification, and can also compactly transmit incoming echoes and append this information to the computer system. Thus, the sensor system is typically configured such that data transmission between the at least two sensors and the computer system operates or can operate according to the above-described methods. Therefore, within the at least two sensors of the sensor system, typically, each ultrasonic received signal is compressed using one of the methods proposed above, i.e., at least two ultrasonic received signals are transmitted to the computer system. In this case, the at least two ultrasonic received signals are reconstructed into a reconstructed ultrasonic received signal within the computer system. The computer system then performs object identification of objects in the sensor environment using the reconstructed ultrasonic received signal. Therefore, contrary to the prior art, the sensors do not perform the object identification. They only provide encoded data concerning the identified signal objects and their parameters, and thus transmit the received signal variation curve in compressed form.

[0194] Preferably, the computer system additionally identifies objects, i.e. obstacles in the sensor environment, by means of reconstructed ultrasonic received signals and, if necessary, additional signals from other sensors (especially radar sensors).

[0195] As a final step, the computer system preferably creates an environmental map based on the identified objects for the sensor, the device to which the sensor belongs, or a device with the sensor as a component.

[0196] The proposed method for transmitting signal variation curve data in compressed form between a sensor and a computer system via a data bus reduces the data bus load, thus lessening the criticality of EMV requirements. Furthermore, it provides additional free data bus capacity for transmitting control commands from the computer system to the sensor, and for transmitting status information and other data from the sensor to the computer system. In this case, the proposed priority for transmitting compressed data of the received signal variation curve and other data (such as status information or fault messages) ensures that safety-related data is transmitted first, thereby avoiding unnecessary downtime for the sensor.

[0197] Figure 3 Section (a) shows the time-varying curves of a conventional ultrasonic echo signal (1) in freely chosen units (see the wider solid line) and its conventional evaluation. This begins from the emission of the transmitted burst pulse (SB) (see the signal variation curve segment shown on the far left) and... Figure 3The part (d) with the reference numeral SB will carry the threshold signal (SW) (see dashed line). Whenever the envelope of the ultrasonic echo signal (1) exceeds the threshold signal (SW), the output (2) (see thinner solid line) is set to logic 1. It is a time-analog interface with digital output levels. Further evaluation is then performed in the control device of the sensor. It is not possible to signal faults or control the sensor via this analog interface, which is compatible with existing technology.

[0198] Figure 3 Section (b) shows the time-varying curve of the conventional ultrasonic echo signal (1) and its conventional evaluation in freely chosen units. It begins with the transmission of a burst pulse (SB), carrying a threshold signal (SW). However, now whenever the envelope signal of the ultrasonic echo signal (1) exceeds the threshold signal (SW), the output (2) is set to a level corresponding to the detected reflection magnitude (see the thicker dotted line). It is a time-simulation interface with analog output levels. Further evaluation is then performed on the sensor. It is not possible to signal faults or control the sensor via this analog interface, which is consistent with existing technology.

[0199] Figure 3 Section (c) shows the ultrasound echo signal used for interpretation, where the linear frequency modulation direction (e.g., A = positive linear frequency modulation, B = negative linear frequency modulation) is marked by a shading line from the upper left to the lower right or from the lower left to the upper right.

[0200] exist Figure 3 The principle of symbolic signal transmission is explained in section (d). For example, only two types of (triangle) signal objects are transmitted here instead of those from... Figure 3 The signal in part (c). Specifically, they are the first triangular object (A) (for both positive and negative linear frequency modulation). Figure 3 (shown in section (d)) and the second triangular object (B) (shown for the case of negative linear frequency modulation). Simultaneously, the transmission time and peak value, as well as the base width of the triangular object if necessary, are transmitted. If the signal is now reconstructed based on these data, the corresponding... Figure 3 The signal in part (d) is used. Signal components that do not correspond to the triangular signal are removed from this signal. Therefore, unidentified signal components are discarded, resulting in significant data compression.

[0201] Figure 4a The diagram shows an unprotected conventional analog transmission in which the envelope signal (1) of the ultrasonic echo signal intersects with the threshold signal (SW).

[0202] Figure 4b This illustrates the unprotected transmission of analyzed data after the ultrasonic echo has been fully received.

[0203] Figure 4c The transmission of compressed data requiring protection is illustrated, in which, in this example, symbols for the basic object of the signal are transmitted essentially without compression.

[0204] Figure 5 The protected transmission of compressed data is illustrated, wherein in this example, symbols for a basic signal object are compressed into symbols for the signal object. First, a first triangular object (59) is identified and transmitted, characterized by a time series consisting of exceeding a threshold, a maximum value, and below a threshold (see...). Figure 5 The time series of signal change curve points 5, 6, and 7 in the time-varying curve of the ultrasonic echo signal in the upper figure. Then, a double peak with a saddle point (60) above the threshold signal is identified. Here, the feature is a time series consisting of the envelope signal (1) exceeding the threshold signal (SW), the maximum value of the envelope signal (1), the minimum value above the threshold signal (SW), the maximum value above the threshold signal (SW), and the signal below the threshold signal (SW) (see signal change curve points 8, 9, 10, 11, and 12 in the upper figure). After identification, the symbol for the double peak with the saddle point is transmitted. In this case, the timestamp is also transmitted together. Preferably, other parameters of the double peak with the saddle point, such as the position of the maximum and minimum values, or the scaling factor, are also transmitted together. Then, as the envelope signal exceeds the threshold signal (SW), followed by the maximum value of the envelope signal, followed by the envelope signal below the threshold signal (SW) (see signal change curve points 13, 14, and 15 in the upper figure), a triangular signal (61) (i.e., the basic signal object) is identified. The double peak (62) is then identified again, but now the minimum value of the envelope signal is below the threshold signal (SW) (see signal variation curve points 16, 17, 18, 19, 20, 21 in the above figure). Therefore, the double peak can be processed, for example, as a separate signal object. Finally, the triangular signal is identified from signal variation curve points 22, 23, 24 in the above figure. It is easy to see that this processing of the signal results in a significant reduction in data.

[0205] Figure 6 It shows that according to Figure 3 The compressed data requires protected transmission, where in this example, not only the envelope but also the confidence signal is evaluated. Figure 6 In the upper and middle sections of the diagram, the threshold signal is indicated by a thick dashed line. It can be seen that the received signal is only evaluated when it exceeds the threshold signal. Figure 6 The dotted signal variation curves in the middle of the graph indicate whether the signal object is modulated with positive or negative linear frequency modulation (see also [reference needed]). Figure 3Parts (c) and (d) are shown, where shading lines of different slopes distinguish between positive and negative linear frequency modulation (LFM). An upward-sloping dotted signal line curve indicates that the signal object has been identified as positive LFM modulation, while a downward-sloping dotted signal line curve indicates that the signal object has been identified as negative LFM modulation.

[0206] For the above and the following content, the following definitions of terms should be noted:

[0207] - The signal object is also called the signal change curve object.

[0208] -Signal object category is also called signal change curve object category

[0209] - The symbol is an identifier for the category of the signal change curve object.

[0210] - Signal object parameters and object parameters are synonymous

[0211] - The basic shape of a signal refers to the characteristics of its change curve.

[0212] By definition, a signal object consists of one or more basic signal objects; that is, a signal variation curve object consists of one or more signal variation curve features. A signal object belongs to one of several signal object categories. A signal object can be described by one or more signal object parameters, relating to, for example, position, size, deformation, and extension.

[0213] The basic objects of a signal can also be called the basic features of the signal change curve, that is, the features of the signal change curve.

[0214] The parameters also describe the shape of the signal object.

[0215] A parameter signal consists of multiple parameter signal values.

[0216] The eigenvector signal is composed of multiple parameter signals.

[0217] The value of the feature vector signal is composed of multiple parameter signal values.

[0218] The feature vector signal is formed by multiple parameter signals. Also known as the parameter vector signal value, the feature vector signal value comprises multiple parameter signal values.

[0219] The various embodiments of the present invention are described below. It should be noted that the feature sets described below can be arbitrarily combined with each other (reference numerals are involved in the drawings). Figure 1 and 2 The illustrations in the image are merely illustrative and should not be interpreted restrictively.

[0220] 1. A method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle.

[0221] - Send ultrasonic burst pulses;

[0222] - Receive ultrasonic signals and generate a received signal;

[0223] - Perform data compression on the received signal to produce compressed data;

[0224] - The compressed data is transmitted to the computer system.

[0225] 2. A method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle.

[0226] -Emit an ultrasonic burst pulse, which has a start 57 and an end 56 for transmitting the ultrasonic burst pulse;

[0227] - Receive the ultrasonic signal and receive it for at least 56 minutes from the end of the transmission of the ultrasonic burst pulse. E Internal signal reception is generated;

[0228] - The compressed data is transmitted to the computer system via a data bus, particularly a single-wire data bus;

[0229] -Including data transmission from the sensor to the computer system 54

[0230] -Beginning with the start command 53 from the computer system via the data bus to the sensor and before the end command 56 for transmitting the ultrasonic burst pulse, or

[0231] -Starting after the start command 53 from the computer system via the data bus to the sensor and before the start 57 of transmitting the ultrasonic burst pulse, and

[0232] -The transmission 54 is executed periodically and continuously after the start instruction 53 until the data transmission 58 ends, and

[0233] -The end of the data transmission 58 occurs in time at the reception time T. E After it ended.

[0234] 3. A method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle.

[0235] -Emits a burst of ultrasonic pulses;

[0236] - Receive ultrasonic signals and generate a received signal;

[0237] - A feature vector signal is formed from the received signal;

[0238] - Identify signal change curve features within the received signal and classify the signal change curve features into identified signal change curve feature categories, wherein at least one assigned signal change curve feature parameter is assigned to each identified signal change curve feature or at least one assigned signal change curve feature parameter is determined for the signal change curve feature;

[0239] - Prioritize the transmission of at least one identified signal variation curve feature category and the at least one assigned signal variation curve feature parameter.

[0240] 4. The method according to number 3, wherein at least one assigned signal change curve feature parameter transmitted along with at least one identified signal change curve feature category is a time value, which describes a time position suitable for inferring the time since the transmission of the previous ultrasonic burst pulse.

[0241] 5. The method according to number 4, including the additional step of determining the distance to the obstacle object based on the time value.

[0242] 6. The method according to number 3 includes the following steps: determining a linear frequency modulation value as an assigned signal variation curve characteristic parameter, the signal variation curve characteristic parameter indicating whether the identified signal variation curve characteristic is an echo of an ultrasonic transmission burst pulse with positive linear frequency modulation, negative linear frequency modulation, or nonlinear frequency modulation characteristics.

[0243] 7. The method according to number 3 includes the step of: generating a confidence signal by forming a correlation between a received signal or a signal derived from the received signal and a reference signal.

[0244] 8. The method according to number 3 includes the following steps: generating a phase signal.

[0245] 9. The method according to number 8 includes the step of generating a phase position confidence signal by forming a correlation between the phase signal or a signal derived from the phase signal and a reference signal.

[0246] 10. The method according to number 9 includes the step of comparing the phase position confidence signal with one or more thresholds to generate discrete phase position confidence signals.

[0247] 11. The method described according to number 3 includes the following steps:

[0248] - A binary, digital, or analog distance value formed between the feature vector signal and one or more prototype values ​​of the signal variation curve feature for an identifiable category of signal variation curve feature;

[0249] When the distance value is lower than one or more predetermined binary, digital, or analog distance values, the identifiable signal change curve feature category is assigned as an identified signal change curve feature.

[0250] 12. According to the method described in number 3, at least one of the signal change curve feature categories is wavelet.

[0251] 13. The method according to number 12, wherein the at least one wavelet is a triangular wavelet.

[0252] 14. The method according to number 12, wherein the at least one wavelet is a rectangular wavelet.

[0253] 15. The method according to number 12, wherein the at least one wavelet is a sinusoidal half-wavelet.

[0254] 16. The method according to number 12, wherein one of the parameters of the signal object is...

[0255] - The time shift of the wavelet of the identified signal change curve characteristics, or

[0256] -Time compression or expansion of wavelets representing the characteristics of identified signal variation curves, or

[0257] - The amplitude of the wavelet representing the characteristics of the identified signal variation curve.

[0258] 17. The method according to number 3, wherein the transmission of the at least one identified signal change curve feature category and the at least one assigned signal change curve feature parameter is performed according to the FIFO principle.

[0259] 18. The method according to number 3, wherein the transmission of the fault state of the sensor

[0260] - Transmission relative to the at least one identified signal variation curve feature category and / or - Transmission relative to the assigned signal variation curve feature parameters

[0261] Proceed with higher priority.

[0262] 19. The method according to number 3, wherein the signal change curve is characterized by the intersection of the amplitude of the envelope signal 1 and the amplitude of the threshold signal SW in the rising direction.

[0263] 20. The method according to number 3, wherein the signal change curve is characterized by the intersection of the amplitude of the envelope signal 1 and the amplitude of the threshold signal SW in the descending direction.

[0264] 21. The method according to number 3, wherein the characteristic of the signal change curve is the maximum value of the amplitude of the envelope signal 1 above the amplitude of the threshold signal SW.

[0265] 22. The method according to number 3, wherein the characteristic of the signal change curve is the minimum value of the amplitude of the envelope signal 1 above the amplitude of the threshold signal SW.

[0266] 23. The method according to number 3, wherein the signal change curve feature is a predefined time series and / or time grouping of other signal change curve features.

[0267] 24. The method according to number 23, wherein transmitting the at least one identified signal change curve feature category and the at least one assigned signal change curve feature parameter is transmitting a signal change curve feature category as a predefined time series of signal change curve features of other signal change curve features, and wherein at least one signal change curve feature category of at least one of the other signal change curve features is not transmitted.

[0268] 25. The method according to number 1 or 3, wherein the data transmission is performed via a bidirectional single-wire data bus, wherein,

[0269] The sensor transmits the data to the computer system in a current-modulated manner, and the computer system transmits the data to the sensor in a voltage-modulated manner.

[0270] 26. The method according to numeral 25, characterized in that the data transmission is performed using a PSI5 data bus and / or a DSI3 data bus.

[0271] 27. The method according to number 25, wherein data is transmitted to the computer system at a transmission rate of >200 kilobits per second, and data is transmitted from the computer system to the at least one sensor at a transmission rate of >10 kilobits per second, preferably 20 kilobits per second.

[0272] 28. The method according to number 25, wherein, in order to transmit data from the sensor to the computer system, a transmitting current is modulated onto the data bus, and wherein the current intensity of the transmitting current is <50mA, preferably <5mA.

[0273] 29. A sensor, particularly an ultrasonic sensor, adapted to perform the method according to one or more of numbers 1 to 28.

[0274] 30. A computer system adapted to perform the method according to one or more of the numbers 1 to 28.

[0275] 31. A method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle, comprising or including the following steps:

[0276] -Emit an ultrasonic burst pulse α;

[0277] - Receives ultrasonic signals and generates a received signal β;

[0278] - Perform data compression on the received signal to produce compressed data γ;

[0279] - The compressed data is transmitted to the computer system δ.

[0280] 32. A method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle, comprising or including the following steps:

[0281] -Emit an ultrasonic burst pulse, which has a start 57 and an end 56α for emitting the ultrasonic burst pulse;

[0282] - Receive the ultrasonic signal and receive it for at least 56 minutes from the end of the transmission of the ultrasonic burst pulse. E Internally formed received signal β;

[0283] - The compressed data γ, δ are transmitted to the computer system via a data bus, particularly a single-wire data bus; - wherein data transmission from the sensor to the computer system 54

[0284] • The start command 53 from the computer system via the data bus to the sensor begins and before the end 56 of transmitting the ultrasonic burst pulse, or

[0285] • After the start command 53 from the computer system via the data bus to the sensor and before the start 57 of transmitting the ultrasonic burst pulse, and

[0286] -The transmission 54 is executed periodically and continuously after the start instruction 53 until the data transmission 58 ends, and

[0287] -The end of the data transmission 58 occurs in time at the reception time T. E After it ended.

[0288] 33. A method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle, comprising or including the following steps:

[0289] -Emits a burst of ultrasonic pulses;

[0290] - Receive ultrasonic signals and generate a received signal;

[0291] - A feature vector signal is formed from the received signal;

[0292] - Identify signal objects within the received signal and classify the signal objects into the identified signal object category.

[0293] • Each signal object thus identified and classified is assigned at least one assigned signal object parameter and a symbol corresponding to the signal object category determined for the signal object, or

[0294] • For each signal object thus identified and classified, at least one assigned signal object parameter and a symbol for the signal object are determined;

[0295] - Transmit at least one symbol of the identified signal object category and at least one assigned signal object parameter of the identified signal object category.

[0296] 34. The method according to number 33, wherein at least one symbol of the identified signal object category and at least one assigned signal object parameter of the identified signal object category are transmitted preferentially.

[0297] 35. The method according to one or more of numbers 33 to 34, wherein at least one assigned signal object parameter transmitted along with at least one identified signal object category is a time value that indicates a time position suitable for inferring from the time since the transmission of the previous ultrasonic burst pulse.

[0298] 36. The method according to one or more of numbers 34 or 35, including the additional steps:

[0299] - Determine the specific distance of the object based on the stated time value.

[0300] 37. The method according to one or more of numbers 33 to 36, including the additional step:

[0301] - Determine the linear frequency modulation value as the assigned signal object parameter, which indicates whether the identified signal object is an echo of an ultrasonic emission burst pulse with positive, negative, or nonlinear frequency modulation characteristics.

[0302] 38. The method according to one or more of numbers 33 to 37, including the additional step:

[0303] - A confidence signal is generated by forming a correlation between the received signal or a signal derived from the received signal on one side and a reference signal on the other side.

[0304] 39. The method according to one or more of numbers 33 to 38, including the additional step:

[0305] - Generates a phase signal.

[0306] 40. The method of claim 39, further comprising the additional step:

[0307] - A phase position confidence signal is generated by correlating the phase signal formed in one aspect or the signal derived from the phase signal with a reference signal.

[0308] 41. The method according to number 40, including the additional step:

[0309] - The phase position confidence signal is compared with one or more thresholds to generate discrete phase position confidence signals.

[0310] 42. The method according to one or more of numbers 33 to 41, including the additional step:

[0311] - A binary, digital, or analog distance value formed between the feature vector signal and one or more signal object prototype values ​​for an identifiable signal object category;

[0312] - When the absolute value of the distance value is numerically lower than one or more predetermined binary, digital, or analog distance values, the identifiable signal object category is assigned as an identified signal object.

[0313] 43. The method described according to one or more of numbers 33 to 42, wherein at least one signal object category is a wavelet.

[0314] 44. The method described according to number 43, wherein the at least one wavelet is a triangular wavelet.

[0315] 45. The method according to one or more of numbers 43 to 44, wherein the at least one wavelet is a rectangular wavelet.

[0316] 46. ​​The method according to one or more of numbers 43 to 45, wherein the at least one wavelet is a sinusoidal half-wavelet.

[0317] 47. The method according to one or more of numbers 43 to 46, wherein one of the parameters of the signal object is...

[0318] • The time shift of the wavelet of the identified signal object, or

[0319] • Time compression or spreading of the wavelet of the identified signal object, or

[0320] • The amplitude of the wavelet of the identified signal object.

[0321] 48. The method according to one or more of numbers 33 to 47, wherein the at least one identified signal object category and the at least one assigned signal object parameter are transmitted according to the FIFO principle, wherein the FIFO principle means that the identified signal object category with an earlier timestamp is transmitted before the identified signal object category with a later timestamp.

[0322] 49. The method according to one or more of numbers 33 to 48, wherein the transmission of the fault state of the sensor is relative to the transmission of the at least one identified signal object category and / or

[0323] • Transmission of parameters relative to the assigned signal object

[0324] Proceed with higher priority.

[0325] 50. The method according to one or more of numbers 33 to 49, wherein the signal object comprises a combination of two, three, four or more signal basic objects.

[0326] 51. The method of claim 50, wherein the basic signal object is the intersection of the absolute value of the amplitude of the envelope signal 1 and the absolute value of the threshold signal SW at the intersection moment.

[0327] 52. The method according to one or more of numbers 50 to 51, wherein the basic signal object is the intersection of the absolute value of the amplitude of the envelope signal 1 and the absolute value of the threshold signal SW in the ascending direction at the intersection moment.

[0328] 53. The method according to one or more of numbers 50 to 52, wherein the basic signal object is the intersection of the absolute value of the amplitude of the envelope signal 1 and the absolute value of the threshold signal SW at the intersection time in a descending direction.

[0329] 54. The method according to one or more of numbers 50 to 53, wherein the signal basic object is the maximum value of the absolute value of the amplitude of the envelope signal 1 at the maximum value time, which is above the absolute value of the threshold signal SW.

[0330] 55. The method according to one or more of numbers 50 to 54, wherein the signal basic object is the minimum value of the absolute value of the amplitude of the envelope signal 1 at the minimum time above the absolute value of the threshold signal SW.

[0331] 56. The method according to one or more of numbers 50 to 55, wherein the signal basic object is a predefined time series and / or time grouping of other signal basic objects.

[0332] 57. The method according to one or more of numbers 33 to 56, wherein transmitting at least one symbol of an identified signal object category and at least one assigned signal object parameter of the identified signal object category is a signal object category that transmits a signal object as a predefined time series of other signal objects, and wherein at least one of these other signal objects is not transmitted.

[0333] 58. The method according to one or more of items 31 to 57,

[0334] -The data transmission is performed via a bidirectional single-wire data bus.

[0335] - wherein the sensor transmits the data to the computer system in a current-modulated manner, and - wherein the computer system transmits the data to the sensor in a voltage-modulated manner.

[0336] 59. The method according to claim 58, wherein the data transmission is performed using a PSI5 data bus and / or a DSI3 data bus.

[0337] 60. The method according to one or more of numbers 58 or 59, wherein data is transmitted to the computer system at a transmission rate greater than 200 kilobits per second, and data is transmitted from the computer system to the at least one sensor at a transmission rate greater than 10 kilobits per second, preferably 20 kilobits per second.

[0338] 61. The method according to one or more of numbers 58, 59, or 60, wherein, in order to transmit data from the sensor to the computer system, a transmitting current is modulated onto the data bus, and wherein the current intensity of the transmitting current is less than 50 mA, preferably less than 5 mA.

[0339] 62. A method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle, comprising the steps of:

[0340] -Emits a burst of ultrasonic pulses;

[0341] - Receives ultrasound signals and forms a time-discrete received signal consisting of a sequence of sampled values.

[0342] -Time data (timestamp) is assigned to each sample value;

[0343] -A first parameter signal with a first characteristic is determined from the sequence of sampled values ​​of the received signal using a first filter.

[0344] • Wherein, the parameter signal is constructed as a time-discrete sequence of parameter signal values, and

[0345] • In this process, exactly one time data (timestamp) is assigned to each parameter signal value;

[0346] - Determine at least one additional parameter signal, which is assigned to a characteristic of the additional parameter signal, from the sequence of sampled values ​​of the received signal by means of an additional filter assigned to the additional parameter signal.

[0347] • Wherein, the other parameter signals are respectively constructed as time-discrete sequences of other parameter signal values, and

[0348] • In this process, each additional parameter signal value is assigned a time data (timestamp) that is identical to the corresponding parameter signal value, and

[0349] -Hereinafter, the first parameter signal and the other parameter signal will be referred to together as the feature vector signal, and

[0350] - Wherein, the feature vector signal is thus constructed as a discrete-time sequence of feature vector signal values, hereinafter also referred to as feature vector signal values, which consist of parameter signal values ​​and other parameter signal values, each having the same time data (time stamp), and

[0351] -In this process, the corresponding time data (timestamp) is assigned to each feature vector signal value formed in this way;

[0352] - Compare the feature vector signal value of the time data with the threshold vector and generate a Boolean result, which can have a first value and a second value;

[0353] - The feature vector signal value and the time data (timestamp) assigned to the feature vector signal value are transmitted from the sensor to the computer system, if the Boolean result is for that time data (timestamp).

[0354] If it has a first value.

[0355] 63. A method for transmitting sensor data, particularly ultrasonic sensor data, from a sensor to a computer system, especially in a vehicle, comprising the steps of:

[0356] -Emits a burst of ultrasonic pulses;

[0357] - Receives ultrasound signals and forms a time-discrete received signal consisting of a sequence of sampled values.

[0358] -Time data (timestamp) is assigned to each sample value;

[0359] - Using at least one filter, determine at least two parameter signals from the sequence of sampled values ​​of the received signal, each relating to the existence of a basic signal object assigned to a corresponding parameter signal.

[0360] • Wherein, the parameter signal is constructed as a time-discrete sequence of the corresponding parameter signal values, and

[0361] • In this process, exactly one time data point is assigned to each parameter signal value;

[0362] -Hereinafter, the first parameter signal and the other parameter signal will be referred to together as the feature vector signal.

[0363] as well as

[0364] - Wherein, the feature vector signal is thus constructed as a time-discrete sequence of feature vector signal values, the feature

[0365] The vector signal value consists of parameter signal values ​​and other parameter signal values, which each have the same time data (time stamp), and

[0366] -In this process, the corresponding time data (timestamp) is assigned to each feature vector signal value formed in this way;

[0367] - Evaluate the time-varying curve of the eigenvector signal and determine the evaluation value (distance) with the time-varying curve.

[0368] In the case of (separation), the signal object is inferred, the signal object is composed of the time series of basic signal objects, and

[0369] Symbols were assigned.

[0370] - Compare the evaluation value of the time data (timestamp) with the threshold vector, and generate a Boolean result.

[0371] The result can have a first value and a second value;

[0372] - Transmit the symbol of the signal object and the time data (timestamp) assigned to the symbol from the sensor.

[0373] The data is input to the computer system if the Boolean result has a first value for the time data (timestamp).

[0374] 64. A sensor, particularly an ultrasonic sensor, adapted for or configured to perform one or more of the methods according to numbers 32 to 63.

[0375] 65. A computer system adapted for or configured to perform the method described according to one or more of numbers 32 to 63.

[0376] 66. A sensor system,

[0377] - Having at least one computer system as described in figure 63, and

[0378] - Equipped with at least two sensors as described in numeral 65

[0379] - wherein the sensor system is configured to operate or be able to operate according to one or more of the methods described in accordance with numbers 32 to 63, or to perform data transmission between the sensor and the computer system.

[0380] 67. The sensor system according to digit 66,

[0381] - wherein the ultrasonic received signals, i.e., at least two ultrasonic received signals, are compressed within the sensor by means of one or more of the methods described in numbers 32 to 63, and transmitted to the computer system.

[0382] system, and

[0383] - wherein the at least two ultrasonic received signals are reconstructed into reconstructed ultrasonic received signals within the computer system.

[0384] 68. The sensor system according to numeral 67, wherein the computer system performs object recognition on objects in the environment of the sensor by means of reconstructed ultrasonic received signals.

[0385] 69. The sensor system according to numeral 68, wherein the computer system performs object recognition on objects in the sensor's environment by means of reconstructed ultrasonic received signals and additional signals from other sensors, particularly radar sensors.

[0386] 70. A sensor system according to one or more of numbers 68 or 69, wherein the computer system creates an environmental map for the sensor or a device in which the sensor is part, based on an identified object.

[0387] List of symbols in the attached diagram

[0388] alpha emission ultrasonic burst pulse

[0389] β receives the ultrasonic burst pulse reflected by the object and converts it into an electrical received signal.

[0390] γ compresses the electrical received signal and forms a sampled electrical received signal, wherein, preferably, a timestamp can be assigned to each sample value of the electrical received signal.

[0391] γb, for example, determines multiple spectral values ​​using a matched filter tailored to the signal object category. These multiple spectral values ​​together form a feature vector. Preferably, this formation occurs sequentially, resulting in a stream of feature vector values. It is also preferable to assign a timestamp value to each feature vector value again.

[0392] γc Optionally, but preferably, the following is performed: normalize the eigenvector spectral coefficients of the corresponding eigenvector of the timestamp value before associating it with the signal object category existing in the form of pre-given eigenvector values ​​in the prototype library; γd determine the distance between the current eigenvector value and the value of the signal object category existing in the form of pre-given eigenvector values ​​in the prototype library.

[0393] γe selects the most similar signal object category in the form of pre-given feature vector values ​​from the (prototype) library, preferably having the smallest distance to the current feature vector, and takes the symbol of the signal object category as the identified signal object along with the timestamp value as compressed data. If necessary, additional data, particularly signal object parameters such as their amplitude, can be taken as compressed data. The compressed data then forms a compressed version of the received signal.

[0394] δ transmits the compressed electrical received signal to the computer system:

[0395] 1. Envelope of the received ultrasound signal

[0396] 2. The output signals (transmitted information) of the existing IO interface

[0397] 3. Information transmitted via the LIN interface according to existing technology

[0398] 4. The first intersection point in the downward direction of the envelope 1 of the received signal and the threshold signal SW.

[0399] The first intersection of the envelope 1 and the threshold signal SW in the upward direction.

[0400] The first maximum value of envelope 1 above the threshold signal SW

[0401] 7. The second intersection of the envelope 1 and the threshold signal SW in the downward direction.

[0402] The second intersection of the 8-envelope 1 and the threshold signal SW in the upward direction

[0403] The second maximum value of envelope 1 above the threshold signal SW.

[0404] The first minimum value of the 10-envelope 1 above the threshold signal SW

[0405] The third maximum value of envelope 11 above the threshold signal SW

[0406] The third intersection of envelope 12 and threshold signal SW in the downward direction

[0407] The third intersection of envelope 1 and threshold signal SW in the upward direction.

[0408] The fourth maximum value of envelope 14 above the threshold signal SW

[0409] The fourth intersection of envelope 1 and threshold signal SW in the downward direction.

[0410] The fourth intersection point of the 16-envelope 1 and the threshold signal SW in the upward direction

[0411] The fifth maximum value of envelope 17 above the threshold signal SW

[0412] The fifth intersection of the 18-envelope 1 and the threshold signal SW in the downward direction.

[0413] The fifth intersection of envelope 1 and threshold signal SW in the upward direction.

[0414] The sixth maximum value of envelope 1 above the threshold signal SW.

[0415] The sixth intersection of envelope 1 and threshold signal SW in the downward direction.

[0416] The sixth intersection of envelope 1 and threshold signal SW in the upward direction.

[0417] 23. Envelope 1 is the seventh maximum value above the threshold signal SW.

[0418] The seventh intersection point of the 24-envelope 1 and the threshold signal SW in the downward direction.

[0419] 25. Envelope during ultrasound burst pulse

[0420] 26. Data at the first intersection point 4 in the downward direction of envelope 1 and threshold signal SW is transmitted via a preferred bidirectional data bus.

[0421] 27. Data at the first intersection point 5 in the upward direction of envelope 1 and threshold signal SW is transmitted via a preferred bidirectional data bus.

[0422] 28. Data of the first maximum value 6 above the threshold signal SW in envelope 1 is transmitted via a preferred bidirectional data bus.

[0423] 29. Data at the second intersection point 7 of envelope 1 and threshold signal SW in the downward direction is transmitted via a preferred bidirectional data bus. 30. Data at the second intersection point 8 of envelope 1 and threshold signal SW in the upward direction is transmitted via a preferred bidirectional data bus. 31. Data at the second maximum value 9 of envelope 1 above threshold signal SW and the exemplary first minimum value 10 of envelope 1 above threshold signal SW are transmitted via a preferred bidirectional data bus.

[0424] 32. Data of the third maximum value 1 above the threshold signal SW of envelope 1 is transmitted via the preferred bidirectional data bus. 34. Data of the third intersection point 12 of envelope 1 and threshold signal SW in the downward direction is transmitted via the preferred bidirectional data bus.

[0425] 35. Data at the third intersection point 13 in the upward direction of envelope 1 and threshold signal SW is transmitted via a preferred bidirectional data bus.

[0426] 36. Data of the fourth maximum value 14 above the threshold signal SW of envelope 1 is transmitted via the preferred bidirectional data bus. 37. Data of the fourth intersection point 15 of envelope 1 and threshold signal SW in the downward direction is transmitted via the preferred bidirectional data bus.

[0427] 38. Data at the fourth intersection point 16 of envelope 1 and threshold signal SW in the upward direction is transmitted via a preferred bidirectional data bus.

[0428] 39. Data of the fifth maximum value 17 above the threshold signal SW of envelope 1 is transmitted via the preferred bidirectional data bus. 40. Data of the fifth intersection point 18 of envelope 1 and threshold signal SW in the downward direction is transmitted via the preferred bidirectional data bus.

[0429] 41. Data at the fifth intersection point 19 in the upward direction of envelope 1 and threshold signal SW is transmitted via a preferred bidirectional data bus.

[0430] 42. Data at the sixth intersection point 21 in the downward direction of envelope 1 and threshold signal SW is transmitted via a preferred bidirectional data bus.

[0431] 43. After reception is completed, the received echo data is transmitted on the LIN bus according to existing technology.

[0432] 44. Data is transmitted on a LIN bus according to existing technology before the ultrasonic burst pulse is emitted.

[0433] 45. Data is transmitted via an I / O interface according to existing technology before the ultrasonic burst pulse is emitted.

[0434] 46. ​​Effect of ultrasonic emission burst pulses on the output signal of an I / O interface according to existing technology

[0435] 47. Signals 5, 6, and 7 of the first echo on the I / O interface according to the prior art.

[0436] 48 Signals of the second echo 8, 9, 10, 11, and 12 on the I / O interface according to the prior art; 49 Signals of the third and fourth echo 13, 14, and 15 on the I / O interface according to the prior art; 50 Signals of the fifth echo 16, 17, and 18 on the I / O interface according to the prior art.

[0437] 51 The sixth echo signals 19, 20, and 21 on the I / O interface according to the prior art

[0438] 52 The seventh echo signals 22, 23, and 24 on the I / O interface according to the prior art

[0439] 53. Start command from computer system to sensor via data bus

[0440] 54 Preferably, periodic automatic data transmission between the sensor and the computer system according to the DSI3 standard

[0441] Diagnostic bits after 55 measurement cycles

[0442] 56. End of ultrasonic burst pulse transmission (end of burst pulse transmission). Preferably, the end of the ultrasonic burst pulse coincides with point 4.

[0443] 57. Beginning of ultrasonic burst pulse transmission (beginning of burst pulse transmission)

[0444] 58. End of data transmission

[0445] a method for transmitting information by means of an I / O interface of existing technology, which transmits received ultrasonic echoes.

[0446] A first triangle object

[0447] au "arbitrary unit" = freely chosen unit

[0448] B Second Triangle Object

[0449] b. Information transmitted in order to transmit received ultrasonic echoes using the existing LIN interface.

[0450] c. Information transmitted for transmitting the received ultrasonic echo using the proposed method and device, with an envelope for comparison.

[0451] d. Information transmitted using the proposed method and device for transmitting received ultrasonic echoes, without an envelope.

[0452] The schematic signal shape of e when transmitting received echo information using an existing I / O interface; the amplitude of the envelope of the received ultrasonic signal En.

[0453] f shows the schematic signal shape when transmitting received echo information via a LIN interface using existing technology. g shows the schematic signal shape when transmitting received echo information via a bidirectional data interface.

[0454] SB emits a burst pulse

[0455] SW threshold

[0456] t time

[0457] T E Reception time. The reception time typically begins 56 days after the end of the transmitted ultrasonic burst pulse. Reception may begin earlier. However, this may lead to problems that may require additional measures.

Claims

1. A method for transmitting sensor data from a sensor to a computer system, comprising the steps of: - Emit an ultrasonic burst pulse; - Receives ultrasound signals and forms a time-discrete ultrasound received signal consisting of a sequence of sampled values. - Time data is assigned to each sample value; - At least two parameter signals are determined from the sequence of sampled values ​​of the received signal using at least one filter, each parameter signal relating to the existence of a signal fundamental object assigned to the corresponding parameter signal. • in, The parameter signals are constructed as time-discrete sequences of the corresponding parameter signal values, and • In this process, a time data is assigned to each parameter signal value; - Wherein, in the following text, the first parameter signal having a first characteristic and the other parameter signal having characteristics assigned to the other parameter signal are collectively referred to as the feature vector signal, and - Wherein, the feature vector signal is thus constructed as a time-discrete sequence of feature vector signal values, which are composed of parameter signal values ​​and other parameter signal values, each having the same time data, and - Wherein, the corresponding time data is assigned to each of the feature vector signal values ​​thus formed; - Evaluate the time-varying curves of the eigenvector signal and, based on the evaluation values ​​having time-varying curves, infer the signal object, which consists of time series of basic signal objects and is assigned signs. - Compare the evaluation values ​​of the time data with a threshold vector, and generate a Boolean result, which can have a first value and a second value; and - Transmit the symbol of the signal object and the time data assigned to the symbol from the sensor to the computer system, if the Boolean result has a first value for the time data.

2. An ultrasonic sensor adapted or configured to perform the method according to claim 1.

3. A computer system adapted or configured to perform the method according to claim 1.

4. A sensor system, - Having at least one computer system according to claim 3, and - Having at least two ultrasonic sensors according to claim 2, - in, The sensor system is configured such that data transmission between the ultrasonic sensor and the computer system operates or is capable of operating according to the method of claim 1.

5. The sensor system according to claim 4, characterized in that, - In each of at least one of the sensors, the ultrasonic received signal, i.e., at least two ultrasonic received signals, is compressed by means of the method according to claim 1, and transmitted to the computer system, and - The at least two ultrasound received signals are reconstructed into reconstructed ultrasound received signals within the at least one computer system.

6. The sensor system according to claim 5, characterized in that, The computer system uses reconstructed ultrasonic received signals to perform object recognition on objects in the environment of the sensor.

7. The sensor system according to claim 6, characterized in that, The computer system performs object recognition on objects in the sensor's environment by means of reconstructed ultrasonic received signals and additional signals from other sensors.

8. The sensor system according to claim 6 or 7, characterized in that, The computer system creates an environmental map based on the identified objects for the sensor or devices in which the sensor is part.

9. A method for transmitting sensor data from a sensor to a computer system, comprising the steps of: -Emits a burst of ultrasonic pulses; - Receives ultrasound signals and forms a time-discrete received signal consisting of a sequence of sampled values. -Time data is assigned to each sample value; -A first parameter signal with a first characteristic is determined from the sequence of sampled values ​​of the received signal using a first filter. • in, The parameter signal is constructed as a time-discrete sequence of parameter signal values, and • In this process, exactly one time data point is assigned to each parameter signal value; - Determine at least one additional parameter signal, which is assigned to a characteristic of the additional parameter signal, from the sequence of sampled values ​​of the received signal by means of an additional filter assigned to the additional parameter signal. • Wherein, the other parameter signals are respectively constructed as time-discrete sequences of other parameter signal values, and • In this process, time data corresponding to the corresponding parameter signal value is allocated to each other parameter signal value, and -Hereinafter, the first parameter signal and the other parameter signal will be referred to together as the feature vector signal, and - Wherein, the characteristic vector signal is thus constructed as a time-discrete sequence of characteristic vector signal values, hereinafter also referred to as characteristic vector signal values, which consist of parameter signal values ​​and other parameter signal values, each having the same time data, and -In this process, the corresponding time data is assigned to each of the feature vector signal values ​​thus formed; - Compare the feature vector signal value of the time data with the threshold vector and generate a Boolean result, which can have a first value and a second value; - The feature vector signal value and the time data assigned to the feature vector signal value are transmitted from the sensor to the computer system if the Boolean result has a first value for the time data.

10. An ultrasonic sensor adapted to or configured to perform the method according to claim 9.

11. A sensor system, -Having at least one computer system, and -Having at least two ultrasonic sensors according to claim 10, -in, The sensor system is configured such that data transmission between the ultrasonic sensor and the computer system operates or is capable of operating according to the method of claim 9.

12. The sensor system according to claim 11, characterized in that, - The ultrasonic received signals, i.e., at least two ultrasonic received signals, are compressed within the sensor by means of the method according to claim 9, and transmitted to the computer system. - The at least two ultrasonic received signals are reconstructed into reconstructed ultrasonic received signals within the computer system.

13. The sensor system according to claim 12, characterized in that, The computer system uses reconstructed ultrasonic received signals to perform object recognition on objects in the environment of the sensor.

14. The sensor system according to claim 13, characterized in that, The computer system performs object recognition on objects in the sensor's environment by means of reconstructed ultrasonic received signals and additional signals from other sensors, particularly radar sensors.

15. The sensor system according to claim 13 or 14, characterized in that, The computer system creates an environmental map for the sensor or a device in which the sensor is part, based on the identified objects.

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