Method of operating a detection device using interference processing with an artificial neural network - Patent Application 20070122997

Abstract

The present invention relates to a method (44) for operating a detection device, particularly a detection device (14) for a vehicle (10), a detection device, a driver assistance system, and a vehicle. In the method (44), at least one electromagnetic beam (26) is emitted by the detection device into a monitoring area of ​​the detection device. The detection device receives the at least one electromagnetic beam originating from the monitoring area and converts it into at least one detection variable (40) that can be processed by at least one evaluation device. Based on the at least one detection variable (40), at least one interference process is performed using at least one artificial neural network (CNN). In the at least one interference process, at least one interference analysis (46) is performed, in which the at least one detection variable (40) is examined for known interference patterns (52) of interference variables using the at least one artificial neural network (CNN). If at least one known interference pattern (52) is recognized, the at least one detection variable (40) is corrected by the interference variable belonging to the at least one recognized interference pattern (52).

Description

[Technical Field]

[0001] The present invention relates to a method for operating a detection device, in particular a detection device for a vehicle, at least one electromagnetic beam is transmitted using a detection device into a region monitored by the detection device; At least one electromagnetic beam originating from the monitoring area is received using a detection device and converted into at least one captured variable that can be processed using at least one evaluation device, At least one interference processing process is performed based on the at least one captured variable using at least one artificial neural network.

[0002] The invention also relates to a detection device, in particular a detection device for a vehicle, comprising: at least one transmitting device for transmitting an electromagnetic beam into a monitoring area of ​​the detection device; at least one means for receiving an electromagnetic beam originating from a surveillance region and determining a capture parameter from the received electromagnetic beam; at least one means for performing an interference treatment process based on the captured variables; At least one of the means comprises at least one artificial neural network.

[0003] Furthermore, the invention relates to a driver assistance system, in particular a driver assistance system for a vehicle, having at least one detection device, the at least one detection device comprising: at least one transmitting device for transmitting an electromagnetic beam into a monitoring area of ​​the at least one detecting device; at least one means for receiving an electromagnetic beam originating from the surveillance region and determining a capture parameter from the received electromagnetic beam; and at least one means for performing an interference treatment process based on the captured variables, the at least one means comprising at least one artificial neural network.

[0004] Furthermore, the present invention relates to a vehicle having at least one detection device, the at least one detection device comprising: at least one transmitting device for transmitting an electromagnetic beam into a monitoring area of ​​the at least one detecting device; at least one means for receiving an electromagnetic beam originating from the surveillance region and determining a capture parameter from the received electromagnetic beam; and at least one means for performing an interference treatment process based on the captured variables, the at least one means comprising at least one artificial neural network. [Background technology]

[0005] A method for operating a radar system having at least two radar sensors is known from DE 10 2020107 372 A1, which provides, inter alia, that the following steps are carried out successively, preferably in the order listed or in any order, although individual and / or all steps can also be carried out repeatedly: performing a signal emission at the radar sensors in order to emit in each case (via the radar sensors) at least one radar signal, preferably via at least one transmitting antenna of the respective radar sensor, in particular in the form of an electromagnetic signal that is emitted into the environment external to the radar sensor, performing signal processing in the radar sensors so that each radar sensor determines an acquisition parameter specific to the respectively emitted radar signal, in particular the emitted radar signal reflected by the target and delayed by the signal propagation time and which can be received, for example, by at least one receiving antenna of the radar sensor; performing an interference assessment in order to in each case detect at least one interference at the radar sensor based on the respective acquisition variables, wherein the interference assessment can preferably be performed centrally for all of the acquisition variables at the respective radar sensor or individually for each acquisition variable, providing at least one, or at least two, or at least four, or at least six adaptation options for avoiding at least one detected interference by adapting the signal radiation; performing an evaluation of at least one adaptation option for each of the radar sensors, in particular by each of the radar sensors; performing an adjustment of the adaptive options between the various radar sensors based on the evaluation; performing an adaptation of the signal radiation in accordance with at least one adaptation option based on the coordination, in particular by selecting an adaptation option only if and / or which adaptation option causes a reduction in interference for a large proportion of the radar sensors.

[0006] The present invention is based on the object of designing a method, a detection device, a driver assistance system and a vehicle of the type mentioned in the introduction, which allows for an improved determination of the capture variable. In particular, the intention is to improve the signal-to-noise ratio of the capture variable. In particular, the intention is alternatively or additionally to improve the determination of the capture variable in terms of costs, in particular in terms of material costs, component costs and / or installation costs, and / or in terms of the effectiveness of the capture variable. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] German Patent Application Publication No. 102020107372(A1) Summary of the Invention

[0008] According to the present invention, in the case of the method, the object is achieved by the fact that at least one interference analysis is performed during at least one interference treatment process, in which analysis at least one capture variable is examined for known interference patterns of interference variables using at least one artificial neural network, and if at least one known interference pattern is recognized, interference variables belonging to the at least one recognized interference pattern are purged from the at least one capture variable.

[0009] According to the invention, at least one electromagnetic beam is transmitted into a monitored area, and the at least one electromagnetic beam originating from the monitored area is received using a detection device and converted into at least one captured variable.

[0010] The electromagnetic radiation originating from the monitored area can be advantageously converted into a captured variable in the form of an electrical received signal by means of a detection device, in particular by means of at least one receiving device which can have at least one antenna, which can be processed by means of electrical means, in particular by means of an electrical control and / or evaluation device.

[0011] The electromagnetic beam that can be received by the detection device may comprise or consist of an electromagnetic echo beam. The electromagnetic echo beam may be derived from an electromagnetic beam transmitted using the detection device and reflected by at least one object. The capture variables determined from the echo beam are specific to the reflecting object. For better discrimination, the capture variables derived solely from the echo beam may also be referred to as "echo reception variables."

[0012] Alternatively or additionally, the received electromagnetic beam may comprise or consist of an interference beam from an interference source. The interference beam received using the detection device is converted into a corresponding reception variable, similar to an echo beam. For better discrimination, the reception variable derived solely from the interference variable may also be called an "interference variable."

[0013] The capture variables can be a superposition of any echo reception variables and any interference variables. If no interference beams are captured, the capture variables consist only of the echo variables, if present. If no echo beams are captured, the capture variables consist only of the interference variables, if present.

[0014] According to the present invention, at least one interference processing process is performed based on at least one captured variable using at least one artificial neural network in order to reduce the influence of any interference sources and corresponding interference variables on the determination of information about the monitored area, in particular object information about objects in the monitored area.

[0015] The object information may be distance, direction and / or velocity variables that characterize the distance, direction and / or velocity of the object relative to the detection device or a corresponding reference point or reference system.

[0016] At least one interference analysis is performed during the at least one interference processing process. During the at least one interference analysis, at least one capture variable is examined for a known interference pattern. The known interference pattern is derived from an interference variable that is known prior to performing the interference analysis. If a known interference pattern is recognized, the corresponding interference variable is purged from the capture variable.

[0017] The known interference source may in particular be an external interference source, which may be another radiation source, in particular a radar source, transmitting an electromagnetic beam in the same wavelength range as the detection device according to the invention or in an overlapping wavelength range.

[0018] An interference beam from a known interference source can induce a characteristic interference pattern in the corresponding interference variable determined using the detection device. In particular, a corresponding noise pattern from the known interference source can be identified in the determined captured variable. Thus, if a known interference pattern is recognized, the corresponding interference variable can be purged from the captured variable. Thus, the signal-to-noise ratio of the captured variable, particularly the echo received variable contained therein, can be improved overall.

[0019] According to the present invention, machine learning is used to analyze the captured variables. Depending on the object type, material, shape, XYZ coordinates, environmental conditions (e.g., rain), external noise, environmental or object dynamics, and other factors, the shape of the received electromagnetic beam will vary and also depend on the transmitted electromagnetic beam.

[0020] The interference analysis uses at least one artificial neural network. For this purpose, a suitable multi-layer neural network (deep neural network) can be specified, which has an input layer, several intermediate (hidden) layers, and an output layer. For training purposes, several different scenarios can be pre-recorded using the detection device and used to train the neural network. Depending on the type of application and the degree of automation, e.g., SAE Level 0 to SAE Level 4, different classes can be used.

[0021] Purging at least one capture variable using at least one interference analysis also allows for the use of a detection device with less accurate components to determine sufficiently good data. It is also possible to use components that may themselves be subject to greater noise. Therefore, simpler and less expensive components can be used overall for the detection device, which can still be used to determine a sufficiently good capture variable for the application, and possibly a corresponding degree of automation. Therefore, the performance of the detection device can be improved by correcting measurements using at least one interference analysis.

[0022] By improving the signal-to-noise ratio of the captured variables, the validity of the data determined therefrom can be improved. Therefore, a higher level of safety can be achieved using the detection device according to the present invention. The detection device according to the present invention can be used to determine data compliant with the automation levels SAE 0 to 4, which are required for autonomous or semi-autonomous driving.

[0023] The present invention can be advantageously used in detection devices for vehicles, particularly automobiles. Advantageously, the present invention can be used in detection devices for land vehicles, particularly cars, trucks, buses, motorcycles, etc., aircraft, particularly drones, and / or ships. The present invention can also be used in detection devices for vehicles that can operate autonomously or at least semi-autonomously. However, the present invention is not limited to detection devices for vehicles. It can also be used in detection devices for steady-state operation of robots and / or machines, particularly construction or transport machines such as cranes, excavators, etc.

[0024] The detection device can be advantageously connected to or be part of at least one electronic control device of the vehicle or machine, in particular a driver assistance system and / or a chassis control system and / or a driver information device and / or a parking assistance system and / or a gesture recognition system, etc. In this way, at least some of the functions of the vehicle or machine can be performed autonomously or semi-autonomously using information acquired by the detection device.

[0025] The detection device can be used to capture stationary or moving objects, in particular vehicles, people, animals, plants, obstacles, uneven road surfaces, in particular potholes or rocks, road boundaries, traffic signs, open spaces, in particular parking spaces, precipitation, etc., and / or movements and / or gestures.

[0026] In one advantageous configuration of the method, at least one interference analysis can be performed repeatedly and the purged capture variables determined from each interference analysis can be combined to form at least one combined capture variable, which allows for a further improvement in the signal-to-noise ratio of the capture variables.

[0027] The at least one interference analysis can advantageously be performed 2 to 10 times, in particular 4 times. The signal-to-noise ratio is further improved with each pass of the at least one interference analysis. When the analysis is performed 4 times, the signal-to-noise ratio is particularly improved by a factor of 2.

[0028] In a further advantageous configuration of the method, a plurality of different electromagnetic beams can be transmitted into the same scene in the monitored area, and a respective capture variable can be determined;

[0029] At least one interference analysis can be performed on at least some of the plurality of captured variables thus determined, and a respective purged captured variable can be determined for at least some of the different transmitted electromagnetic beams;

[0030] At least some of the purged capture variables thus determined may be combined to form at least one combined capture variable.

[0031] This allows for a further improvement in the signal-to-noise ratio of the capture variables.

[0032] To capture the same scene, different electromagnetic beams can be transmitted within correspondingly small time windows.

[0033] Advantageously, multiple different electromagnetic beams can be transmitted sequentially to the same scene in the monitored area, thereby avoiding the transmitted electromagnetic beams interfering with each other.

[0034] Four different electromagnetic beams can be advantageously sent into the same scene, each capable of determining the capture variables and performing a separate interferometric analysis, which allows for correspondingly small time windows to be performed, and therefore the captured scene changes as little as possible.

[0035] The different electromagnetic beams may differ in terms of shape, wavelength, pulse duration, transmission duration, transmission power, coding, etc. By varying the transmitted electromagnetic beam, the corresponding echo received variable can be better distinguished from any interfering variable, thus allowing the interfering variable to be better identified and removed.

[0036] In a further advantageous configuration of the method, an artificial convolutional neural network can be used as at least one artificial neural network. An artificial convolutional neural network (CNN) is a biologically inspired machine learning concept aimed at extracting features. Since noise has patterns, particularly interference patterns, that differ from regular signals, particularly echo beam patterns, and particularly object patterns, the captured variables acquired after recognizing the interference pattern can be correspondingly reduced. In this case, it is even possible to vary the electromagnetic beam transmitted to the monitored area using the detection device for scanning. In this way, at least one interference analysis can be used to determine which electromagnetic beams originate from the beam transmitted by the detection device. Interference noise can be identified from this recognition and therefore removed by calculation.

[0037] In a further advantageous configuration of the method, During the at least one interferometric analysis, the at least one acquisition variable can be first examined for a known object pattern caused by an electromagnetic echo beam reflected off a known object; If the at least one known object pattern is recognized, an echo capture variable corresponding to the at least one known object pattern can be removed from the at least one capture variable; The at least one captured variable from which the recognized at least one echo capture variable has been removed can then be examined for known interference patterns of interference variables using at least one artificial neural network, and if the at least one known interference pattern is recognized, the interference variables belonging to the at least one recognized interference pattern can be purged from the original at least one captured variable, which can include the at least one echo capture variable, thereby further improving the signal-to-noise ratio.

[0038] As a result of the fact that at least one capture variable is first removed from the echo capture variable using a known object pattern, the corresponding interference pattern can be better identified, thus improving the removal of the original capture variable from the interference variable.

[0039] To some extent, object patterns caused by objects whose object patterns are already known can be first removed from at least one original captured variable. The object-pattern-removed captured variable can then be subjected to at least one further interference analysis, during which interference variables with known interference patterns can be recognized. The recognized interference variables can then be removed from at least one original captured variable, so that this purged captured variable ideally contains only object echo variables, provided that all interference variables have been identified.

[0040] In a further advantageous configuration of the method, Predefined interference patterns and / or possibly object patterns can be used for at least one interference analysis; and / or Interference patterns and / or object patterns learned during operation of the detection device can be used in at least one interference analysis, thus allowing the method to have more flexible access to a larger number of known interference patterns and / or known object patterns.

[0041] Predefined interference patterns and / or object patterns can be used in at least one interference analysis. These patterns can be learned in advance, particularly under laboratory conditions, and stored in a corresponding storage medium, particularly a storage medium of the detection device. In this way, when performing the method, the corresponding interference patterns and / or object patterns can be accessed more quickly.

[0042] Alternatively or additionally, interference patterns and / or object patterns learned during operation can be used, which allows the number of known interference patterns and / or object patterns to be continuously increased, which also allows the method to be continuously improved.

[0043] In a further advantageous configuration of the method, The signal converted from the electromagnetic beam using the receiving device of the detection device, in particular the electrical received signal, can be used as the capture variable; and / or Object information about an object captured during measurement by the detection device can be used as a capture variable, and the object information can be determined from a received signal, in particular an electrical received signal, converted from the electromagnetic beam using a receiving device of the detection device. In this way, at least one interference analysis can be performed at an appropriate processing level.

[0044] The received signal can be advantageously used as a capture variable, so that the interference analysis can be performed directly on the received signal at a lower processing level, in this way the interference variables can be removed very quickly.

[0045] Electrical reception signals, in particular voltage variables, can be advantageously used as capture variables. The electrical reception signals are generated during the conversion of the electromagnetic beam by means of the detection device, in particular by means of a receiving device. The electrical reception signals can be processed by means of electrical means, in particular by means of an electrical evaluation device.

[0046] The received signal may be an echo received signal derived from an echo beam, an interference signal derived from an interference beam, or a superposition of an echo received signal and an interference signal.

[0047] Alternatively or additionally, object information can be used as a capture variable. In this way, interference analysis can be performed at a higher processing level. Therefore, the usefulness of images with object information, especially range images, can be improved.

[0048] In a further advantageous configuration of the method, the method can be used to operate a detection device in the form of a radar sensor used to transmit an electromagnetic beam in the form of a radar beam.

[0049] Radar sensors are highly variable in the transmitted radar beam. This also allows for varying acquisition parameters to improve discrimination between object and interference patterns. Therefore, the same scene can be scanned using different radar beams, particularly consecutively. Thus, the signal-to-noise ratio can be improved overall in the purged acquisition parameters.

[0050] At least one receiving device of the detection device, in particular of a radar sensor, can advantageously be configured to receive an electromagnetic beam, in particular a radar beam, of the same type as the electromagnetic beam transmitted using the detection device.

[0051] The wavelength range in which the at least one receiving device is able to receive the electromagnetic beam may advantageously comprise the wavelength range in which the electromagnetic beam, in particular the radar beam, is emitted using a detection device, so that at least echoes of the transmitted electromagnetic beam, in particular the radar beam, can be reliably received.

[0052] In a further advantageous configuration of the method, at least one purged acquisition variable, in particular optionally at least one purged combined acquisition variable, can be further processed, in particular subjected to image processing, and / or At least one transmitting device and / or at least one receiving device of the detection apparatus may be adjusted based on at least one purged acquisition variable, in particular possibly on at least one purged combined acquisition variable.

[0053] At least one purged captured variable, and in particular possibly at least one purged combined captured variable, can be further advantageously processed to obtain further information about the monitored area.

[0054] At least one item of object information, in particular at least one distance variable, at least one direction variable and / or at least one velocity variable, can advantageously be determined from at least one purged capture variable, in particular possibly at least one purged combined capture variable, thereby enabling a more accurate characterization of the captured scene.

[0055] At least one purged acquisition variable, and in particular possibly at least one purged combined acquisition variable, can advantageously be subjected to image processing, which allows further interference effects to be removed.

[0056] Alternatively or additionally, at least one transmitting device and / or at least one receiving device of the detection device can be adjusted based on at least one purged acquisition variable, in particular possibly on at least one purged combined acquisition variable, thereby making it possible to adapt the performance of the detection device to the prevailing situation.

[0057] Furthermore, according to the invention, this object is achieved in the case of a detection device by the fact that the detection device comprises at least part of the means for carrying out the method according to the invention.

[0058] According to the invention, the detection device comprises at least one interference analysis means which can be used to perform an interference analysis according to the invention.

[0059] The detection device can advantageously comprise at least one artificial neural network, in particular an artificial convolutional neural network, which can be used to check the captured variables for known interference patterns of the interference variables when performing the interference analysis, and if a known interference pattern is recognized, the interference variables belonging to the recognized interference pattern can be purged from the captured variables.

[0060] Interference patterns can be better recognized using artificial convolutional neural networks.

[0061] In an advantageous embodiment, the detection device may be a radar sensor. The monitoring area may be monitored for objects in a non-contact manner using the radar sensor. The radar sensor may be variably adjusted based on the emitted radar beam. Therefore, the shape, pulse duration, length, and / or encoding of the radar beam, among other things, may be varied. By transmitting different radar beams to the same scene, the radar sensor may be used in this way to determine more acquisition variables for the same captured scene. Therefore, the identification of interference patterns may be further improved.

[0062] This object is further achieved according to the invention in the case of a driver assistance system by the fact that the driver assistance system comprises at least part of the means for carrying out the method according to the invention.

[0063] According to the invention, a driver assistance system comprises at least one detection device and at least part of means for carrying out the method according to the invention for operating the at least one detection device.

[0064] Driver assistance systems can be used to operate a vehicle autonomously or semi-autonomously.

[0065] At least one monitored area of ​​the vehicle's environment and / or interior can be monitored for objects using the detection device. Distance, direction, and / or speed variables characterizing the distance, direction, and / or speed of the captured object can be determined using the at least one detection device. Information obtained using the at least one detection device can be used in conjunction with a driver assistance system for operating the vehicle autonomously or semi-autonomously.

[0066] According to the present invention, a driver assistance system comprises at least part of the means for carrying out the method according to the present invention. At least one detection device of a driver assistance system can advantageously comprise at least part of the means for carrying out the method according to the present invention. Thus, if at least one detection device is part of a driver assistance system, part of the means of the at least one detection device for carrying out the method according to the present invention is also part of the driver assistance system, i.e. also part of the means of the driver assistance system for carrying out the method according to the present invention. Thus, this applies to means of a vehicle comprising at least one driver assistance system and / or at least one detection device.

[0067] According to the invention, this object is further achieved in the case of a vehicle by the fact that the vehicle comprises at least part of the means for carrying out the method according to the invention.

[0068] The vehicle can advantageously have at least one driver assistance system, in particular at least one driver assistance system according to the invention, which can be used to operate the vehicle autonomously or semi-autonomously.

[0069] Alternatively or additionally, the vehicle may have at least one detection device, in particular at least one detection device according to the invention. At least one monitored area of ​​the environment of the vehicle and / or the interior of the vehicle may be monitored for objects using the detection device.

[0070] The at least one detection device, in particular the at least one detection device according to the invention, can advantageously be connected to or part of a driver assistance system, in particular the at least one driver assistance system according to the invention, in this way information acquired using the at least one detection device can be used by the driver assistance system for operating the vehicle autonomously or semi-autonomously.

[0071] Furthermore, the features and advantages indicated in relation to the method according to the invention, the detection device according to the invention, the driver assistance system according to the invention and the vehicle according to the invention, as well as their respective advantageous configurations, can be applied in a corresponding manner to one another and vice versa. Of course, the individual features and advantages can be combined with one another, in which case further advantageous effects can be obtained that exceed the sum of the individual effects. [Brief explanation of the drawings]

[0072] Further advantages, features and details of the present invention will become apparent from the following description in which exemplary embodiments of the present invention are described in more detail with reference to the drawings. Those skilled in the art will also be able to consider the disclosed features individually in combination with the drawings, the description and the claims, and combine them to form further suitable combinations. The drawings are schematic.

[0073] [Figure 1] 1 is a front view of a vehicle having a driver assistance system with a radar sensor; [Figure 2] 2 shows a functional diagram of a driver assistance system with a radar sensor from FIG. 1; [Figure 3] 3 shows the time profile of the electrical raw received signal determined from the radar echo signal and the electromagnetic interference beam using the receiving device of the radar sensor from FIGS. 1 and 2, as well as the time profile of the corresponding electrical echo received signal and electrical interference signal; [Figure 4] 4 shows the time profile of the raw received signal from FIG. [Figure 5] 4 shows the time profile of the echo received signal from FIG. [Figure 6] 3 shows a flowchart of a method for operating the radar sensor from FIGS. 1 and 2;

[0074] In the drawings, the same parts are given the same reference numerals. DETAILED DESCRIPTION OF THE INVENTION

[0075] Figure 1 shows a front view of a vehicle 10 in the form of an automobile. The vehicle 10 has a driver assistance system 12. The vehicle 10 can operate autonomously or semi-autonomously using the driver assistance system 12. Figure 2 shows the driver assistance system 12 in a functional diagram.

[0076] The driver assistance system 12 comprises a detection device in the form of a radar sensor 14. The driver assistance system 12 also comprises a central processing unit 16.

[0077] The radar sensor 14 is, by way of example, located on the front fender of the vehicle 10 and is directed into a monitoring area 18 in the forward direction of travel of the vehicle 10. The radar sensor 14 may also be located in different positions and oriented in different directions on the vehicle 10. The driver assistance system 12 may also have multiple radar sensors 14 that may be located in different positions on the vehicle 10 with different orientations. Furthermore, the driver assistance system 12 may have different detection devices.

[0078] The present invention will be described by way of example using one radar sensor 14 shown in Figures 1 and 2. However, the present invention can accordingly be used with other radar sensors or other detection devices that use electromagnetic beams to monitor a corresponding surveillance area.

[0079] The radar sensor 14 comprises a transmitting device 20, for example with a transmitting antenna Tx, a receiving device 22, for example with a receiving antenna Rx, and a control and evaluation device 24, for example an electronic control and evaluation device.

[0080] The sending device 20 and the receiving device 22 are each functionally connected to a control and evaluation device 24. This allows information to be exchanged between the sending device 20, the receiving device 22 and the control and evaluation device 24.

[0081] The control and evaluation device 24 is connected to the central processing unit 16 of the driver assistance system 12. This allows information to be exchanged between the radar sensor 14 or the control and evaluation device 24 and the central processing unit 16.

[0082] The radar sensor 14 may also include multiple transmit antennas Tx and multiple receive antennas Rx. The radar sensor 14 may be in the form of a multiple-input multiple-output (MIMO) radar sensor.

[0083] The transmitting device 20 can be used to generate an electrical scanning signal that can be transmitted into the monitored area 18 using a transmitting antenna Tx, for example, as an electromagnetic scanning beam in the form of a radar signal 26. The radar signal 26 can be transmitted as a radar pulse in the form of a chirp, for example. The transmitting device 20 can be used to vary the transmitted radar signal 26, for example, by varying the shape, pulse duration, signal duration, and / or coding of the radar signal 26.

[0084] The radar signal 26 may be reflected by objects 28 located within the surveillance area 18 .

[0085] The radar sensor 14 can be used to capture stationary or moving objects 28, such as vehicles, people, animals, plants, obstacles, uneven road surfaces, e.g., potholes or rocks, road boundaries, traffic signs, open spaces, e.g., parking spaces, precipitation, etc., and / or movements and / or gestures.

[0086] The radar signal 26 reflected by the object 28 towards the radar sensor 14 can be received as an electromagnetic beam in the form of a radar return signal 30 using the receiving antenna Rx of the receiving device 22 .

[0087] The received radar return signal 30 can be converted into a captured variable in the form of an electrical echo receive signal 38 using the receiving device 22. Figures 3 and 5 show time profiles of an exemplary electrical echo receive signal 38 resulting from the radar return signal 30 of the exemplary radar signal 26.

[0088] Depending on the propagation time of the transmitted radar signal 26 until the corresponding radar return signal 30 is received, object information about the captured object 28 can be determined. For example, distance variables 32, direction variables, and velocity variables characterizing the distance, direction, and velocity of the captured object 28 in a reference system relative to, for example, the radar sensor 14 can be determined. Indirect or direct propagation time methods can be used. When using a MIMO radar sensor 14, the distance variable 32 can be determined from the phase difference between the electrical scanning signal used to generate the radar signal 26 and the electrical echo receive signal 38 of the captured radar return signal 30.

[0089] The object information is determined in a control and evaluation device 24 .

[0090] In addition to receiving radar return signals 30 from captured objects 28, the receiving antenna Rx of the receiving device 22 is also used to receive electromagnetic interference beams 34, e.g., from external interference sources 42. The electromagnetic interference beams 34 are converted into electrical interference signals 36 using the receiving device 22.

[0091] The interference source 42 may be, for example, another radar sensor emitting an interference beam 34 in the form of a radar beam. Figure 2 shows, by way of example, three interference sources 42, the reference numbers of which are given the indices 1, 2 and 3 for better differentiation. The reference numbers of the corresponding electrical interference signals 36, the time profile of which is shown in Figure 3, are therefore given using the indices 1, 2 and 3.

[0092] The electrical echo receive signal 38 originating from the echo signal 30 and the electrical interference signal 36 are superimposed to form a captured variable in the form of an electrical raw receive signal 40. Figures 3 and 4 show, by way of example, the time profile of the raw receive signal 40 for the scene shown in Figure 2 with three interference sources 421, 421 and 423.

[0093] The raw received signal 40 depends on the type, material, shape and spatial position of the reflecting object 28, e.g., its position in a defined frame of reference. Furthermore, the raw received signal 40 depends on the environmental conditions, e.g., the amount of precipitation prevailing, external noise, the environment or the dynamics of the captured object 28. Furthermore, the raw received signal 40 depends on the radar signal 26 used.

[0094] For comparison, FIG. 3 shows the time profiles of an exemplary raw electrical receive signal 40, the corresponding echo receive signal 38, and three electrical interference signals 361, 362, and 363.

[0095] The electrical interference signals 361, 362 and 363 originate from three interference sources 421, 422 and 423 which emit electromagnetic interference beams 341, 342 and 343 respectively.

[0096] Figure 4 shows only the time profile of the raw received signal 40 from Figure 3. Figure 5 shows the time profile of the electrical echo received signal 38 from Figure 3 after an interference processing process, where the interfering signals 361, 362 and 363 have been removed according to a method described in more detail below.

[0097] The interfering signal 36 impairs the signal-to-noise ratio of the echo receive signal 38, thus impairing the accuracy of the determined object information about the object 28 captured by the radar sensor 14.

[0098] In order to be able to determine the most accurate possible object information about the object 28, for example, an accurate distance variable 32, an accurate direction variable and / or an accurate velocity variable for the object 28, it is necessary to improve the signal-to-noise ratio.

[0099] To this end, an interference handling process is performed in a method 44 for operating the radar sensor 14. The method 44 is shown as a flow chart in FIG.

[0100] During the interference processing process, the interference analysis 46 is carried out using an artificial neural network, for example realized as a convolutional neural network CNN.

[0101] As an example, the method 44 performs four interference analyses 46. It is also possible to perform more or fewer interference analyses 46. The signal-to-noise ratio improves with the number of interference analyses 46.

[0102] For each of the interferometric analyses 46, a radar signal 26 is transmitted and a corresponding echo signal 30 is captured and converted into a raw received signal 40. The four interferometric analyses 46 are performed over a short time interval on the same scene within the monitored area 18. A different variation of the radar signal 26 is used for each of the interferometric analyses 46, resulting in four different variations of the radar signal 26 used for the four interferometric analyses 46. For easy distinction, the references to the four different variations of the radar signal 26 are indexed 1, 2, 3, and 4 as follows:

[0103] For clarity, the four interference analyses 46 are shown at the same level in the flowchart of Fig. 6. The interference analyses 46 and the corresponding radar measurements are performed consecutively in time. The arrangement and principle of the four interference analyses 46 are identical. Therefore, the same reference symbols are used in the figure. In a way that represents all four interference analyses 46, the interference analysis 46 of the radar signal 261 on the left side of Fig. 6 will be explained in more detail below using the example scene shown in Fig. 2.

[0104] In a measurement step 48, a radar measurement is performed with the radar signal 261. The corresponding echo signal 30 and the interfering beam 34 from the interference source 42 shown as an example in Figure 2 are received using the receive antenna Rx of the receiving device 22 and converted into an electrical raw receive signal 40. The time profile of the raw receive signal 40 is shown in Figures 3 and 4.

[0105] The raw received signal 40 is sent to a neural network CNN.

[0106] Furthermore, a known interference pattern 52 of the known electrical interference signal and a known object pattern 54 of the known object 28 are transmitted to the neural network CNN from a pattern memory 50. The pattern memory 50 is, for example, part of the control and evaluation device 24.

[0107] The interference pattern 52 is characterized by the time profile of the electrical interference signal 36. The known interference pattern 52 may be a pattern of interference signals 36 that typically occur when operating the vehicle 10. For example, the known interference signal 36 may result from an interference beam 34 transmitted by a radar sensor on another vehicle.

[0108] The object pattern 54 is characterized by a time profile of the electrical echo receive signal 38. The known object pattern 54 may be, for example, a pattern of the echo receive signal 38 of an object 28 that typically occurs during operation of the vehicle 10. The known object 28 may be, for example, a vehicle, a person, an animal, a plant, an obstacle, an uneven road surface such as a pothole or rock, a road boundary, a traffic sign, an open space such as a parking space, etc.

[0109] The known interference pattern 52 and the known object pattern 54 are predetermined by a reference measurement using a known interference source 42 or a known object 28, for example, at the end of a production line, and stored in the pattern memory 50. The reference measurement may be performed, for example, under laboratory conditions. Alternatively or additionally, the known interference pattern 52 and / or the known object pattern 54 may also be recorded, e.g., "learned," during normal operating conditions of the vehicle 10.

[0110] In the described exemplary embodiment, it is assumed that for the interference signal 36 from the scene of Figure 2, a corresponding known interference pattern 52 is stored in pattern memory 50. It is also assumed that for the echo receive signal 38 of an object 28 shown therein, such as a road sign, a corresponding known object pattern 54 is stored in pattern memory 50.

[0111] The raw received signal 40 is compared with known object patterns 54 in a neural network in an object purging step 56. A pattern recognition method can be implemented for this purpose, for example. If a match with a known object pattern 54, in this case a road sign object pattern 54, is identified, the raw received signal 40 is reduced by the identified echo received signal 38 of the known object pattern 54, i.e., the road sign, and provided as a reduced received signal 58 to an interference analysis step 60.

[0112] In an interference analysis step 60, the reduced received signal 58 is compared with the known interference pattern 52. A pattern recognition method can be implemented for this purpose, for example. If a match with the known interference pattern 52 is recognized, the original raw received signal 40 is reduced by the interference signal 36 of the corresponding known interference pattern 52 in a purge step 62. In the exemplary embodiment shown, the pattern of the interference signal 36 is caused by interfering beams 341, 341, and 343 from three interference sources 421, 421, and 423 shown in the scene of FIG. 2 and matches the corresponding known interference pattern 52 stored, for example, in the pattern memory 50. Thus, the original raw received signal 40 is reduced by the interference signals 361, 361, and 363.

[0113] After removing the effects of the recognized interference signals 361, 361 and 363, if all interference signals 361, 361 and 363 occurring during the measurement are identified using the known interference pattern 52, the interference is purged and only the echo received signal 38 originating from the reflecting object 28, i.e., the road sign, remains.

[0114] The purged echo receive signals 38 determined in each of the four exemplary interference analyses 46 are combined to form a combined echo receive signal 66 in a superposition step 64 .

[0115] In an information determination step 68 , object information, such as distance variable 32 , direction variable and / or velocity, about the captured object 28 is determined from the combined echo receive signal 66 .

[0116] Optionally, the object information may be subjected to further processing, for example image processing.

[0117] The object information, for example the distance variable 32 , is sent to the central processing unit 16 of the driver assistance system 12 .

[0118] Optionally, the settings of the transmitting device 20 and / or the receiving device 22 may be adapted to the current scene based on the combined echo received signal 66 .

[0119] Instead of being performed based on the raw received signals 40 as acquisition variables, the interference analysis 46 may also be performed based on object information, such as distance variables 32, direction variables and / or velocity variables, as acquisition variables, in which case the object information is predetermined based on the corresponding raw received signals 40.

Claims

1. A method (44) for operating a detection device (14), particularly a detection device (14) for a vehicle (10), comprising: At least one electromagnetic beam (26) is transmitted using the detection device (14) into a monitoring area (18) of the detection device (14); At least one electromagnetic beam (30, 34) originating from the monitoring area (18) 1 , 34 2 , 34 3 ) is received using said detection device (14) and converted into at least one captured variable (40) that can be processed using at least one evaluation device (24), At least one interference processing process is performed based on at least one capture variable (40) using at least one artificial neural network (CNN); 1. A method according to claim 1, wherein at least one interference analysis (46) is performed during the at least one interference processing process, in which the at least one capture variable (40) is examined for known interference patterns (52) of interference variables (36) using at least one artificial neural network (CNN), and if at least one known interference pattern (52) is recognized, interference variables (36) belonging to the at least one recognized interference pattern (52) are purged from the at least one capture variable (40).

2. 2. The method of claim 1, wherein the at least one interference analysis is performed repeatedly and the purged capture variables determined from each interference analysis are combined to form at least one combined capture variable.

3. Several different electromagnetic beams (26 1 , 26 2 , 26 3 , 26 4 ) are transmitted to the same scene in the surveillance area (18) and respective capture variables (40) are determined; At least one interference analysis (46) is performed on at least some of the plurality of captured variables (40) thus determined, respectively, to determine the interference between the different transmitted electromagnetic beams (26). 1 , 26 2 , 26 3 , 26 4 determining respective purged capture variables (38) for at least a portion of the 3. The method of claim 1, wherein at least some of the plurality of purged trapped variables (38) thus determined are combined to form at least one combined trapped variable (66).

4. 4. The method according to claim 1, wherein an artificial convolutional neural network is used as at least one artificial neural network (CNN).

5. During the at least one interference analysis (46), the at least one capture variable (40) is first examined for a known object pattern (54) caused by an electromagnetic echo beam (30) reflected off a known object (28); If the at least one known object pattern (54) is recognized, the echo capture variable (38) corresponding to the at least one known object pattern (54) is removed from the at least one capture variable (40); 5. The method according to claim 1, wherein the at least one captured variable (58) from which the recognized at least one echo capture variable (38) has been removed is then examined for known interference patterns (52) of interference variables (36) using at least one artificial neural network (CNN), and if at least one known interference pattern (52) is recognized, interference variables (36) belonging to the at least one recognized interference pattern (52) are purged from the original at least one captured variable (40) which may contain the at least one echo capture variable (38).

6. a predefined interference pattern (52) and / or possibly an object pattern (54) is used for the at least one interference analysis (46); and / or 6. The method according to claim 1, wherein an interference pattern (52) and / or an object pattern (54) learned during operation of the detection device (14) is used for the at least one interference analysis (46).

7. The receiving device (22) of the detection system (14) is used to detect the electromagnetic beams (30, 34). 1 , 34 2 , 34 3 ) is used as the capture variable (40), in particular the electrical received signal converted from the and / or 7. The method according to claim 1, wherein object information (32) about an object (28) captured during measurement by the detection device (14) is used as a capture variable (40), and the object information is determined from a received signal (38), in particular an electrical received signal, converted from an electromagnetic beam (30) using a receiving device (22) of the detection device (14).

8. 8. The method according to any one of claims 1 to 7, characterized in that the method (44) is used for operating a detection device (14) in the form of a radar sensor used to transmit an electromagnetic beam (26) in the form of a radar beam.

9. At least one purged capture variable (40), in particular possibly at least one purged combined capture variable (66), is further processed, in particular subjected to image processing, and / or 9. The method according to claim 1, wherein at least one transmitting device (20) and / or at least one receiving device (22) of the detection device (14) is adjusted based on the at least one purged capture variable (38), in particular possibly based on the at least one purged combined capture variable (66).

10. A detection device (14), particularly a detection device (14) for a vehicle (10), comprising: at least one transmitting device (20) for transmitting an electromagnetic beam (26) into a monitoring area (18) of the detection device (14); The electromagnetic beams (30, 34) originating from the monitoring area (18) 1 , 34 2 , 34 3 ) and receiving the received electromagnetic beams (30, 34 1 , 34 2 , 34 3 at least one means (22) for determining a capture variable (40) from the at least one means (24) for performing an interference processing process based on the captured variables (40), said at least one means (24) comprising at least one artificial neural network (CNN); 10. A detection device (14), characterized in that the detection device (14) comprises at least part of the means for carrying out the method according to any one of claims 1 to 9.

11. 11. The detection device (14) according to claim 10, characterized in that the detection device (14) is a radar sensor.

12. A driver assistance system (12), in particular a driver assistance system (12) for a vehicle (10), having at least one detection device (14), the at least one detection device (14) comprising: at least one transmitting device (20) for transmitting an electromagnetic beam (26) into a monitoring area (18) of the at least one detecting device (14); The electromagnetic beams (30, 34) originating from the monitoring area (18) 1 , 34 2 , 34 3 ) and receiving the received electromagnetic beam (30, 34 1 , 34 2 , 34 3 at least one means (22) for determining a capture variable (40) from the at least one means (24) for performing an interference processing process based on the captured variables (40), the at least one means (24) comprising at least one artificial neural network (CNN); A driver assistance system (12), characterized in that the driver assistance system (12) comprises at least part of means for carrying out the method according to any one of claims 1 to 9.

13. A vehicle (10) having at least one detection device (14), the at least one detection device (14) comprising: at least one transmitting device (20) for transmitting an electromagnetic beam (26) into a monitoring area (18) of the at least one detecting device (14); The electromagnetic beams (30, 34) originating from the monitoring area (18) 1 , 34 2 , 34 3 ) and receiving the received electromagnetic beam (30, 34 1 , 34 2 , 34 3 at least one means (22) for determining a capture variable (40) from the at least one means (24) for performing an interference processing process based on the captured variables (40), the at least one means (24) comprising at least one artificial neural network (CNN); A vehicle (10), characterized in that the vehicle (10) comprises at least part of means for carrying out the method according to any one of claims 1 to 9.

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