Controller for an acoustic transducer, parking assistance control system and method of operating a piezoelectric-based sensor

Abstract

The present invention relates to a controller for an acoustic transducer, a parking assistance control system, and a method of operating a piezoelectric-based sensor. The present disclosure provides an exemplary controller comprising: a transmitter that drives an acoustic transducer to produce a sound pulse train; a receiver that senses a response of the acoustic transducer to an echo; and processing circuitry coupled to the transmitter and the receiver, the processing circuitry configured to convert the received response into output data by: correlating the response with a drive signal to obtain a correlated response; distinguishing a non-peak region from a peak region in the correlated response; deriving a noise level in a portion of the correlated response based on the non-peak region within the portion; calculating a signal-to-noise ratio (SNR) of a peak signal within the portion as a ratio of a peak value of the peak signal to the noise level in the portion of the correlated response; and accepting the peak signal as an echo only when the SNR of the peak signal exceeds a predetermined threshold.

Description

Technical Field

[0001] This disclosure generally relates to controllers for acoustic transducers, parking assistance control systems, and methods for operating piezoelectric-based sensors, particularly to ultrasonic sensors suitable for monitoring the environment around a vehicle, and more specifically to sensors employing echo detection with background noise-based shielding. Background Technology

[0002] Modern cars are equipped with a wide variety of sensors. For example, cars are now typically equipped with arrays of ultrasonic sensors to monitor the distance between the car and any nearby people, pets, vehicles, or obstacles. Due to environmental "noise" and safety concerns, each of these sensors may be required to provide dozens of measurements per second as the car moves. Reliably performing such sensor arrays is important even in environments that change in complex ways. Noticeable small differences (such as the presence or absence of a curb, or even the difference between a paved surface and a gravel surface) can significantly alter the characteristic reflections of poles, posts, or other small obstacles.

[0003] It is known that parking assist sensors encounter noise from various sources, including, for example, aerodynamic noise, such as vibrations from other vehicles operating nearby; ultrasonic waves from other sources, such as sensors on other vehicles, parking occupancy detectors, and traffic light control systems; cross-correlation noise between different frequency bands; and so on. Therefore, such noise needs to be adequately addressed in the detection and evaluation of any received ultrasonic signals. Summary of the Invention

[0004] Therefore, the present invention discloses a controller for an acoustic transducer, a parking assist control system, and a method for providing echo detection with background noise-based shielding.

[0005] According to one aspect of this application, a controller for an acoustic transducer is provided, characterized in that the controller comprises: a transmitter that drives the acoustic transducer using a drive signal to generate an acoustic pulse train; a receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; and processing circuitry coupled to the transmitter and the receiver, the processing circuitry being configured to convert the received response into output data by: correlating the response with the drive signal to obtain a correlated amplitude signal; distinguishing between peak and non-peak regions in the correlated amplitude signal; deriving the noise level in the non-peak region of a portion of the correlated amplitude signal based on the correlated amplitude signal in the non-peak region; calculating the SNR (signal-to-noise ratio) of the peak signal in the portion as the ratio of the peak value of the peak signal to the noise level in the portion of the correlated amplitude signal; and accepting the peak signal as an echo only when the SNR of the peak signal exceeds a predetermined threshold.

[0006] In one embodiment, the controller for the acoustic transducer is characterized in that the processing circuit is further configured to: determine a derivative signal based on the relevant amplitude signal; and accept the peak signal as an echo only when the derivative signal corresponding to the peak signal exceeds a derivative threshold.

[0007] In one embodiment, the controller for the acoustic transducer is characterized in that the derivative threshold is a CFAR threshold determined according to a CFAR (Continuous False Alarm Rate) algorithm applied to the derivative signal.

[0008] In one embodiment, the controller for the acoustic transducer is characterized in that distinguishing the peak region from the non-peak region includes calculating a CFAR threshold using a CFAR algorithm and comparing the relevant amplitude signal with the CFAR threshold, wherein the processing circuit is further configured to accept the peak signal as an echo only if the peak signal is within one of the peak regions.

[0009] According to another aspect, a parking assistance control system is provided, characterized in that the system includes a microcontroller, at least one controller for an acoustic transducer, and a communication bus coupled to the microcontroller and the at least one controller, the controller including: a transmitter that drives the acoustic transducer using a drive signal to generate an acoustic pulse train; a receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; a processing circuit coupled to the receiver to convert the received response into output data; and an interface that transmits the output data through the communication bus, wherein at least one of the processing circuit and the microcontroller is configured to: correlate the response with a pulse pattern to obtain a correlated response; distinguish peak regions and non-peak regions in the correlated response; derive the noise level in the non-peak region only using the non-peak region within a portion of the correlated response; calculate the SNR (signal-to-noise ratio) of the peak signal within the portion as the ratio of the peak value of the peak signal to the noise level; and accept the peak signal as an echo only when the SNR of the peak signal exceeds a predetermined threshold.

[0010] In one implementation, the parking assistance control system is characterized in that the microcontroller is configured to use a CFAR (Continuous False Alarm Rate) threshold to distinguish between peak and off-peak areas in the relevant response.

[0011] In one embodiment, the parking assistance control system is characterized in that the microcontroller further determines a derivative signal based on the relevant response, and accepts the peak signal as an echo only when the derivative signal corresponding to the peak signal exceeds a derivative threshold.

[0012] According to another aspect, a method for operating a piezoelectric-based sensor is provided, characterized in that the method includes: driving a piezoelectric transducer to generate a pulse train of acoustic energy; obtaining a response from the piezoelectric transducer; correlating the response relative to the driving signal to obtain a correlated response; distinguishing between peak regions and non-peak regions in the correlated response; deriving a noise level in the non-peak region only using a portion of the correlated response; calculating the SNR (signal-to-noise ratio) of the peak signal in the portion as the ratio of the peak value of the peak signal to the noise level; and accepting the peak signal as an echo only when the SNR of the peak signal exceeds a predetermined threshold.

[0013] In one embodiment, the method of operating a piezoelectric-based sensor is characterized in that the method further includes reporting the peak signal as ground reflection if the SNR is below the predetermined threshold.

[0014] According to another aspect, a controller for an acoustic transducer is provided, characterized in that the controller comprises: a transmitter that drives the acoustic transducer using a drive signal to generate an acoustic pulse train; a receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; and processing circuitry coupled to the transmitter and the receiver, the processing circuitry being configured to convert the received response into output data by: correlating the response with the drive signal to obtain a correlated response; distinguishing between peak and non-peak regions in the correlated response; using the non-peak regions in a portion of the correlated response to derive a noise level; calculating the SNR (signal-to-noise ratio) of the peak signal within the portion as the ratio of the peak value of the peak signal to the noise level; and identifying the peak signal as a ground reflection if the SNR is below a predetermined threshold. Attached Figure Description

[0015] Figure 1 A top view of an exemplary vehicle equipped with parking assist sensors.

[0016] Figure 2 This is a block diagram of an exemplary parking assistance system.

[0017] Figure 3 This is a circuit diagram of an exemplary parking assist sensor.

[0018] Figure 4A and Figure 5A A graph illustrating the exemplary signal curves of the reference technology is shown.

[0019] Figure 4B and Figure 5B A graph illustrating the exemplary signal curves of this technique is shown.

[0020] Figure 6This is a block diagram of the first example of a processing circuit.

[0021] Figure 7 This is a block diagram of the second exemplary processing circuit.

[0022] Figure 8 This is a block diagram of the third exemplary processing circuit.

[0023] Figure 9 This is a block diagram of the fourth example of the processing circuit.

[0024] Figure 10 This is a block diagram of the fifth exemplary processing circuit. Detailed Implementation

[0025] This application claims priority to U.S. Provisional Application 63 / 127,599, filed December 18, 2020, entitled “Ultrasonic Sensor System,” inventors M. Hustava, P. Kostelnik, and D. Bartos. This application further relates to U.S. Application 16 / 530,654, filed August 2, 2019, entitled “Ultrasonic Sensor Having Edge-Based Echo Detection,” inventors M. Hustava and J. Kantor. Both of these applications are incorporated herein by reference.

[0026] It should be understood that the accompanying drawings and the following description do not limit this disclosure, but rather provide a basis for those skilled in the art to understand all modifications, equivalents and alternatives that fall within the scope of the claims.

[0027] Use the context as an example. Figure 1 A vehicle 102 equipped with a set of ultrasonic parking assist sensors 104 is shown. The number and configuration of sensors in the sensor arrangement vary, and it is not uncommon to have six sensors on each bumper, with two additional sensors on each side acting as blind spot detectors. Some envisioned sensor arrangements include 24 ultrasonic sensors arranged around the vehicle. This sensor arrangement can be used to detect and measure the distance to objects in various detection areas, where individual measurements and collaborative measurements (e.g., triangulation, multi-receiver) are possible.

[0028] An ultrasonic sensor is a transceiver, meaning each sensor can transmit and receive a train of ultrasonic sounds. The transmitted train of sounds propagates outward from the vehicle until it encounters an object or some other form of acoustic impedance mismatch and is reflected. The reflected train of sounds returns to the vehicle as the "echo" of the transmitted train. The time between the transmitted train and the received echo indicates the distance to the point of reflection. In many systems, only one sensor transmits at a time, but all sensors can be configured to measure the resulting echo. However, multiple simultaneous transmissions can be supported by using orthogonal waveforms or transmissions to non-overlapping detection areas.

[0029] While the parking assistance system context is used as an example herein, the concepts disclosed herein can be applied to any type of obstacle detection and may be particularly well-suited for those where reliability and rapid response are prioritized. To mitigate any trade-off between reliability and extended detection range, appropriate modulation can be added to the transmitted pulse to address the drawbacks of increasing pulse length. Subsequently, a correlator can be used to shorten or compress the echo of a longer modulated transmitted pulse.

[0030] In various implementations, chirped modulation signals are used. A chirp is a transmitted pulse that changes frequency during transmission. One form of modulation for the transmitted pulse is, for example, linear frequency modulation (“LFM”) chirp. An upper chirp is a chirp where the frequency increases during transmission, and a lower chirp is a chirp where the frequency decreases during transmission. For clarity, the examples used herein will consider linear increases or decreases; however, in various implementations, this increase or decrease is not linear. Variable rate chirps increase and decrease in frequency at different rates during the pulse. Correlators can compress the echo of the chirped signal without introducing a large amount or any correlated noise. Therefore, peak detection of the echo is advantageous without reducing time resolution. Furthermore, LFM chirps can withstand Doppler shifts without any increase in correlated noise or with minimal increase in correlated noise. LFM chirps can be used as transmitted pulses for measuring the distance to obstacles or objects located in front of a sensor system.

[0031] For clarity, as used herein, the term "pulse" refers to a single drive signal in a series of drive signals. Compared to amplitude modulation (AM) signals, such chirped pulses can have a long duration, for example, greater than 1 millisecond, such as in the range of 2 to 3 milliseconds.

[0032] Figure 2An electronic control unit (ECU) 202, coupled to various ultrasonic sensors 204 as the center of a star topology, is shown. Of course, other topologies, including serial, parallel, and hierarchical (tree) topologies, are also suitable and are envisioned for use according to the principles disclosed herein. To provide automatic parking assistance, the ECU 202 can be further connected to a set of actuators, such as a turn signal actuator 206, a steering actuator 208, a brake actuator 210, and a throttle actuator 212. The ECU 202 can be further coupled to a user interactive interface 214 to accept user input and provide displays of various measurements and system status. Using the interface, sensors, and actuators, the ECU 202 can provide automatic parking, assisted parking, lane change assistance, obstacle and blind spot detection, and other desired features.

[0033] Now for reference Figure 3 One possible sensor configuration is described, illustrating a three-terminal configuration with two terminals for power and one terminal for I / O. Other communication and power technologies, such as those provided in the DSI3, LIN, and CAN standards, are also suitable, and their use is envisioned in accordance with the principles disclosed herein. In addition... Figure 3 In addition to the two power terminals (Vbat and GND) shown in the implementation scheme, each of the exemplary ultrasonic sensors is connected to ECU 202 via a single input / output (“I / O” or “IO”) line. When the I / O line is not actively driven low (“enabled” state) via ECU 202 or sensor controller 302, it can be biased to the supply voltage via a pull-up resistor (“disabled” state). The communication protocol is designed so that at any given time only one of the two controllers (ECU 202 or sensor controller 302) enables the I / O line.

[0034] The sensor controller 302 includes an I / O interface 303 that monitors the activation of the I / O lines caused by the ECU 202 when in recessive mode, and drives the state of the I / O lines when in dominant mode. The ECU transmits commands to the sensor by activating the I / O lines, with different commands represented by activation lengths. Commands may include "send and receive" commands, "receive only" commands, and "data mode" commands.

[0035] Sensor controller 302 includes core logic 304 that operates according to firmware and parameters stored in non-volatile memory 305 to parse commands from the ECU and perform appropriate operations, including the transmission and reception of ultrasonic pulse trains. To transmit the ultrasonic pulse train, core logic 304 is coupled to transmitter 306, which drives a set of transmitting terminals on sensor controller 302 using a suitably modulated local oscillator signal from voltage-controlled oscillator 307. The transmitter terminals are coupled to piezoelectric element PZ via transformer M1. Transformer M1 gradually increases the voltage from the sensor controller (e.g., 12 volts) to a suitable level (e.g., tens of volts) for driving the piezoelectric element. Piezoelectric element PZ has a resonant frequency that can be tuned using external components (such as a parallel capacitor C3) and a resonant quality factor (Q) that can be similarly tuned, for example, using a parallel resistor R1.

[0036] As used herein, the term "piezoelectric transducer" includes not only the piezoelectric element but also the supporting circuitry for tuning, driving, and sensing the piezoelectric element. In exemplary embodiments, these supporting elements are a transformer M1, a tuning resistor and a tuning capacitor, and a DC isolation capacitor. Optionally, the output and input capacitances of the transmitter 306 and amplifier 308 may also be included as parasitic characteristics of the supporting circuitry considered part of the transducer. However, the use of the term "piezoelectric transducer" does not necessarily require the presence of any supporting circuitry, as the piezoelectric element can be used independently without such supporting elements. In the illustrated embodiment, a pair of DC isolation capacitors C1, C2 couples the piezoelectric element to a pair of receiving terminals of a sensor controller to prevent high voltage. Further protection is provided by an internal voltage clamp on the receiving terminals. Such protection may be desired for intervals during which the piezoelectric element is transmitting.

[0037] Commands received via I / O lines trigger core logic 304 to operate the transmitter and receiver, and provide measurement results to ECU 202 via I / O lines, also referred to herein as the communication bus. Measurement results are also referred to herein as output data. The preferred communication bus is the DSI3 bus, but other communication buses such as LIN, SENT, and CAN are not excluded. Core logic 304 can monitor the status of other sensors, such as undervoltage or overvoltage of the supply voltage during the transmission of ultrasonic pulse trains, transmitter thermal shutdown, hardware errors, incomplete power-on resets, etc. Core logic 304 can detect and classify multiple such transducer fault states and error conditions, storing appropriate fault codes in internal registers or non-volatile memory 305.

[0038] Since the received echo signal is typically in the millivolt or microvolt range, the front-end amplifier 308 amplifies the signal from the receiving terminal. The mixer 309 multiplies the amplified received signal with a local oscillator signal to downconvert the modulated signal to baseband, where it is then digitized by an analog-to-digital converter (ADC) and processed in a digital signal processor (DSP) 310. Alternatively, the received signal can be digitized before downconversion, in which case the mixer 309 can be an in-phase / quadrature (I / Q) digital mixer 309, providing zero-intermediate-frequency (ZIF) IQ data as its output. (Although the term "ZIF" is used herein, the downconverted signal may be a low-intermediate-frequency or "near-baseband" signal in implementation.)

[0039] The DSP 310 employs programmable methods to monitor piezoelectric transducers during pulse train transmissions, detecting any echoes and measuring their parameters, such as time-of-flight (ToF), duration, and peak amplitude. These methods can utilize threshold comparison, minimum interval, peak detection, zero-crossing detection and counting, noise level determination, and other customizable techniques tailored to improve reliability and accuracy. The DSP 310 can further process the amplified received signal to analyze transducer characteristics, such as resonant frequency and quality factor, and can further detect transducer fault conditions.

[0040] In one embodiment, the DSP includes a digital filter configured to cooperate with a memory to store finite impulse response (FIR) filter coefficients. As described above, in one embodiment, mixer 309 is a quadrature mixer. This I / Q digital mixer 309 has an input connected to the output of the analog-to-digital converter, an input for receiving the mixed signal FTX, and a first output and a second output for providing in-phase and quadrature signals, respectively, corresponding to the amplitude and phase of the signal input from the acoustic transducer in the complex plane.

[0041] As described above, in one specific embodiment, mixer 309 is a quadrature mixer. This I / Q digital mixer 309 has an input connected to the output of an analog-to-digital converter (not shown) for receiving a mixed signal F. TXThe input includes a first output and a second output, respectively, for providing in-phase and quadrature signals corresponding to the amplitude and phase of the signal input from the acoustic transducer in the complex plane. The DSP may include one or more digital filters configured to retrieve and use filter coefficients stored in memory for operation on the ZIF-IQ signal. More specifically, the digital filters may include a low-pass filter and a correlator. Even more specifically, at least one correlator filter has coefficients matching the shape of the transmitted pulse at baseband, such that the filter output exhibits a peak at the location where an echo appears in the down-converted received signal.

[0042] The DSP may further include programmable modules or dedicated circuitry for other operations, including phase derivation, amplitude measurement, downsampling, amplitude calibration (attenuation control), noise suppression, peak detection, reverberation monitoring, and transducer diagnostics, as well as an interface for host communication. The amplitude detector module or circuitry operates on the digitized and downconverted received signal, combining the in-phase and quadrature signal components to output the amplitude signal.

[0043] In an exemplary implementation, if an object reflects the transmitted pulse, the piezoelectric transducer provides a received signal that includes the echo of the chirped signal, which is the input signal at the I / Q digital mixer 309. Once any residual reverberation from the transmitted pulse has subsided, the chirped echo signal for near-field object detection can be detected. The I / Q digital mixer 309 converts the received signal into a sum frequency and a difference frequency, where the difference frequency is in the baseband (zero frequency). The I / Q digital mixer 309 outputs both the in-phase and quadrature-phase components of the received signal. One or more correlators receive the in-phase and quadrature-phase components and generate a correlation signal with a peak value, where the received signal contains the echo of the transmitted pulse. Two correlators can be used for dual-channel operation, where a high-channel correlator is used to detect high-channel chirp and a low-channel correlator is used to detect low-channel chirp.

[0044] During implementation, the received and digitized response includes not only any reflections from the ranging signal emitted by the acoustic transducer, but also noise. This noise originates from a variety of potential sources. The noise component is periodic with the measurement sequence and is therefore repeatedly acquired as part of the response. This periodic noise can be electrical noise, acoustic noise, structural noise, or processing noise. Examples of processing noise include autocorrelation noise (i.e., within a single channel, such as chirp and AM) and cross-correlation noise (between different measurement channels). One source of interfering noise is noise resulting from ground reflections of sound pulse trains, i.e., reflections from the ground, soil, or road where the vehicle (integrated with the sensor) is parked or driven. Such ground reflections tend to be received relatively shortly after the residual reverberation dissipates. However, the timing of reception, the number of reflections, and the signal strength of the ground reflections all appear to depend on the type of ground. Furthermore, there may be real echo signals hidden between ground reflections that should not be removed. Another source of interfering noise is found in systems that employ data compression to transmit sensor signals to the ECU for processing. This noise can be classified as compressed noise and may again produce false echoes, i.e., signals with a strength comparable to or even greater than the signal representing the echo, but still simply due to noise.

[0045] Figure 4A and Figure 5A Two exemplary correlation amplitude curves (“amplitudes”) are shown, processed as described in incorporated U.S. Application 16 / 530,654 (“Ultrasonic Sensor Having Edge-Based Echo Detection”) to perform edge-based echo detection. More specifically, the processor has processed the correlation amplitudes to detect falling edges where the amplitude exceeds a CFAR threshold and the (negative) derivative exceeds the threshold, thereby producing a curve labeled “edge”. In the case where a falling edge is detected by the correlation amplitude being above a time-dependent threshold, the processor asserts that the echo detection signal (“echo”) will be transmitted to the ECU as a pulse output signal or as other encoded echo information.

[0046] The echoes detected in these figures include ground reflections (i.e., echoes detected more than 16 milliseconds ago), which is likely undesirable for most parking assistance systems. Of course, reflections from real obstacles may also be present, so it is desirable to distinguish such reflections from ground reflections. Therefore, this paper provides an improved method for distinguishing between real and false echoes, and an improved controller with processing circuitry configured to perform such a method. The method and the corresponding controller can be configured to provide a signal indicating the presence and / or type of ground reflections. Such a signal can be provided from the controller to the ECU in any suitable format.

[0047] Figure 6 This is a block diagram of a processing circuit according to a first embodiment of the present technology. Figures 7 to 10 Corresponding processing circuitry according to other embodiments of the present invention is shown. The same reference numerals in these figures correspond to the same or corresponding parts. It should be observed that the block diagrams are schematic in nature and simplified to omit features not directly related to the disclosed invention. For example, specific processing of channels such as chirped channels is not specified herein. An example of a block diagram specifying processing of chirped channels is disclosed, for instance, in U.S. Patent Application 16 / 378,722, filed April 9, 2019, entitled “Acoustic distance measuring circuit and method for low frequency modulation (LFM) chirp signals,” inventors Marek Hustava and Tomas Suchy, which is incorporated herein by reference. However, typical processing circuitry may include more functions, as illustrated in Figure 4 and the corresponding description in U.S. Patent Application 16 / 724,783, filed December 23, 2019, entitled “Piezoelectric transducer controller having model-based sideband balancing,” by inventors Tomas Suchy, Jiri Kantor, and Marek Hustava, which is incorporated herein by reference.

[0048] Figure 6 An exemplary block diagram shows a mixer 602 and a correlation filter 604. The mixer is used to downconvert the signal received from the piezoelectric transducer (RECV) to baseband, and the correlation filter convolves the downconverted signal with the shape of the transmitted pulse to produce a correlation signal. (Multiple filters or multiple sets of filter coefficients can be used to provide separate correlation signals for the upper and lower sideband signals). An amplitude element 606 determines the absolute value of the correlation signal, or in some alternative embodiments, squares the correlation signal to produce a correlation amplitude or energy signal, which is provided to various other elements for processing to detect peaks indicating the reflected energy (echo) of the transmitted pulse from an obstacle.

[0049] CFAR element 608 operates on a relevant amplitude or energy signal to provide a CFAR threshold (CT) signal according to a constant false alarm rate (CFAR) algorithm. Various CFAR algorithms are described in the literature, including the previously incorporated U.S. Patent Application 16 / 530,654, filed August 2, 2019, entitled “Ultrasonic Sensor Having Edge-Based Echo Detection,” by inventors M. Hustava and J. Kantor (cited in U.S. Patent 5,793,326 (“Hofele”)). Suitable CFAR algorithm variants include, for example, CASH-CFAR (Unit Average Statistical Hofele CFAR) and Ordered Statistical CFAR (OS-CFAR). In short, a CFAR algorithm performs statistical processing within a moving window to determine a threshold representing background “clutter,” the processing operation excluding any strong peaks from the threshold determination that might represent valid echoes. CFAR variants differ in the precision of their statistical processing, such as whether min-max-sum, sorting, or averaging operations are used, and whether appropriate weighting or scaling is employed to achieve a sufficient distinction between valid echoes and background noise. Various parameters of the algorithm (e.g., block size, window size) can be tuned to optimize the adaptiveness of the threshold. CFAR offset values ​​can be stored in memory and added to the algorithm-based threshold to provide further tuning of the CT signal.

[0050] CFAR element 608 can operate on a symmetrical or asymmetrical window around the “current” sample of the correlated amplitude signal. Accordingly, delay element 609 can be used to provide a suitable time offset between the “previous” correlated amplitude signal supplied to CFAR element 608 and the “current” correlated amplitude signal supplied to other elements of the processing circuitry. Comparator 610 compares the current correlated amplitude signal with a CFAR threshold signal, asserting a selection signal for multiplexer 612 to indicate when the correlated amplitude signal is above the threshold (“peak region”), and deasserting the selection signal to indicate when the correlated amplitude signal is below the threshold (“non-peak region”). Noise averaging block 614 receives a selection signal at an inverting enable ( / EN) input (also known as a disable input), which disables the operation of noise averaging block 614 when the comparator output is asserted. In this way, the averaging block operates on the non-peak region of the signal and ignores the non-peak region of the correlated amplitude signal.

[0051] According to this technology, a noise level is calculated in a noise level calculator 614 based on the signal in the relevant amplitude signal that is only outside the peak region. A noise averaging block 614 calculates the average value within a given portion or moving window of the non-peak relevant amplitude signal. As an example, a separate average value is calculated for each portion of the amplitude signal. The length of the signal portion or moving window is appropriately predefined and / or controllable, for example, under the control of a microcontroller (ECU). The noise averaging block 614 may be provided with a clock signal to define the length of the amplitude signal portion. For example, in an advantageous embodiment, the length of the signal portion is 0.1 ms to 10 ms, or, for example, 0.5 ms to 5 ms, such as 1 ms to 4 ms or 2.5 ms to 3.0 ms. The averaging block may, for example, be configured to sum the signal in the non-peak region of the signal portion and divide it by the duration of the non-peak region of the signal portion. While this application refers to an average value, it should be understood that the resulting average value can be any type of average value known to those skilled in the art, including median, arithmetic mean (mean), modulus, geometric mean and / or weighted average, and exponential rolling average.

[0052] For each peak in the current relevant amplitude signal, peak measurement element 618 determines the signal strength by identifying the peak value (local maximum). Signal-to-noise ratio (SNR) block 616 receives each peak value from peak measurement element 618 and calculates the SNR value for that peak using the corresponding noise average value from the noise averaging block. It is noted here that block 616 is not limited to any defined formula, such as SNR = 20log 10 (Signal / Noise). In practice, given the hardware complexity typically associated with logarithmic calculations, it might be preferable to use a simple ratio or other calculation that is monotonically related to the defined formula in the region of interest. Comparator 620 compares the SNR value to a predetermined SNR threshold (ST) value, asserting an echo detection signal only if the peak's SNR value exceeds this threshold. Although not shown here, the output of peak measurement element 618 can also be obtained from the sensor when the echo detection signal is asserted.

[0053] When information about ground reflection is needed, such information can be obtained as the identified peak signal without asserting the echo detection signal. Specific alternative implementations are not excluded, including separate comparators for information about ground reflection.

[0054] Figure 7 This is a block diagram of a second embodiment of the processing circuit according to the present technology. This second embodiment is related to... Figure 6The first embodiment shown differs in that an additional criterion is applied to exclude false echoes. This additional criterion is based on an evaluation of the derivative signal from the correlated response. The derivative block 722 determines the time derivative of the correlated amplitude signal. A possible specific implementation is described, for example, in incorporated application 16 / 530,654 (“Ultrasonic sensor having edge-based echo detection”). Comparator 724 compares the derivative signal to a predetermined derivative threshold (DT) value. In this example, the threshold is retrieved from memory, but may alternatively be calculated based on one or more values ​​in memory. The output signal is passed to logic AND block 726, which asserts an echo detection signal only if the derivative exceeds DT and the peak SNR exceeds ST (indicated by the assertion of the output of comparator 620). A second delay element 709 is included within the derivative calculation path to provide a suitable time offset that takes into account the CFAR element delay and the SNR determination delay, such that the input to logic AND block 726 corresponds to the same given sample of the correlated amplitude signal.

[0055] Therefore, if the derivative signal exceeds the threshold in comparator block 724, only any pulse output from comparator 620 is accepted. This second criterion is based on the fact that the rising and / or falling edges of the observed valid echo peaks are easily distinguishable, allowing the boundaries of the echo to be identified more accurately. Thus, the start of an echo can be detected when the derivative signal rises above a predefined edge threshold. The end of an echo will be detected when the derivative signal falls below another predefined edge threshold. Therefore, any signal with a peak level above the SNR ratio threshold but lacking a properly shaped amplitude peak will still be rejected. Although not shown in one of the figures, alternatives to comparator 610 and / or other methods may be used to distinguish peak regions from other regions.

[0056] Figure 8 This is a block diagram of a third embodiment of the processing circuit according to the present technology. It is similar to... Figure 6 The implementation scheme is as follows, but comparator 610 is further connected to multiplexer 812 on the main signal path to suppress the non-peak portions of the relevant amplitude signal and only pass the peak portions of the relevant amplitude signal to peak measurement block 616. Therefore, the peak measurement results provided by peak measurement block 618, and correspondingly, the SNR measurement results generated by block 616, are only for those peaks exceeding the CFAR threshold. As previously stated, comparator 620 asserts an echo detection signal only when the calculated SNR exceeds the SNR threshold.

[0057] Figure 9A block diagram of a fourth embodiment of the processing circuit according to the present technology is shown. Similar to the previous embodiments, comparator 610 disables noise averaging block 614 when the relevant amplitude signal exceeds the CFAR threshold. Figure 7 Similar to the implementation, derivative block 722 determines the time derivative of the relevant amplitude signal, and comparator 724 detects when the (rising or falling) edge derivative exceeds a threshold. However, unlike gating the output of comparator 620, derivative comparator 724 controls main path multiplexer 912 to transmit the relevant amplitude signal only if the derivative criterion is met and also suppresses the relevant amplitude signal. Perhaps appropriately, the result of comparator 724 is first converted into a pulse to specify the duration of the echo peak. Peak measurement block 618, and correspondingly, SNR calculation block 616, operate only on peaks with the necessary rising and / or falling edge definitions. When the calculated SNR value exceeds the SNR threshold, comparator 620 asserts an echo detection signal.

[0058] Although Figure 7 and Figure 9 The instruction is to calculate the derivative from the correlated amplitude signal in block 722, but this does not preclude the derivative signal from being provided as a separate input, such as from a separate correlator or its separate calculation. Preferably, the derivative threshold used in comparator 724 is derived from a CFAR algorithm suitable for determining a suitable derivative threshold.

[0059] Figure 10 It shows that Figure 8 and Figure 9 A fifth embodiment of the feature combination. The main signal path includes a multiplexer 812 controlled by comparator 810 to transmit only the peak regions of the signal, and further includes a multiplexer 912 controlled by derivative comparator 724 to transmit only those peaks that satisfy the derivative criterion. Therefore, peak measurement block 618 and thus SNR block 616 operate only on those peaks that satisfy the CFAR and derivative criteria, and comparator 620 asserts the echo detection signal only when the SNR criterion is met.

[0060] Figure 4B and Figure 5B The results of echo detection using CFAR, derivative, and SNR standards are shown, indicating the suppression of (most) spurious echoes that are not suppressed in the reference technique. Therefore, the sensing method and controller using the SNR standard provide a more reliable output. Furthermore, by reducing the number of spurious echoes (potentially to zero), the total number of detected echoes is reduced, decreasing the amount of data that may need to be transmitted from the sensor to the ECU via a limited bandwidth bus. This reduction in data volume can advantageously reduce measurement latency, as well as the corresponding increase in measurement repetition time and latency. Such advantages can be amplified in higher bandwidth buses supporting multiple sensors.

[0061] It should also be noted that this technique advantageously shields against spurious echoes that may be attributable to compression noise. More specifically, it should be noted that some parking assist sensing systems compress raw data, such as zero intermediate frequency (ZIF) IQ data, correlated amplitude data, and / or time-of-flight (ToF) data, for transmission from the sensor controller to the microcontroller or ECU. Compression can introduce noise, which some systems incorrectly interpret as echoes. The SNR standard, optionally combined with CFAR and derivative standards, achieves shielding against such spurious echoes.

[0062] It should be noted that the processing and processing circuits disclosed in this invention can be implemented in a sensor controller, and alternatively, at least some of the processing and processing circuits disclosed in this invention can be implemented in an ECU or microcontroller that receives raw data from the sensor controller. When processing is implemented by the sensor controller, it is conceivable that excluded peaks that may represent ground reflections can still be transmitted to the ECU at least intermittently. Alternatively, excluded peaks that may represent ground reflections can be compared with a stored reference signal, and if a suitable match is found, a suitable signal indicating the presence and / or type of ground reflection can be transmitted to the ECU. Other data transmitted to the ECU may include data specifying noise levels, and / or data specifying the locations of falling and rising edges, such as those obtained in the analysis through derivative-based processing.

[0063] Another potential advantage of this invention is the reduction in the necessary size of the memory on or connected to the controller. Individually removing ground reflections allows the CFAR algorithm to execute with a reduced memory buffer compared to what would otherwise be required. The CFAR memory buffer depends at least in part on the number of echo peaks that need to be stored in the memory. It has been found that the number of echo peaks to be stored can be less than 30, preferably less than 25, or more preferably 20 or less, or even 15 or less. Acceptable results can be achieved even with 10 stored echo peaks or less.

[0064] While the operations shown and described above are presented as occurring sequentially for illustrative purposes, in practice, this method can be performed by multiple integrated circuit components that operate simultaneously and even speculatively to achieve out-of-order operation. This sequential description is not intended to be limiting. Furthermore, the foregoing description assumes the use of an I / O line bus, but other bus implementations, including LIN, CAN, and DSI3, are contemplated. These and many other modifications, equivalents, and alternatives will become apparent to those skilled in the art once the foregoing disclosure is fully understood. For example, the correlation amplitude signal can be determined by squaring the output of the correlation filter or by discarding the sign bit of the binary representation. It is intended that the following claims be construed as encompassing all such modifications, equivalents, and alternatives where applicable.

[0065] In summary, an exemplary controller includes: a transmitter that drives an acoustic transducer using a drive signal to generate an acoustic pulse train; a receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; and processing circuitry coupled to the transmitter and the receiver, the processing circuitry being configured to convert the received response into output data by: correlating the response with the drive signal to obtain a correlated amplitude signal; distinguishing between peak and non-peak regions in the correlated amplitude signal; deriving the noise level in the non-peak region of the correlated amplitude signal based on the correlated amplitude signal in the non-peak region of the portion of the correlated amplitude signal; calculating the signal-to-noise ratio (SNR) of the peak signal in the portion as the ratio of the peak value of the peak signal to the noise level in the portion of the correlated amplitude signal; and accepting the peak signal as an echo only if the SNR of the peak signal exceeds a predetermined threshold.

[0066] An exemplary parking assistance control system includes a microcontroller, at least one controller for an acoustic transducer, and a communication bus coupled to the microcontroller and the at least one controller. The controller includes: a transmitter that drives the acoustic transducer using a drive signal to generate an acoustic pulse train; a receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; processing circuitry coupled to the receiver to convert the received response into output data; and an interface that transmits the output data via the communication bus. At least one of the processing circuitry and the microcontroller is configured to: correlate the response with a pulse pattern to obtain a correlated response; distinguish peak regions from non-peak regions in the correlated response; derive the noise level in the non-peak region only using a portion of the correlated response; calculate the signal-to-noise ratio (SNR) of the peak signal within the portion as the ratio of the peak value of the peak signal to the noise level; and accept the peak signal as an echo only when the SNR of the peak signal exceeds a predetermined threshold.

[0067] An exemplary method of operating a piezoelectric-based sensor includes: driving a piezoelectric transducer to generate a train of acoustic energy pulses; obtaining a response from the piezoelectric transducer; correlating the response relative to the driving signal to obtain a correlated response; distinguishing between peak and non-peak regions in the correlated response; deriving a noise level in the non-peak region only using a portion of the correlated response; calculating the signal-to-noise ratio (SNR) of the peak signal in the portion as the ratio of the peak value of the peak signal to the noise level; and accepting the peak signal as an echo only if the SNR of the peak signal exceeds a predetermined threshold.

[0068] Another exemplary controller for an acoustic transducer includes: a transmitter that drives the acoustic transducer using a drive signal to generate an acoustic pulse train; a receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; and processing circuitry coupled to the transmitter and the receiver, the processing circuitry being configured to convert the received response into output data by: correlating the response with the drive signal to obtain a correlated response; distinguishing between peak and non-peak regions in the correlated response; using the non-peak region in a portion of the correlated response to derive a noise level; calculating the signal-to-noise ratio (SNR) of the peak signal within the portion as the ratio of the peak value of the peak signal to the noise level; and identifying the peak signal as a ground reflection if the SNR is below a predetermined threshold.

[0069] Each of the foregoing examples can be used individually or in combination, and can include one or more of the following features in any suitable combination: 1. Using processing circuitry or a microcontroller to determine a derivative signal based on a relevant amplitude signal, and accepting the peak signal as an echo only if the derivative signal corresponding to the peak signal exceeds a derivative threshold. 2. The derivative threshold is a CFAR threshold determined according to a Continuous False Alarm Rate (CFAR) algorithm applied to the derivative signal. 3. A memory for storing the derivative threshold. 4. Calculating the CFAR threshold using the Continuous False Alarm Rate (CFAR) algorithm and comparing the relevant amplitude signal with the CFAR threshold to distinguish between peak and non-peak regions. 5. Accepting the peak signal as an echo only if the peak signal is within one of the peak regions. 6. The processing circuitry includes a peak measurement element for detecting the peak. 7. Providing an output indicating the presence of ground reflection. 8. The output indicating ground reflection is based on a calculated SNR ratio.

[0070] Although in some countries, dependent claims are written down to refer to individual claims as a matter of claim drafting rules, it is observed that the inventor can foresee any combination of dependent claims with any of the preceding claims and is considered to be included in the complete disclosure of this application. Furthermore, it should be understood that a dependent claim designated for one claim class also applies to another claim class, but is omitted only for the purpose of limiting the total number of claims and any claim fees that may arise from them.

Claims

1. A controller for an acoustic transducer, characterized in that, The controller includes: A transmitter that uses a drive signal to drive the acoustic transducer to generate an acoustic pulse train; A receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; A processing circuit, coupled to the transmitter and the receiver, is configured to convert the received response into output data in such a manner as follows: The response is correlated with the driving signal to obtain a related amplitude signal; By comparing the relevant amplitude signal with the continuous false alarm rate (CFAR) threshold, the peak region and non-peak region in the relevant amplitude signal are distinguished. The noise level in the non-peak region of the relevant amplitude signal is derived based on the relevant amplitude signal in a portion of the relevant amplitude signal; Calculate the signal-to-noise ratio (SNR) of the peak signal within the specified portion as the ratio of the peak value of the peak signal to the noise level in the specified portion of the associated amplitude signal; and The peak signal is accepted as an echo only if the SNR of the peak signal exceeds a predetermined threshold.

2. The controller for an acoustic transducer according to claim 1, characterized in that, The processing circuit is further configured as follows: The derivative signal is determined based on the relevant amplitude signal; The peak signal is accepted as an echo only when the derivative signal corresponding to the peak signal exceeds the derivative threshold.

3. The controller for an acoustic transducer according to claim 2, characterized in that, The derivative threshold is the CFAR threshold determined based on the Continuous False Alarm Rate (CFAR) algorithm applied to the derivative signal.

4. The controller for an acoustic transducer according to any one of claims 1 to 3, characterized in that, The step of distinguishing the peak region from the non-peak region includes calculating the CFAR threshold using the CFAR algorithm, wherein the processing circuit is further configured to accept the peak signal as an echo only when the peak signal is within one of the peak regions.

5. A parking assistance control system, characterized in that, The system includes a microcontroller, at least one controller for an acoustic transducer, and a communication bus coupled to the microcontroller and the at least one controller, wherein the controller includes: A transmitter that uses a drive signal to drive the acoustic transducer to generate an acoustic pulse train; A receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; Processing circuitry, coupled to the receiver, to convert the received response into output data; and The interface transmits the output data through the communication bus. Wherein, at least one of the processing circuit and the microcontroller is configured as follows: The response is correlated with the impulse mode to obtain a correlated response; The peak and non-peak regions in the correlation response are distinguished by comparing the correlation response with the continuous false alarm rate (CFAR) threshold. The noise level in the portion of the relevant response is derived using only the non-peak region within that portion. Calculate the signal-to-noise ratio (SNR) of the peak signal within the specified portion as the ratio of the peak value of the peak signal to the noise level; and The peak signal is accepted as an echo only if the SNR of the peak signal exceeds a predetermined threshold.

6. The parking assistance control system according to claim 5, characterized in that, The microcontroller further determines the derivative signal based on the relevant response, and accepts the peak signal as an echo only when the derivative signal corresponding to the peak signal exceeds the derivative threshold.

7. A method for operating a piezoelectric-based sensor, characterized in that, The method includes: A driving signal is used to drive a piezoelectric transducer to generate a pulse train of sound energy. A response is obtained from the piezoelectric transducer; The response is correlated with the drive signal to obtain a correlated response; The peak and non-peak regions in the correlation response are distinguished by comparing the correlation response with the continuous false alarm rate (CFAR) threshold. The noise level in the portion of the relevant response is derived using only the non-peak region within that portion. Calculate the signal-to-noise ratio (SNR) of the peak signal within the specified portion as the ratio of the peak value of the peak signal to the noise level; and The peak signal is accepted as an echo only if the SNR of the peak signal exceeds a predetermined threshold.

8. The method for operating a piezoelectric-based sensor according to claim 7, characterized in that, The method further includes: if the SNR is lower than the predetermined threshold, then reporting the peak signal as ground reflection.

9. A controller for an acoustic transducer, characterized in that, The controller includes: A transmitter that uses a drive signal to drive the acoustic transducer to generate an acoustic pulse train; A receiver that senses the response of the acoustic transducer to the echo of each acoustic pulse train; A processing circuit, coupled to the transmitter and the receiver, is configured to convert the received response into output data in such a manner as follows: The response is correlated with the drive signal to obtain a correlated response; The peak and non-peak regions in the correlation response are distinguished by comparing the correlation response with the continuous false alarm rate (CFAR) threshold. The noise level is derived using the non-peak region of a portion of the relevant response; Calculate the signal-to-noise ratio (SNR) of the peak signal within the specified portion as the ratio of the peak value of the peak signal to the noise level; and If the SNR is below a predetermined threshold, the peak signal is identified as ground reflection.

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