WO2021170133A1 - 提升目标探测精度的方法、集成电路、无线电器件及电子设备 - Google Patents

提升目标探测精度的方法、集成电路、无线电器件及电子设备 Download PDF

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WO2021170133A1
WO2021170133A1 PCT/CN2021/078409 CN2021078409W WO2021170133A1 WO 2021170133 A1 WO2021170133 A1 WO 2021170133A1 CN 2021078409 W CN2021078409 W CN 2021078409W WO 2021170133 A1 WO2021170133 A1 WO 2021170133A1
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Prior art keywords
speed
target
distance
velocity
fourier transform
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PCT/CN2021/078409
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English (en)
French (fr)
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张小龙
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加特兰微电子科技(上海)有限公司
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Priority to US17/998,802 priority Critical patent/US20230258766A1/en
Publication of WO2021170133A1 publication Critical patent/WO2021170133A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers
    • G01S7/354—Extracting wanted echo-signals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/08—Systems for measuring distance only
    • G01S13/32—Systems for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated
    • G01S13/34—Systems for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated using transmission of continuous, frequency-modulated waves while heterodyning the received signal, or a signal derived therefrom, with a locally-generated signal related to the contemporaneously transmitted signal
    • G01S13/343—Systems for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated using transmission of continuous, frequency-modulated waves while heterodyning the received signal, or a signal derived therefrom, with a locally-generated signal related to the contemporaneously transmitted signal using sawtooth modulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/411—Identification of targets based on measurements of radar reflectivity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/50—Systems of measurement based on relative movement of target
    • G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
    • G01S13/583—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves and based upon the Doppler effect resulting from movement of targets
    • G01S13/584—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves and based upon the Doppler effect resulting from movement of targets adapted for simultaneous range and velocity measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers
    • G01S7/356—Receivers involving particularities of FFT processing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G01S7/4052—Means for monitoring or calibrating by simulation of echoes
    • G01S7/4056—Means for monitoring or calibrating by simulation of echoes specially adapted to FMCW
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/42—Simultaneous measurement of distance and other co-ordinates
    • G01S13/44—Monopulse radar, i.e. simultaneous lobing

Definitions

  • This application relates to the technical field of radar signal processing, in particular to a method for improving the accuracy of target detection, computer equipment, storage media, integrated circuits, radio devices, and electronic equipment.
  • a method for improving the accuracy of target detection may include:
  • the target peak value is compensated by using the speed ambiguity multiple, and the target data obtained based on the compensated target peak number is used as the real target data, which is more effective than the target data obtained in the traditional way.
  • Accuracy especially for scenes where the target speed is too high, can effectively improve the accuracy of target detection.
  • the method may further include:
  • the target peak data is compensated based on the speed blur multiple, and the target data is acquired based on the compensated target peak number.
  • the speed fuzzy multiple can be used to compensate, thereby effectively reducing the adverse effect of the high speed of the target on target detection, improving the accuracy of target detection, and for low-speed applications
  • target detection can be performed directly in a traditional way.
  • the target data may include at least one of distance, speed, angle, and shape.
  • the angle and point cloud data of the target are acquired (for example, the shape and posture based on the point cloud data), etc., the speed and/distance of the target need to be compensated first.
  • the acquiring speed ambiguity multiple and target peak data based on the received echo signal includes:
  • the compensation operation in the embodiment of the present application is performed between CFAR and DOA (Direction of Arrival Estimation) based on the traditional signal processing procedure.
  • the compensating the target peak data based on the speed blur multiple includes:
  • the obtaining the compensation amount based on the compensation coefficient and the speed blur multiple includes:
  • the compensation amount is acquired based on the compensation coefficient, the velocity blur multiple, the margin of the Doppler frequency shift, and the sampling interval of velocity dimensional Fourier transform input data.
  • the obtaining the compensation coefficient based on the sampling interval of the velocity-dimensional Fourier transform input data includes:
  • the compensation coefficient is acquired based on the sweep bandwidth, the size of the window function, the number of Fourier transform points, the sweep center frequency point, the sampling rate, and the sampling interval of the velocity-dimensional Fourier transform input data.
  • the target peak data includes a distance factor
  • the compensation amount includes a distance compensation amount
  • the compensation coefficient includes a distance compensation coefficient
  • the The size of the window function includes the size of the velocity-dimensional window function, the number of points of the Fourier transform includes the number of points of the distance-dimensional window function; the frequency-based sweep bandwidth, the size of the window function, the number of Fourier transform points, and the frequency sweep center
  • the frequency point, the sampling rate, and the sampling interval of the velocity-dimensional Fourier transform input data to obtain the compensation coefficient include:
  • the distance compensation amount is obtained based on the distance compensation coefficient and the speed blur multiple, and the distance factor of the target peak data is compensated based on the distance compensation amount, so as to obtain the target value distance.
  • the target peak data includes a speed factor
  • the compensation amount includes a speed compensation amount
  • the compensation coefficient includes a speed compensation coefficient
  • the The size of the window function includes the size of the distance-dimensional window function
  • the number of points of the Fourier transform includes the number of points of the velocity-dimensional window function
  • the frequency-based sweep bandwidth includes the size of the window function, the number of Fourier transform points, and the frequency sweep center
  • the frequency point, the sampling rate, and the sampling interval of the velocity-dimensional Fourier transform input data to obtain the compensation coefficient include:
  • Input data based on the sweep bandwidth, the size of the distance dimension window function, the number of points of the velocity dimensional Fourier transform, the sweep center frequency point, the sampling rate, and the velocity dimensional Fourier transform Obtain the speed compensation coefficient at a sampling interval of
  • the speed compensation amount is obtained based on the speed compensation coefficient and the speed blur multiple, and the speed factor of the target peak data is compensated based on the speed compensation amount, so as to obtain the target value speed.
  • An embodiment of the present application also provides a computer device, which may include a memory and a processor, the memory stores a computer program, and the processor implements the method described in any one of the embodiments of the present application when the computer program is executed. A step of.
  • the embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in any one of the embodiments of the present application are implemented.
  • the embodiment of the present application also provides an integrated circuit, which may include:
  • the signal transceiver channel is used to transmit radio signals and receive the wave signals formed by the back reflection of the radio signals by the target;
  • the signal processing module is used to obtain target object data based on the method described in any one of the embodiments of the present application.
  • the signal processing module includes:
  • a signal processing unit configured to obtain speed ambiguity multiples and target peak data based on the echo signal
  • a compensation unit configured to compensate the target peak data based on the speed blur multiple
  • the data processing unit is used to obtain target data based on the compensated peak value of the target.
  • the radio signal is a millimeter wave signal.
  • the integrated circuit is an AiP (Antenna in Package, that is, packaged antenna) chip or AoC (Antenna on Chip, that is, an antenna on chip) chip.
  • AiP Antenna in Package, that is, packaged antenna
  • AoC Antenna on Chip, that is, an antenna on chip
  • the embodiment of the present application also provides a radio device, which may include:
  • the integrated circuit as described in any one of the embodiments of the present application is arranged on the carrier;
  • the antenna is arranged on the carrier or integrated with the integrated circuit to form an AiP or AoC structure, and is used for transmitting and receiving radio signals.
  • the embodiment of the present application also provides an electronic device, including:
  • the device body The device body;
  • the radio device described in the embodiment of the present application set on the device body
  • the radio device is used for target detection and/or communication.
  • FIG. 1 is a schematic diagram of a radar system provided by an embodiment of this application.
  • FIG. 2 is a schematic diagram of an integrated circuit provided by an embodiment of the application.
  • FIG. 3 is a flowchart of a method for improving target detection accuracy provided by an embodiment of this application.
  • FIG. 4 is a schematic diagram of a chirp signal waveform provided by an embodiment of the application.
  • FIG. 5 is a schematic diagram of a CFAR result provided by an embodiment of this application.
  • FIG. 6 is a flowchart of a method for calculating a speed compensation value provided by an embodiment of the application
  • FIG. 7 is a flowchart of a method for calculating a distance compensation value provided by an embodiment of the application.
  • FIG. 8 is a flowchart of another method for obtaining a compensated speed factor according to an embodiment of the application.
  • FIG. 9 is a flowchart of another method for improving target detection accuracy according to an embodiment of the application.
  • FIG. 10 is a block diagram of a device for improving target detection accuracy provided by an embodiment of the application.
  • the method for improving the accuracy of target detection provided in this embodiment can be applied to various sensing systems.
  • FMCW radar as an example to describe the relevant technical content of this application in detail, but it should be noted that the content recorded in this application is not limited to radar products, and is also applicable to all other target detection sensors.
  • FMCW Frequency Modulation Continuous Wave
  • the basic principle of FMCW radar speed and distance measurement is: use the transmitting antenna to transmit radio signals (ie transmitting signals) to detect the target in the detection area, the transmitted signal is reflected by the target to form an echo signal, and then the receiving antenna receives the above-mentioned echo signal.
  • radio signals ie transmitting signals
  • the processing module mixes the echo signal to obtain an intermediate frequency signal, and continues analog-to-digital conversion, sampling, distance-dimensional Fourier transform (ie 1D FFT), velocity-dimensional Fourier transform (ie 2D FFT), and constant false alarm detection (Ie CFAR), fluctuation direction estimation (ie DOA) and other operations, and then obtain the target's distance, speed, angle and other information, and can perform subsequent point cloud imaging and live body based on the detected target information (ie target data) Application of physical sign detection and monitoring.
  • ie 1D FFT distance-dimensional Fourier transform
  • ie 2D FFT velocity-dimensional Fourier transform
  • Ie CFAR constant false alarm detection
  • DOA fluctuation direction estimation
  • the FMCW radar may include a signal generator F, which is used to synthesize electromagnetic wave signals.
  • the transmitting end of the radar system includes a transmitting antenna Tx, and the receiving end includes a receiving antenna Rx.
  • the transmitting antenna Tx will transmit signals as electromagnetic waves.
  • the radar system also includes a mixer. In the mixer, the transmitted signal can be used to mix the received echo signal to obtain a mixed signal. Then, based on the above-mentioned basic principles of FMCW radar speed and distance measurement, parameters such as the speed and distance of the target are measured.
  • embodiments of the present application provide a method, computer equipment, storage media, integrated circuits, radio devices, and electronic equipment for improving the accuracy of target detection.
  • the method for improving the accuracy of target detection provided by the embodiments of the present application can be applied to the integrated circuit as shown in FIG. (Such as millimeter wave signals, terahertz signals, etc.), as well as wave signals formed by the back reflection of the received radio signal by the target, and the signal processing module 202 can perform signal processing on the echo signal to implement the description in any embodiment of the present application The method then obtains the target data.
  • the above-mentioned signal processing module 202 may include a signal processing unit 2021, a compensation unit 2022, a data processing unit 2023, etc.
  • the signal processing unit 2021 may be used to obtain velocity ambiguity multiples and target peak data, etc. based on the echo signal.
  • the compensation unit 2022 can be used to compensate the target peak data based on the speed blur multiple, and the data processing unit 2023 can be used to obtain target data based on the compensated target peak number.
  • the above-mentioned integrated circuit may be a chip structure that does not include an antenna structure, or a structure that integrates an antenna (such as AiP (English: Antennas in Package, abbreviation: AiP) chip or AoC (English: Antenna on Chip, Abbreviation: AoC) chip, etc.), the above-mentioned radio signal may be a millimeter wave signal.
  • AiP American: Antennas in Package, abbreviation: AiP
  • AoC American: Antenna on Chip, Abbreviation: AoC
  • the above-mentioned integrated circuit can use a unified digital controller to connect with the digital function module of the system-on-chip through a digital control interface, and then realize the unified configuration management of the operation status of the digital function module in the system-on-chip through the configuration module and state machine, which improves the integrated circuit Operational control efficiency of the system-on-chip.
  • the integrated circuit can also include other digital circuits, digital functional modules, and operation control equipment.
  • Various digital circuits are the basic structure of integrated circuits. Different digital circuits can realize different functions of integrated circuits. Digital functional modules It is used to detect whether each digital circuit is working properly.
  • the operation control device can perform unified configuration management on the digital function module.
  • the digital controller in the operation control device can send the control signal for function detection to the digital function module through the digital control interface.
  • the configuration information and status information are stored in the module.
  • the configuration information can be obtained from the outside.
  • the state machine is used to control the working process of the integrated circuit.
  • the state machine can read the configuration information stored in the configuration module and control the digital controller accordingly.
  • the signal is output to the digital function module to realize the control of the digital function module to detect each digital circuit.
  • the method for improving target detection accuracy provided in this embodiment may be applied to a radio device, and the radio device includes: a carrier; the integrated circuit as described in the foregoing embodiment; On the carrier; the antenna is set on the carrier to send and receive radio signals, where the antenna can also be integrated into the package of the above-mentioned integrated circuit to form an AiP structure, or the antenna can be integrated on a chip to form an on-chip antenna AoC structure,
  • the carrier may be a printed circuit board PCB or the like.
  • the present application also provides a device, including: a device body; and a radio device as in the above-mentioned embodiment provided on the device body; wherein the radio device is used for target detection and/or communication .
  • the radio device may be disposed outside the device body, in another embodiment of the present application, the radio device may also be disposed inside the device body, in other embodiments of the present application In this case, the radio device may also be partly arranged inside the device body, and partly arranged outside the device body.
  • radio devices can achieve functions such as target detection and communication by transmitting and receiving signals.
  • the above-mentioned device body may be intelligent transportation equipment (such as cars, bicycles, motorcycles, ships, subways, trains, etc.), security equipment (such as cameras), smart wearable devices (such as bracelets, Glasses, etc.), smart home devices (such as TVs, air conditioners, smart lights, etc.), various communication devices (such as mobile phones, tablets, etc.), as well as barriers, smart traffic lights, smart signs, traffic cameras, and other Such industrialized manipulators (or robots), etc., can also be various instruments used to detect vital sign parameters and various equipment equipped with the instruments.
  • the radio device may be the radio device set forth in any embodiment of this application. The structure and working principle of the radio device have been described in detail in the above embodiments, and will not be repeated here.
  • FIG. 3 shows a flowchart of a method for improving target detection accuracy provided by an embodiment of the present application.
  • the method for improving target detection accuracy can be applied to the radar system shown in FIG. 1, as shown in FIG. 3.
  • the method for improving target detection accuracy may include the following steps:
  • Step 301 Obtain speed ambiguity multiple and target peak data based on the received echo signal.
  • the electromagnetic wave of the transmitting signal emitted by the transmitting antenna of the FMCW radar is a high-frequency frequency-modulated continuous wave, and its frequency changes regularly with time.
  • the high-frequency continuous wave is generally sawtooth, triangle, etc. This application takes the sawtooth as an example for description.
  • the electromagnetic wave in each frequency modulation period T is called chirp (translation: chirp), and the frequency of each chirp increases linearly with time .
  • the echo signal received by the receiving antenna of the FMCW radar is the electromagnetic wave reflected by the target. As shown in FIG. 4, it shows the waveform of the transmitted signal tx and the waveform of the echo signal rx.
  • the process of mixing the transmitted signal tx and the echo signal rx can be: mixing the transmitted signal and the echo signal to obtain the difference frequency signal IF signal, which is the mixed signal, and can also be called the intermediate frequency signal .
  • the sampled data on a chirp can be stored as rows of a matrix. For example, there are M chirps. Correspondingly, there are M rows in the rows of the matrix, and the number of sampling points in each chirp is N, which means that the columns of the matrix have N columns, so you can get one M ⁇ N sampling data matrix.
  • N-point FFT For the chirp of each frequency modulation period (that is, each row), N-point FFT can be performed separately, that is, the distance-dimensional Fourier transform, and then the M chirps are subjected to a longitudinal Doppler FFT across the chirp, that is, the velocity-dimensional Fourier transform.
  • the combined operation of transform, distance FFT (line by line) and Doppler FFT (line by column) can be regarded as a two-dimensional FFT of the corresponding sampled data for each frame.
  • the two-dimensional FFT can be used to obtain parameters such as the distance and speed of the target. Therefore, the peak position of the two-dimensional FFT can correspond to the distance and speed of the target in front of the radar.
  • CFAR constant false alarm detection
  • Sweep bandwidth B distance-dimensional Fourier transform points nfft1, velocity-dimensional Fourier transform points nfft2 (can also be considered as the size (LZ) of velocity-dimensional FFT), sampling interval T of velocity-dimensional FFT input data, sweep Frequency center frequency point fc, sampling rate Fs, target distance R, target normal velocity v, distance dimension window function size Win1size, velocity dimension window function size Win2size, Doppler frequency shift margin frd, Doppler frequency shift fD, Chirp serial number n (also pulse serial number), time offset ts from the starting point of chirp within chirp, mixing signal amplitude A and velocity ambiguity multiple q; among them, velocity The ambiguity factor q can be used to represent the number of folds between the true Doppler shift fD and the pulse repetition frequency F.
  • T is the sampling interval of the sensor velocity dimension FFT input data for the non-virtual array
  • v 0.5 ⁇ fD, where ⁇ is the transmitted signal wavelength.
  • fD ⁇ 0.5F it can be determined that the speed of the target is within the speed range of the radar.
  • the speed range of the radar is -10m/s to +10m/s, and the moving speed of the target is 8m/s, then the speed measured by the radar The speed of the target is not blurred.
  • the speed of the target exceeds the speed range of the radar.
  • the speed range of the radar is -10m/s to +10m/s, and the moving speed of the target is 11m/s.
  • the radar will consider the speed of the target to be -9m/s, and when the speed of the target is 31m/s, 51m/s, after the folding effect, the radar speed measurement will be judged to be -9m/s.
  • the radar cannot distinguish the number of folds between the real Doppler shift fD and the pulse repetition frequency F, that is, the frequency interval between the two, so the speed ambiguity appears.
  • Step 302 Compensate the target peak data based on the speed blur multiple.
  • the compensation coefficient may be obtained based on the sampling interval of the velocity-dimensional Fourier transform input data first, and then the compensation amount may be obtained based on the compensation coefficient and the velocity ambiguity multiple, and the target peak data may be compensated based on the compensation amount.
  • the compensation amount can be obtained based on the compensation coefficient, the velocity ambiguity multiple, the margin of the Doppler frequency shift, and the sampling interval of the velocity-dimensional Fourier transform input data.
  • the following formula can be used to obtain the compensation amount:
  • Peak-comp comp*(q+frd*T); Among them, Peak-comp is the compensation amount, and comp is the compensation coefficient.
  • the compensation amount Peak-comp may include the distance factor compensation amount K peak-comp and the speed factor
  • the compensation amount P peak-comp may include the distance compensation coefficient rng-comp and the speed compensation coefficient vel-comp. That is, the distance factor compensation amount K peak-comp is used to compensate the distance factor P peak of the target peak data, and the speed factor compensation amount P peak-comp is used to compensate the speed factor K peak of the target peak data.
  • the formula for distance factor compensation can be:
  • the speed factor compensation formula can be:
  • the compensation coefficient can be obtained based on the sweep bandwidth, the size of the window function, the number of Fourier transform points, the sweep center frequency, the sampling rate, and the sampling interval of the velocity-dimensional Fourier transform input data .
  • the distance of the target when obtaining the distance of the target based on the peak number of the compensated target, it can be based on the sweep bandwidth, the size of the velocity dimension window function, the number of distance Fourier transform points, the sweep center frequency point, and the sampling rate And the sampling interval of the velocity-dimensional Fourier transform input data to obtain the distance compensation coefficient.
  • the speed of the target when obtaining the speed of the target based on the compensated peak number of the target, it can be based on the sweep bandwidth, the size of the distance dimension window function, the number of points of the speed dimension Fourier transform, the sweep center frequency point, and the sampling rate And the sampling interval of the velocity-dimensional Fourier transform input data to obtain the velocity compensation coefficient.
  • Step 303 Obtain target object data based on the compensated peak value of the target object.
  • the aforementioned target data may include at least one of distance, speed, angle, and shape.
  • the method for improving the accuracy of target detection provided by the embodiments of the present application, after the two-dimensional fast Fourier transform and constant false alarm detection, and before the direction of arrival estimation, by using the speed ambiguity multiple to obtain the speed factor and/or the CFAR
  • the distance factor is compensated, and the speed of the target and the distance from the target to the radar are determined according to the compensated speed factor and the compensated distance factor, which can effectively improve the target and reduce the speed and/or distance of the acquired target Accuracy.
  • the velocity compensation value and the distance compensation value are respectively determined according to the velocity ambiguity multiple, the margin of the Doppler shift residue, and the sampling interval of the velocity-dimensional Fourier transform input data, etc., Need to judge whether the speed blur multiple is greater than 0.
  • the speed blur factor is greater than 0, it indicates that there is speed blur.
  • the speed blur multiple is equal to 0, it means that there is no speed blur.
  • the target when the speed blur multiple is equal to 0, that is, there is no speed blur, and the target can be considered to be in a low-speed motion state without compensation. Therefore, it is determined that both the speed compensation value and the distance compensation value are zero.
  • the speed blur factor is greater than 0, there is speed blur, and the target can be considered to be in a high-speed motion state, and the speed needs to be corrected and compensated. Therefore, take the remaining margin based on the speed blur factor and Doppler frequency shift Determine the velocity compensation value with the sampling interval of the velocity-dimensional Fourier transform input data.
  • a speed threshold also can be considered as a speed blur threshold
  • the compensation operation it is also possible to pre-set a speed threshold (also can be considered as a speed blur threshold), and to determine whether it is necessary to perform the above based on the currently acquired target speed value (or speed blur multiple).
  • the compensation operation That is, if the obtained target speed value (or speed blur multiple) is greater than the preset speed threshold (or speed blur threshold), the above compensation operation can be performed; otherwise, the compensation operation may not be performed, such as continuing to use the traditional Signal processing flow to obtain target data.
  • the compensation step can be saved, thereby improving the calculation efficiency of the radar.
  • the sampling of the input data is based on the velocity blur factor, Doppler shift margin, and velocity dimensional Fourier transform input data.
  • the process of determining the speed compensation value at intervals may include the following steps:
  • Step 601 Obtain a speed compensation coefficient.
  • the speed compensation coefficient may be a preset constant.
  • the process of obtaining the velocity compensation coefficient may be: obtaining the number of points of the velocity-dimensional Fourier transform, and determining the speed according to the number of points of the velocity-dimensional Fourier transform, the center frequency of the sweep and the sampling rate Compensation factor.
  • the following formula may also be used to obtain the speed compensation coefficient, namely:
  • the number of points nfft2 of the velocity-dimensional Fourier transform can be considered as the number of rows for performing the distance FFT.
  • the sampling rate F s may refer to the sampling frequency when digitally sampling the mixing signal.
  • the sampled data before performing the two-dimensional fast Fourier transform, may be window-multiplied in the velocity dimension and the distance dimension respectively.
  • the size of the velocity dimension window function can be set to win2size
  • the size of the distance dimension window function can be set to win1size.
  • the size of the distance dimension window function win1size, the sampling interval T of the velocity dimension Fourier transform input data, the number of velocity dimension Fourier transform points nfft2, the sweep center frequency point f c, and the sampling rate F s can be input to calculate Speed compensation coefficient.
  • Step 602 Determine the speed compensation value according to the speed compensation coefficient, the speed ambiguity multiple, the margin of the Doppler frequency shift, and the sampling interval of the speed-dimensional Fourier transform input data.
  • the expression of the speed compensation value may be as follows:
  • the velocity compensation coefficient vel_comp the velocity ambiguity multiple q, the margin f rd of the Doppler frequency shift, and the sampling interval T of the velocity-dimensional Fourier transform input data can be input to calculate the velocity compensation value.
  • the expression of the speed compensation value may be determined according to the time domain expression of the mixing signal.
  • the time domain expression of the mixed signal after the transmitted signal and the echo signal are mixed can be as follows:
  • the expression of the speed compensation value can be determined.
  • the velocity compensation coefficient is determined according to the number of points of the velocity dimensional Fourier transform, the center frequency point of the sweep frequency, and the sampling rate. Introducing the number of points of the velocity dimension Fourier transform, the center frequency of the sweep frequency and the sampling rate into the process of determining the velocity compensation value can improve the accuracy of the velocity compensation value and the accuracy of the compensated velocity factor. Therefore, the accuracy of the velocity can be improved.
  • the factor determines the accuracy of the target’s speed.
  • the sampling of the input data according to the velocity blur factor, Doppler shift margin, and velocity dimensional Fourier transform may include the following steps:
  • Step 701 Obtain a distance compensation coefficient.
  • the distance compensation coefficient may be a preset constant.
  • the process of obtaining the distance compensation coefficient may be: obtaining the number of distance-dimensional Fourier transform points, and determining the distance compensation according to the number of distance-dimensional Fourier transform points, the center frequency of the sweep and the sampling rate coefficient.
  • the expression of the distance compensation coefficient may be as follows:
  • sampling interval T of the input data of the velocity dimension Fourier transform, the number of points of the distance dimension Fourier transform, the center frequency of the sweep frequency and the sampling rate can be input into the above formula to calculate the distance compensation coefficient.
  • the sampled data before performing the two-dimensional fast Fourier transform, may be window-multiplied in the velocity dimension and the distance dimension respectively.
  • the size of the velocity dimension window function can be set to win2size
  • the size of the distance dimension window function can be set to win1size.
  • the expression of the distance compensation coefficient can be as follows:
  • the size of the velocity dimension window function win2size, the sampling interval T of the velocity dimension Fourier transform input data, the number of points of the distance dimension Fourier transform nfft1, the sweep center frequency point f c and the sampling rate F s can be input into the above formula , Calculate the speed compensation coefficient.
  • Step 702 Determine the distance compensation value according to the distance compensation coefficient, the velocity ambiguity multiple, the margin of the Doppler frequency shift, and the sampling interval of the velocity dimensional Fourier transform input data.
  • the expression of the distance compensation value may be as follows:
  • the distance compensation coefficient rng_comp the velocity ambiguity multiple q, the margin of the Doppler frequency shift residue f rd, and the sampling interval T of the velocity-dimensional Fourier transform input data can be input into the above equation to calculate the distance compensation value.
  • the distance compensation coefficient is determined according to the number of points of the distance-dimensional Fourier transform, the center frequency of the sweep frequency, and the sampling rate, and the number of points of the distance-dimensional Fourier transform, the center frequency of the sweep frequency, and the sampling rate are introduced into the distance.
  • the accuracy of the distance compensation value can be improved, and the accuracy of the compensated distance factor can be improved. Therefore, the accuracy of the distance of the target object determined according to the distance factor can be improved.
  • the two-dimensional fast Fourier transform includes the velocity-dimensional Fourier transform.
  • the velocity factor is compensated according to the velocity compensation value, and the compensated
  • the speed factor process can also include the following steps:
  • Step 801 When the velocity factor is greater than or equal to a preset multiple of the number of points of the velocity dimensional Fourier transform, the difference between the velocity factor and the number of points of the velocity dimensional Fourier transform is used as the first velocity factor.
  • the preset multiple is greater than 0 and less than 1.
  • the preset multiple of the number of points of the velocity-dimensional Fourier transform may be 0.5 times.
  • Step 802 When the velocity factor is less than a preset multiple of the number of points of the velocity-dimensional Fourier transform, the velocity factor is used as the first velocity factor.
  • Step 803 Compensate the first speed factor according to the speed compensation value to obtain the compensated speed factor.
  • different first speed factors are determined according to different judgment conditions, so that the compensated speed factor can more accurately reflect the actual movement speed information of the target, and the accuracy of the compensated speed factor is improved, thereby The accuracy of the speed of the determined target is improved.
  • the speed compensation value and the distance compensation value are both zero.
  • the target object is determined according to the compensated speed factor and the compensated distance factor.
  • Step 901 Determine the speed granularity according to the center frequency point of the frequency sweep, and determine the speed of the target object according to the speed granularity and the speed factor.
  • the process of determining the speed granularity according to the center frequency of the sweep includes: obtaining the center frequency of the sweep as f c and the sampling interval T of the speed-dimensional Fourier transform input data. Input the sweep center frequency point f c and the sampling interval T of the velocity-dimensional Fourier transform input data into the velocity granularity expression, and the velocity granularity can be calculated.
  • the expression of speed granularity can be: Among them, f c is the center frequency of the sweep, T is the sampling interval of the velocity-dimensional Fourier transform input data, and n is the chirp number.
  • Step 902 Determine the distance granularity according to the frequency sweep bandwidth corresponding to the echo signal, and determine the distance from the target to the radar according to the distance granularity and the distance factor.
  • the speed of the target and the distance from the target to the radar can be determined through simple calculations based on the speed granularity and distance granularity, which simplifies the calculation process and improves the calculation response of the radar. speed.
  • FIG. 10 shows a block diagram of an apparatus for improving target detection accuracy provided by an embodiment of the present application.
  • the apparatus for improving target detection accuracy may be configured in the implementation environment shown in FIG. 1.
  • the device for improving target detection accuracy may include a determination module 1001, a compensation value determination module 1002, a compensation module 1003, and a speed and distance determination module 1004, wherein:
  • the determination module 1001 is used to perform two-dimensional fast Fourier transform and constant false alarm detection based on the echo signal to obtain the peak data of the target, the velocity ambiguity multiple, the margin of the Doppler frequency shift, and the velocity dimension Fu
  • the sampling interval of the input data of the inner leaf transform, etc., the peak data can include the speed factor and the distance factor;
  • the compensation value determining module 1002 is used to determine the speed compensation value and/or the distance compensation value according to the speed ambiguity multiple, the margin of the Doppler shift residue, and the sampling interval of the speed-dimensional Fourier transform input data;
  • the compensation module 1003 is used to compensate the speed factor according to the speed compensation value to obtain the compensated speed factor, and to compensate the distance factor according to the distance compensation value to obtain the compensated distance factor;
  • the speed and distance determination module 1004 is used to determine the speed and distance of the target object according to the compensated speed factor and the compensated distance factor.
  • the compensation value determination module 1002 is also used to determine the input data according to the velocity ambiguity multiple, the margin of the Doppler frequency shift, and the velocity dimensional Fourier transform when the velocity ambiguity multiple is greater than 0.
  • the sampling interval determines the velocity compensation value; the distance compensation value is determined according to the velocity ambiguity multiple, the margin of the Doppler frequency shift, and the sampling interval of the velocity-dimensional Fourier transform input data.
  • the compensation value determining module 1002 is also used to obtain the speed compensation coefficient; according to the speed compensation coefficient, the speed ambiguity multiple, the margin of the Doppler frequency shift, and the speed dimensional Fourier transform input data The sampling interval determines the speed compensation value.
  • the compensation value determining module 1002 is further configured to determine the speed compensation coefficient according to the number of points of the speed dimensional Fourier transform, the center frequency of the sweep frequency, and the sampling rate.
  • the compensation value determining module 1002 is also used to obtain distance compensation coefficients; according to the distance compensation coefficient, the velocity ambiguity multiple, the margin of the Doppler frequency shift, and the velocity dimensional Fourier transform input data The sampling interval determines the distance compensation value.
  • the compensation value determining module 1002 is further configured to determine the distance compensation coefficient according to the number of distance-dimensional Fourier transform points, the center frequency of the sweep frequency, and the sampling rate.
  • the compensation value determining module 1002 is further configured to determine that the speed compensation value and the distance compensation value are both zero when the speed fuzzy multiple is equal to 0;
  • the speed and distance determination module 1004 is also used to determine the speed granularity according to the center frequency of the sweep, and determine the speed of the target object according to the speed granularity and the speed factor; determine the distance granularity according to the sweep bandwidth corresponding to the echo signal, and determine the distance granularity according to the distance granularity.
  • the sum distance factor determines the distance from the target to the radar.
  • the compensation module 1003 is further configured to, when the speed factor is greater than or equal to a preset multiple of the number of points of the speed dimensional Fourier transform, the difference between the speed factor and the number of points of the speed dimensional Fourier transform As the first velocity factor; when the velocity factor is less than the preset multiple of the number of points of the velocity dimension Fourier transform, the velocity factor is taken as the first velocity factor; the first velocity factor is compensated according to the velocity compensation value to obtain the compensated velocity factor.
  • the compensation module 1003 is further configured to subtract the speed compensation value from the first speed factor to obtain the compensated speed factor.
  • the compensation module 1003 is further configured to subtract the distance compensation value from the distance factor to obtain the compensated distance factor.
  • each module in the above device for improving the accuracy of target detection can be implemented in whole or in part by software, hardware, and a combination thereof.
  • the above-mentioned modules can be embedded in the form of hardware or independent of the processor in the radar system, or can be stored in the memory of the radar system in the form of software, so that the processor can call and execute the corresponding operations of the above-mentioned modules.
  • a computer device including a memory and a processor, and a computer program is stored in the memory, and the processor implements the steps in the foregoing method embodiments when the processor executes the computer program.
  • a computer-readable storage medium on which a computer program is stored, and the computer program is executed by a processor to implement the steps in the foregoing method embodiments.
  • Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory may include random access memory (RAM) or external cache memory.
  • RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Channel (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

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Abstract

一种提升目标探测精度的方法、计算机设备、存储介质、集成电路、无线电器件及电子设备，涉及雷达信号处理技术领域。该提升目标探测精度的方法包括：基于接收到的回波信号，获取速度模糊倍数和目标物峰值数据（301）；基于该速度模糊倍数对目标物峰值进行补偿（302）；并基于补偿后的目标物峰值数获取目标物数据，将其作为真实目标物数据（303）。该方法获得的真实目标物数据相较于传统方式获取的目标物数据更加精准，尤其是针对目标物速度过大的场景，更能有效的提升目标探测的精度。

Description

提升目标探测精度的方法、集成电路、无线电器件及电子设备
相关申请的交叉引用
本申请要求于2020年02月28日提交中国专利局、申请号为202010131027.X、发明名称为“雷达测速测距方法、装置、雷达系统及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及雷达信号处理技术领域，特别是涉及一种提升目标探测精度的方法、计算机设备、存储介质、集成电路、无线电器件及电子设备。
背景技术
目前，针对FMCW传感器，在利用二维快速傅里叶变换进行目标探测时，当目标物的速度过快时，很容易发生模糊问题(如速度模糊和/或距离模糊等)，导致目标探测精度较低。
发明内容
基于此，有必要针对上述存在的目标探测精度较低的问题，提供一种提升目标探测精度的方法、计算机设备、存储介质、集成电路、无线电器件及电子设备。
在一个可选的实施例中，一种提升目标检测精度的方法，可包括：
基于接收到的回波信号，获取速度模糊倍数和目标物峰值数据；
基于所述速度模糊倍数对所述目标物峰值数据进行补偿；以及
基于补偿后的目标物峰值数获取目标物数据。
在该实施例中，通过利用速度模糊倍数对目标物峰值进行补偿，并基于补偿后的目标物峰值数所获取的目标物数据作为真实目标物数据，相较于传统方式获取的目标物数据更加精准，尤其是针对目标物速度过大的场景，更能有效的提升目标探测的精度。
可选的，所述方法还可包括：
预设速度阈值；
获取目标物速度；以及
判断所述目标物的速度是否大于所述预设阈值；
其中，若所述目标物的速度大于所述预设阈值，则基于所述速度模糊倍数对所述目标物峰值数据进行补偿，并基于补偿后的目标物峰值数获取目标物数据。
在该实施例中，通过预先判断目标物的速度是否大于预设速度阈值，再确定是否进行后续的补偿操作，以根据不同的应用场景采用相异的目标探测方法，继而可使得目标探测 方式与应用场景需求相适应；即针对高速的应用场景，可利用速度模糊倍数进行补偿操作，进而有效降低目标物的高速度对于目标探测所产生的不利影响，提升目标探测的精度，而针对低速的应用场景，则可无需进行后续的补偿操作，直接采用传统的方式进行目标探测。
可选的，所述目标物数据可包括距离、速度、角度和形状等中的至少一种。
需要注意的是，若是获取目标物的角度、点云数据(如基于点云数据获取形状、姿态等)等时，则需要先对目标物的速度和/距离进行补偿操作。
可选的，所述基于接收到的回波信号，获取速度模糊倍数和目标物峰值数据，包括：
对所述回波信号进行模数转换(A/D)、采样(sample)、距离维傅里叶变换(1D FFT)、速度维度傅里叶变换(2D FFT)和恒虚警检测(CFAR)，以获取所述速度模糊倍数和所述目标物峰值数据。
需要说明的是，针对FMCW传感器，基于传统信号处理的流程，在CFAR与DOA(波达方向估计)之间进行本申请实施例中的补偿操作。
可选的，所述基于所述速度模糊倍数对所述目标物峰值数据进行补偿，包括：
基于速度维傅里叶变换输入数据的采样间隔获取补偿系数；
基于所述补偿系数和所述速度模糊倍数获取补偿量；以及
基于所述补偿量对所述目标物峰值数据进行补偿。
可选的，所述基于所述补偿系数和所述速度模糊倍数获取补偿量，包括：
基于所述补偿系数、所述速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔来获取所述补偿量。
可选的，所述基于速度维傅里叶变换输入数据的采样间隔获取补偿系数，包括：
基于扫频带宽、窗函数的大小、傅里叶变换的点数、扫频中心频点、采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述补偿系数。
可选的，当基于补偿后的目标物峰值数获取目标物的距离时，所述目标物峰值数据包括距离因子，所述补偿量包括距离补偿量，所述补偿系数包括距离补偿系数，所述窗函数的大小包括速度维窗函数的大小，所述傅里叶变换的点数包括距离维窗函数的点数；所述基于扫频带宽、窗函数的大小、傅里叶变换的点数、扫频中心频点、采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述补偿系数，包括：
基于所述扫频带宽、所述速度维窗函数的大小、所述距离维傅里叶变换的点数、所述扫频中心频点、所述采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述距离补偿系数；
其中，基于所述距离补偿系数和所述速度模糊倍数获取所述距离补偿量，并基于所述距离补偿量对所述目标物峰值数据的距离因子进行补偿，以用于获取所述目标物的距离。
可选的，当基于补偿后的目标物峰值数获取目标物的速度时，所述目标物峰值数据包括速度因子，所述补偿量包括速度补偿量，所述补偿系数包括速度补偿系数，所述窗函数的大小包括距离维窗函数的大小，所述傅里叶变换的点数包括速度维窗函数的点数；所述 基于扫频带宽、窗函数的大小、傅里叶变换的点数、扫频中心频点、采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述补偿系数，包括：
基于所述扫频带宽、所述距离维窗函数的大小、所述速度维傅里叶变换的点数、所述扫频中心频点、所述采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述速度补偿系数；
其中，基于所述速度补偿系数和所述速度模糊倍数获取所述速度补偿量，并基于所述速度补偿量对所述目标物峰值数据的速度因子进行补偿，以用于获取所述目标物的速度。
本申请实施例还提供了一种计算机设备，可包括存储器和处理器，所述存储器存储有计算机程序，所述处理器执行所述计算机程序时实现本申请实施例中任一项所述的方法的步骤。
本申请实施例还提供了一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现本申请实施例中任一项所述的方法的步骤。
本申请实施例还提供了一种集成电路，可包括：
信号收发通道，用于发射无线电信号，以及接收所述无线电信号被目标物回反射所形成波信号；
信号处理模块，用于基于如本申请实施例中任意一项所述的方法获取目标物数据。
可选的，所述信号处理模块包括：
信号处理单元，用于基于所述回波信号获取速度模糊倍数和目标物峰值数据；
补偿单元，用于基于所述速度模糊倍数对所述目标物峰值数据进行补偿；以及
数据处理单元，用于基于补偿后的目标物峰值数获取目标物数据。
可选的，所述无线电信号为毫米波信号。
可选的，所述集成电路为AiP(Antenna in Package，即封装天线)芯片或AoC(Antenna on Chip，即片上天线)芯片。
本申请实施例还提供了一种无线电器件，可包括：
承载体；
如本申请实施例中任意一项所述集成电路，设置在所处承载体上；以及
天线，设置在所述承载体上，或者与所述集成电路集成为一体器件形成AiP或AoC结构，用于发收无线电信号。
本申请实施例还提供了一种电子设备，包括：
设备本体；以及
设置于所述设备本体上的本申请实施例中所述的无线电器件；
其中，所述无线电器件用于目标检测和/或通信。
附图说明
图1为本申请实施例提供的一种雷达系统的示意图；
图2为本申请实施例提供的一种集成电路的示意图；
图3为本申请实施例提供的一种提升目标探测精度的方法的流程图；
图4为本申请实施例提供的一种chirp信号波形示意图；
图5为本申请实施例提供的一种CFAR结果示意图；
图6为本申请实施例提供的一种速度补偿值的计算方法的流程图；
图7为本申请实施例提供的一种距离补偿值的计算方法的流程图；
图8为本申请实施例提供的另一种获取补偿后的速度因子的方法的流程图；
图9为本申请实施例提供的另一种提升目标探测精度的方法的流程图；
图10为本申请实施例提供的一种提升目标探测精度的装置的模块图。
具体实施例方式
为使本申请的目的、技术方案和优点更加清楚，下面将结合附图对本申请实施方式作进一步地详细描述。
本实施例提供的提升目标探测精度的方法，可以适用于各种传感系统中。
下面就以FMCW雷达为例，对本申请的相关技术内容进行详细说明，但需要说明的是，本申请所记载的内容并不局限于雷达产品，也适用于其他一切能够目标探测传感器中。
目前，调频连续波雷达FMCW(英文：Frequency Modulation Continuous Wave，简称：FMCW)既可测距又可测速，并且在近距离测量上的优势日益明显，因此被广泛地用于车辆避障。
FMCW雷达测速测距的基本原理是：利用发射天线发射无线电信号(即发射信号)对检测区域进行目标探测，发射信号被目标物反射形成回波信号，然后接收天线接收上述的回波信号，信号处理模块对该回波信号进行混频得到中频信号，并继续模数转换、采样、距离维傅里叶变换(即1D FFT)、速度维傅里叶变换(即2D FFT)、恒虚警检测(即CFAR)、波动方向估计(即DOA)等操作，进而得到目标的距离、速度、角度等信息，并可根据所检测到的目标信息(即目标物数据)进行后续的点云成像、活体体征检测及监控等应用。
如图1所示，该FMCW雷达可包括信号产生器F，信号产生器用于合成电磁波信号，雷达系统的发射端包括发射天线Tx，接收端包括接收天线Rx，发射天线Tx将发射信号以电磁波的形式发射出去，电磁波在传播的过程中，遇到目标物后，会被目标物反射回来，该反射回来的电磁波可以称为回波信号，雷达系统的接收天线Rx可以接收该回波信号。雷达系统还包括混频器mixer，混频器mixer中可以采用发射信号对接收到的回波信号进行混频，得到混频信号。然后基于上述FMCW雷达测速测距的基本原理测量目标物的速度和距离等参数。
然而，上述测速测距方法，计算出的目标物的速度以及目标物到雷达的距离的精度较低。
为了解决上述技术问题，本申请实施例提供了一种提升目标探测精度的方法、计算机 设备、存储介质、集成电路、无线电器件及电子设备，下面，首先对本申请实施例提供的提升目标探测精度的方法所涉及到的实施环境进行简要说明。
本申请实施例提供的提升目标检测精度的方法可以适用于如图2所示的集成电路中，该集成电路可包括信号收发通道201和信号处理模块202等，信号收发通道201可用于发射无线电信号(如毫米波信号、太赫兹信号等)，以及接收无线电信号被目标物回反射所形成波信号，而信号处理模块202则可用对回波信号进行信号处理以实现本申请任一实施例所阐述的方法进而获取目标物数据。
可选的，上述的信号处理模块202可包括信号处理单元2021、补偿单元2022和数据处理单元2023等，信号处理单元2021可用于基于回波信号获取速度模糊倍数和目标物峰值数据等，补偿单元2022则可用于基于速度模糊倍数对目标物峰值数据进行补偿，而数据处理单元2023则可用于基于补偿后的目标物峰值数获取目标物数据。
可选的，上述的集成电路可为不包含天线结构的芯片结构，也可为集成有天线的结构(如AiP(英文：Antennas in Package，简称：AiP)芯片或AoC(英文：Antenna on Chip，简称：AoC)芯片等)，上述无线电信号可以为毫米波信号。
上述集成电路，可以采用统一的数字控制器通过数字控制接口与片上系统的数字功能模块连接，再通过配置模块和状态机实现对片上系统中数字功能模块运行状态的统一配置管理，提高了集成电路中片上系统的运行控制效率。
具体地，在该集成电路中，还可以包括其他数字电路、数字功能模块以及运行控制设备，各类数字电路为集成电路的基础构成，不同的数字电路可以实现集成电路的不同功能，数字功能模块用于检测各个数字电路工作是否正常，运行控制设备可以对数字功能模块进行统一的配置管理，运行控制设备中的数字控制器可以通过数字控制接口向数字功能模块发送进行功能检测的控制信号，配置模块中存储有配置信息与状态信息，配置信息可以由外部获取，状态机用于控制集成电路的工作流程，状态机可以读取配置模块中存储的配置信息，对控制数字控制器产生相应的控制信号输出给数字功能模块，以实现控制数字功能模块对各个数字电路进行检测。
在一种可选的实现方式中，本实施例提供的提升目标探测精度的方法，可以适用于无线电器件，该无线电器件包括：承载体；如上述实施例所述的集成电路，该集成电路设置在承载体上；天线，设置在承载体上，用于发收无线电信号，其中天线还可集成于上述集成电路的封装中形成AiP结构中，也可天线集成于芯片上形成片上天线AoC结构，承载体则可以为印刷电路板PCB等。
在一种可选的实现方式中，本申请还提供一种设备，包括：设备本体；以及设置于设备本体上的如上述实施例的无线电器件；其中，无线电器件用于目标检测和/或通信。
具体地，在本申请的一个实施例中，无线电器件可以设置在设备本体的外部，在本申请的另一个实施例中，无线电器件还可以设置在设备本体的内部，在本申请的其他实施例中，无线电器件还可以一部分设置在设备本体的内部，一部分设置在设备本体的外部。本 申请对此不作限定，具体视情况而定。需要说明的是，无线电器件可通过发射及接收信号实现诸如目标检测及通信等功能。
在一个可选的实施例中，上述设备本体可为智能交通运输设备(如汽车、自行车、摩托车、船舶、地铁、火车等)、安防设备(如摄像头)、智能穿戴设备(如手环、眼镜等)、智能家居设备(如电视、空调、智能灯等)、各种通信设备(如手机、平板电脑等)等，以及诸如道闸、智能交通指示灯、智能指示牌、交通摄像头及各种工业化机械手(或机器人)等，也可为用于检测生命特征参数的各种仪器以及搭载该仪器的各种设备。无线电器件则可为本申请任一实施例中所阐述的无线电器件，无线电器件的结构和工作原理在上述实施例中已经进行了详细说明，此处不在一一赘述。
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。
请参考图3，其示出了本申请实施例提供的一种提升目标探测精度的方法的流程图，该提升目标探测精度的方法可以应用于图1所示的雷达系统中，如图3所示，该提升目标探测精度的方法可以包括以下步骤：
步骤301、基于接收到的回波信号，获取速度模糊倍数和目标物峰值数据。
FMCW雷达的发射天线发出的发射信号的电磁波为高频调频连续波，其频率随时间规律变化。该高频连续波一般为锯齿形、三角形等，本申请以锯齿形为例进行说明，每个调频周期T内的电磁波称为chirp(译文：啁啾)，每个chirp的频率随时间线性增加。
FMCW雷达的接收天线接收的回波信号是目标物反射回来的电磁波。如图4所示，其示出了发射信号tx波形和回波信号rx波形。将发射信号tx与回波信号rx混频的过程可以是：对发射信号与回波信号进行混频处理，得到差频信号IF signal，该差频信号即混频信号，也可称为中频信号。
对混频信号进行数字采样，得到采样数据。可以将一个chirp上的采样数据存储为矩阵的行，例如有M个chirp，相应地，矩阵的行有M行，每个chirp采样点数为N，表示矩阵的列有N列，这样可以得到一个M×N的采样数据矩阵。
对于每个调频周期的chirp(即每一行)，可以分别做N点FFT，即距离维傅里叶变换，再对M个chirp进行跨chirp做纵向的多普勒FFT，即速度维傅里叶变换，距离FFT(逐行)和多普勒FFT(逐列)的联合操作可视作每帧对应采样数据的二维FFT，二维FFT可用于获取目标物的距离和速度等参数。因此二维FFT的峰值位置可对应雷达前方目标的距离和速度。继续进行恒虚警检测(即CFAR)其结果可以如图5所示，其中，虚线表示对应关系，CFAR的峰值位置对应的峰值数据包括速度因子P peak和距离因子K peak。
可选的，在进行上述的二维FFT及CFAR后，还可以获得以下数据：
扫频带宽B、距离维傅里叶变换的点数nfft1、速度维傅里叶变换的点数nfft2(也可认为是速度维FFT的size(LZ))、速度维FFT输入数据的采样间隔T、扫频中心频点fc、 采样率Fs、目标物的距离R、目标物的法向速度v、距离维窗函数的大小Win1size、速度维窗函数的大小Win2size、多普勒频移取余的余量frd、多普勒频移fD、Chirp序号n(也即脉冲(pulse)序号)、chirp内距离chirp起点的时间偏移ts、混频信号振幅A和速度模糊倍数q等参数信息；其中，速度模糊倍数q可用于表示真实的多普勒频移fD与脉冲重复频率F之间的折叠次数。
需要说明的是，在本申请实施例的公式中，j为虚数单位，即
Figure PCTCN2021078409-appb-000001
同时，T为针对非虚拟阵列的传感器速度维FFT输入数据的采样间隔，而TD为虚拟天线阵列的传感器速度维FFT输入数据的采样间隔(即根据是否为虚拟天线阵列，可将本申请实施例公式中的T和TD进行互换)；例如，针对发射天线每次发射一个chirp的虚拟天线阵列，TD＝TxAnt×Tr，Tr为单个chirp的周期，TxAnt为发射天线个数，而针对发射天线每次发射一个chirp的单发射天线，T＝Tr。
另外，在本申请实施例中，多普勒频移取余的余量frd需要满足以下条件：
Figure PCTCN2021078409-appb-000002
其中，f D＝f rd+q·F,q∈Z，F＝1/T，-F/2≤frd≤F/2，Z为自然数。
在FMCW雷达中，由于是通过利用回波信号相对于发射信号的真实的多普勒频移fD来确定目标物相对雷达的法向速度v，v＝0.5λ×fD，其中，λ是发射信号波长。当fD≤0.5F时，可以确定目标物的速度在雷达的测速范围内，例如雷达测速范围为-10m/s至+10m/s，目标物的运动速度为8m/s，那么雷达测得的目标物的速度不模糊。
而当fD＞0.5F时，也就是说，目标物的速度超出了雷达的测速范围，例如雷达测速范围为-10m/s至+10m/s，目标物的运动速度为11m/s，那么经过折叠效应，雷达会认为目标物的速度为-9m/s，并且，当目标物的速度为31m/s、51m/s时，经过折叠效应，雷达测速都会判断为-9m/s。雷达无法分辨真实的多普勒频移fD与脉冲重复频率F之间的折叠次数，即二者之间的频率间隔，因此出现了速度模糊。
步骤302、基于所述速度模糊倍数对所述目标物峰值数据进行补偿。
可选的，可先基于速度维傅里叶变换输入数据的采样间隔获取补偿系数，然后基于补偿系数和速度模糊倍数获取补偿量，并基于补偿量对所述目标物峰值数据进行补偿。
具体的，可基于补偿系数、速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔来获取补偿量。例如，可采用以下公式来获取补偿量：
Peak-comp＝comp*(q+frd*T)；其中，Peak-comp为补偿量，comp为补偿系数。
可选的，一般为对CFAR后获取的目标物峰值数据的速度因子K peak和/距离因子P peak进行补偿，相应的，补偿量Peak-comp可包括距离因子补偿量K peak-comp和速度因子补偿量P peak-comp，补偿系数comp则可包括距离补偿系数rng-comp和速度补偿系数vel-comp。即可采用距离因子补偿量K peak-comp对目标物峰值数据的距离因子P peak进行补偿，并采用速度因子补偿量P peak-comp对目标物峰值数据的速度因子K peak进行补偿。
可选的，距离因子补偿量的公式可为：
Figure PCTCN2021078409-appb-000003
而速度因 子补偿量的公式则可为：
Figure PCTCN2021078409-appb-000004
在一个可选的实施例中，可基于扫频带宽、窗函数的大小、傅里叶变换的点数、扫频中心频点、采样率和速度维傅里叶变换输入数据的采样间隔获取补偿系数。
可选的，当基于补偿后的目标物峰值数获取目标物的距离时，可基于扫频带宽、速度维窗函数的大小、距离维傅里叶变换的点数、扫频中心频点、采样率和速度维傅里叶变换输入数据的采样间隔获取该距离补偿系数。
例如，可采用以下的公式获取距离补偿系数：
Figure PCTCN2021078409-appb-000005
可选的，当基于补偿后的目标物峰值数获取目标物的速度时，可基于扫频带宽、距离维窗函数的大小、速度维傅里叶变换的点数、扫频中心频点、采样率和速度维傅里叶变换输入数据的采样间隔获取速度补偿系数。
例如，可采用以下的公式获取距离补偿系数：
Figure PCTCN2021078409-appb-000006
可选的，可用CFAR得到的速度因子P peak减去速度补偿值P peak_comp，得到补偿后的速度因子P，即P＝P peak-P peak_comp。相应的，也可基于差值获取补偿后的距离因子k，即K＝K peak-K peak_comp。
步骤303、基于补偿后的目标物峰值数获取目标物数据。
其中，上述的目标物数据可包括距离、速度、角度和形状等中的至少一种。
例如，可采用以下的公式获取目标物的距离R：
Figure PCTCN2021078409-appb-000007
相应的，可采用以下的公式获取目标物的速度v：
Figure PCTCN2021078409-appb-000008
本申请实施例提供的提升目标探测精度的方法，在二维快速傅里叶变换及恒虚警检测之后，且在波达方向估计之前，通过利用速度模糊倍数对CFAR得到的速度因子和/或距离因子进行了补偿，并根据补偿后的速度因子和补偿后的距离因子，来确定目标物的速度和目标物到雷达的距离，进而能够有效提高目标减少所获取目标物的速度和/或距离的精度。
在一种可选的实现方式中，在根据速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔等分别确定速度补偿值和距离补偿值之前，需要判断速度模糊倍数是否大于0。当速度模糊倍数大于0时，表示存在速度模糊。而当速度模糊倍数等 于0时，表示不存在速度模糊。
可选的，当速度模糊倍数等于0时，即不存在速度模糊，可以认为目标物处于低速运动状态，无需进行补偿。因此，确定速度补偿值和距离补偿值均为零。
可选的，当速度模糊倍数大于0时，即存在速度模糊，可以认为目标物处于高速运动状态，需要对速度进行校正补偿，因此，根据速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔等确定速度补偿值。
在另一个可选的实施方式中，也可通过预先设定速度阈值(也可认为是速度模糊阈值)，并基于当前所获取的目标物速度值(或速度模糊倍数)来判断是否需要进行上述的补偿操作。即，若是所获取的目标物速度值(或速度模糊倍数)大于预先设定速度阈值(或速度模糊阈值)，即可进行上述补偿操作；否则，则可不用进行补偿操作，如继续采用传统的信号处理流程来获取目标物数据。
本申请实施例中，根据速度模糊倍数确定是否需要对速度因子和/或距离因子进行补偿，当不需要进行补偿时，可以节省补偿步骤，从而提高雷达的运算效率。
在一种可选的实现方式中，如图6所示，当速度模糊倍数大于0时，根据速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔确定速度补偿值的过程可以包括以下步骤：
步骤601、获取速度补偿系数。
在一种可选的实现方式中，速度补偿系数可以是预先设置好的常数。
在另一种可选的实现方式中，获取速度补偿系数的过程可以是：获取速度维傅里叶变换的点数，根据速度维傅里叶变换的点数、扫频中心频点和采样率确定速度补偿系数。
可选的，本申请实施例中，还可采用如下公式来获取的速度补偿系数，即：
Figure PCTCN2021078409-appb-000009
本申请实施例中，速度维傅里叶变换的点数nfft2可以认为是进行距离FFT的行数。采样率F s可以是指对混频信号进行数字采样时的采样频率。
在另一种可选的实现方式中，在进行二维快速傅里叶变换之前，可以对采样数据在速度维和距离维分别进行乘窗操作。其中，可选的，速度维窗函数的大小可以设为win2size，距离维窗函数的大小可以设为win1size。
在乘窗操作下，速度补偿系数的表达式如下所示：
Figure PCTCN2021078409-appb-000010
即可以将距离维窗函数的大小win1size、速度维傅里叶变换输入数据的采样间隔T、速度维傅里叶变换的点数nfft2、扫频中心频点f c和采样率F s输入，计算出速度补偿系数。
步骤602、根据速度补偿系数、速度模糊倍数、多普勒频移取余的余量和速度维傅里 叶变换输入数据的采样间隔确定速度补偿值。
可选的，本申请实施例中，速度补偿值的表达式可以如下所示：
Figure PCTCN2021078409-appb-000011
即可以将速度补偿系数vel_comp、速度模糊倍数q、多普勒频移取余的余量f rd和速度维傅里叶变换输入数据的采样间隔T输入，以计算出速度补偿值。
可选的，本申请实施例中，速度补偿值的表达式可以根据混频信号的时域表达式确定。其中，发射信号和回波信号混频后的混频信号的时域表达式可以如下所示：
Figure PCTCN2021078409-appb-000012
即通过对混频信号进行离散化数字采样，可确定速度补偿值的表达式。
本申请实施例中，通过根据速度维傅里叶变换的点数、扫频中心频点和采样率确定速度补偿系数。将速度维傅里叶变换的点数、扫频中心频点和采样率引入速度补偿值的确定过程中，可以提高速度补偿值的精度，提高了补偿后的速度因子的精度，因此可以提高根据速度因子确定的目标物的速度的精度。
在一种可选的实现方式中，如图7所示，当速度模糊倍数大于0时，根据速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔确定距离补偿值的过程可以包括以下步骤：
步骤701、获取距离补偿系数。
在一种可选的实现方式中，距离补偿系数可以是预先设置好的常数。
在一种可选的实现方式中，获取距离补偿系数的过程可以是：获取距离维傅里叶变换的点数，根据距离维傅里叶变换的点数、扫频中心频点和采样率确定距离补偿系数。
可选的，本申请实施例中，距离补偿系数的表达式可以如下所示：
Figure PCTCN2021078409-appb-000013
即可以将速度维傅里叶变换输入数据的采样间隔T、距离维傅里叶变换的点数、扫频中心频点和采样率输入上式，计算出距离补偿系数。
在另一种可选的实现方式中，在进行二维快速傅里叶变换之前，可以对采样数据在速度维和距离维分别进行乘窗操作。其中，可选的，速度维窗函数的大小可以设为win2size，距离维窗函数的大小可以设为win1size。
在乘窗操作下，距离补偿系数的表达式可以如下所示：
Figure PCTCN2021078409-appb-000014
即可以将速度维窗函数的大小win2size、速度维傅里叶变换输入数据的采样间隔T、距离维傅里叶变换的点数nfft1、扫频中心频点f c和采样率F s输入上式中，计算出速度补 偿系数。
步骤702、根据距离补偿系数、速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔确定距离补偿值。
可选的，本申请实施例中，距离补偿值的表达式可以如下所示：
Figure PCTCN2021078409-appb-000015
即可以将距离补偿系数rng_comp、速度模糊倍数q、多普勒频移取余的余量f rd和速度维傅里叶变换输入数据的采样间隔T输入上式，以计算出距离补偿值。
本申请实施例中，通过根据距离维傅里叶变换的点数、扫频中心频点和采样率确定距离补偿系数，将距离维傅里叶变换的点数、扫频中心频点和采样率引入距离补偿值的确定过程中，可以提高距离补偿值的精度，提高了补偿后的距离因子的精度，因此可以提高根据距离因子确定的目标物的距离的精度。
在一种可选的实现方式中，本申请实施例中，二维快速傅里叶变换包括速度维傅里叶变换，如图8所示，根据速度补偿值对速度因子进行补偿，得到补偿后的速度因子的过程还可以包括以下步骤：
步骤801、当速度因子大于或等于速度维傅里叶变换的点数的预设倍数时，将速度因子与速度维傅里叶变换的点数的差值作为第一速度因子。
可选的，该预设倍数大于0小于1。
可选的，速度维傅里叶变换的点数的预设倍数可以是0.5倍。
本申请实施例中，第一速度因子可以用P peak'表示，当P peak≥nfft2，P peak'＝P peak-nfft2。
步骤802、当速度因子小于速度维傅里叶变换的点数的预设倍数时，将速度因子作为第一速度因子。
当P peak＜nfft2，P peak'＝P peak。
步骤803、根据速度补偿值对第一速度因子进行补偿，得到补偿后的速度因子。
可选的，根据速度补偿值对第一速度因子进行补偿的过程可以是：用第一速度因子减去速度补偿值得到补偿后的速度因子P＝P peak'-P peak_comp。
本申请实施例中，根据不同的判断条件确定不同的第一速度因子，以使得补偿后的速度因子可以更准确地反映目标物实际的运动速度信息，提高了补偿后的速度因子的精度，从而提高了确定的目标物的速度的精度。
在一种可选的实现方式中，当速度模糊倍数等于0时，速度补偿值和距离补偿值均为零，在这种情况下，根据补偿后的速度因子和补偿后的距离因子确定目标物的速度和距离的过程可以如图9所示，包括以下步骤：
步骤901、根据扫频中心频点确定速度粒度，根据速度粒度和速度因子确定目标物的速度。
其中，根据扫频中心频点确定速度粒度的过程包括：获取扫频中心频点为f c和速度维 傅里叶变换输入数据的采样间隔T。将扫频中心频点为f c和速度维傅里叶变换输入数据的采样间隔T输入至速度粒度的表达式中，可以计算出速度粒度。其中速度粒度的表达式可以是：
Figure PCTCN2021078409-appb-000016
其中，f c为扫频中心频点，T为速度维傅里叶变换输入数据的采样间隔，n为chirp序号。
可选的，可根据速度粒度和速度因子确定目标物的速度，即V＝Δv·P peak。
步骤902、根据回波信号对应的扫频带宽确定距离粒度，根据距离粒度和距离因子确定目标物到雷达的距离。
根据回波信号对应的扫频带宽B确定距离粒度，其中，距离粒度的表达式可以表示为：
Figure PCTCN2021078409-appb-000017
根据距离粒度和距离因子确定目标物到雷达的距离，即R＝K peak·ΔR。
本申请实施例中，当速度模糊倍数等于0时，基于速度粒度和距离粒度通过简单的运算即可确定目标物的速度和目标物到雷达的距离，简化了运算过程，提高了雷达的运算反应速度。
请参考图10，其示出了本申请实施例提供的一种提升目标探测精度的装置的框图，该提升目标探测精度的装置可以配置在图1所示的实施环境中。如图10所示，该提升目标探测精度的装置可以包括确定模块1001、补偿值确定模块1002、补偿模块1003和速度和距离确定模块1004，其中：
确定模块1001，用于基于回波信号进行二维快速傅里叶变换和恒虚警检测，以得到目标物的峰值数据、速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔等，峰值数据可包括速度因子和距离因子；
补偿值确定模块1002，用于根据速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔分别确定速度补偿值和/或距离补偿值；
补偿模块1003，用于根据速度补偿值对速度因子进行补偿得到补偿后的速度因子，根据距离补偿值对距离因子进行补偿，得到补偿后的距离因子；
速度和距离确定模块1004，用于根据补偿后的速度因子和补偿后的距离因子确定目标物的速度和距离。
在本申请的一个实施例中，补偿值确定模块1002还用于当速度模糊倍数大于0时，根据速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔确定速度补偿值；根据速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔确定距离补偿值。
在本申请的一个实施例中，补偿值确定模块1002还用于获取速度补偿系数；根据速度补偿系数、速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样 间隔确定速度补偿值。
在本申请的一个实施例中，补偿值确定模块1002还用于根据速度维傅里叶变换的点数、扫频中心频点和采样率确定速度补偿系数。
在本申请的一个实施例中，补偿值确定模块1002还用于获取距离补偿系数；根据距离补偿系数、速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔确定距离补偿值。
在本申请的一个实施例中，补偿值确定模块1002还用于根据距离维傅里叶变换的点数、扫频中心频点和采样率确定距离补偿系数。
在本申请的一个实施例中，补偿值确定模块1002还用于当速度模糊倍数等于0时，确定速度补偿值和距离补偿值均为零；
相应的，速度和距离确定模块1004还用于根据扫频中心频点确定速度粒度，根据速度粒度和速度因子确定目标物的速度；根据回波信号对应的扫频带宽确定距离粒度，根据距离粒度和距离因子确定目标物到雷达的距离。
在本申请的一个实施例中，补偿模块1003还用于当速度因子大于或等于速度维傅里叶变换的点数的预设倍数时，将速度因子与速度维傅里叶变换的点数的差值作为第一速度因子；当速度因子小于速度维傅里叶变换的点数的预设倍数时，将速度因子作为第一速度因子；根据速度补偿值对第一速度因子进行补偿，得到补偿后的速度因子。
在本申请的一个实施例中，补偿模块1003还用于将第一速度因子减去速度补偿值得到补偿后的速度因子。
在本申请的一个实施例中，补偿模块1003还用于将距离因子减去距离补偿值得到补偿后的距离因子。
关于提升目标探测精度的装置的具体限定可以参见上文中对于提升目标探测精度的方法的限定，在此不再赘述。上述提升目标探测精度的装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于雷达系统中的处理器中，也可以以软件形式存储于雷达系统中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在一个实施例中，还提供了一种计算机设备，包括存储器和处理器，存储器中存储有计算机程序，该处理器执行计算机程序时实现上述各方法实施例中的步骤。
在一个实施例中，提供了一种计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现上述各方法实施例中的步骤。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程 ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对申请专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (17)

  1. 一种提升目标检测精度的方法，其特征在于，所述方法包括：
    基于接收到的回波信号，获取速度模糊倍数和目标物峰值数据；
    基于所述速度模糊倍数对所述目标物峰值数据进行补偿；以及
    基于补偿后的目标物峰值数获取目标物数据。
  2. 根据权利要求1所述的方法，其特征在于，还包括：
    预设速度阈值；
    获取目标物速度；以及
    判断所述目标物的速度是否大于所述预设阈值；
    其中，若所述目标物的速度大于所述预设阈值，则基于所述速度模糊倍数对所述目标物峰值数据进行补偿，并基于补偿后的目标物峰值数获取目标物数据。
  3. 根据权利要求1所述的方法，其特征在于，所述目标物数据包括距离、速度、角度和形状中的至少一种。
  4. 根据权利要求1-3中任意一项所述的方法，其特征在于，所述基于接收到的回波信号，获取速度模糊倍数和目标物峰值数据，包括：
    对所述回波信号进行模数转换、采样、距离维傅里叶变换、速度维度傅里叶变换和恒虚警检测，以获取所述速度模糊倍数和所述目标物峰值数据。
  5. 根据权利要求1-4中任意一项所述的方法，其特征在于，所述基于所述速度模糊倍数对所述目标物峰值数据进行补偿，包括：
    基于速度维傅里叶变换输入数据的采样间隔获取补偿系数；
    基于所述补偿系数和所述速度模糊倍数获取补偿量；以及
    基于所述补偿量对所述目标物峰值数据进行补偿。
  6. 根据权利要求5所述的方法，其特征在于，所述基于所述补偿系数和所述速度模糊倍数获取补偿量，包括：
    基于所述补偿系数、所述速度模糊倍数、多普勒频移取余的余量和速度维傅里叶变换输入数据的采样间隔来获取所述补偿量。
  7. 根据权利要求1-4中任意一项所述的方法，其特征在于，所述基于速度维傅里叶变换输入数据的采样间隔获取补偿系数，包括：
    基于扫频带宽、窗函数的大小、傅里叶变换的点数、扫频中心频点、采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述补偿系数。
  8. 根据权利要求7所述的方法，其特征在于，当基于补偿后的目标物峰值数获取目标物的距离时，所述目标物峰值数据包括距离因子，所述补偿量包括距离补偿量，所述补偿系数包括距离补偿系数，所述窗函数的大小包括速度维窗函数的大小，所述傅里叶变换的点数包括距离维窗函数的点数；所述基于扫频带宽、窗函数的大小、傅里叶变换的点数、扫频中心频点、采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述补偿系数， 包括：
    基于所述扫频带宽、所述速度维窗函数的大小、所述距离维傅里叶变换的点数、所述扫频中心频点、所述采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述距离补偿系数；
    其中，基于所述距离补偿系数和所述速度模糊倍数获取所述距离补偿量，并基于所述距离补偿量对所述目标物峰值数据的距离因子进行补偿，以用于获取所述目标物的距离。
  9. 根据权利要求7所述的方法，其特征在于，当基于补偿后的目标物峰值数获取目标物的速度时，所述目标物峰值数据包括速度因子，所述补偿量包括速度补偿量，所述补偿系数包括速度补偿系数，所述窗函数的大小包括距离维窗函数的大小，所述傅里叶变换的点数包括速度维窗函数的点数；所述基于扫频带宽、窗函数的大小、傅里叶变换的点数、扫频中心频点、采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述补偿系数，包括：
    基于所述扫频带宽、所述距离维窗函数的大小、所述速度维傅里叶变换的点数、所述扫频中心频点、所述采样率和所述速度维傅里叶变换输入数据的采样间隔获取所述速度补偿系数；
    其中，基于所述速度补偿系数和所述速度模糊倍数获取所述速度补偿量，并基于所述速度补偿量对所述目标物峰值数据的速度因子进行补偿，以用于获取所述目标物的速度。
  10. 一种计算机设备，包括存储器和处理器，所述存储器存储有计算机程序，其特征在于，所述处理器执行所述计算机程序时实现权利要求1至9中任一项所述的方法的步骤。
  11. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现权利要求1至9中任一项所述的方法的步骤。
  12. 一种集成电路，其特征在于，包括：
    信号收发通道，用于发射无线电信号，以及接收所述无线电信号被目标物回反射所形成波信号；
    信号处理模块，用于基于如权利要求1-9中任意一项所述的方法获取目标物数据。
  13. 根据权利要求12所述的集成电路，其特征在于，所述信号处理模块包括：
    信号处理单元，用于基于所述回波信号获取速度模糊倍数和目标物峰值数据；
    补偿单元，用于基于所述速度模糊倍数对所述目标物峰值数据进行补偿；以及
    数据处理单元，用于基于补偿后的目标物峰值数获取目标物数据。
  14. 根据权利要求13所述的集成电路，其特征在于，所述无线电信号为毫米波信号。
  15. 根据权利要求12-14中任意一项所述的集成电路，其特征在于，所述集成电路为AiP芯片或AoC芯片。
  16. 一种无线电器件，其特征在于，包括：
    承载体；
    如权利要求12-14中任意一项所述集成电路，设置在所处承载体上；以及
    天线，设置在所述承载体上，或者与所述集成电路集成为一体器件形成AiP或AoC结构，用于发收无线电信号。
  17. 一种电子设备，其特征在于，包括：
    设备本体；以及
    设置于所述设备本体上的如权利要求16所述的无线电器件；
    其中，所述无线电器件用于目标检测和/或通信。
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