WO2022061598A1 - 一种信号噪声滤除方法、装置、存储介质及激光雷达 - Google Patents

一种信号噪声滤除方法、装置、存储介质及激光雷达 Download PDF

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WO2022061598A1
WO2022061598A1 PCT/CN2020/117182 CN2020117182W WO2022061598A1 WO 2022061598 A1 WO2022061598 A1 WO 2022061598A1 CN 2020117182 W CN2020117182 W CN 2020117182W WO 2022061598 A1 WO2022061598 A1 WO 2022061598A1
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signal
frequency signal
beat frequency
initial
autocorrelation
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PCT/CN2020/117182
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English (en)
French (fr)
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朱琳
任亚林
汪敬
牛犇
篠原磊磊
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深圳市速腾聚创科技有限公司
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Priority to CN202080004327.XA priority Critical patent/CN114531900A/zh
Priority to PCT/CN2020/117182 priority patent/WO2022061598A1/zh
Publication of WO2022061598A1 publication Critical patent/WO2022061598A1/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
    • G01S7/41—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

Definitions

  • the present application relates to the field of computer technology, and in particular, to a signal noise filtering method, device, storage medium, and lidar.
  • Frequency Modulated Continuous Wave LiDAR belongs to a continuous wave LiDAR based on coherent detection. It transmits a continuous wave whose frequency changes linearly during the frequency sweep period as the transmit signal, and a part of the transmit signal is used as the local oscillator signal. The remaining part is emitted outward for detection, and the echo signal returned after being reflected by the object forms a difference frequency signal with the local oscillator signal. Since the signal is easily affected by the inherent noise of the lidar system and the environment during the actual detection process, the signal-to-noise ratio is low, and the effective difference frequency signal cannot be extracted well.
  • Embodiments of the present application provide a signal noise filtering method, device, storage medium, and laser radar, which can improve the signal-to-noise ratio of the beat frequency signal and improve the success rate of effective beat frequency frequency extraction.
  • an embodiment of the present application provides a signal noise filtering method, including:
  • the initial beat frequency signal is a beat frequency signal containing a noise signal
  • the useful signal is determined as a time-domain difference frequency signal after denoising.
  • performing at least one autocorrelation process on the initial beat frequency signal to obtain a useful signal of the initial beat frequency signal includes:
  • performing at least one autocorrelation process on the initial beat frequency signal to obtain a useful signal of the initial beat frequency signal includes:
  • the second autocorrelation function is determined as the initial beat frequency signal, and the execution of the initial beat frequency signal is performed.
  • performing at least one autocorrelation process on the initial beat frequency signal to obtain a useful signal of the initial beat frequency signal includes:
  • the third autocorrelation function When the second signal-to-noise ratio indicated by the third autocorrelation function is less than or equal to the signal-to-noise threshold, and the number of processing times is less than the number of times threshold, determining the third autocorrelation function as the initial beat frequency signal, and Transfer to the steps of performing autocorrelation processing on the initial beat frequency signal, obtaining a third autocorrelation function of the initial beat frequency signal, and updating the number of times of the autocorrelation processing;
  • the third autocorrelation function is determined as the useful signal corresponding to the initial beat frequency signal ;
  • the third autocorrelation function is determined as the corresponding signal of the initial beat frequency signal useful signal.
  • determining the useful signal as the denoised time-domain difference frequency signal includes:
  • the useful signal is determined as a time-domain difference frequency signal after denoising.
  • Fourier transform processing is performed on the time-domain beat-frequency signal to obtain a frequency-domain beat-frequency signal, and a beat-frequency frequency value corresponding to the maximum amplitude is obtained from the frequency-domain beat-frequency signal.
  • an embodiment of the present application provides a signal noise filtering device, including:
  • an initial signal acquisition unit configured to acquire an initial beat frequency signal generated by the lidar, where the initial beat frequency signal is a beat frequency signal containing a noise signal;
  • a signal processing unit configured to perform autocorrelation processing on the initial beat frequency signal at least once to obtain a useful signal of the initial beat frequency signal
  • a denoising signal determining unit configured to determine the useful signal as a denoised time-domain difference frequency signal.
  • the signal processing unit includes:
  • a first signal processing subunit configured to perform autocorrelation processing on the initial beat frequency signal to obtain a first autocorrelation function of the initial beat frequency signal
  • a function processing subunit configured to perform autocorrelation processing on the first autocorrelation function to obtain a useful signal corresponding to the initial beat frequency signal.
  • the signal processing unit includes:
  • the signal processing unit includes:
  • a second signal processing subunit configured to perform autocorrelation processing on the initial beat frequency signal to obtain a second autocorrelation function of the initial beat frequency signal
  • a first notification subunit configured to determine the second autocorrelation function as the initial beat frequency signal when the first signal-to-noise ratio indicated by the second autocorrelation function is less than or equal to a signal-to-noise threshold, and notify the first Two signal processing subunits perform autocorrelation processing on the initial beat frequency signal to obtain a second autocorrelation function of the initial beat frequency signal, until the first signal-to-noise ratio is greater than the signal-to-noise threshold, and the The second autocorrelation function is determined as the useful signal corresponding to the initial beat frequency signal.
  • the signal processing unit includes:
  • a third signal processing subunit configured to perform autocorrelation processing on the initial beat frequency signal, obtain a third autocorrelation function of the initial beat frequency signal, and update the processing times of the autocorrelation processing;
  • a second notification subunit configured to determine the third autocorrelation function as the signal-to-noise ratio indicated by the third autocorrelation function is less than or equal to the signal-to-noise threshold and the number of processing times is less than the number of times threshold
  • notify the third signal processing subunit to perform autocorrelation processing on the initial beat frequency signal obtain a third autocorrelation function of the initial beat frequency signal, and update the number of times of the autocorrelation processing ;
  • a signal determination subunit configured to determine the third autocorrelation function as the initial value when the second signal-to-noise ratio indicated by the third autocorrelation function is greater than a signal-to-noise threshold and the number of processing times is less than the number of times threshold
  • the useful signal corresponding to the difference frequency signal
  • the signal determination subunit is further configured to, when the second signal-to-noise ratio indicated by the third autocorrelation function is less than or equal to a signal-to-noise threshold, and the number of times of processing is equal to the number of times threshold, the third autocorrelation function It is determined as the useful signal corresponding to the initial beat frequency signal.
  • the denoising signal determining unit is specifically configured to determine the useful signal as a denoised time-domain difference frequency signal when the target signal-to-noise ratio indicated by the useful signal is greater than a signal-to-noise threshold.
  • a beat frequency acquisition unit configured to perform Fourier transform processing on the time domain beat frequency signal to obtain a frequency domain beat frequency signal, and obtain a beat frequency value corresponding to the maximum amplitude in the frequency domain beat frequency signal.
  • An aspect of an embodiment of the present application provides a computer storage medium, where the computer storage medium stores a computer program, the computer program includes program instructions, and the program instructions, when executed by a processor, execute the above method steps.
  • An aspect of the embodiments of the present application provides a lidar, including a processor, a memory, and an input and output interface;
  • the processor is respectively connected to the memory and the input and output interface, wherein the input and output interface is used for page interaction, the memory is used to store program codes, and the processor is used to call the program codes , to perform the above method steps.
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, at least one autocorrelation process can be performed on the initial beat frequency signal to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the signal correlation degree, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of beat frequency extraction is acquiring the initial beat frequency signal containing the noise signal generated by the lidar.
  • 1 is a system architecture diagram of signal noise filtering provided by an embodiment of the present application.
  • FIG. 2 is a schematic flowchart of a signal noise filtering method provided by an embodiment of the present application
  • FIG. 3 is a schematic flowchart of a signal noise filtering method provided by an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of a signal noise filtering method provided by an embodiment of the present application.
  • FIG. 5 is a schematic flowchart of a signal noise filtering method provided by an embodiment of the present application.
  • FIG. 6 is a schematic diagram of an example of a spectrum after Fourier transform is performed on a signal provided by an embodiment of the present application
  • FIG. 7 is an exemplary schematic diagram of the success rate of extracting useful signals under different signal-to-noise ratios of signals provided by an embodiment of the present application.
  • FIG. 8 is an exemplary schematic diagram of the number of successful times of extracting useful signals under different detection distances and different signal-to-noise ratios provided by an embodiment of the present application;
  • FIG. 9 is a schematic structural diagram of a signal noise filtering device provided by an embodiment of the present application.
  • FIG. 10 is a schematic structural diagram of a signal noise filtering device provided by an embodiment of the present application.
  • FIG. 11 is a schematic structural diagram of a signal processing unit provided by an embodiment of the present application.
  • FIG. 12 is a schematic structural diagram of a signal processing unit provided by an embodiment of the present application.
  • FIG. 13 is a schematic structural diagram of a signal processing unit provided by an embodiment of the present application.
  • FIG. 14 is a schematic structural diagram of a lidar provided by an embodiment of the present application.
  • the embodiment of the present application can be applied to the detection scenarios of lidar, for example: detection scenarios such as environmental monitoring, aerospace, communication, automatic driving navigation, positioning, etc., the emission signal of lidar changes periodically according to the law of triangular waves, It transmits the signal to the detection target, receives the echo signal returned by the detection target, and obtains the initial beat frequency signal formed by the transmitted signal and the echo signal. It includes analog-to-digital conversion processing, signal filtering processing, signal data extraction, signal data calculation, etc., and then manages operations such as storage and display of the signal spectrum and data generated by the signal processor through the background management device.
  • detection scenarios such as environmental monitoring, aerospace, communication, automatic driving navigation, positioning, etc.
  • the emission signal of lidar changes periodically according to the law of triangular waves, It transmits the signal to the detection target, receives the echo signal returned by the detection target, and obtains the initial beat frequency signal formed by the transmitted signal and the echo signal. It includes analog-to-digital conversion processing, signal filtering processing, signal data extraction, signal data calculation
  • the embodiment of the present application Signal specifically proposes a signal noise filtering device
  • the signal noise filtering device can be set in the signal processor, or can be used as an independent device to realize the noise filtering processing of the initial beat frequency signal
  • the signal noise The filtering device can obtain the initial beat frequency signal generated by the lidar, the initial beat frequency signal is a beat frequency signal containing a noise signal, and the signal noise filtering device performs at least one autocorrelation process on the initial beat frequency signal, A useful signal of the initial beat frequency signal is obtained, and the signal noise filtering device determines the useful signal as a denoised time domain beat frequency signal.
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, at least one autocorrelation process can be performed on the initial beat frequency signal to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the signal correlation degree, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of beat frequency extraction is acquiring the initial beat frequency signal containing the noise signal generated by the lidar.
  • FIG. 2 provides a schematic flowchart of a signal noise filtering method according to an embodiment of the present application.
  • the method in this embodiment of the present application may include the following steps S101 to S103.
  • the emission signal of the lidar changes periodically according to the law of the triangular wave, transmits the signal to the detection target, and receives the echo signal returned by the detection target. Because the emission signal and the echo signal are easily affected by the inherent characteristics of the lidar system and the environment, etc. Therefore, an initial beat frequency signal with a noise signal is presented in the frequency spectrum.
  • the signal noise filtering device obtains the initial beat frequency signal generated by the lidar, and the initial beat frequency signal is a signal containing noise. difference frequency signal.
  • the signal noise filtering device may perform autocorrelation processing on the initial beat frequency signal at least once to obtain a useful signal of the initial beat frequency signal. It can be understood that the autocorrelation operation can improve the signal Therefore, in an optional implementation manner of this embodiment of the present application, the signal noise filtering device can further improve the signal-to-noise ratio of the initial beat frequency signal by two methods of autocorrelation processing and at least one autocorrelation processing convergence.
  • the second autocorrelation processing is to perform two autocorrelation operations on the initial beat frequency signal; at least one autocorrelation processing convergence may be performed on the initial beat frequency signal for one or more repetitions of autocorrelation Operation processing, until the signal-to-noise ratio indicated by the obtained auto-correlation function meets the signal-to-noise threshold, the auto-correlation function obtained by the last auto-correlation operation processing is determined as a useful signal; at least one auto-correlation processing convergence can also be set with an auto-correlation function.
  • the threshold for the number of correlation processing, in the process of performing one or more repeated autocorrelation operations on the initial beat frequency signal if the signal-to-noise ratio indicated by the autocorrelation function is not always obtained to meet the signal-to-noise threshold, but the autocorrelation processing If the processing times meet the times threshold, the autocorrelation function obtained by the last autocorrelation operation is determined as a useful signal. Both methods can improve the signal-to-noise ratio of the initial beat frequency signal, and effectively extract the useful signal.
  • the signal noise filtering device may determine the useful signal as a denoised time-domain difference frequency signal. It can be understood that, in order to further ensure that the useful signal can be extracted, the signal noise filtering device It can be detected whether the target signal-to-noise ratio indicated by the useful signal is greater than the signal-to-noise threshold, and the signal-to-noise threshold can be set according to the actual situation. When the target signal-to-noise ratio indicated by the useful signal is greater than the signal-to-noise threshold, the signal The noise filtering device can determine the useful signal as the denoised time-domain difference frequency signal.
  • the detection process of the target SNR can be determined according to the actual situation, for example: for the useful signal containing high intensity
  • the initial beat frequency signal of the signal can be processed by only one autocorrelation, so that the signal-to-noise ratio can be improved more effectively; for the initial beat frequency signal containing the useful signal with general strength, after the second autocorrelation processing, it can be The signal-to-noise ratio can be effectively improved, and the target signal-to-noise ratio can not be detected at this time; and for the initial beat frequency signal with a weak useful signal, whether the second autocorrelation processing or at least one autocorrelation processing is used to converge.
  • the target SNR it is necessary to detect the target SNR to ensure that the target SNR meets certain requirements (for example, greater than the signal-to-noise threshold), so as to facilitate the subsequent extraction of the difference frequency of the useful signal;
  • certain requirements for example, greater than the signal-to-noise threshold
  • the target SNR it can also detect the processing times of the autocorrelation processing, so as to limit the processing times to a certain amount when the target SNR still cannot meet certain requirements. range (for example, equal to the threshold of times) to ensure the processing efficiency of the difference frequency frequency extraction of the useful signal.
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, at least one autocorrelation process can be performed on the initial beat frequency signal to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the signal correlation degree, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of beat frequency extraction is acquiring the initial beat frequency signal containing the noise signal generated by the lidar.
  • FIG. 3 provides a schematic flowchart of a signal noise filtering method according to an embodiment of the present application. As shown in FIG. 3 , the method in this embodiment of the present application may include the following steps S201 to S205.
  • the emission signal of the lidar changes periodically according to the law of the triangular wave, transmits the signal to the detection target, and receives the echo signal returned by the detection target. Because the emission signal and the echo signal are easily affected by the inherent characteristics of the lidar system and the environment, etc. Therefore, an initial beat frequency signal with a noise signal is presented in the frequency spectrum.
  • the signal noise filtering device obtains the initial beat frequency signal generated by the lidar, and the initial beat frequency signal is a signal containing noise. difference frequency signal.
  • the signal noise filtering device may perform autocorrelation operation processing on the initial beat frequency signal to obtain a first autocorrelation function of the initial beat frequency signal, and the autocorrelation operation It can be selected as unbiased autocorrelation operation, which specifically reflects the correlation degree of the signal at different times t 1 and t 2 , which can be expressed as:
  • R x E[x(t 1 )x(t 2 )]
  • x(t 1 ) and x(t 2 ) represent the values at times t 1 and t 2 in the initial beat frequency signal x(t), respectively, and the first autocorrelation function R x , t 1 and t 2 can be randomly selected according to actual needs, or t 1 and t 2 can be selected according to the signal period, that is, the distance between t 1 and t 2 is one signal period.
  • the signal noise filtering device may perform autocorrelation processing on the first autocorrelation function again to obtain a useful signal corresponding to the initial difference frequency signal, and the signal noise filtering device takes R x as x (t), by selecting the same values at times t 1 and t 2 , and performing autocorrelation processing, a useful signal corresponding to the initial beat frequency signal is obtained.
  • the signal noise filtering device may determine the useful signal as a denoised time-domain difference frequency signal. It can be understood that, in order to further ensure that the useful signal can be extracted, the signal noise filtering device It can be detected whether the target signal-to-noise ratio indicated by the useful signal is greater than the signal-to-noise threshold, and the signal-to-noise threshold can be set according to the actual situation. When the target signal-to-noise ratio indicated by the useful signal is greater than the signal-to-noise threshold, the signal The noise filtering device can determine the useful signal as the denoised time-domain difference frequency signal. Of course, the detection process of the target SNR can be determined according to the actual situation whether it needs to be performed.
  • the initial beat frequency signal of the signal can effectively improve the signal-to-noise ratio after the secondary autocorrelation processing.
  • the detection of the target signal-to-noise ratio can not be performed, and for the initial beat frequency signal with a weak useful signal,
  • the use of secondary autocorrelation processing still requires the detection of the target signal-to-noise ratio to ensure that the target signal-to-noise ratio meets certain requirements (eg, greater than the signal-to-noise threshold), so as to facilitate subsequent extraction of the difference frequency of the useful signal.
  • both the time-domain beat frequency signal and the initial beat-frequency signal can be expressed as beat-frequency signals in the time domain, and the initial beat-frequency signal is the beat-frequency signal in the time domain before denoising, and the time-domain beat signal The beat frequency signal is the beat frequency signal in the time domain after denoising.
  • the signal noise filtering device may perform Fourier transform processing on the time-domain beat-frequency signal to obtain a frequency-domain beat-frequency signal, and obtain a beat-frequency corresponding to the maximum amplitude from the frequency-domain beat-frequency signal frequency value, the Fourier transform processing can be selected as fast Fourier transform processing, the frequency domain beat frequency signal can be specifically represented as a beat frequency signal in the frequency domain after denoising, the signal noise filtering device
  • the position of the maximum amplitude value can be obtained in the spectrum diagram formed by the frequency-domain beat frequency signal, and the corresponding frequency value of the position can be determined as the beat frequency value of the useful signal.
  • the useful signal is specifically expressed as the transmitted signal returned by the detection target. Real and effective difference frequency signal.
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, the initial beat frequency signal can be subjected to secondary autocorrelation processing to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the degree of signal correlation, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of beat frequency extraction by detecting the target signal-to-noise ratio, it is ensured that the target signal-to-noise ratio meets certain requirements, so as to facilitate the subsequent extraction of the beat frequency of the useful signal.
  • FIG. 4 provides a schematic flowchart of a signal noise filtering method according to an embodiment of the present application. As shown in FIG. 4 , the method in this embodiment of the present application may include the following steps S301 to S306.
  • the emission signal of the lidar changes periodically according to the law of the triangular wave, transmits the signal to the detection target, and receives the echo signal returned by the detection target. Because the emission signal and the echo signal are easily affected by the inherent characteristics of the lidar system and the environment, etc. Therefore, an initial beat frequency signal with a noise signal is presented in the frequency spectrum.
  • the signal noise filtering device obtains the initial beat frequency signal generated by the lidar, and the initial beat frequency signal is a signal containing noise. difference frequency signal.
  • the signal noise filtering device performs autocorrelation processing on the initial beat frequency signal to obtain a second autocorrelation function of the initial beat frequency signal
  • the autocorrelation operation can be optionally an unbiased autocorrelation operation, It specifically reflects the correlation degree of the signal at different times t 1 and t 2 , which can be expressed as:
  • R x E[x(t 1 )x(t 2 )]
  • x(t 1 ) and x(t 2 ) represent the values at time t 1 and t 2 in the initial difference frequency signal x(t), respectively, and the second autocorrelation function R x , t 1 is obtained through autocorrelation operation processing t 1 and t 2 can be randomly selected according to actual needs, or t 1 and t 2 can be selected according to the signal period, that is, the distance between t 1 and t 2 is one signal period.
  • the signal-to-noise filtering device may determine the second autocorrelation function as the initial beat frequency signal , and go to step S302, when the first signal-to-noise ratio indicated by the second autocorrelation function is less than or equal to the signal-to-noise threshold, the signal-to-noise filtering device may take R x as x(t), and then pass Select the same values at t 1 and t 2 , perform autocorrelation processing, and obtain the second autocorrelation function again, and repeat this process until the convergence condition of the first signal-to-noise ratio greater than the signal-to-noise threshold is detected. , go to step S304.
  • the signal-to-noise filtering device may determine the second autocorrelation function as the useful signal corresponding to the initial beat frequency signal, that is, the The signal noise filtering device may determine the last obtained Rx as the useful signal corresponding to the initial beat frequency signal.
  • the signal noise filtering device may determine the useful signal as a denoised time-domain difference frequency signal. It can be understood that, in order to further ensure that the useful signal can be extracted, the signal noise filtering device It can be detected whether the target signal-to-noise ratio indicated by the useful signal is greater than the signal-to-noise threshold, and the signal-to-noise threshold can be set according to the actual situation. When the target signal-to-noise ratio indicated by the useful signal is greater than the signal-to-noise threshold, the signal The noise filtering device can determine the useful signal as the denoised time-domain difference frequency signal. Of course, the detection process of the target SNR can be determined according to the actual situation whether it needs to be performed.
  • the initial beat frequency signal of the signal can effectively improve the signal-to-noise ratio after the secondary autocorrelation processing.
  • the detection of the target signal-to-noise ratio can be omitted, and for the initial beat frequency signal with a weak useful signal, Regardless of whether the second autocorrelation process or at least one autocorrelation process converges, the target SNR needs to be detected to ensure that the target SNR meets certain requirements (for example, it is greater than the signal-to-noise threshold), so as to facilitate subsequent The difference frequency of the useful signal is extracted.
  • the target SNR needs to be detected to ensure that the target SNR meets certain requirements (for example, it is greater than the signal-to-noise threshold), so as to facilitate subsequent The difference frequency of the useful signal is extracted.
  • both the time-domain beat frequency signal and the initial beat-frequency signal can be expressed as beat-frequency signals in the time domain, and the initial beat-frequency signal is the beat-frequency signal in the time domain before denoising, and the time-domain beat signal The beat frequency signal is the beat frequency signal in the time domain after denoising.
  • the signal noise filtering device may perform Fourier transform processing on the time-domain beat-frequency signal to obtain a frequency-domain beat-frequency signal, and obtain a beat-frequency corresponding to the maximum amplitude from the frequency-domain beat-frequency signal frequency value, the Fourier transform processing can be selected as fast Fourier transform processing, the frequency domain beat frequency signal can be specifically represented as a beat frequency signal in the frequency domain after denoising, the signal noise filtering device
  • the position of the maximum amplitude value can be obtained in the spectrum diagram formed by the frequency-domain beat frequency signal, and the corresponding frequency value of the position can be determined as the beat frequency value of the useful signal.
  • the useful signal is specifically expressed as the transmitted signal returned by the detection target. Real and effective difference frequency signal.
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, at least one autocorrelation process can be performed on the initial beat frequency signal to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the signal correlation degree, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of beat frequency extraction by detecting the target signal-to-noise ratio, it is ensured that the target signal-to-noise ratio meets certain requirements, so as to facilitate the subsequent extraction of the beat frequency of the useful signal.
  • FIG. 5 provides a schematic flowchart of a signal noise filtering method according to an embodiment of the present application.
  • the method in this embodiment of the present application may include the following steps S401 to S407.
  • the emission signal of the lidar changes periodically according to the law of the triangular wave, transmits the signal to the detection target, and receives the echo signal returned by the detection target. Because the emission signal and the echo signal are easily affected by the inherent characteristics of the lidar system and the environment, etc. Therefore, an initial beat frequency signal with a noise signal is presented in the frequency spectrum.
  • the signal noise filtering device obtains the initial beat frequency signal generated by the lidar, and the initial beat frequency signal is a signal containing noise. difference frequency signal.
  • the signal noise filtering device performs autocorrelation processing on the initial beat frequency signal to obtain a second autocorrelation function of the initial beat frequency signal
  • the autocorrelation operation can be optionally an unbiased autocorrelation operation, It specifically reflects the correlation degree of the signal at different times t 1 and t 2 , which can be expressed as:
  • R x E[x(t 1 )x(t 2 )]
  • x(t 1 ) and x(t 2 ) represent the values at time t 1 and t 2 in the initial difference frequency signal x(t), respectively, and the second autocorrelation function R x , t 1 is obtained through autocorrelation operation processing t 1 and t 2 can be randomly selected according to actual needs, or t 1 and t 2 can be selected according to the signal period, that is, the distance between t 1 and t 2 is one signal period.
  • the signal noise filtering device may also record the processing times of the autocorrelation processing. It can be understood that after the autocorrelation processing is performed once, the processing times can be updated. For example, the initial processing times are 0. After one autocorrelation processing, the processing times are increased by one, and so on.
  • the signal-to-noise filtering device may The function is determined to be the initial beat frequency signal, and the process goes to step S402.
  • the The signal noise filtering device can take Rx as x (t), and then perform autocorrelation processing by selecting the same values at time t1 and t2 to obtain a third autocorrelation function again, and use the number of processing times to perform autocorrelation processing. Add one, and repeat this process until it is detected that at least one of the two convergence conditions is satisfied, then go to step S404 or step S405.
  • one convergence condition is that the second signal-to-noise ratio indicated by the third autocorrelation function satisfies the signal-to-noise threshold
  • another convergence condition is that the number of times of autocorrelation processing is limited within the number of times threshold, the signal-to-noise threshold and the The number of thresholds can be set according to actual needs.
  • the signal-to-noise ratio of the initial beat frequency signal can be effectively improved after autocorrelation processing, thereby improving the success rate of extracting useful signals in the initial beat frequency signal;
  • the useful signal can be extracted from the initial beat-frequency signal at this time. The number of processing times of the correlation processing is limited, which can ensure the extraction efficiency of the difference frequency frequency of the useful signal.
  • the signal-to-noise filtering apparatus may determine the third autocorrelation function as the initial difference
  • the useful signal corresponding to the frequency signal that is , the signal noise filtering device may determine the Rx obtained last time as the useful signal corresponding to the initial difference frequency signal.
  • the signal-to-noise filtering device may The function is determined as the useful signal corresponding to the initial beat frequency signal, that is, the signal noise filtering device may determine the Rx obtained last time as the useful signal corresponding to the initial beat frequency signal.
  • step S404 and step S405 respectively indicate that when any one of the two convergence conditions is satisfied, the last obtained Rx can be determined as the useful signal corresponding to the initial beat frequency signal;
  • the third autocorrelation function is determined as the initial The useful signal corresponding to the difference frequency signal.
  • the signal-noise filtering device may determine the useful signal as the denoised time-domain beat frequency signal.
  • the processing times of autocorrelation processing can also be detected, so that when the target signal-to-noise ratio still cannot meet certain requirements, the processing times are limited to a certain range (for example, equal to the times threshold) to ensure Processing efficiency of beat frequency extraction of useful signals.
  • both the time-domain beat frequency signal and the initial beat-frequency signal can be expressed as beat-frequency signals in the time domain, and the initial beat-frequency signal is the beat-frequency signal in the time domain before denoising, and the time-domain beat signal The beat frequency signal is the beat frequency signal in the time domain after denoising.
  • the signal noise filtering device may perform Fourier transform processing on the time-domain beat-frequency signal to obtain a frequency-domain beat-frequency signal, and obtain a beat-frequency corresponding to the maximum amplitude from the frequency-domain beat-frequency signal frequency value, the Fourier transform processing can be selected as fast Fourier transform processing, the frequency domain beat frequency signal can be specifically represented as a beat frequency signal in the frequency domain after denoising, the signal noise filtering device
  • the position of the maximum amplitude value can be obtained in the spectrum diagram formed by the frequency-domain beat frequency signal, and the corresponding frequency value of the position can be determined as the beat frequency value of the useful signal.
  • the useful signal is specifically expressed as the transmitted signal returned by the detection target. Real and effective difference frequency signal.
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, at least one autocorrelation process can be performed on the initial beat frequency signal to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the signal correlation degree, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of the beat frequency extraction by detecting the target signal-to-noise ratio, it is ensured that the target signal-to-noise ratio meets certain requirements, so as to facilitate the subsequent extraction of the beat frequency frequency of the useful signal; Limitation, on the basis of improving the success rate of extracting the useful signal in the initial beat frequency signal, the extraction efficiency of the beat frequency of the useful signal can be improved.
  • FIG. 6 a schematic diagram of an example spectrum of a signal after Fourier transform is provided for an embodiment of the present application.
  • Figure 6 shows the spectrograms of three kinds of signals.
  • the three kinds of signals are the original pure signal (that is, the original pure beat frequency signal) and the original beat frequency signal obtained after processing by Fast Fourier Transform (FFT).
  • FFT Fast Fourier Transform
  • the signal and the initial beat frequency signal are obtained after autocorrelation processing and FFT processing.
  • the beat frequency of the useful signal is (4 ⁇ 10 8 ) Hz; while for the signal obtained only by FFT processing, the beat frequency corresponding to the maximum amplitude is located in Fig. 6.
  • the beat frequency of the useful signal cannot be effectively and accurately obtained only by FFT processing; for the signal obtained after autocorrelation processing and FFT processing, the beat frequency is the same as the original transmitted signal. Consistent. Therefore, by performing autocorrelation processing on the initial beat frequency signal, the noise signal in the initial beat frequency signal can be effectively filtered, thereby improving the success rate of effective beat frequency extraction.
  • FIG. 7 an exemplary schematic diagram of the success rate of extracting useful signals from signals under different signal-to-noise ratios is provided for this embodiment of the present application.
  • the solid line represents the detection success rate of extracting the beat frequency of the detection target in the initial beat frequency signal processed only by FFT;
  • the dotted line represents the initial beat frequency signal processed by autocorrelation and FFT, The detection success rate of the beat frequency frequency of the detection target is extracted.
  • the noise signal can be filtered more effectively under different signal-to-noise ratios.
  • the useful signal of the detection target can be obtained, and the difference frequency of the useful signal can be obtained.
  • FIG. 8 an exemplary schematic diagram of the number of successful times of extracting useful signals under different detection distances and different signal-to-noise ratios is provided for this embodiment of the present application.
  • the solid line represents the detection success rate of extracting the beat frequency of the detection target in the initial beat frequency signal processed only by FFT;
  • the dashed line represents the initial beat frequency signal processed by autocorrelation and FFT, The detection success rate of the beat frequency frequency of the detection target is extracted.
  • the initial difference frequency signal can be more effectively filtered under different signal-to-noise ratios after autocorrelation processing.
  • the useful signal of the detected target can be obtained, and the difference frequency of the useful signal can be obtained, and it is not affected by the target distance of the detected target.
  • the signal noise filtering device provided by the embodiment of the present application will be described in detail below with reference to FIG. 9 to FIG. 13 .
  • the signal noise filtering device in FIG. 9-FIG. 13 is used to execute the method of the embodiment shown in FIG. 2-FIG. 8 of the present application.
  • FIG. 9-FIG. 13 is used to execute the method of the embodiment shown in FIG. 2-FIG. 8 of the present application.
  • FIG. 2 to FIG. 8 of the present application please refer to the embodiments shown in FIG. 2 to FIG. 8 of the present application.
  • FIG. 9 is a schematic structural diagram of an apparatus for filtering signal noise according to an embodiment of the present application.
  • the signal noise filtering apparatus 1 in the embodiment of the present application may include: an initial signal acquiring unit 11 , a signal processing unit 12 and a denoising signal determining unit 13 .
  • an initial signal acquisition unit 11 configured to acquire an initial beat frequency signal generated by the lidar, where the initial beat frequency signal is a beat frequency signal containing a noise signal;
  • a signal processing unit 12 configured to perform autocorrelation processing on the initial beat frequency signal at least once to obtain a useful signal of the initial beat frequency signal
  • the de-noised signal determination unit 13 is configured to determine the useful signal as a de-noised time-domain difference frequency signal.
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, at least one autocorrelation process can be performed on the initial beat frequency signal to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the signal correlation degree, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of beat frequency extraction is acquiring the initial beat frequency signal containing the noise signal generated by the lidar.
  • FIG. 10 is a schematic structural diagram of an apparatus for filtering signal noise according to an embodiment of the present application.
  • the signal noise filtering apparatus 1 in the embodiment of the present application may include: an initial signal obtaining unit 11 , a signal processing unit 12 , a denoising signal determining unit 13 , and a beat frequency obtaining unit 14 .
  • an initial signal acquisition unit 11 configured to acquire an initial beat frequency signal generated by the lidar, where the initial beat frequency signal is a beat frequency signal containing a noise signal;
  • a signal processing unit 12 configured to perform autocorrelation processing on the initial beat frequency signal at least once to obtain a useful signal of the initial beat frequency signal
  • the signal processing unit 12 may include:
  • a first signal processing subunit 121 configured to perform autocorrelation processing on the initial beat frequency signal to obtain a first autocorrelation function of the initial beat frequency signal
  • the function processing subunit 122 is configured to perform autocorrelation processing on the first autocorrelation function to obtain a useful signal corresponding to the initial beat frequency signal.
  • the signal processing unit 12 may include:
  • the second signal processing subunit 123 is configured to perform autocorrelation processing on the initial beat frequency signal to obtain a second autocorrelation function of the initial beat frequency signal;
  • the first notification subunit 124 is configured to determine the second autocorrelation function as the initial beat frequency signal when the first signal-to-noise ratio indicated by the second autocorrelation function is less than or equal to the signal-to-noise threshold, and notify The second signal processing subunit 123 performs autocorrelation processing on the initial beat frequency signal to obtain a second autocorrelation function of the initial beat frequency signal, until the first signal-to-noise ratio is greater than the signal-to-noise threshold, and The second autocorrelation function is determined as a useful signal corresponding to the initial beat frequency signal.
  • the signal processing unit 12 may include:
  • the third signal processing subunit 125 is configured to perform autocorrelation processing on the initial beat frequency signal, obtain a third autocorrelation function of the initial beat frequency signal, and update the processing times of the autocorrelation processing;
  • the second notification subunit 126 is configured to determine the third autocorrelation function when the second signal-to-noise ratio indicated by the third autocorrelation function is less than or equal to the signal-to-noise threshold, and the number of processing times is less than the number of times threshold For the initial beat frequency signal, notify the third signal processing sub-unit 125 to perform autocorrelation processing on the initial beat frequency signal, obtain a third autocorrelation function of the initial beat frequency signal, and update the autocorrelation function of the autocorrelation processing. processing times;
  • the signal determination subunit 127 is configured to determine the third autocorrelation function as the The useful signal corresponding to the initial difference frequency signal;
  • the signal determination subunit 127 is further configured to, when the second signal-to-noise ratio indicated by the third autocorrelation function is less than or equal to the signal-to-noise threshold, and the number of processing times is equal to the number of times threshold, determine the third autocorrelation function.
  • the function is determined as the useful signal corresponding to the initial beat frequency signal.
  • a denoising signal determining unit 13 configured to determine the useful signal as a denoised time-domain difference frequency signal
  • the denoising signal determining unit 13 is specifically configured to determine the useful signal as a denoised time-domain difference frequency signal when the target signal-to-noise ratio indicated by the useful signal is greater than a signal-to-noise threshold.
  • the beat frequency acquisition unit 14 is configured to perform Fourier transform processing on the time domain beat frequency signal to obtain a frequency domain beat frequency signal, and obtain the beat frequency value corresponding to the maximum amplitude in the frequency domain beat frequency signal .
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, at least one autocorrelation process can be performed on the initial beat frequency signal to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the signal correlation degree, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of beat frequency extraction by detecting the target signal-to-noise ratio, it is ensured that the target signal-to-noise ratio meets certain requirements, so as to facilitate the subsequent extraction of the beat frequency of the useful signal.
  • An embodiment of the present application further provides a computer storage medium, where the computer storage medium can store a plurality of program instructions, and the program instructions are suitable for being loaded by a processor and executing the above-mentioned embodiments shown in FIG. 2 to FIG. 4 .
  • the computer storage medium can store a plurality of program instructions, and the program instructions are suitable for being loaded by a processor and executing the above-mentioned embodiments shown in FIG. 2 to FIG. 4 .
  • the lidar 1000 may include: at least one processor 1001 , such as a CPU, at least one network interface 1004 , input/output interface 1003 , memory 1005 , and at least one communication bus 1002 .
  • the communication bus 1002 is used to realize the connection and communication between these components.
  • the network interface 1004 may optionally include a standard wired interface and a wireless interface (eg, a WI-FI interface).
  • the memory 1005 may be high-speed RAM memory or non-volatile memory, such as at least one disk memory.
  • the memory 1005 may also be at least one storage device located away from the aforementioned processor 1001 .
  • the memory 1005 as a computer storage medium may include an operating system, a network communication module, an input/output interface module, and a noise filtering application program.
  • the input and output interface 1003 is mainly used to provide an input interface for the user and the access device, and obtain data input by the user and the access device.
  • the processor 1001 may be configured to invoke the noise filtering application program stored in the memory 1005, and specifically perform the following operations:
  • the initial beat frequency signal is a beat frequency signal containing a noise signal
  • the useful signal is determined as a time-domain difference frequency signal after denoising.
  • the processor 1001 when performing autocorrelation processing on the initial beat frequency signal at least once to obtain a useful signal of the initial beat frequency signal, the processor 1001 specifically performs the following operations:
  • the processor 1001 when performing autocorrelation processing on the initial beat frequency signal at least once to obtain an autocorrelation function of the initial beat frequency signal, the processor 1001 specifically performs the following operations:
  • the second autocorrelation function is determined as the initial beat frequency signal, and the execution of the initial beat frequency signal is performed.
  • the processor 1001 when performing autocorrelation processing on the initial beat frequency signal at least once to obtain a useful signal of the initial beat frequency signal, the processor 1001 specifically performs the following operations:
  • the third autocorrelation function When the second signal-to-noise ratio indicated by the third autocorrelation function is less than or equal to the signal-to-noise threshold, and the number of processing times is less than the number of times threshold, determining the third autocorrelation function as the initial beat frequency signal, and Transfer to the steps of performing autocorrelation processing on the initial beat frequency signal, obtaining a third autocorrelation function of the initial beat frequency signal, and updating the number of times of the autocorrelation processing;
  • the third autocorrelation function is determined as the useful signal corresponding to the initial beat frequency signal ;
  • the third autocorrelation function is determined as the corresponding signal of the initial beat frequency signal useful signal.
  • the processor 1001 determines the useful signal as the denoised time-domain difference frequency signal
  • the processor 1001 specifically performs the following operations:
  • the useful signal is determined as a time-domain difference frequency signal after denoising.
  • processor 1001 further performs the following operations:
  • Fourier transform processing is performed on the time-domain beat-frequency signal to obtain a frequency-domain beat-frequency signal, and a beat-frequency frequency value corresponding to the maximum amplitude is obtained from the frequency-domain beat-frequency signal.
  • the initial beat frequency signal by acquiring the initial beat frequency signal containing the noise signal generated by the lidar, at least one autocorrelation process can be performed on the initial beat frequency signal to obtain the useful signal of the initial beat frequency signal, and finally the useful signal is determined. is the time-domain difference frequency signal after denoising.
  • the initial beat frequency signal can be processed into an autocorrelation function based on the signal correlation degree, which effectively improves the signal-to-noise ratio of the signal, and extracts the weak useful signal in the initial beat frequency signal, thereby improving the effective signal-to-noise ratio.
  • the success rate of beat frequency extraction by detecting the target signal-to-noise ratio, it is ensured that the target signal-to-noise ratio meets certain requirements, so as to facilitate the subsequent extraction of the beat frequency of the useful signal.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM) or the like.

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Abstract

一种信号噪声滤除方法、装置、存储介质及激光雷达，其中方法包括：获取激光雷达产生的初始差频信号（S101），所述初始差频信号为含有噪声信号的差频信号；对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号（S102）；将所述有用信号确定为去噪后的时域差频信号（S103）。可以提高差频信号的信噪比，提高有效的差频频率提取的成功率。

Description

一种信号噪声滤除方法、装置、存储介质及激光雷达 技术领域
本申请涉及计算机技术领域，尤其涉及一种信号噪声滤除方法、装置、存储介质及激光雷达。
背景技术
调频连续波激光雷达(Frequency Modulated Continuous Wave，FMCW)属于一种基于相干探测的连续波激光雷达，在扫频周期内发射频率线性变化的连续波作为发射信号，发射信号的一部分作为本振信号，其余部分向外出射进行探测，被物体反射后返回的回波信号与本振信号形成差频信号。由于信号在实际探测过程中容易受到激光雷达系统、环境等固有噪声的影响，导致信噪比较低，无法较好的提取有效的差频信号。
发明内容
本申请实施例提供一种信号噪声滤除方法、装置、存储介质及激光雷达，可以提高差频信号的信噪比，提高有效的差频频率提取的成功率。
本申请实施例一方面提供了一种信号噪声滤除方法，包括：
获取激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号；
对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号；
将所述有用信号确定为去噪后的时域差频信号。
其中，所述对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号，包括：
对所述初始差频信号进行自相关处理，得到所述初始差频信号的第一自相关函数；
对所述第一自相关函数进行自相关处理，得到所述初始差频信号对应的有用信号。
其中，所述对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号，包括：
对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数；
当所述第二自相关函数指示的第一信噪比小于或等于信噪阈值时，将所述第二自相关函数确定为所述初始差频信号，并转入执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数的步骤，直至所述第一信噪比大于所述信噪阈值，将所述第二自相关函数确定为所述初始差频信号对应的有用信号。
其中，所述对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号，包括：
对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数；
当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号，并转入执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数的步骤；
当所述第三自相关函数指示的第二信噪比大于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号；
当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数等于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号。
其中，所述将所述有用信号确定为去噪后的时域差频信号，包括：
当所述有用信号指示的目标信噪比大于信噪阈值时，将所述有用信号确定为去噪后的时域差频信号。
其中，还包括：
对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值。
本申请实施例一方面提供了一种信号噪声滤除装置，包括：
初始信号获取单元，用于获取激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号；
信号处理单元，用于对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号；
去噪信号确定单元，用于将所述有用信号确定为去噪后的时域差频信号。
其中，所述信号处理单元包括：
第一信号处理子单元，用于对所述初始差频信号进行自相关处理，得到所述初始差频信号的第一自相关函数；
函数处理子单元，用于对所述第一自相关函数进行自相关处理，得到所述初始差频信号对应的有用信号。
其中，所述信号处理单元包括：
所述信号处理单元包括：
第二信号处理子单元，用于对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数；
第一通知子单元，用于当所述第二自相关函数指示的第一信噪比小于或等于信噪阈值时，将所述第二自相关函数确定为所述初始差频信号，通知第二信号处理子单元执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数，直至所述第一信噪比大于所述信噪阈值，将所述第二自相关函数确定为所述初始差频信号对应的有用信号。
其中，所述信号处理单元包括：
第三信号处理子单元，用于对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数；
第二通知子单元，用于当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号，通知第三信号处理子单元执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数；
信号确定子单元，用于当所述第三自相关函数指示的第二信噪比大于信噪阈值，且所 述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号；
所述信号确定子单元，还用于当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数等于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号。
其中，所述去噪信号确定单元具体用于当所述有用信号指示的目标信噪比大于信噪阈值时，将所述有用信号确定为去噪后的时域差频信号。
其中，还包括：
差频频率获取单元，用于对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值。
本申请实施例一方面提供了一种计算机存储介质，所述计算机存储介质存储有计算机程序，所述计算机程序包括程序指令，所述程序指令当被处理器执行时，执行上述的方法步骤。
本申请实施例一方面提供了一种激光雷达，包括处理器、存储器、输入输出接口；
其中，所述处理器分别与所述存储器和所述输入输出接口相连，其中，所述输入输出接口用于页面交互，所述存储器用于存储程序代码，所述处理器用于调用所述程序代码，以执行上述的方法步骤。
在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行至少一次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过至少一次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱的有用信号，进而提高了有效的差频频率提取的成功率。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请实施例提供的信号噪声滤除的系统架构图；
图2是本申请实施例提供的一种信号噪声滤除方法的流程示意图；
图3是本申请实施例提供的一种信号噪声滤除方法的流程示意图；
图4是本申请实施例提供的一种信号噪声滤除方法的流程示意图；
图5是本申请实施例提供的一种信号噪声滤除方法的流程示意图；
图6是本申请实施例提供的对信号作傅里叶变换后的频谱举例示意图；
图7是本申请实施例提供的信号在不同信噪比下提取有用信号的成功率的举例示意图；
图8是本申请实施例提供的在不同探测距离和不同信噪比下提取有用信号的成功次数的举例示意图；
图9是本申请实施例提供的一种信号噪声滤除装置的结构示意图；
图10是本申请实施例提供的一种信号噪声滤除装置的结构示意图；
图11是本申请实施例提供的一种信号处理单元的结构示意图；
图12是本申请实施例提供的一种信号处理单元的结构示意图；
图13是本申请实施例提供的一种信号处理单元的结构示意图；
图14是本申请实施例提供的一种激光雷达的结构示意图。
具体实施方式
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，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
请结合图1-图8所示实施例，对本申请实施例提供的信号噪声滤除方法进行详细介绍。
请参见图1，为本申请实施例提供了一种信号噪声滤除的系统架构图。如图1所示，本申请实施例可以应用于激光雷达探测的场景，例如：环境监测、航天、通信、自动驾驶导航、定位等探测场景，激光雷达的发射信号按三角波的规律周期性变化，对探测目标进行信号发射，并接收由探测目标返回的回波信号，并获取发射信号与回波信号形成的初始差频信号，初始差频信号可以通过信号处理器进行一系列的信号处理过程，包括模数转换处理、信号滤波处理、信号数据提取、信号数据计算等，进而通过后台管理设备对信号处理器生成的信号谱、数据等进行存储、展示等管理操作。
由于发射信号和回波信号容易受到激光雷达系统、环境等固有噪声的影响，因而在频谱中呈现的是带有噪声信号的初始差频信号，本申请实施例为了去除初始差频信号中的噪声信号，具体提出了一种信号噪声滤除装置，所述信号噪声滤除装置可以设置于所述信号处理器中，也可以作为独立设备，实现对初始差频信号的噪声滤除处理，信号噪声滤除装置可以获取激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号，所述信号噪声滤除装置对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号，所述信号噪声滤除装置将所述有用信号确定为去噪后的时域差频信号。在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行至少一次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过至少一次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱的有用信号，进而提高了有效的差频频率提取的成功率。
基于图1的系统架构，请一并参见图2，为本申请实施例提供了一种信号噪声滤除方法的流程示意图。如图2所示，本申请实施例的所述方法可以包括以下步骤S101-步骤S103。
S101，获取激光雷达产生的初始差频信号；
具体的，激光雷达的发射信号按三角波的规律周期性变化，对探测目标进行信号发射，并接收由探测目标返回的回波信号，由于发射信号和回波信号容易受到激光雷达系统、环境等固有噪声的影响，因而在频谱中呈现的是带有噪声信号的初始差频信号，所述信号噪 声滤除装置获取所述激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号。
S102，对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号；
具体的，所述信号噪声滤除装置可以对所述初始差频信号进行至少一次自相关处理，以得到所述初始差频信号的有用信号，可以理解的是，通过自相关运算是可以提高信号的信噪比，因此在本申请实施例可选的实施方式中，所述信号噪声滤除装置可以通过二次自相关处理以及至少一次自相关处理收敛两种方式进一步提升初始差频信号的信噪比，其中，二次自相关处理是对所述初始差频信号进行两次自相关运算处理；至少一次自相关处理收敛可以是对所述初始差频信号进行一次或多次重复的自相关运算处理，直至运算得到的自相关函数所指示的信噪比满足信噪阈值时，将最后一次自相关运算处理得到的自相关函数确定为有用信号；至少一次自相关处理收敛还可以设置有自相关处理的次数阈值，在对所述初始差频信号进行一次或多次重复的自相关运算处理过程，若始终未得到自相关函数所指示的信噪比满足信噪阈值，但自相关处理的处理次数满足次数阈值，则将最后一次自相关运算处理得到的自相关函数确定为有用信号。两种方式均可以提升初始差频信号的信噪比，有效的对有用信号进行提取。
S103，将所述有用信号确定为去噪后的时域差频信号；
具体的，所述信号噪声滤除装置可以将所述有用信号确定为去噪后的时域差频信号，可以理解的是，为了进一步保证可以对有用信号进行提取，所述信号噪声滤除装置可以检测所述有用信号指示的目标信噪比是否大于信噪阈值，所述信噪阈值可以依据实际情况进行设置，当所述有用信号指示的目标信噪比大于信噪阈值时，所述信号噪声滤除装置可以将所述有用信号确定为去噪后的时域差频信号，当然，对于目标信噪比的检测过程可以依据实际情况确定是否需要执行，例如：对于包含强度较高的有用信号的初始差频信号，可以只需一次自相关处理后，使得信噪比得到更有效的提高；对于包含了强度一般的有用信号的初始差频信号，在通过二次自相关处理后，可以使得信噪比得到有效的提高，此时可以不进行目标信噪比的检测；而对于有用信号较为微弱的初始差频信号，无论是采用二次自相关处理还是至少一次自相关处理收敛的方式，都需要进行目标信噪比的检测，以保证目标信噪比满足一定的需求(例如大于信噪阈值)，以便于后续对有用信号的差频频率进行提取；当然对于有用信号较为微弱的初始差频信号，在进行目标信噪比的检测的同时，还可以对自相关处理的处理次数进行检测，以在目标信噪比仍无法满足一定的需求的情况下，将处理次数限定在一定的范围(例如等于次数阈值)，以保证有用信号的差频频率提取的处理效率。
在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行至少一次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过至少一次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱的有用信号，进而提高了有效的差频频率提取的成功率。
基于图1的系统架构，请一并参见图3，为本申请实施例提供了一种信号噪声滤除方法的流程示意图。如图3所示，本申请实施例的所述方法可以包括以下步骤S201-步骤S205。
S201，获取激光雷达产生的初始差频信号；
具体的，激光雷达的发射信号按三角波的规律周期性变化，对探测目标进行信号发射，并接收由探测目标返回的回波信号，由于发射信号和回波信号容易受到激光雷达系统、环境等固有噪声的影响，因而在频谱中呈现的是带有噪声信号的初始差频信号，所述信号噪声滤除装置获取所述激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号。
进一步的，所述初始差频信号可以表示为x(t)，原始纯净差频信号为s(t)，噪声信号为n(t)，则有x(t)＝s(t)+n(t)，其中，所述原始纯净差频信号可以为差频信号在无噪声的理想环境下所形成的差频信号。
S202，对所述初始差频信号进行自相关处理，得到所述初始差频信号的第一自相关函数；
具体的，针对二次自相关处理，所述信号噪声滤除装置可以对所述初始差频信号进行自相关运算处理，得到所述初始差频信号的第一自相关函数，所述自相关运算可选为无偏自相关运算，其具体反映了信号在不同时刻t 1和t 2取值的相关程度，具体可以表达为：
R x＝E[x(t 1)x(t 2)]
其中x(t 1)和x(t 2)分别表示初始差频信号x(t)中t 1和t 2时刻的取值，通过自相关运算处理得到第一自相关函数R x，t 1和t 2可以依据实际需求进行随机选择，也可以依据信号周期对t 1和t 2进行选择，即t 1和t 2的距离为一个信号周期。
S203，对所述第一自相关函数进行自相关处理，得到所述初始差频信号对应的有用信号；
具体的，所述信号噪声滤除装置可以对所述第一自相关函数再进行一次自相关处理，得到所述初始差频信号对应的有用信号，所述信号噪声滤除装置将R x作为x(t)，在通过选择相同的t 1和t 2时刻的取值，进行自相关处理，得到所述初始差频信号对应的有用信号。
S204，将所述有用信号确定为去噪后的时域差频信号；
具体的，所述信号噪声滤除装置可以将所述有用信号确定为去噪后的时域差频信号，可以理解的是，为了进一步保证可以对有用信号进行提取，所述信号噪声滤除装置可以检测所述有用信号指示的目标信噪比是否大于信噪阈值，所述信噪阈值可以依据实际情况进行设置，当所述有用信号指示的目标信噪比大于信噪阈值时，所述信号噪声滤除装置可以将所述有用信号确定为去噪后的时域差频信号，当然，对于目标信噪比的检测过程可以依据实际情况确定是否需要执行，例如：对于包含了强度一般的有用信号的初始差频信号，在通过二次自相关处理后，可以使得信噪比得到有效的提高，此时可以不进行目标信噪比的检测，而对于有用信号较为微弱的初始差频信号，采用二次自相关处理还是需要进行目标信噪比的检测，以保证目标信噪比满足一定的需求(例如大于信噪阈值)，以便于后续对有用信号的差频频率进行提取。
需要说明的是，所述时域差频信号和所述初始差频信号均可以表示为时域上的差频信号，初始差频信号为去噪前的时域上的差频信号，时域差频信号为去噪后的时域上的差频 信号。
S205，对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值；
具体的，所述信号噪声滤除装置可以对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值，所述傅里叶变换处理可选为快速傅里叶变换处理，所述频域差频信号具体可以表示为去噪后的频域上的差频信号，所述信号噪声滤除装置可以在频域差频信号所形成的频谱图中获取最大幅值的位置，并将该位置对应的频率值确定为有用信号的差频频率值，有用信号具体表示为发射信号经探测目标返回的真实有效的差频信号。
在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行二次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过二次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱的有用信号，进而提高了有效的差频频率提取的成功率；通过进行目标信噪比的检测，保证了目标信噪比满足一定的需求，以便于后续对有用信号的差频频率进行提取。
基于图1的系统架构，请一并参见图4，为本申请实施例提供了一种信号噪声滤除方法的流程示意图。如图4所示，本申请实施例的所述方法可以包括以下步骤S301-步骤S306。
S301，获取激光雷达产生的初始差频信号；
具体的，激光雷达的发射信号按三角波的规律周期性变化，对探测目标进行信号发射，并接收由探测目标返回的回波信号，由于发射信号和回波信号容易受到激光雷达系统、环境等固有噪声的影响，因而在频谱中呈现的是带有噪声信号的初始差频信号，所述信号噪声滤除装置获取所述激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号。
进一步的，所述初始差频信号可以表示为x(t)，原始纯净差频信号为s(t)，噪声信号为n(t)，则有x(t)＝s(t)+n(t)，其中，所述原始纯净差频信号可以为差频信号在无噪声的理想环境下所形成的差频信号。
S302，对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数；
具体的，所述信号噪声滤除装置对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数，所述自相关运算可选为无偏自相关运算，其具体反映了信号在不同时刻t 1和t 2取值的相关程度，具体可以表达为：
R x＝E[x(t 1)x(t 2)]
其中，x(t 1)和x(t 2)分别表示初始差频信号x(t)中t 1和t 2时刻的取值，通过自相关运算处理得到第二自相关函数R x，t 1和t 2可以依据实际需求进行随机选择，也可以依据信号周期对t 1和t 2进行选择，即t 1和t 2的距离为一个信号周期。
S303，当所述第二自相关函数指示的第一信噪比小于或等于信噪阈值时，将所述第二自相关函数确定为所述初始差频信号；
具体的，当所述第二自相关函数指示的第一信噪比小于或等于信噪阈值时，所述信号噪声滤除装置可以将所述第二自相关函数确定为所述初始差频信号，并转入执行步骤S302，在所述第二自相关函数指示的第一信噪比小于或等于信噪阈值时，所述信号噪声滤除装置可以将R x作为x(t)，再通过选择相同的t 1和t 2时刻的取值，进行自相关处理，再次得到第二自相关函数，重复执行此过程，直至检测到第一信噪比大于所述信噪阈值这一收敛条件时，转入执行步骤S304。
S304，当所述第一信噪比大于所述信噪阈值时，将所述第二自相关函数确定为所述初始差频信号对应的有用信号；
具体的，当所述第一信噪比大于所述信噪阈值时，所述信号噪声滤除装置可以将所述第二自相关函数确定为所述初始差频信号对应的有用信号，即所述信号噪声滤除装置可以将最后一次得到的R x确定为所述初始差频信号对应的有用信号。
S305，将所述有用信号确定为去噪后的时域差频信号；
具体的，所述信号噪声滤除装置可以将所述有用信号确定为去噪后的时域差频信号，可以理解的是，为了进一步保证可以对有用信号进行提取，所述信号噪声滤除装置可以检测所述有用信号指示的目标信噪比是否大于信噪阈值，所述信噪阈值可以依据实际情况进行设置，当所述有用信号指示的目标信噪比大于信噪阈值时，所述信号噪声滤除装置可以将所述有用信号确定为去噪后的时域差频信号，当然，对于目标信噪比的检测过程可以依据实际情况确定是否需要执行，例如：对于包含了强度一般的有用信号的初始差频信号，在通过二次自相关处理后，可以使得信噪比得到有效的提高，此时可以不进行目标信噪比的检测，而对于有用信号较为微弱的初始差频信号，无论是采用二次自相关处理还是至少一次自相关处理收敛的方式，都需要进行目标信噪比的检测，以保证目标信噪比满足一定的需求(例如大于信噪阈值)，以便于后续对有用信号的差频频率进行提取。二次自相关处理的过程可以参见图3所示实施例的具体描述，在此不进行赘述。
需要说明的是，所述时域差频信号和所述初始差频信号均可以表示为时域上的差频信号，初始差频信号为去噪前的时域上的差频信号，时域差频信号为去噪后的时域上的差频信号。
S306，对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值；
具体的，所述信号噪声滤除装置可以对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值，所述傅里叶变换处理可选为快速傅里叶变换处理，所述频域差频信号具体可以表示为去噪后的频域上的差频信号，所述信号噪声滤除装置可以在频域差频信号所形成的频谱图中获取最大幅值的位置，并将该位置对应的频率值确定为有用信号的差频频率值，有用信号具体表示为发射信号经探测目标返回的真实有效的差频信号。
在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行至少一次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过至少一次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱 的有用信号，进而提高了有效的差频频率提取的成功率；通过进行目标信噪比的检测，保证了目标信噪比满足一定的需求，以便于后续对有用信号的差频频率进行提取。
基于图1的系统架构，请一并参见图5，为本申请实施例提供了一种信号噪声滤除方法的流程示意图。如图5所示，本申请实施例的所述方法可以包括以下步骤S401-步骤S407。
S401，获取激光雷达产生的初始差频信号；
具体的，激光雷达的发射信号按三角波的规律周期性变化，对探测目标进行信号发射，并接收由探测目标返回的回波信号，由于发射信号和回波信号容易受到激光雷达系统、环境等固有噪声的影响，因而在频谱中呈现的是带有噪声信号的初始差频信号，所述信号噪声滤除装置获取所述激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号。
进一步的，所述初始差频信号可以表示为x(t)，原始纯净差频信号为s(t)，噪声信号为n(t)，则有x(t)＝s(t)+n(t)，其中，所述原始纯净差频信号可以为差频信号在无噪声的理想环境下所形成的差频信号。
S402，对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数；
具体的，所述信号噪声滤除装置对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数，所述自相关运算可选为无偏自相关运算，其具体反映了信号在不同时刻t 1和t 2取值的相关程度，具体可以表达为：
R x＝E[x(t 1)x(t 2)]
其中，x(t 1)和x(t 2)分别表示初始差频信号x(t)中t 1和t 2时刻的取值，通过自相关运算处理得到第二自相关函数R x，t 1和t 2可以依据实际需求进行随机选择，也可以依据信号周期对t 1和t 2进行选择，即t 1和t 2的距离为一个信号周期。
所述信号噪声滤除装置还可以记录有自相关处理的处理次数，可以理解的是，在进行了一次自相关处理后，可以对所述处理次数进行更新，例如：初始的处理次数为0，进行一次自相关处理后将处理次数加一，以此类推。
S403，当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号，并转入执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数，更新所述自相关处理的处理次数的步骤；
具体的，当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数小于次数阈值时，所述信号噪声滤除装置可以将所述第三自相关函数确定为所述初始差频信号，并转入执行步骤S402，在所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数小于次数阈值时，所述信号噪声滤除装置可以将R x作为x(t)，再通过选择相同的t 1和t 2时刻的取值，进行自相关处理，再次得到第三自相关函数，并将所述处理次数加一，重复执行此过程，直至检测到满足两个收敛条件中的至少一个收敛条件时，转入执行步骤S404或步骤S405。
可选的，一个收敛条件为第三自相关函数指示的第二信噪比满足信噪阈值，另一个收 敛条件为自相关处理的处理次数限定在次数阈值内，所述信噪阈值和所述次数阈值可以根据实际需求进行设置。通过设置信噪阈值，可以在自相关处理后，可以有效的提升初始差频信号的信噪比，进而提升初始差频信号中有用信号的提取成功率；而通过设置次数阈值，在对初始差频信号进行预设次数的自相关处理后，尽管初始差频信号的信噪比仍然无法达到信噪阈值，但此时已经可以在初始差频信号中提取到有用信号，因此通过次数阈值对自相关处理的处理次数进行限制，可以保证对有用信号的差频频率的提取效率。
S404，当所述第三自相关函数指示的第二信噪比大于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号；
具体的，在所述第二信噪比大于所述信噪阈值，且所述处理次数小于次数阈值时，所述信号噪声滤除装置可以将所述第三自相关函数确定为所述初始差频信号对应的有用信号，即所述信号噪声滤除装置可以将最后一次得到的R x确定为所述初始差频信号对应的有用信号。
S405，当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数等于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号；
具体的，在所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数等于次数阈值时，所述信号噪声滤除装置可以将所述第三自相关函数确定为所述初始差频信号对应的有用信号，即所述信号噪声滤除装置可以将最后一次得到的R x确定为所述初始差频信号对应的有用信号。
在本申请实施例中，步骤S404和步骤S405分别表示当满足两个收敛条件中的任一收敛条件时，就可以将最后一次得到的R x确定为所述初始差频信号对应的有用信号；当然本申请实施例还存在当所述第三自相关函数指示的第二信噪比大于信噪阈值，且所述处理次数等于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号。
S406，将所述有用信号确定为去噪后的时域差频信号；
具体的，所述信号噪声滤除装置可以将所述有用信号确定为去噪后的时域差频信号，可以理解的是，对于有用信号较为微弱的初始差频信号，在进行目标信噪比的检测的同时，还可以对自相关处理的处理次数进行检测，以在目标信噪比仍无法满足一定的需求的情况下，将处理次数限定在一定的范围(例如等于次数阈值)，以保证有用信号的差频频率提取的处理效率。
需要说明的是，所述时域差频信号和所述初始差频信号均可以表示为时域上的差频信号，初始差频信号为去噪前的时域上的差频信号，时域差频信号为去噪后的时域上的差频信号。
S407，对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值；
具体的，所述信号噪声滤除装置可以对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值，所述傅里叶变换处理可选为快速傅里叶变换处理，所述频域差频信号具体可以表示为去噪后的频域上的差频信号，所述信号噪声滤除装置可以在频域差频信号所形成的频谱图中获取最大幅值的位置，并将该位置对应的频率值确定为有用信号的差频频率值，有用信号具体表示为发射信 号经探测目标返回的真实有效的差频信号。
在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行至少一次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过至少一次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱的有用信号，进而提高了有效的差频频率提取的成功率；通过进行目标信噪比的检测，保证了目标信噪比满足一定的需求，以便于后续对有用信号的差频频率进行提取；通过对自相关处理的处理次数进行限制，可以在提升初始差频信号中有用信号的提取成功率的基础上，提升对有用信号的差频频率的提取效率。
请参见图6，为本申请实施例提供了对信号作傅里叶变换后的频谱举例示意图。图6示出了三种信号的频谱图，三种信号分别是原始纯净信号(即原始纯净差频信号)、初始差频信号经过快速傅里叶变换(Fast Fourier Transform，FFT)处理后得到的信号以及初始差频信号经过自相关处理以及FFT处理后的得到的信号。
由图6可知，原始纯净信号作为标准的信号，其有用信号的差频频率为(4×10 8)Hz；而仅通过FFT处理得到的信号，其最大幅值对应的差频频率位于图6的“黑色箭头”处，显然，仅通过FFT处理并无法有效的对有用信号的差频频率进行准确获取；对于经过自相关处理以及FFT处理后的得到的信号，其差频频率与原始传经信号一致。因此，通过对初始差频信号进行自相关处理，可以有效的滤除初始差频信号中的噪声信号，进而提高了有效的差频频率提取的成功率。
请参见图7，为本申请实施例提供了信号在不同信噪比下提取有用信号的成功率的举例示意图。如图7所示，实线表示在仅经过FFT处理的初始差频信号中，提取探测目标的差频频率的探测成功率；虚线表示在经过自相关处理和FFT处理的初始差频信号中，提取探测目标的差频频率的探测成功率。
对于不同信噪比中各信噪比下的1000次处理的场景中，显然，初始差频信号在经过自相关处理后，在不同信噪比下都可以更有效的对噪声信号进行滤除，从而得到探测目标的有用信号，并可以获取有用信号的差频频率。
请参见图8，为本申请实施例提供了在不同探测距离和不同信噪比下提取有用信号的成功次数的举例示意图。如图8所示，实线表示在仅经过FFT处理的初始差频信号中，提取探测目标的差频频率的探测成功率；虚线表示在经过自相关处理和FFT处理的初始差频信号中，提取探测目标的差频频率的探测成功率。
对于不同探测目标的目标距离以及不同信噪比的1000次处理的场景中，初始差频信号在经过自相关处理后，在不同信噪比下都可以更有效的对噪声信号进行滤除，从而得到探测目标的有用信号，并可以获取有用信号的差频频率，且不受探测目标的目标距离的影响。
基于图1的系统架构，下面将结合附图9-附图13，对本申请实施例提供的信号噪声滤 除装置进行详细介绍。需要说明的是，附图9-附图13中的信号噪声滤除装置，用于执行本申请图2-图8所示实施例的方法，为了便于说明，仅示出了与本申请实施例相关的部分，具体技术细节未揭示的，请参照本申请图2-图8所示的实施例。
请参见图9，为本申请实施例提供了一种信号噪声滤除装置的结构示意图。如图9所示，本申请实施例的所述信号噪声滤除装置1可以包括：初始信号获取单元11、信号处理单元12和去噪信号确定单元13。
初始信号获取单元11，用于获取激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号；
信号处理单元12，用于对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号；
去噪信号确定单元13，用于将所述有用信号确定为去噪后的时域差频信号。
在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行至少一次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过至少一次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱的有用信号，进而提高了有效的差频频率提取的成功率。
请参见图10，为本申请实施例提供了一种信号噪声滤除装置的结构示意图。如图10所示，本申请实施例的所述信号噪声滤除装置1可以包括：初始信号获取单元11、信号处理单元12、去噪信号确定单元13和差频频率获取单元14。
初始信号获取单元11，用于获取激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号；
信号处理单元12，用于对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号；
具体的，在本申请的第一种可行的实施方式中，请一并参见图11，为本申请实施例提供了一种信号处理单元的结构示意图。如图11所示，所述信号处理单元12可以包括：
第一信号处理子单元121，用于对所述初始差频信号进行自相关处理，得到所述初始差频信号的第一自相关函数；
函数处理子单元122，用于对所述第一自相关函数进行自相关处理，得到所述初始差频信号对应的有用信号。
在本申请的第二种可行的实施方式中，请一并参见图12，为本申请实施例提供了一种信号处理单元的结构示意图。如图12所示，所述信号处理单元12可以包括：
第二信号处理子单元123，用于对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数；
第一通知子单元124，用于当所述第二自相关函数指示的第一信噪比小于或等于信噪阈值时，将所述第二自相关函数确定为所述初始差频信号，通知第二信号处理子单元123执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数，直至所述第一信噪比大于所述信噪阈值，将所述第二自相关函数确定为所述初始差频信号对 应的有用信号。
在本申请的第三种可行的实施方式中，请一并参见图13，为本申请实施例提供了一种信号处理单元的结构示意图。如图13所示，所述信号处理单元12可以包括：
第三信号处理子单元125，用于对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数；
第二通知子单元126，用于当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号，通知第三信号处理子单元125执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数；
信号确定子单元127，用于当所述第三自相关函数指示的第二信噪比大于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号；
所述信号确定子单元127，还用于当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数等于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号。
去噪信号确定单元13，用于将所述有用信号确定为去噪后的时域差频信号；
具体实现中，所述去噪信号确定单元13具体用于当所述有用信号指示的目标信噪比大于信噪阈值时，将所述有用信号确定为去噪后的时域差频信号。
差频频率获取单元14，用于对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值。
在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行至少一次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过至少一次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱的有用信号，进而提高了有效的差频频率提取的成功率；通过进行目标信噪比的检测，保证了目标信噪比满足一定的需求，以便于后续对有用信号的差频频率进行提取。
本申请实施例还提供了一种计算机存储介质，所述计算机存储介质可以存储有多条程序指令，所述程序指令适于由处理器加载并执行如上述图2-图4所示实施例的方法步骤，具体执行过程可以参见图2-图4所示实施例的具体说明，在此不进行赘述。
请参见图14，为本申请实施例提供了一种激光雷达的结构示意图。如图14所示，所述激光雷达1000可以包括：至少一个处理器1001，例如CPU，至少一个网络接口1004，输入输出接口1003，存储器1005，至少一个通信总线1002。其中，通信总线1002用于实现这些组件之间的连接通信。其中，网络接口1004可选的可以包括标准的有线接口、无线接口(如WI-FI接口)。存储器1005可以是高速RAM存储器，也可以是非不稳定的存储器(non-volatile memory)，例如至少一个磁盘存储器。存储器1005可选的还可以是至少一个位于远离前述处理器1001的存储装置。如图14所示，作为一种计算机存储介质的存 储器1005中可以包括操作系统、网络通信模块、输入输出接口模块以及噪声滤除应用程序。
在图14所示的激光雷达1000中，输入输出接口1003主要用于为用户以及接入设备提供输入的接口，获取用户以及接入设备输入的数据。
在一个实施例中，处理器1001可以用于调用存储器1005中存储的噪声滤除应用程序，并具体执行以下操作：
获取激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号；
对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号；
将所述有用信号确定为去噪后的时域差频信号。
可选的，所述处理器1001在执行对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号时，具体执行以下操作：
对所述初始差频信号进行自相关处理，得到所述初始差频信号的第一自相关函数；
对所述第一自相关函数进行自相关处理，得到所述初始差频信号对应的有用信号。
可选的，所述处理器1001在执行对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的自相关函数时，具体执行以下操作：
对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数；
当所述第二自相关函数指示的第一信噪比小于或等于信噪阈值时，将所述第二自相关函数确定为所述初始差频信号，并转入执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数的步骤，直至所述第一信噪比大于所述信噪阈值，将所述第二自相关函数确定为所述初始差频信号对应的有用信号。
可选的，所述处理器1001在执行对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号时，具体执行以下操作：
对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数；
当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号，并转入执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数的步骤；
当所述第三自相关函数指示的第二信噪比大于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号；
当所述第三自相关函数指示的第二信噪比小于或等于信噪阈值，且所述处理次数等于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号。
可选的，所述处理器1001在执行将所述有用信号确定为去噪后的时域差频信号时，具体执行以下操作：
当所述有用信号指示的目标信噪比大于信噪阈值时，将所述有用信号确定为去噪后的时域差频信号。
可选的，所述处理器1001还执行以下操作：
对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值。
在本申请实施例中，通过获取激光雷达产生的含有噪声信号的初始差频信号，可以对初始差频信号进行至少一次自相关处理，以得到初始差频信号的有用信号，最终将有用信号确定为去噪后的时域差频信号。通过至少一次自相关处理，可以基于信号相关程度将初始差频信号处理为自相关函数，有效的提高了信号的信噪比，提取到初始差频信号中微弱的有用信号，进而提高了有效的差频频率提取的成功率；通过进行目标信噪比的检测，保证了目标信噪比满足一定的需求，以便于后续对有用信号的差频频率进行提取。
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，所述的程序可存储于一计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实施例的流程。其中，所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory，ROM)或随机存储记忆体(Random Access Memory，RAM)等。
以上所揭露的仅为本申请较佳实施例而已，当然不能以此来限定本申请之权利范围，因此依本申请权利要求所作的等同变化，仍属本申请所涵盖的范围。

Claims (10)

  1. 一种信号噪声滤除方法，其特征在于，包括：
    获取激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号；
    对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号；
    将所述有用信号确定为去噪后的时域差频信号。
  2. 根据权利要求1所述的方法，其特征在于，所述对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号，包括：
    对所述初始差频信号进行自相关处理，得到所述初始差频信号的第一自相关函数；
    对所述第一自相关函数进行自相关处理，得到所述初始差频信号对应的有用信号。
  3. 根据权利要求1所述的方法，其特征在于，所述对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号，包括：
    对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数；
    当所述第二自相关函数指示的第一信噪比小于或等于信噪阈值时，将所述第二自相关函数确定为所述初始差频信号，并转入执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第二自相关函数的步骤，直至所述第一信噪比大于所述信噪阈值，将所述第二自相关函数确定为所述初始差频信号对应的有用信号。
  4. 根据权利要求1所述的方法，其特征在于，所述对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号，包括：
    对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数；
    当所述第三自相关函数指示的第一信噪比小于或等于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号，并转入执行对所述初始差频信号进行自相关处理，得到所述初始差频信号的第三自相关函数，更新所述自相关处理的处理次数的步骤；
    当所述第三自相关函数指示的第一信噪比大于信噪阈值，且所述处理次数小于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号；
    当所述第三自相关函数指示的第一信噪比小于或等于信噪阈值，且所述处理次数等于次数阈值时，将所述第三自相关函数确定为所述初始差频信号对应的有用信号。
  5. 根据权利要求1或3所述的方法，其特征在于，所述将所述有用信号确定为去噪后的时域差频信号，包括：
    当所述有用信号指示的目标信噪比大于信噪阈值时，将所述有用信号确定为去噪后的时域差频信号。
  6. 根据权利要求1所述的方法，其特征在于，还包括：
    对所述时域差频信号进行傅里叶变换处理，得到频域差频信号，在所述频域差频信号中获取最大幅值对应的差频频率值。
  7. 一种信号噪声滤除装置，其特征在于，包括：
    初始信号获取单元，用于获取激光雷达产生的初始差频信号，所述初始差频信号为含有噪声信号的差频信号；
    信号处理单元，用于对所述初始差频信号进行至少一次自相关处理，得到所述初始差频信号的有用信号；
    去噪信号确定单元，用于将所述有用信号确定为去噪后的时域差频信号。
  8. 根据权利要求6所述的装置，其特征在于，所述信号处理单元包括：
    第一信号处理子单元，用于对所述初始差频信号进行自相关处理，得到所述初始差频信号的第一自相关函数；
    函数处理子单元，用于对所述第一自相关函数进行自相关处理，得到所述初始差频信号对应的有用信号。
  9. 一种激光雷达，其特征在于，包括处理器、存储器、输入输出接口；
    所述处理器分别与所述存储器和所述输入输出接口相连，其中，所述输入输出接口用于页面交互，所述存储器用于存储程序代码，所述处理器用于调用所述程序代码，以执行如权利要求1-6任一项所述的方法。
  10. 一种计算机存储介质，其特征在于，所述计算机存储介质存储有计算机程序，所述计算机程序包括程序指令，所述程序指令当被处理器执行时，执行如权利要求1-6任一项所述的方法。
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