Anti-vibration detection method and device, storage medium

Abstract

The application provides an anti-vibration detection method and device and a storage medium. The anti-vibration detection method comprises the following steps: S1, acquiring a vibration period of a radar sensor in a vibration environment; S2, taking n times or 1 / n times of the vibration period as a slow-time-dimension detection interval, wherein n is a positive integer; S3, acquiring sampling data of a radar sensor on a return signal based on the slow-time-dimension detection interval; and S4, performing target detection according to the sampling data. Based on this, the application can be considered as using an adaptive slow-time-dimension detection interval to sample a return signal, so that zero-speed clutter energy caused by base vibration can be avoided to leak to a non-zero-speed area, so as to improve the suppression effect of the radar sensor on static clutter in the vibration environment, and ensure the accuracy of the detection result of at least a moving target.

Description

Technical Field

[0001] This application relates to the field of radar sensor tracking technology and the field of target detection technology using radio waves, specifically to a vibration-resistant detection method and device, and a storage medium. Background Technology

[0002] With the development of intelligent technologies, radar sensors, represented by millimeter-wave radar, have been widely used in target detection in smart homes, smart healthcare, and smart cities. In these scenarios, radar sensors are primarily used to detect moving targets entering their detection range. For example, in a home lighting system, once a radar sensor detects someone entering its detection range, it can turn on the lighting equipment. Predictably, in these scenarios, it is necessary to exclude static objects relative to the radar sensor within the detection range. Currently, when detecting moving targets, radar sensors typically rely on static clutter suppression modules to suppress zero-velocity clutter reflected from static objects, thereby preventing zero-velocity clutter from entering the detection module and forming false targets. False targets refer to static objects being incorrectly identified as moving targets. However, if the base on which the radar sensor is installed has vibrating components or is in contact with vibrating components, such as the base vibrating due to the vibration of an air conditioner, the radar sensor will also vibrate. At this time, there will be relative motion between the radar sensor and the static objects in its environment. The original zero-velocity clutter energy will leak into the non-zero-velocity region, thus forming energy leakage in the velocity dimension. This energy leakage will bypass the static clutter suppression module and reach the detection module, ultimately forming false targets and deteriorating the detection effect of the radar sensor. Summary of the Invention

[0003] In view of this, this application provides a vibration-resistant detection method, device, and storage medium, which can at least improve the problem of poor suppression of static clutter by radar sensors in vibration environments.

[0004] This application provides a vibration detection method, including:

[0005] S1. Obtain the vibration period of the radar sensor in a vibration environment;

[0006] S2. Use n times or 1 / n times the vibration period as the slow time dimension detection interval, where n is a positive integer;

[0007] S3. Based on the slow time-dimensional detection interval, obtain the sampling data of the radar sensor on the echo signal;

[0008] S4. Perform target detection based on the sampled data.

[0009] Optionally, obtaining the vibration period of the radar sensor in a vibration environment includes:

[0010] Identifying false target point clouds from range Doppler point clouds detected by radar sensors;

[0011] The Doppler frequencies of all the false target point clouds are combined to obtain the vibrational Doppler frequencies;

[0012] The reciprocal of the vibration Doppler frequency is calculated according to the reciprocal relationship T * ƒ = 1 and used as the vibration period; where T is the vibration period and ƒ is the vibration Doppler frequency.

[0013] Optionally, identifying the false target point cloud from the range Doppler point cloud detected by the radar sensor includes:

[0014] Two point clouds in the Doppler point cloud that are equidistant from the radar sensor and have Doppler frequencies that are one positive and one negative with equal absolute values ​​are identified as false target point clouds.

[0015] Optionally, the step of merging the Doppler frequencies of all false target point clouds to obtain the vibrational Doppler frequencies includes the following:

[0016] The average value of the Doppler frequencies of all false target point clouds is obtained as the vibrational Doppler frequency;

[0017] The vibrational Doppler frequencies are obtained by maximizing the ratio of the Doppler frequencies of all false target point clouds.

[0018] The Doppler frequencies of all false target point clouds are filtered according to preset conditions, and the filtering results are merged to obtain the vibration Doppler frequencies.

[0019] Optionally, the slow time dimension detection interval remains unchanged within the same frame of the radar sensor.

[0020] Optionally, the method further includes: within the first frame after the radar sensor is first activated, the radar sensor uses a preset value as a slow time dimension detection interval and acquires sampling data of the echo signal;

[0021] For each subsequent frame, S1 to S2 are executed to obtain the corresponding slow time dimension detection interval, and S1 to S3 are executed on the current frame based on the slow time dimension detection interval obtained in the previous frame.

[0022] In other words, the echo signal is sampled using the slow-time dimension detection interval obtained in the first frame to generate a range Doppler point cloud. Based on the range Doppler point cloud generated in the first frame, the vibration period corresponding to the second frame is obtained. Then, according to S1 to S2, the slow-time dimension detection interval corresponding to the second frame is obtained; and so on, the slow-time dimension detection interval corresponding to each subsequent frame is obtained. This allows for optimal matching of the base with vibration frequency varying over time, ensuring the accuracy of the target detection results.

[0023] Optionally, the preset value is the slow time dimension detection interval of the frame corresponding to the most recent target detection.

[0024] Optionally, when the slow time dimension detection interval is 1 / n times the vibration period, step S3 includes:

[0025] Based on the slow time-dimensional detection interval, the radar sensor acquires the echo signal of each frame;

[0026] The echo signal of each frame is sampled according to the vibration period to obtain n signal subsequences;

[0027] The average value of the n signal subsequences is used as the zero-velocity clutter estimator;

[0028] Subtract the corresponding zero-velocity clutter estimate from the echo signal of each frame to obtain the non-zero-velocity clutter, thereby obtaining the sampling data of the echo signal of each frame.

[0029] This application provides a vibration detection device, including a processor and a memory. The memory stores a vibration detection program, and when the vibration detection program is executed by the processor, it implements the steps of the vibration detection method as described in any of the preceding claims.

[0030] This application provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of the vibration detection method as described in any of the preceding claims.

[0031] As described above, when the radar sensor is in a vibrating environment, this application uses n times or 1 / n times the vibration period as the slow time dimension detection interval. Since the vibration mode of the radar sensor caused by its base is usually reciprocating motion, that is, moving from the first position to the second position according to the forward vibration mode, and then returning to the first position according to the backward vibration mode and continuing to cycle, setting the slow time dimension detection interval exactly to n times or 1 / n times the vibration period means that the position of the base is the same each time the radar sensor samples, so that the base vibration image just disappears, thereby concentrating the energy caused by the base vibration to zero-velocity clutter, thereby improving the radar sensor's suppression effect on static clutter in a vibrating environment and ensuring the accuracy of at least the detection results of moving targets.

[0032] In addition, the vibration period changes accordingly when the radar sensor performs echo sampling for each frame, so that the corresponding slow time dimension detection interval also changes accordingly. This can be regarded as using an adaptive slow time dimension detection interval for echo sampling, which can adaptively ensure the suppression effect of static clutter within each frame, and further ensure the accuracy of the detection results for at least moving targets. Attached Figure Description

[0033] Figure 1 This is a schematic flowchart of a vibration detection method provided in an embodiment of this application;

[0034] Figure 2 This is a schematic diagram of a process for obtaining the vibration period of a radar sensor according to an embodiment of this application;

[0035] Figure 3 This is a schematic diagram of a process for obtaining non-zero velocity clutter provided in an embodiment of this application;

[0036] Figure 4 This is a structural schematic diagram of an anti-vibration detection device provided in an embodiment of this application. Detailed Implementation

[0037] During radar sensor detection, the echo signals from static objects such as walls, ceilings, and tables do not change over time. This means that the echo signals from static objects remain constant in the radar sensor's received signals at different times; such echo signals are called zero-velocity clutter. The principle of static clutter suppression is to subtract the zero-velocity clutter estimate from the echo signal to obtain non-zero-velocity clutter. This allows for the extraction of point cloud signals, such as moving targets (range Doppler point clouds), from the non-zero-velocity clutter, which can then be fed into application modules such as trajectory tracking and human presence sensing to achieve intelligent services. However, in vibrating environments, radar sensors are subject to vibration. This relative motion between the radar sensor and static objects in its environment leads to poor static clutter suppression, and zero-velocity clutter can form false target point clouds, further deteriorating the radar sensor's detection performance.

[0038] To address the aforementioned problems in the prior art, this application provides a vibration detection method, device, and storage medium. These protected subjects are based on the same concept, and their problem-solving principles are essentially the same or similar. The implementation methods of each protected subject can be referred to mutually, and repeated details will not be elaborated upon.

[0039] In the scheme of this application, n times or 1 / n times the vibration period of the radar sensor (also known as "radar" in the art) is used as the slow time dimension detection interval of the radar sensor. Since the vibration mode of the radar sensor caused by its base is usually reciprocating motion, that is, moving from the first position to the second position according to the forward vibration mode, and then returning to the first position according to the backward vibration mode and continuing to cycle, setting the slow time dimension detection interval exactly to n times or 1 / n times the vibration period means that the position of the base is the same each time the radar sensor samples, so that the base vibration image just disappears. In this way, the energy caused by the base vibration is concentrated to zero-velocity clutter, improving the suppression effect of the radar sensor on static clutter in the vibration environment, and ensuring the accuracy of the detection results of at least moving targets.

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly described below in conjunction with specific embodiments and corresponding drawings. Obviously, the embodiments described below are only a part of the embodiments of this application, and not all of them. Unless otherwise specified, the following embodiments and their technical features can be combined with each other, and also belong to the technical solutions of this application.

[0041] Figure 1 This is a schematic flowchart of a vibration-resistant detection method provided in an embodiment of this application. This vibration-resistant detection method can also be called a "method," and is at least used to control a radar sensor to detect moving targets while excluding stationary targets in a vibration environment. The executing entity for each step can be an adapted vibration-resistant detection device, or a storage medium, processor, controller, etc., with vibration-resistant detection functionality.

[0042] like Figure 1 As shown, the method includes at least the following steps S1 to S4.

[0043] S1. Obtain the vibration period of the radar sensor in a vibration environment.

[0044] The radar sensor includes, but is not limited to, an FMCW (Frequency Modulated Continuous Wave) millimeter-wave radar sensor. The vibration environment includes, but is not limited to, a situation where the radar sensor is mounted on a base (also known as a "radar sensor base"), and this base is vibrated by other vibrating components in the environment, thereby causing the radar sensor to vibrate. For example, the radar sensor is installed in household appliances such as air conditioners and fans; once these appliances vibrate, the radar sensor is placed in a vibration environment.

[0045] In one example, combining Figure 2 As shown, the method of obtaining the vibration period of the radar sensor may include steps S11 to S13.

[0046] S11. Identify false target point clouds from the range Doppler point clouds detected by radar sensors.

[0047] A radar sensor emits chirp signals at a preset frame rate to detect the surrounding environment and receives the echo signal of each chirp signal, thus forming a dense three-dimensional spatial discrete point, or point cloud signal. Then, using the Doppler relation and the sampled data of the echo signals, the Doppler frequencies of these three-dimensional spatial discrete points are calculated, thus forming the range-Doppler point cloud. The range-Doppler point cloud at least contains the distance information between these discrete points and the radar sensor.

[0048] Because the radar sensor operates in a vibrating environment, the echo signals reflected back from static objects in this environment exhibit time-division variables. These time-division variables are identified and incorporated into the calculations to generate corresponding point cloud signals, thus forming false target point clouds. These false target point clouds, mixed with the point cloud signals of real objects such as moving targets, cause interference and degrade the detection effect. Therefore, it is necessary to identify false target point clouds from the range-Doppler point clouds detected by the radar sensor. In one example, this application can identify two point clouds in the range-Doppler point cloud that are equidistant from the radar sensor and have Doppler frequencies that are one positive and one negative with equal absolute values ​​as false target point clouds. Since the vibration caused by the base is a reciprocating motion, the energy leakage caused by this vibration is generally symmetrically distributed along the Doppler frequency dimension. Therefore, it is reasonable and easy to operate to regard paired point clouds with equidistant distances and symmetrically distributed Doppler frequencies in the range-Doppler point cloud as false target point clouds.

[0049] S12. Combine the Doppler frequencies of all false target point clouds to obtain the vibration Doppler frequencies.

[0050] Merging the Doppler frequencies of all false target point clouds can be considered as obtaining the Doppler frequency information of all false target point clouds. According to the principle of relativity of vibration, for radar sensors, it is the current environment that is vibrating, that is, all static objects in the environment are vibrating. Therefore, merging the false target point clouds caused by all static objects can improve the estimation accuracy of the vibration period and suppress the influence of misjudgment during the identification of false target point clouds.

[0051] In one example, the vibrational Doppler frequency can be obtained by any of the following merging methods.

[0052] Merging Method 1: Obtain the average Doppler frequencies of all false target point clouds as the vibrational Doppler frequencies. For example, if the number of identified false target point clouds is N, the corresponding Doppler frequencies are F1, F2, ... F... NThen the average value (F1+F2+...+F) N ) / N, which is the vibration Doppler frequency.

[0053] Method 2: Perform Maximum Ratio Combining (MRC) on the Doppler frequencies of all false target point clouds to obtain the vibrational Doppler frequencies. MRC refers to weighted combining of the Doppler frequencies of each false target point cloud. The weight of each Doppler frequency is proportional to its corresponding signal-to-noise ratio (SNR), thereby maximizing the combined Doppler frequency. For example, the following MRC formula can be used to obtain the vibrational Doppler frequencies.

[0054]

[0055]

[0056] in, The vibration Doppler frequency obtained by maximizing the ratio combination. The number of the fake target point cloud, Let i be the weight corresponding to the i-th false target point cloud. For the i-th pseudo-target point cloud, Let be the fading coefficient corresponding to the i-th false target point cloud. Let be the noise variance corresponding to the i-th false target point cloud.

[0057] Merging Method 3: The Doppler frequencies of all false target point clouds are filtered according to preset conditions, and the filtering results are merged to obtain the vibrational Doppler frequency. This method is essentially selection merging (SC) of the Doppler frequencies of all false target point clouds. The preset conditions are to select the false target point cloud with the highest signal-to-noise ratio or signal power, and then use its corresponding Doppler frequency as the vibrational Doppler frequency.

[0058] S13. Calculate the reciprocal of the vibration Doppler frequency according to the reciprocal relationship T * ƒ = 1, and use it as the vibration period; where T is the vibration period and ƒ is the vibration Doppler frequency.

[0059] In other words, the reciprocal of the vibration Doppler frequency, 1 / ƒ, is taken as the vibration period of the radar sensor.

[0060] S2. Use n times or 1 / n times the vibration period as the slow time dimension detection interval, where n is a positive integer.

[0061] S3. Based on the slow time dimension detection interval, obtain the sampling data of the radar sensor on the echo signal.

[0062] S4. Perform target detection based on the sampled data.

[0063] The so-called slow-time dimension detection interval refers to the period of slow-time dimension detection, that is, the time interval between two adjacent environmental detections or two adjacent echo signals. By performing slow-time dimension calculations on the sampled data obtained based on the slow-time dimension detection interval, the velocity information of the moving target can be obtained, thus at least completing the detection of the moving target. In one example, the slow-time dimension calculation is a slow-time dimension Fast Fourier Transform. Performing a Fast Fourier Transform on range gate signals with the same number in a segment yields the frequency domain representation of that segment, i.e., the velocity spectrum. Analyzing the velocity spectrum then determines whether a target has been detected. In other words, the slow-time dimension calculation is performing a Fast Fourier Transform on range gates with the same number in the range spectrum in the slow-time dimension.

[0064] Within the same frame of a radar sensor, the slow-time dimension detection interval remains constant. However, the slow-time dimension detection interval of the radar sensor in each frame is determined by the vibration period within that frame. In other words, the slow-time dimension detection interval of the radar sensor in each frame may not have a necessary correlation, which means that the slow-time dimension detection intervals in any two frames may be the same or different.

[0065] In other examples of this application, the slow-time dimension detection intervals of the radar sensor within each frame can be correlated. For example, for two adjacent frames, they are referred to as the "previous frame" and the "current frame" according to their temporal order, respectively. The current frame can also be referred to as the "next frame." The radar sensor can obtain the slow-time dimension detection interval of the next frame based on the slow-time dimension detection interval of the previous frame. Accordingly, the method can be implemented as follows:

[0066] In the first frame after the radar sensor is first activated, the radar sensor uses a preset value as the slow time dimension detection interval to perform environmental detection, thereby generating a range Doppler point cloud. In one example, the preset value is the slow time dimension detection interval of the frame corresponding to the most recent target detection. Then, false target point clouds are identified from the range Doppler point cloud generated from the first frame, and the Doppler frequencies of all false target point clouds are merged to obtain the vibration Doppler frequency. Then, the reciprocal of the vibration Doppler frequency is calculated according to the aforementioned reciprocal relationship to serve as the vibration period of the radar sensor in the first frame.

[0067] For each subsequent frame, steps S1 to S2 are executed to obtain the corresponding slow-time dimension detection interval, and steps S1 to S3 are executed on the current frame based on the slow-time dimension detection interval obtained in the previous frame. That is, the echo signal is sampled using the slow-time dimension detection interval obtained in the first frame to generate a range Doppler point cloud, and the vibration period corresponding to the second frame is obtained based on the range Doppler point cloud generated in the first frame. Then, the slow-time dimension detection interval corresponding to the second frame is obtained according to steps S1 to S2; and so on, to obtain the slow-time dimension detection interval corresponding to each subsequent frame. This allows for optimal matching of the base with vibration frequencies varying over time, ensuring the accuracy of the target detection results.

[0068] For example, for the second frame, the vibration period determined in the first frame is used as the vibration period of the radar sensor in the second frame, that is, the vibration frequency in the first frame is used as the vibration frequency of the radar sensor in the second frame. The slow-time dimension detection interval of the radar sensor in the second frame is obtained through the aforementioned step S2. Then, sampling in the second frame is completed based on the aforementioned step S3. In the third frame, the radar sensor detects the range Doppler point cloud based on the slow-time dimension detection interval of the second frame, identifies false target point clouds from it, and merges the Doppler frequencies of all false target point clouds to obtain the vibration Doppler frequency. The reciprocal of the vibration Doppler frequency is calculated according to the reciprocal relationship and used as the vibration period of the radar sensor in the third frame. Then... The aforementioned step S2 is executed to obtain the slow-time dimension detection interval of the radar sensor in the third frame. Then, based on the aforementioned step S3, sampling in the third frame is completed. In the fourth frame, the radar sensor detects the range Doppler point cloud based on the slow-time dimension detection interval of the third frame, identifies false target point clouds from it, and merges the Doppler frequencies of all false target point clouds to obtain the vibration Doppler frequency. The reciprocal of the vibration Doppler frequency is calculated according to the reciprocal relationship and used as the vibration period of the radar sensor in the fourth frame. Then, the aforementioned step S2 is executed to obtain the slow-time dimension detection interval of the radar sensor in the fourth frame. Then, based on the aforementioned step S3, sampling in the fourth frame is completed. This process is repeated until sampling of all frames is completed.

[0069] Based on the above, this application embodiment uses n times or 1 / n times the vibration period as the slow time dimension detection interval. Since the vibration mode of the radar sensor caused by its base is usually reciprocating motion, that is, moving from the first position to the second position according to the forward vibration mode, and then returning to the first position according to the backward vibration mode and continuing to cycle, setting the slow time dimension detection interval exactly to n times or 1 / n times the vibration period means that the position of the base is the same each time the radar sensor samples, so that the base vibration image just disappears, thereby concentrating the energy caused by the base vibration to zero-velocity clutter, thereby improving the suppression effect of the radar sensor on static clutter in the vibration environment and ensuring the accuracy of the detection results for at least moving targets.

[0070] In addition, the vibration period changes accordingly when the radar sensor performs echo sampling for each frame, which also changes the corresponding slow time dimension detection interval. This can be regarded as using an adaptive slow time dimension detection interval for echo sampling, which can adaptively ensure the suppression effect of static clutter within each frame and further ensure the accuracy of the detection results of moving targets.

[0071] When the slow-time dimension detection interval is 1 / n times the vibration period, the slow-time dimension detection interval is shorter than the vibration period, resulting in a large number of received echo signals. To ensure that each echo signal can be suppressed by static clutter, this application can set a zero-velocity clutter estimate for all echo signals. In one example, combined with... Figure 3 As shown, step S3 may include the following steps S31 to S34.

[0072] S31. Based on the slow time-dimensional detection interval, the radar sensor acquires the echo signal of each frame;

[0073] S32. Sample the echo signal of each frame according to the vibration period to obtain n signal subsequences;

[0074] S33. Use the average value of the n signal sub-sequences as the zero-velocity clutter estimator;

[0075] S34. Subtract the corresponding zero-velocity clutter estimate from the echo signal of each frame to obtain the non-zero-velocity clutter, thereby obtaining the sampling data of the echo signal of each frame.

[0076] For example, sampling the echo signal of a certain frame yields n signal subsequences with intervals equal to the vibration period: [1,n+1,2*n+1…], [2,n+2,2*n+2…], …, [n,2*n,3*n…]. The average value of each signal subsequence is used as the zero-velocity clutter estimate for all echo signals belonging to this frame. This means that all echo signals in this frame have corresponding zero-velocity clutter estimates. Finally, by subtracting the corresponding zero-velocity clutter estimates from all echo signals, the echoes of static objects can be removed. This can further avoid interference caused by false target point clouds and further improve the detection effect of radar sensors.

[0077] This application embodiment also provides a storage medium storing a vibration detection program, which is essentially a computer program, and when executed by a processor, the vibration detection program implements the steps of the vibration detection method as in any example.

[0078] The storage medium includes, but is not limited to, any one of read-only memory (ROM), random access memory (RAM), magnetic disk, and optical disk.

[0079] Since the vibration detection program stored in the storage medium can execute the steps in the vibration detection method of any embodiment provided in this application, it can achieve the beneficial effects that the vibration detection method of any of the foregoing embodiments can achieve, as detailed in the foregoing embodiments, which will not be repeated here.

[0080] This application also provides a vibration detection device or chip, including a memory and a processor. The memory stores a vibration detection program, which, when executed by the processor, implements the steps of the vibration detection method of any of the foregoing embodiments. And / or, the vibration detection device or chip is provided with a storage medium as shown in the above example, and the processor loads the storage medium to execute the steps of the vibration detection method, thereby achieving the beneficial effects that the vibration detection method of the corresponding embodiment can achieve.

[0081] Figure 4 This is a structural schematic diagram of a vibration detection device provided in an embodiment of this application. Figure 4 As shown, the vibration detection device 40 includes:

[0082] The acquisition module 41 is used to acquire the vibration period of the radar sensor in a vibration environment;

[0083] The sampling module 42 is used to take n times or 1 / n times the vibration period as a slow time dimension detection interval, and to acquire the sampling data of the radar sensor on the echo signal based on the slow time dimension detection interval.

[0084] Processing module 43 is used to perform target detection based on the sampled data.

[0085] It should be understood that the various modules of the vibration detection device 40 described above can be represented as physical devices or virtual modules (i.e., commonly referred to as logical modules) in actual scenarios. A single module can be implemented by a single physical device or by two or more physical devices working together. Similarly, the function performed by a single module can be implemented by a single physical device or by two or more physical devices working together. Furthermore, the functions corresponding to each module can be implemented by the corresponding steps of the vibration detection method in any of the foregoing embodiments.

[0086] The above are only some embodiments of this application and do not limit the patent scope of this application. For those skilled in the art, any equivalent structural transformations made using the content of this specification and drawings are similarly included within the patent protection scope of this application.

[0087] The use of step designations such as S1 and S2 in this document is intended to more clearly and concisely describe the corresponding content and does not constitute a substantial restriction on the order. In specific implementation, those skilled in the art may execute S2 first and then S1, etc., but these should all be within the protection scope of this application.

[0088] Although this document uses terms such as "first," "second," etc., to describe various types of information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. Furthermore, the singular forms "a," "an," and "the" are intended to also include the plural forms. The terms "or" and "and / or" are interpreted as inclusive, or meaning either one or any combination thereof. Exceptions to this definition only arise when combinations of elements, functions, steps, or operations are inherently mutually exclusive in some way.

Claims

1. A vibration detection method, characterized in that, include: S1. Obtain the vibration period of the radar sensor in a vibration environment, including: From the range Doppler point cloud obtained by the radar sensor, identify two point clouds that are equidistant from the radar sensor, have Doppler frequencies that are one positive and one negative and have equal absolute values, and use them as false target point clouds. The Doppler frequencies of all the false target point clouds are combined to obtain the vibrational Doppler frequencies; The reciprocal of the vibration Doppler frequency is calculated according to the reciprocal relationship T * ƒ = 1 and used as the vibration period; where T is the vibration period and ƒ is the vibration Doppler frequency. S2. Use n times or 1 / n times the vibration period as the slow time dimension detection interval, where n is a positive integer; S3. Based on the slow time-dimensional detection interval, obtain the sampling data of the radar sensor on the echo signal; S4. Perform target detection based on the sampled data.

2. The vibration detection method according to claim 1, characterized in that, The step of merging the Doppler frequencies of all false target point clouds to obtain the vibrational Doppler frequencies includes the following: The average value of the Doppler frequencies of all false target point clouds is obtained as the vibrational Doppler frequency; The vibrational Doppler frequencies are obtained by maximizing the ratio of the Doppler frequencies of all false target point clouds. The Doppler frequencies of all false target point clouds are filtered according to preset conditions, and the filtering results are merged to obtain the vibration Doppler frequencies.

3. The vibration detection method according to claim 1, characterized in that, Within the same frame of the radar sensor, the slow time dimension detection interval remains unchanged.

4. The vibration detection method according to claim 3, characterized in that, The method further includes: in the first frame after the radar sensor is first activated, the radar sensor uses a preset value as a slow time dimension detection interval and acquires sampling data of the echo signal; For each subsequent frame, S1 to S2 are executed to obtain the corresponding slow time dimension detection interval, and S1 to S3 are executed on the current frame based on the slow time dimension detection interval obtained in the previous frame.

5. The vibration detection method according to claim 4, characterized in that, The preset value is the slow time dimension detection interval of the frame corresponding to the most recent target detection.

6. The vibration detection method according to claim 1, characterized in that, When the slow-time dimension detection interval is 1 / n times the vibration period, S3 includes: Based on the slow time-dimensional detection interval, the radar sensor acquires the echo signal of each frame; The echo signal of each frame is sampled according to the vibration period to obtain n signal subsequences; The average value of the n signal subsequences is used as the zero-velocity clutter estimator; Subtract the corresponding zero-velocity clutter estimate from the echo signal of each frame to obtain the non-zero-velocity clutter, thereby obtaining the sampling data of the echo signal of each frame.

7. A vibration detection device, characterized in that, It includes a processor and a memory, wherein the memory stores an anti-vibration detection program, and when the anti-vibration detection program is executed by the processor, it implements the steps of the anti-vibration detection method as described in any one of claims 1 to 6.

8. A storage medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the steps of the vibration detection method as described in any one of claims 1 to 6.

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