Multi-path effect suppression method and system based on W-band radar and storage medium
By sampling and Fourier transforming the echo pulse signal of W-band radar, combining Doppler feature analysis and correlation calculation, multipath targets are identified and eliminated, and the problem of radar detection accuracy decreases in complex environments is solved. Achieve higher detection accuracy and system reliability.
Patent Information
- Application Number
- CN202411437333.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-15
- Publication Date
- 2025-02-07
AI Technical Summary
W-band radars in complex environments cause the target detection accuracy to decrease due to the multipath effect. The traditional suppression method increases power consumption, cost, volume and weight, making it difficult to apply in actual engineering.
By obtaining the echo pulse signal reflected by the W-band radar from the target, performing sampling and two-dimensional fast Fourier transformation, generating a data matrix, performing Doppler feature analysis and correlation calculation, identifying and eliminating the multiple generated by the multipath effect Radical goals, retain real goals.
It significantly improves the target detection and recognition capabilities of W-band radar in complex environments, reduces misjudgment and false alarms, and improves the accuracy of target detection and the reliability of radar system.
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Figure CN119395643A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to a method, system and storage medium for suppressing multipath effects based on a W-band radar, and belongs to the technical field of radar signal processing. Background Art
[0002] Band radar has significant advantages in regional tracking and monitoring, including low cost, small size, light weight, and excellent performance in environmental adaptability and target information acquisition, making it expected to become the dominant technology in this field. However, in practical applications, due to strong reflectors in the environment, the signal received by the radar contains multipath signals in addition to the target signal. These multipath signals are similar to the target signal characteristics, and sometimes have a higher signal-to-noise ratio, making it difficult for traditional signal processing algorithms to distinguish, thereby interfering with normal target detection.
[0003] In order to suppress the multipath effect, traditional methods include optimization of antenna and receiver positions, multi-antenna technology, equalizer and frequency modulation spread spectrum technology. However, these methods require updates to software and hardware, which increases the power consumption, cost, volume and weight of W-band radar, which is not conducive to its application in practical engineering. Therefore, a new technology is needed to solve these problems. Summary of the invention
[0004] The purpose of the present invention is to provide a method, system and storage medium for suppressing multipath effects based on W-band radar, which can effectively distinguish and process real targets and multipath targets, thereby improving the target detection accuracy of W-band radar.
[0005] In order to solve the above technical problems, the present invention is implemented by adopting the following technical solutions.
[0006] In a first aspect, the present invention provides a method for suppressing multipath effects based on a W-band radar, comprising: Obtain M echo pulse signals reflected by the W-band radar from the target, and sample N points for each pulse signal to obtain M N sampling data; The sampled data is subjected to a two-dimensional fast Fourier transform to generate M N data matrix; where M represents the Doppler dimension and N represents the distance dimension; Detecting the distance dimension N of the data matrix to determine the distance unit corresponding to each target; Performing Doppler feature analysis on the Doppler dimension M of the data matrix, extracting the Doppler feature vector of each target, and calculating correlation information between different targets using the Doppler feature vector of each target; According to the Doppler feature vectors of the targets and the correlation information between different targets, and in combination with the distance units corresponding to the targets, multipath targets generated by the multipath effect are identified and eliminated, and real targets are retained.
[0007] In combination with the first aspect, further, extracting the Doppler feature vector of each target includes: Selecting the complex Doppler eigenvector of each target from the Doppler dimension M of the data matrix; Performing a modulo operation on the complex Doppler eigenvector to obtain a real Doppler eigenvector; The real number Doppler feature vector is normalized to obtain the normalized Doppler feature vector of each target.
[0008] In combination with the first aspect, further, the expression of the Doppler characteristic vector is: s = (| |,| |,…| |); = ( , ,…, ; Where s represents the set of real-valued Doppler eigenvectors; represents the first complex Doppler eigenvector; represents the second complex Doppler eigenvector; represents the kth complex Doppler eigenvector; represents the set of modular eigenvectors; The Doppler eigenvector representing the first target; represents the Doppler eigenvector of the second target; represents the Doppler feature vector of the kth target.
[0009] In combination with the first aspect, further, the calculating correlation information between different targets includes: Randomly select two target Doppler feature vectors from the Doppler feature vectors of each target, and mark them as a first target Doppler feature vector and a second target Doppler feature vector respectively; The autocorrelation value of the first target Doppler eigenvector, the cross-correlation value of the first target Doppler eigenvector and the second target Doppler eigenvector are calculated respectively.
[0010] In combination with the first aspect, further, the calculation expressions of the autocorrelation value of the first target Doppler feature vector, the first target Doppler feature vector and the cross-correlation value of the second target Doppler feature vector are respectively:
[0011] in, represents the autocorrelation value of the first target Doppler eigenvector; represents the first target Doppler feature vector and the second target Doppler feature vector; M represents the Doppler dimension; m represents the Doppler unit array subscript; k represents the distance unit array subscript; Indicates the array subscript used in the Doppler eigenvector autocorrelation calculation; Indicates the array subscript used in the Doppler eigenvector cross-correlation calculation.
[0012] In combination with the first aspect, further, the identifying and distinguishing the real target from the false target generated by the multipath effect includes: Normalizing the autocorrelation value of the first target Doppler feature vector, the first target Doppler feature vector, and the cross-correlation value of the second target Doppler feature vector, respectively, and calculating the absolute value difference between the normalized autocorrelation value and the cross-correlation value to obtain a similarity difference measurement value; If the similarity difference measure value is less than a preset similarity threshold, the first target Doppler feature vector is similar to the second target Doppler feature vector, and further compares the distances from the first target Doppler feature vector and the second target Doppler feature vector to the W-band radar; If the distance from the first target Doppler feature vector to the W-band radar is greater than the distance from the second mode feature vector to the W-band radar, the first target Doppler feature vector is a multipath target generated by a multipath effect and is removed, and the second target Doppler feature vector is retained; if the distance from the first target Doppler feature vector to the W-band radar is less than the distance from the second mode feature vector to the W-band radar, the second target Doppler feature vector is a multipath target generated by a multipath effect and is removed, and the first target Doppler feature vector is retained; If the similarity difference measure value is greater than a preset dissimilarity threshold, the first target Doppler feature vector is dissimilar to the second target Doppler feature vector, and the first mode feature vector and the second mode feature vector are true targets and are retained.
[0013] In combination with the first aspect, further, the expressions for normalizing the autocorrelation value of the first mode eigenvector and the cross-correlation value between the first mode eigenvector and the second mode eigenvector are respectively:
[0014] in, represents the autocorrelation value of the first mode eigenvector after normalization; Represents the cross-correlation value between the first mode eigenvector and the second mode eigenvector after normalization.
[0015] In combination with the first aspect, further, the expression of the similarity difference measurement value is:
[0016] in, Represents the similarity difference measure.
[0017] In a second aspect, a multipath effect suppression system based on a W-band radar includes: The data sampling module is used to obtain M echo pulse signals reflected by the W-band radar from the target, and sample N points for each pulse signal to obtain M N sampling data; The data conversion module is used to perform a two-dimensional fast Fourier transform on the sampled data to generate an M N data matrix; where M represents the Doppler dimension and N represents the distance dimension; A monitoring module, used to detect the distance dimension in the data matrix and determine the distance unit corresponding to the target; An analysis module, used for performing Doppler feature analysis on the Doppler dimension M of the data matrix, extracting the Doppler feature vector of each target, and calculating the correlation information between different targets using the Doppler feature vector of each target; The screening module is used to identify and eliminate multipath targets generated by multipath effects according to the Doppler feature vectors of the targets and the correlation information between different targets, and in combination with the distance units corresponding to the targets, so as to retain the real targets.
[0018] In a third aspect, a computer-readable storage medium stores a computer program, wherein the computer program implements the steps of the method described in the first aspect when executed by a processor.
[0019] Compared with the prior art, the present invention has the following beneficial effects: The present invention can significantly improve the detection and recognition capabilities of W-band radars in complex environments. First, by collecting M echo pulse signals and sampling them at N points, we obtain a large amount of data, which provides a rich information basis for subsequent analysis. Then, these sampled data are processed using a two-dimensional fast Fourier transform to generate an M×N data matrix, which contains not only the distance information of the target, but also the Doppler information, allowing us to analyze the target from two dimensions.
[0020] By detecting the distance dimension, we can accurately determine the location of the target, while the analysis of the Doppler dimension enables us to capture the motion characteristics of the target. By extracting the Doppler feature vector, we can not only identify the target, but also calculate the correlation information between different targets, which is crucial for distinguishing real targets from false targets generated by multipath effects.
[0021] Finally, by combining the correlation information between Doppler feature vectors and the distance information of the target, we can effectively identify and eliminate multipath targets and retain only the real targets. This method greatly improves the performance of the radar system in a multipath environment, reduces misjudgments and false alarms, and improves the accuracy of target detection and the reliability of the radar system. This has important practical significance for application scenarios that require precise target tracking in complex environments, such as military reconnaissance, air traffic control, and meteorological monitoring. With this method, W-band radar can provide higher quality monitoring results while maintaining a lower cost and smaller size, making it a valuable radar technology in a variety of applications. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] Figure 1 Shown is a schematic diagram of a W-band radar generating multipath targets provided by an embodiment of the present invention; Figure 2 FIG. 1 is a schematic diagram of a method for suppressing multipath effects based on a W-band radar provided by an embodiment of the present invention; Figure 3 The figure shows a short-distance multipath scene effect diagram provided by an embodiment of the present invention; Figure 4 The figure shows the actual measured effect of short-range multipath suppression provided by an embodiment of the present invention; Figure 5 The figure shows a long-distance multipath scene effect diagram provided by an embodiment of the present invention; Figure 6 The figure shows the actual measured effect of long-distance multipath suppression provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0023] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.
[0024] The term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " generally indicates that the related objects are in an "or" relationship. Example 1
[0025] See also Figure 1 After the W-band radar signal is reflected by the real target, a part of the echo pulse signal returns to the W-band radar receiver along the original transmission path, representing the real target; the other part of the signal is reflected by the real target and scattered around, and is reflected again by strong reflectors such as buildings and the ground, and then returns to the W-band radar, forming a multipath target.
[0026] from Figure 1 It can be seen that the distance of the real target is: (1) in, represents the emission path; The echo path representing the real target; Indicates the distance to the real target.
[0027] Here, set Indicates that the transmission path is equal to Represents the echo path of the real target, so the detection distance of the multipath target is: (2) in, Indicates the path of the real target reflected from the strong reflector; Represents the echo path of a multipath target; represents the predicted location path; Indicates the detection distance of multipath targets.
[0028] From formulas (1) and (2), it can be seen that the detection distance of multipath targets is greater than that of real targets. If multipath targets are not eliminated through signal processing, two targets may be mistakenly detected within the detection range of the W-band radar. This false detection increases the false alarm probability of the W-band radar.
[0029] To remove multipath targets, see Figure 2 This embodiment introduces a method for suppressing multipath effects based on W-band radar, comprising the following steps: Step S1: obtain M echo pulse signals reflected by the W-band radar from the target, and sample N points for each pulse signal to obtain M N sampling data; Here, the W-band radar transmits M pulse signals each time, and the receiver samples N points for each signal, so the signal data size received by the radar once is M. N points.
[0030] Step S2: Perform a two-dimensional fast Fourier transform on the sampled data to generate M N data matrix; where M represents the Doppler dimension and N represents the distance dimension; Here, the number of columns N of the data matrix represents the distance dimension, that is, different distance units; the number of rows M of the data matrix represents the Doppler dimension, that is, the speed or motion state of the target.
[0031] Step S3, detecting the distance dimension N of the data matrix to determine the distance unit corresponding to each target; Here we use ( ) represents the distance unit where each target is located, where K represents the number of targets in the echo pulse signal, and K <N。
[0032] Step S4, performing Doppler feature analysis on the Doppler dimension M of the data matrix, extracting the Doppler feature vector of each target, and using the Doppler feature vector of each target to calculate the correlation information between different targets; First, the complex Doppler feature vectors corresponding to each target are selected from the Doppler dimension M in the data matrix, and the dimension of each vector is 1 M; Next, performing a modulo operation on the complex Doppler feature vector, thereby converting the complex Doppler feature vector into a real Doppler feature vector; Finally, all real Doppler feature vectors are normalized to standardize the size of the real Doppler feature vectors, thereby obtaining the normalized Doppler feature vectors corresponding to each target.
[0033] Furthermore, the expression of the Doppler characteristic vector of each target is: s = (| |,| |,…| |) (3) (4) Where s represents the set of real-valued Doppler eigenvectors; represents the first complex Doppler eigenvector; represents the second complex Doppler eigenvector; represents the kth complex Doppler eigenvector; represents the set of modular eigenvectors; The Doppler eigenvector representing the first target; represents the Doppler eigenvector of the second target; represents the Doppler feature vector of the kth target.
[0034] Step S5: According to the Doppler feature vectors of the targets and the correlation information between different targets, and in combination with the distance units corresponding to the targets, the multipath targets generated by the multipath effect are identified and eliminated, and the real targets are retained.
[0035] Randomly select two target Doppler feature vectors from the Doppler feature vectors of each target, and mark them as a first target Doppler feature vector and a second target Doppler feature vector respectively; The autocorrelation value of the first target Doppler eigenvector, the cross-correlation value of the first target Doppler eigenvector and the second target Doppler eigenvector are calculated respectively.
[0036] The calculation expressions of the autocorrelation value of the first target Doppler feature vector, the cross-correlation value of the first target Doppler feature vector and the second target Doppler feature vector are respectively: (5) in, represents the autocorrelation value of the first target Doppler eigenvector; represents the cross-correlation value between the first target Doppler feature vector and the second target Doppler feature vector; M represents the Doppler dimension; m represents the Doppler unit array subscript; k represents the distance unit array subscript; Indicates the array subscript used in the Doppler eigenvector autocorrelation calculation; Indicates the array subscript used in the Doppler eigenvector cross-correlation calculation.
[0037] Further, the autocorrelation value of the first target Doppler feature vector, the first target Doppler feature vector and the cross-correlation value of the second target Doppler feature vector are respectively normalized, and the normalized expressions are: (6) in, represents the autocorrelation value of the first mode eigenvector after normalization; Represents the cross-correlation value between the first mode eigenvector and the second mode eigenvector after normalization.
[0038] In order to determine whether two targets are real targets or multipath targets, the absolute value difference between the normalized autocorrelation value and the cross-correlation value is calculated according to formula (6) to obtain a similarity difference metric value. The expression of the similarity difference metric value is: (7) in, Represents the similarity difference measure, and its value range is [0,1].
[0039] It should be noted that It helps us understand the similarity between the Doppler feature vectors of two targets. If the two targets are two unrelated real targets, the autocorrelation value and cross-correlation value of the normalized micro-Doppler feature vector are not similar, that is, is close to 1. On the contrary, if the two targets are two real targets and multipath targets, the autocorrelation value and cross-correlation value of the normalized micro-Doppler feature vector are similar, that is, Approaching 0.
[0040] Specifically, based on The value of is determined by taking the following steps: If the similarity difference metric value If the distance between the first target Doppler feature vector and the second target Doppler feature vector is smaller than the preset similarity threshold, the first target Doppler feature vector is similar to the second target Doppler feature vector, and the distances between the first target Doppler feature vector and the second target Doppler feature vector and the W-band radar are further compared; if the distance between the first target Doppler feature vector and the W-band radar is greater than the distance between the second mode feature vector and the W-band radar, the first target Doppler feature vector is a multipath target generated by the multipath effect and is eliminated, and the second target Doppler feature vector is retained. On the contrary, if the distance between the first target Doppler feature vector and the W-band radar is less than the distance between the second mode feature vector and the W-band radar, the second target Doppler feature vector is a multipath target generated by the multipath effect and is eliminated, and the first target Doppler feature vector is retained; If the similarity difference metric value If the value is greater than a preset dissimilarity threshold, the first target Doppler feature vector is dissimilar to the second target Doppler feature vector, and the first mode feature vector and the second mode feature vector are real targets and are retained.
[0041] The above steps can effectively distinguish and process real targets and multipath targets, thereby improving the target detection accuracy of W-band radar. Example 2
[0042] A multipath effect suppression system based on W-band radar, comprising: The data sampling module is used to obtain M echo pulse signals reflected by the W-band radar from the target, and sample N points for each pulse signal to obtain M N sampling data; The data conversion module is used to perform a two-dimensional fast Fourier transform on the sampled data to generate an M N data matrix; where M represents the Doppler dimension and N represents the distance dimension; A monitoring module, used to detect the distance dimension in the data matrix and determine the distance unit corresponding to the target; An analysis module, used for performing Doppler feature analysis on the Doppler dimension M of the data matrix, extracting the Doppler feature vector of each target, and calculating the correlation information between different targets using the Doppler feature vector of each target; The screening module is used to identify and eliminate multipath targets generated by multipath effects according to the Doppler feature vectors of the targets and the correlation information between different targets, and in combination with the distance units corresponding to the targets, so as to retain the real targets. Example 3
[0043] A computer-readable storage medium stores a computer program, wherein the computer program implements the steps of the method described in Example 1 when executed by a processor. Example 4
[0044] In a multipath environment, such as the roadside fence of a subway construction site, the radar signal will encounter multiple reflection paths during propagation, resulting in multiple reflections of the signal. In such an environment, we consider the situation of target movement, that is, the target (whether it is a simulated target for testing or an actual target) moves from a short distance to a long distance, that is, the target moves in the direction away from the radar. The display control system of the W-band radar, namely the display control, is the interface used by the operator to observe and control the radar. It uses a two-dimensional polar coordinate system, the distance is displayed in the form of concentric circles, the azimuth is expressed in a clockwise direction from north, and the background is black. It is mainly used for large-scale dynamic perception and scene monitoring. Within the distance range of 150 meters to 400 meters, the operator can simultaneously observe the stable tracks of the multipath target (marked as P130) and the real target (marked as P126) through the display control. Among them, the multipath target is a false target formed by multiple reflections of the radar signal in the environment, while the real target is the actual target.
[0045] The simultaneous appearance of such multipath targets and real target tracks will interfere with the operator's correct judgment of the position of the real target. This interference may make it difficult for the operator to distinguish which track is the real target and which is the false target caused by the multipath effect. This not only affects the performance of the radar system, but also its reliability, because incorrect judgment may lead to important operational decision-making errors. Therefore, distinguishing between real targets and multipath targets and reducing the interference of multipath effects on radar detection are the key to improving the accuracy and reliability of radar systems.
[0046] In practical applications, Figure 3 The effect of a close-range multipath scenario is shown, where the tracks of multipath targets and real targets are clearly visible. Figure 4 It shows that after applying multipath suppression technology, multipath targets are effectively suppressed in close-range environments, and the track of the real target is clearer. Figure 5 The effect of the long-range multipath scenario is shown, which is similar to the close-range scenario, but the target is farther away. Figure 6 The measured results after long-distance multipath suppression are demonstrated, showing that multipath suppression technology can also effectively filter out multipath targets at longer distances and improve the accuracy of radar detection. Through these measured results, we can see the application effect of multipath suppression technology at different distances, proving the effectiveness of this technology in improving the accuracy and reliability of radar systems.
[0047] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0048] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0049] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0050] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0051] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.
Claims
1. A method for suppressing multipath effects based on W-band radar, characterized in that: include: Obtain M echo pulse signals reflected by the W-band radar from the target, and sample N points for each pulse signal to obtain M N sampling data; The sampled data is subjected to a two-dimensional fast Fourier transform to generate M N data matrix; where M represents the Doppler dimension and N represents the distance dimension; Detecting the distance dimension N of the data matrix to determine the distance unit corresponding to each target; Performing Doppler feature analysis on the Doppler dimension M of the data matrix, extracting the Doppler feature vector of each target, and calculating correlation information between different targets using the Doppler feature vector of each target; According to the Doppler feature vectors of the targets and the correlation information between different targets, and in combination with the distance units corresponding to the targets, multipath targets generated by the multipath effect are identified and eliminated, and real targets are retained.
2. The method for suppressing multipath effects based on W-band radar according to claim 1, characterized in that: The step of extracting the Doppler feature vector of each target comprises: Selecting the complex Doppler eigenvector of each target from the Doppler dimension M of the data matrix; Performing a modulo operation on the complex Doppler eigenvector to obtain a real Doppler eigenvector; The real number Doppler feature vector is normalized to obtain the normalized Doppler feature vector of each target.
3. The method for suppressing multipath effects based on W-band radar according to claim 2, characterized in that: The expression of the Doppler eigenvector is: s = (| |，| |，…| |)； ； Where s represents the set of real-valued Doppler eigenvectors; represents the first complex Doppler eigenvector; represents the second complex Doppler eigenvector; represents the kth complex Doppler eigenvector; represents the set of modular eigenvectors; The Doppler eigenvector representing the first target; The Doppler eigenvector representing the second target; represents the Doppler feature vector of the kth target.
4. The method for suppressing multipath effects based on W-band radar according to claim 1, characterized in that: The calculation of correlation information between different targets includes: Randomly select two target Doppler feature vectors from the Doppler feature vectors of each target, and mark them as a first target Doppler feature vector and a second target Doppler feature vector respectively; The autocorrelation value of the first target Doppler eigenvector, the cross-correlation value of the first target Doppler eigenvector and the second target Doppler eigenvector are calculated respectively.
5. The method for suppressing multipath effects based on W-band radar according to claim 4, characterized in that: The calculation expressions of the autocorrelation value of the first target Doppler feature vector, the cross-correlation value of the first target Doppler feature vector and the second target Doppler feature vector are respectively: ； in, represents the autocorrelation value of the first target Doppler eigenvector; represents the first target Doppler feature vector and the second target Doppler feature vector; M represents the Doppler dimension; m represents the Doppler unit array subscript; k represents the distance unit array subscript; Indicates the array subscript used in the Doppler eigenvector autocorrelation calculation; Indicates the array subscript used in the Doppler eigenvector cross-correlation calculation.
6. The method for suppressing multipath effects based on W-band radar according to claim 4, characterized in that: The identifying and eliminating multipath targets generated by the multipath effect includes: Normalizing the autocorrelation value of the first target Doppler feature vector, the first target Doppler feature vector, and the cross-correlation value of the second target Doppler feature vector, respectively, and calculating the absolute value difference between the normalized autocorrelation value and the cross-correlation value to obtain a similarity difference measurement value; If the similarity difference measure value is less than a preset similarity threshold, the first target Doppler feature vector is similar to the second target Doppler feature vector, and further compares the distances from the first target Doppler feature vector and the second target Doppler feature vector to the W-band radar; If the distance from the first target Doppler feature vector to the W-band radar is greater than the distance from the second mode feature vector to the W-band radar, the first target Doppler feature vector is a multipath target generated by a multipath effect and is removed, and the second target Doppler feature vector is retained; if the distance from the first target Doppler feature vector to the W-band radar is less than the distance from the second mode feature vector to the W-band radar, the second target Doppler feature vector is a multipath target generated by a multipath effect and is removed, and the first target Doppler feature vector is retained; If the similarity difference measure value is greater than a preset dissimilarity threshold, the first target Doppler feature vector is dissimilar to the second target Doppler feature vector, and the first mode feature vector and the second mode feature vector are true targets and are retained.
7. The method for suppressing multipath effects based on W-band radar according to claim 6, characterized in that: The expressions for normalizing the autocorrelation value of the first mode eigenvector and the cross-correlation value between the first mode eigenvector and the second mode eigenvector are respectively: ； in, represents the autocorrelation value of the first mode eigenvector after normalization; Represents the cross-correlation value between the first mode eigenvector and the second mode eigenvector after normalization.
8. The method for suppressing multipath effects based on W-band radar according to claim 6, characterized in that: The expression of the similarity difference measurement value is: ； in, Represents the similarity difference measure.
9. A multipath effect suppression system based on W-band radar, characterized in that: include: The data sampling module is used to obtain M echo pulse signals reflected by the W-band radar from the target, and sample N points for each pulse signal to obtain M N sampling data; The data conversion module is used to perform a two-dimensional fast Fourier transform on the sampled data to generate an M N data matrix; where M represents the Doppler dimension and N represents the distance dimension; A monitoring module, used to detect the distance dimension in the data matrix and determine the distance unit corresponding to the target; An analysis module, used for performing Doppler feature analysis on the Doppler dimension M of the data matrix, extracting the Doppler feature vector of each target, and calculating the correlation information between different targets using the Doppler feature vector of each target; The screening module is used to identify and eliminate multipath targets generated by multipath effects according to the Doppler feature vectors of the targets and the correlation information between different targets, and in combination with the distance units corresponding to the targets, so as to retain the real targets.
10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.