False point elimination method, device and equipment based on multi-detection point direction finding

Abstract

The invention provides a false point elimination method, device and equipment based on multi-detection point direction finding. The method comprises the following steps: acquiring a plurality of continuous echo signals, and combining the plurality of continuous echo signals to obtain to-be-processed data; wherein the to-be-processed data is data arranged according to a distance dimension and a speed dimension; sequentially performing digital beam forming, moving target detection and constant false alarm detection processing on the to-be-processed data to obtain a plurality of initial target points; forming a plurality of to-be-processed input groups by the plurality of initial target points and adjacent points of the plurality of initial target points; performing angle measurement processing on the plurality of to-be-processed input groups to obtain a plurality of initial target angle measurement results; and deleting the to-be-processed input groups with the initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point greater than the angle threshold in the plurality of to-be-processed input groups to obtain the final target point, and by introducing more context information and space consistency constraints, the screening accuracy of the final target point is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of radar signal processing, and in particular to a method, device and equipment for eliminating false points based on multi-detection point direction finding. Background Art

[0002] Radar is an important detection method in modern military and civilian fields, and its performance is directly related to the accuracy and real-time performance of target detection. In the process of radar signal processing, the target signal often coexists with various noises, clutter and interference signals. These non-target signals pose a severe challenge to the normal operation of the radar. Especially in complex environments, such as cities, mountainous areas or oceans, due to the complexity of topography, climatic conditions and electromagnetic environment, the echo signal received by the radar contains a large amount of background clutter and interference. These clutters not only increase the data processing burden of the radar system, but also may cause the target signal to be submerged, thereby affecting the radar's detection performance and target recognition ability. Therefore, how to effectively suppress clutter and improve the accuracy and real-time performance of radar signal processing has become a key issue in the current development of radar technology.

[0003] In order to solve the clutter suppression problem in radar signal processing, a variety of technical means have been widely used. Among them, moving target indication (MTI) and moving target detection (MTD) are two commonly used clutter suppression methods. MTI suppresses stationary clutter by designing filters to improve the radar's signal-to-noise ratio, thereby realizing the detection of moving targets. MTD further distinguishes between targets and clutter relative to the radar by optimizing the Doppler difference of the filter group at a certain point in the Doppler frequency band to achieve the best match, thereby improving the signal-to-noise ratio and target detection capability. In addition, constant false alarm detection (CFAR) technology is also an important part of radar signal processing. It dynamically adjusts the target detection threshold according to the radar receiving data to maximize the target detection probability while keeping the false alarm rate unchanged. These existing technologies have improved the clutter suppression capability and target detection performance of the radar system to a certain extent.

[0004] Although the existing radar signal processing algorithms have achieved certain results in clutter suppression and target detection, there are still many shortcomings. First, the complexity of environmental noise and clutter makes it difficult to ensure the quality of radar signals. Especially in complex environments, existing algorithms often find it difficult to achieve complete clutter suppression, resulting in a large number of clutter signals being reported to the radar system. This not only increases the data processing burden of the radar system, but may also cause the target signal to be misjudged or missed. Secondly, the existing algorithms have limited target recognition capabilities in complex environments. Background clutter and interference may make the target similar to the background signal, making it difficult to accurately distinguish between the target and the clutter, resulting in an increase in the false alarm rate. These problems not only affect the accuracy and real-time performance of the radar system, but also limit the application and development of radar technology in a wider range of fields. Therefore, a more efficient and accurate radar signal processing algorithm is needed to meet the challenges of clutter suppression and target detection in complex environments. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention provides a method, device and equipment for removing false points based on multi-detection point direction measurement.

[0006] The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0007] In a first aspect, the present invention provides a method for removing false points based on multi-detection point direction finding, comprising:

[0008] Acquire multiple continuous echo signals, and combine the multiple continuous echo signals to obtain data to be processed; wherein the data to be processed is data arranged according to the distance dimension and the speed dimension obtained by using data completion processing;

[0009] Performing digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed in sequence to obtain a plurality of initial target points;

[0010] The multiple initial target points and the adjacent points of the multiple initial target points are used together to form multiple input groups to be processed;

[0011] Performing angle measurement processing on multiple input groups to be processed to obtain multiple initial target angle measurement results;

[0012] Among multiple input groups to be processed, the initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point are all greater than the angle threshold, and the input groups to be processed are deleted to obtain the final target point.

[0013] Optionally, acquiring a plurality of continuous echo signals and combining the plurality of continuous echo signals to obtain data to be processed includes:

[0014] S201, acquiring multiple continuous echo signals;

[0015] S202, performing mixing filtering and AD sampling processing on multiple continuous echo signals to obtain AD sampling data;

[0016] S203, performing data padding processing on the AD sampling data to obtain AD padding data; the AD padding data is arranged according to the distance dimension;

[0017] S204, executing steps S201-S203 in sequence according to the order of the continuous wave signals emitted by the radar to obtain data to be processed.

[0018] Optionally, digital beamforming, moving target detection, and constant false alarm detection are sequentially performed on the data to be processed to obtain a plurality of initial target points, including:

[0019] Performing digital beamforming DBF processing on the data to be processed to obtain beam information;

[0020] Perform moving target detection (MTD) processing on the beam information to obtain the moving target result;

[0021] SO-CFAR is used to perform constant false alarm detection on the moving target results to obtain multiple initial target points.

[0022] Optionally, after performing digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed in sequence to obtain a plurality of initial target points, the method further includes:

[0023] Sorting the signal-to-noise ratios corresponding to the multiple initial target points in descending order to obtain a sorting result;

[0024] Take the first N initial target points in the sorting result as the first screening target points.

[0025] Optionally, after taking the first N initial target points in the sorting result as the first screening target points, the method further includes:

[0026] Performing angle measurement processing on the first screening target point to obtain the screening point angle measurement result;

[0027] The first screening target point that does not meet the angle range in the screening point angle measurement result is deleted to obtain the second screening target point; the angle range is the angle range of the beam where the first screening target point in the beam information is located.

[0028] Optionally, a plurality of initial target points and a plurality of adjacent points of the initial target points are collectively formed into a plurality of input groups to be processed, including:

[0029] The second screening target point and the adjacent points of the second screening target point together constitute a plurality of input groups to be processed.

[0030] Optionally, multiple input groups to be processed are subjected to angle measurement processing to obtain multiple initial target angle measurement results, including:

[0031] The sum and difference beam scanning method is used to perform angle measurement processing on multiple input groups to be processed, and multiple initial target angle measurement results are obtained.

[0032] In a second aspect, the present invention provides a false point elimination device based on multi-detection point direction measurement, and the false point elimination device based on multi-detection point direction measurement includes: an acquisition unit, a processing unit, a construction unit, an angle measurement unit, and a screening unit;

[0033] The acquisition unit is used to: acquire multiple continuous echo signals, and combine the multiple continuous echo signals to obtain data to be processed; wherein the data to be processed is data arranged according to the distance dimension and the speed dimension obtained by using data completion processing;

[0034] The processing unit is used to: perform digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed in sequence to obtain multiple initial target points;

[0035] The construction unit is used to: combine multiple initial target points and the adjacent points of the multiple initial target points to form multiple input groups to be processed;

[0036] The angle measurement unit is used to: perform angle measurement processing on a plurality of input groups to be processed to obtain a plurality of initial target angle measurement results;

[0037] The screening unit is used to delete the input groups to be processed whose initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point are greater than the angle threshold, so as to obtain the final target point.

[0038] In a third aspect, the present invention provides a false point removal device based on multi-detection point direction finding, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, when the false point removal device based on multi-detection point direction finding is running, the processor and the storage medium communicate through the bus, and the processor executes the machine-readable instructions to perform the steps of the false point removal method based on multi-detection point direction finding as described in the first aspect above.

[0039] The present invention provides a method, device and equipment for removing false points based on multi-detection point direction finding. A method for removing false points based on multi-detection point direction finding includes: obtaining multiple continuous echo signals, and combining the multiple continuous echo signals to obtain data to be processed; wherein the data to be processed is data arranged according to the distance dimension and the speed dimension obtained by using data completion processing; performing digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed in sequence to obtain multiple initial target points; the multiple initial target points and the adjacent points of the multiple initial target points together constitute multiple input groups to be processed; performing angle measurement processing on the multiple input groups to be processed to obtain multiple initial target angle measurement results; deleting the input groups to be processed whose initial target angle measurement results corresponding to the initial target points and the adjacent points of the initial target points are greater than the angle threshold in the multiple input groups to be processed, to obtain the final target point. In the present invention, a plurality of continuous echo signals are combined to obtain data to be processed, and a preliminary constant false alarm detection is performed on the data to be processed to obtain an initial target point, and the initial target point and the adjacent points corresponding to the initial target point are taken as a group to be processed as an input group, and the angle measurement of the point traces in each input group to be processed is compared. Since the angle measurement results of the real target point and its nearby adjacent points are not much different, but the angle measurement results of the false point and its nearby adjacent points are quite different, the final target point can be determined according to the angle measurement results. That is, the method of the present invention improves the accuracy and robustness of the screening of the final target point by introducing more contextual information and spatial consistency constraints.

[0040] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic flow chart of a method for removing false points based on multi-detection point direction finding provided by an embodiment of the present invention;

[0042] Figure 2 The schematic diagram of the arrangement of the data to be processed is shown exemplarily;

[0043] Figure 3 The schematic diagram of the simulation results using the existing target point screening process is exemplarily shown;

[0044] Figure 4 The schematic diagram of the simulation result using the target point screening method of the present invention is exemplarily shown;

[0045] Figure 5 Another schematic diagram of simulation results using the existing target point screening process is exemplarily shown;

[0046] Figure 6 Another schematic diagram of simulation results using the target point screening method of the present invention is exemplarily shown;

[0047] Figure 7 A schematic structural diagram of a false point removal device based on multi-detection point direction finding provided by an embodiment of the present invention;

[0048] Figure 8 A schematic structural diagram of a false point elimination device based on multi-detection point direction finding provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0050] In order to improve the accuracy of screening the final target point, an embodiment of the present invention provides a method for eliminating false points based on multi-detection point direction finding. Figure 1 A flow chart of a method for removing false points based on multi-detection point direction finding provided by an embodiment of the present invention is shown as follows: Figure 1 As shown, including:

[0051] S101. Acquire multiple continuous echo signals, and combine the multiple continuous echo signals to obtain data to be processed.

[0052] The data to be processed are data arranged according to the distance dimension and the speed dimension obtained by data completion processing.

[0053] Specifically, after the radar transmits a continuous wave signal and encounters a target in space, the reflected echo signal is received by a receiving antenna. Usually, multiple continuous echo signals are combined into a frame of data to form data to be processed for signal processing. Figure 2 The following is an exemplary diagram showing the arrangement of the data to be processed. Figure 2 As shown in the figure, the data to be processed is data with two dimensions, distance dimension and speed dimension, and PRT represents the number of pulses emitted by the radar per second. The combination process of the data to be processed is: the echo signal is mixed and filtered and AD sampled to obtain the AD sampling data of a certain point, and the AD sampling data of a certain point is padded to an integer power of 2 in length, and used as one of the rows of a frame of data. This row is the distance dimension of the data. The above processing process is performed in sequence according to the order in which the radar transmits the continuous wave signal, and arranged in columns to obtain the data to be processed.

[0054] It is understandable that arranging data according to the distance dimension and the speed dimension and performing appropriate padding can make the subsequent processing more efficient. This data organization method helps improve the performance of the radar system, especially for the detection and classification of moving targets.

[0055] Optionally, S101 may specifically include:

[0056] S201. Acquire multiple continuous echo signals.

[0057] S202 , performing mixing filtering and AD sampling processing on a plurality of continuous echo signals to obtain AD sampling data.

[0058] S203, performing data padding processing on the AD sampling data to obtain AD padding data; the AD padding data is arranged according to the distance dimension.

[0059] S204, executing steps S201-S203 in sequence according to the order of the continuous wave signals emitted by the radar to obtain data to be processed.

[0060] S102 , sequentially performing digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed to obtain a plurality of initial target points.

[0061] Optionally, S102 may specifically include:

[0062] Performing digital beamforming DBF processing on the data to be processed to obtain beam information;

[0063] Perform moving target detection (MTD) processing on the beam information to obtain the moving target result;

[0064] SO-CFAR is used to perform constant false alarm detection on the moving target results to obtain multiple initial target points.

[0065] In this embodiment, a digital beamforming DBF processing method is used to compensate for the phase difference caused by the propagation path difference caused by the different spatial positions of the sensors for the data to be processed in a certain direction, and realize in-phase superposition, thereby achieving maximum energy reception in this direction and completing the beamforming in this direction to receive useful desired signals. This method of gathering the directional gain received by the array in a specified direction is equivalent to forming a "beam", and finally obtaining beam information.

[0066] The target detection MTD processing can use the Doppler filter bank to suppress various clutters, thereby improving the radar's ability to detect moving targets in a cluttered background. MTD technology distinguishes clutter from moving targets by using different Doppler frequencies. It can not only filter out clutter, but also distinguish targets of different moving speeds, thus greatly improving the ability to detect moving targets in a cluttered background.

[0067] S103, multiple initial target points and multiple adjacent points of the initial target points are combined to form multiple input groups to be processed.

[0068] It should be noted that the multiple initial target points obtained after the SO-CFAR constant false alarm detection process are target points containing clutter and interference, and can be further screened.

[0069] Optionally, after S103, the method further includes:

[0070] Sorting the signal-to-noise ratios corresponding to the multiple initial target points in descending order to obtain a sorting result;

[0071] Take the first N initial target points in the sorting result as the first screening target points.

[0072] Specifically, a minimum signal-to-noise ratio threshold TH can be set first snr , assuming that there are M initial target points after completing SO-CFAR. Sort the signal-to-noise ratios of the M initial target points in descending order, and select the points with a signal-to-noise ratio greater than the minimum threshold TH in the sorted results. snr The first N initial target points are selected to obtain the first screening target point.

[0073] Optionally, after taking the first N initial target points in the sorting result as the first screening target points, the method further includes:

[0074] Performing angle measurement processing on the first screening target point to obtain the screening point angle measurement result;

[0075] The first screening target point that does not meet the angle range in the screening point angle measurement result is deleted to obtain the second screening target point; the angle range is the angle range of the beam where the first screening target point in the beam information is located.

[0076] That is to say, in this embodiment, if the angle measurement result of the screening point corresponding to the current first screening target point does not conform to the angle range of the beam where the first screening target point is located, the first screening target point is also deleted.

[0077] Optionally, S103 may further include:

[0078] The second screening target point and the adjacent points of the second screening target point together constitute a plurality of input groups to be processed.

[0079] S104: Perform angle measurement processing on multiple input groups to be processed to obtain multiple initial target angle measurement results.

[0080] The embodiment of the present invention provides a false point elimination method based on multi-detection point direction finding, comprising: acquiring multiple continuous echo signals, and combining the multiple continuous echo signals to obtain data to be processed; wherein the data to be processed is data arranged according to a distance dimension and a speed dimension obtained by using data completion processing; performing digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed in sequence to obtain multiple initial target points; the multiple initial target points and the multiple adjacent points of the initial target points together constitute multiple input groups to be processed; performing angle measurement processing on the multiple input groups to be processed to obtain multiple initial target angle measurement results; and deleting the input groups to be processed whose initial target angle measurement results corresponding to the initial target points and the adjacent points of the initial target points are greater than an angle threshold in the multiple input groups to be processed, to obtain a final target point. In an embodiment of the present invention, a plurality of continuous echo signals are combined to obtain data to be processed, and a preliminary constant false alarm detection is performed on the data to be processed to obtain an initial target point, and the initial target point and the adjacent points corresponding to the initial target point are taken as a group to be processed as an input group, and the angle measurement of the point traces in each input group to be processed is compared. Since the angle measurement results of the real target point and its nearby adjacent points are not much different, but the angle measurement results of the false point and its nearby adjacent points are quite different, the final target point can be determined according to the angle measurement results. That is, the method of the present invention improves the accuracy and robustness of the screening of the final target point by introducing more context information and spatial consistency constraints.

[0081] Optionally, S104 may specifically include:

[0082] The sum and difference beam scanning method is used to perform angle measurement processing on multiple input groups to be processed, and multiple initial target angle measurement results are obtained.

[0083] S105, deleting the input groups to be processed whose initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point are greater than the angle threshold, to obtain the final target point.

[0084] Specifically, in this embodiment, among multiple input groups to be processed, the input groups to be processed whose initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point are both greater than the angle threshold are deleted to obtain a final processed input group, and the initial target point corresponding to the final processed input group is used as the final target point.

[0085] The angle threshold can be calculated based on the mean μ and variance σ of the initial target angle measurement results of each input group to be processed. 2 In this embodiment, μ+2σ can be used as an example. 2As the angle threshold corresponding to the input group to be processed, specifically, by analyzing the statistical characteristics (mean and variance, etc.) of a group of points (the input group to be processed), we can better understand the noise distribution and set the angle threshold accordingly. This helps to distinguish the real target points from the random fluctuations caused by noise, further improving the anti-noise performance of the system.

[0086] It can be understood that in this embodiment, the initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point are used to screen the final target point, which can increase the spatial consistency constraint. That is, verification from the angle consistency. Specifically, the real target usually exhibits relatively stable angle characteristics in continuous radar scanning. By comparing the angles of multiple points in the same group, it can be verified whether these points come from the same physical target. If the angle of a point is significantly different from the angle of the surrounding neighboring points, it is likely to be a false point caused by noise or clutter. In addition, for a moving target, its position and angle should have a certain degree of continuity and coherence. By comparing the angle changes of adjacent points, abnormal jumps or mutations can be detected, thereby excluding those illogical points.

[0087] It should be noted that, in this embodiment, the adjacent points of the initial target point may specifically be point traces adjacent to the initial target point in four directions: up, down, left, and right.

[0088] In order to verify the effectiveness of the false point elimination method based on multi-detection point direction finding provided by the embodiment of the present invention, a simulation experiment was also carried out.

[0089] The simulation uses a 24G linear frequency modulation continuous wave radar to collect data from the drone, and the collected data is screened according to the existing target point screening process (MTI, MTD and CFAR processing are performed on the collected data in turn) and the false point elimination method provided by the present invention. Specifically, the 24G linear frequency modulation continuous wave radar is set to sample the environment and obtain five consecutive frames of point traces. Based on the five consecutive frames of point traces, two screening methods are used for comparison. Figure 3 A schematic diagram of simulation results using an existing target point screening process is shown as an example. Figure 4 The following is a schematic diagram showing the simulation results of the target point screening method of the present invention. Figure 3 and Figure 4 By comparing the above data, it can be clearly seen that the method of the present invention can significantly remove the noise.

[0090] Based on the above simulation experiment, the UAV is made to fly vertically, and the above two methods are still used to screen the target points. Figure 5 Another schematic diagram of simulation results using the existing target point screening process is exemplarily shown. Figure 6Another schematic diagram of simulation results using the target point screening method of the present invention is shown as an example. Figure 5 and Figure 6 It can be seen that the method of the present invention has a better clutter removal effect and can report the target track more accurately.

[0091] The method provided in the embodiment of the present invention can be applied to an electronic device. Specifically, the electronic device can be: a desktop computer, a portable computer, an intelligent mobile terminal, a server, etc., which is not limited in the embodiment of the present invention.

[0092] Based on the same inventive concept, an embodiment of the present invention further provides a false point elimination device based on multi-detection point direction measurement. Figure 7 The present invention provides a schematic diagram of a false point removal device based on multi-detection point direction finding according to an embodiment of the present invention. Figure 7 As shown, it includes: an acquisition unit 701, a processing unit 702, a construction unit 703, an angle measurement unit 704 and a screening unit 705;

[0093] The acquisition unit 701 is used to: acquire multiple continuous echo signals, and combine the multiple continuous echo signals to obtain data to be processed; wherein the data to be processed is data arranged according to the distance dimension and the speed dimension obtained by using data completion processing;

[0094] The processing unit 702 is used to: perform digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed in sequence to obtain multiple initial target points;

[0095] The construction unit 703 is used to: combine the multiple initial target points and the adjacent points of the multiple initial target points to form multiple input groups to be processed;

[0096] The angle measuring unit 704 is used to: perform angle measurement processing on multiple input groups to be processed to obtain multiple initial target angle measurement results;

[0097] The screening unit 705 is used to delete the input groups to be processed whose initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point are greater than the angle threshold, so as to obtain the final target point.

[0098] Figure 8A structural diagram of a false point removal device based on multi-detection point direction finding provided by an embodiment of the present invention includes: a processor 810, a storage medium 820 and a bus 830, wherein the storage medium 820 stores machine-readable instructions executable by the processor 810, and when the false point removal device based on multi-detection point direction finding is running, the processor 810 communicates with the storage medium 820 through the bus 830, and the processor 810 executes the machine-readable instructions to execute the steps of the above method embodiment. The specific implementation method and technical effect are similar and will not be repeated here.

[0099] The storage medium may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk storage. Optionally, the storage medium may also be at least one storage device located away from the aforementioned processor.

[0100] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0101] It should be noted that the terms "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention.

[0102] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification.

[0103] Although the present invention is described herein in conjunction with various embodiments, in the process of implementing the claimed invention, those skilled in the art can understand and implement other changes of the above disclosed embodiments by viewing the drawings and the disclosed content. In the description of the present invention, the term "comprising" does not exclude other components or steps, "one" or "an" does not exclude multiple situations, and the meaning of "multiple" is two or more, unless otherwise clearly and specifically limited. In addition, certain measures are recorded in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0104] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the scope of protection of the present invention.

Claims

1. A method for eliminating false points based on multi-detection point direction finding, characterized in that: include: Acquire multiple continuous echo signals, and combine the multiple continuous echo signals to obtain data to be processed; wherein the data to be processed is data arranged according to the distance dimension and the speed dimension obtained by using data completion processing; Performing digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed in sequence to obtain a plurality of initial target points; The multiple initial target points and the adjacent points of the multiple initial target points together form a plurality of input groups to be processed; Performing angle measurement processing on the multiple input groups to be processed to obtain multiple initial target angle measurement results; Among the multiple input groups to be processed, the input groups to be processed whose initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point are both greater than the angle threshold are deleted to obtain a final target point.

2. The method for eliminating false points based on multi-detection point direction finding according to claim 1, characterized in that: The step of acquiring a plurality of continuous echo signals and combining the plurality of continuous echo signals to obtain data to be processed comprises: S201, acquiring the multiple continuous echo signals; S202, performing mixing filtering and AD sampling processing on the multiple continuous echo signals to obtain AD sampling data; S203, performing data padding processing on the AD sampling data to obtain AD padding data; the AD padding data is arranged according to the distance dimension; S204, executing steps S201-S203 in sequence according to the order of the continuous wave signals emitted by the radar to obtain the data to be processed.

3. The method for eliminating false points based on multi-detection point direction finding according to claim 1, characterized in that: The method sequentially performs digital beamforming, moving target detection, and constant false alarm detection processing on the data to be processed to obtain a plurality of initial target points, including: Performing digital beamforming (DBF) processing on the data to be processed to obtain beam information; Performing moving target detection (MTD) processing on the beam information to obtain a moving target result; SO-CFAR is used to perform constant false alarm detection processing on the moving target result to obtain the multiple initial target points.

4. The method for eliminating false points based on multi-detection point direction finding according to claim 3, characterized in that: After the digital beam forming, moving target detection, and constant false alarm detection processing are sequentially performed on the data to be processed to obtain a plurality of initial target points, the method further includes: Sorting the signal-to-noise ratios corresponding to the multiple initial target points in descending order to obtain a sorting result; Take the first N initial target points in the sorting result as the first screening target points.

5. The method for eliminating false points based on multi-detection point direction finding according to claim 4, characterized in that: After taking the first N initial target points in the sorting result as the first screening target points, the method further includes: Performing angle measurement processing on the first screening target point to obtain an angle measurement result of the screening point; The first screening target point that does not conform to the angle range in the screening point angle measurement result is deleted to obtain a second screening target point; the angle range is the angle range of the beam where the first screening target point in the beam information is located.

6. The method for eliminating false points based on multi-detection point direction finding according to claim 5, characterized in that: The step of forming a plurality of input groups to be processed by combining the plurality of initial target points and the adjacent points of the plurality of initial target points comprises: The second screening target point and the adjacent points of the second screening target point together constitute the multiple input groups to be processed.

7. The method for eliminating false points based on multi-detection point direction finding according to claim 1, characterized in that: The performing angle measurement processing on the plurality of input groups to be processed to obtain a plurality of initial target angle measurement results includes: The plurality of input groups to be processed are subjected to angle measurement processing by adopting a sum-and-difference beam scanning method to obtain the plurality of initial target angle measurement results.

8. A false point elimination device based on multi-detection point direction finding, characterized in that: The false point elimination device based on multi-detection point direction measurement includes: an acquisition unit, a processing unit, a construction unit, an angle measurement unit and a screening unit; The acquisition unit is used to: acquire a plurality of continuous echo signals, and combine the plurality of continuous echo signals to obtain data to be processed; wherein the data to be processed is data arranged according to the distance dimension and the speed dimension obtained by using data completion processing; The processing unit is used to: sequentially perform digital beam forming, moving target detection, and constant false alarm detection processing on the data to be processed to obtain a plurality of initial target points; The construction unit is used to: combine the multiple initial target points and the adjacent points of the multiple initial target points to form a plurality of input groups to be processed; The angle measurement unit is used to: perform angle measurement processing on the multiple input groups to be processed to obtain multiple initial target angle measurement results; The screening unit is used to delete the input groups to be processed in which the initial target angle measurement results corresponding to the initial target point and the adjacent points of the initial target point are greater than the angle threshold, so as to obtain the final target point.

9. A false point elimination device based on multi-detection point direction finding, characterized in that: include: A processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the false point removal device based on multi-detection point direction finding is running, the processor communicates with the storage medium through the bus, and the processor executes the machine-readable instructions to perform the steps of the false point removal method based on multi-detection point direction finding as described in any one of claims 1 to 7.

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