Target detection method, processing chip, electronic equipment and storage medium

Abstract

A target detection method, a processing chip, an electronic device and a storage medium relate to the communication field, and the method comprises the following steps: obtaining a distance Doppler matrix in a Doppler division multiplexing mode; based on the distance Doppler matrix, determining a reference matrix for constant false alarm rate detection and a to-be-detected matrix for constant false alarm rate detection; performing target detection based on the reference matrix and the to-be-detected matrix; wherein the number of elements in the reference matrix is less than the number of elements in the distance Doppler matrix; the number of elements in the to-be-measured matrix is less than the number of elements in the distance Doppler matrix.

Description

Technical Field

[0001] This application belongs to the field of communications, specifically relating to a target detection method, a processing chip, an electronic device, and a storage medium. Background Technology

[0002] Currently, vehicle-mounted millimeter-wave radar is widely used for target detection in the communications field. The Constant False Alarm Rate (CFAR) algorithm is frequently employed in target detection using vehicle-mounted millimeter-wave radar. CFAR is an algorithm for signal processing of vehicle-mounted millimeter-wave radar, aiming to adaptively detect targets in the radar echo signal even without knowing the statistical characteristics of the target signal. The CFAR algorithm maintains a constant false alarm rate despite changes in background noise. The process involves preprocessing the electromagnetic wave signal received by the vehicle-mounted millimeter-wave radar, statistically analyzing the background noise characteristics based on the preprocessing results to obtain a threshold, and comparing the detected value of the received electromagnetic wave signal with the threshold to determine whether a target exists within the range of the received electromagnetic wave signal.

[0003] In the above process, after preprocessing the electromagnetic wave signal, the range Doppler matrix is ​​obtained, and then the constant false alarm rate algorithm is executed based on the range Doppler matrix.

[0004] However, in Doppler multiplexing mode, the range-Doppler matrix comprises multiple sub-matrices corresponding to multiple sub-bands. When performing a constant false alarm rate (CFAR) algorithm based on the range-Doppler matrix, the CFAR method is first applied to each of the multiple sub-matrices separately, and then the results of these multiple CFAR calculations are fused to analyze whether a target exists within the range of the electromagnetic signal received by the vehicle-mounted millimeter-wave radar. This method of applying the CFAR algorithm multiple times to the range-Doppler matrix in Doppler multiplexing mode results in the entire target detection process consuming significant storage and computational resources. Summary of the Invention

[0005] This application provides a target detection method, processing chip, electronic device, and storage medium, which can solve the problem in related technologies that the entire target detection process consumes a lot of storage and computing resources due to the execution of multiple constant false alarm rate algorithms on the range Doppler matrix in Doppler submultiplexing mode.

[0006] In a first aspect, embodiments of this application provide a target detection method, the method comprising:

[0007] Obtain the range-Doppler matrix in Doppler multiplexing mode;

[0008] Based on the range Doppler matrix, a reference matrix for constant false alarm rate detection and a test matrix for constant false alarm rate detection are determined.

[0009] Target detection is performed based on the reference matrix and the matrix to be tested;

[0010] The reference matrix has fewer elements than the range-Doppler matrix; the test matrix has fewer elements than the range-Doppler matrix.

[0011] Secondly, embodiments of this application provide a processing chip, including:

[0012] The acquisition module retrieves the range-Doppler matrix in Doppler multiplexing mode;

[0013] The determination module is used to determine, based on the range Doppler matrix, a reference matrix for constant false alarm rate detection and a test matrix for constant false alarm rate detection;

[0014] The detection module is used to perform target detection based on the reference matrix and the matrix to be tested;

[0015] The reference matrix has fewer elements than the range-Doppler matrix; the test matrix has fewer elements than the range-Doppler matrix.

[0016] Thirdly, embodiments of this application provide an electronic device including a processor and a memory. The memory stores programs or instructions that run on the processor, and when executed by the processor, the programs or instructions implement the steps of the method described in the first aspect. The processor may include the processing chip mentioned in the second aspect.

[0017] Fourthly, embodiments of this application provide a computer-readable storage medium storing a program or instructions that, when executed, implement the steps of the method described in the first aspect.

[0018] Fifthly, embodiments of this application provide a computer program product, the computer program product including a computer program that, when executed by a processor, implements the steps of the method described in the first aspect.

[0019] In this embodiment, a range-Doppler matrix in Doppler multiplexing mode is obtained; based on the range-Doppler matrix, a reference matrix and a test matrix for constant false alarm rate (CFAR) detection are determined; target detection is performed based on the reference matrix and the test matrix; wherein the number of elements in the reference matrix is ​​less than the number of elements in the range-Doppler matrix; and the number of elements in the test matrix is ​​less than the number of elements in the range-Doppler matrix. Thus, by determining a reference matrix and a test matrix with fewer elements than the range-Doppler matrix based on the range-Doppler matrix in Doppler multiplexing mode, and then performing target detection based on the reference matrix and the test matrix for CFAR detection, compared to the method of performing CFAR detection using the original range-Doppler matrix, using a reference matrix and a test matrix with fewer elements than the range-Doppler matrix reduces the computational load for CFAR detection, thereby significantly saving storage and computational resources. Attached Figure Description

[0020] Figure 1 This is a flowchart of a target detection method provided in an embodiment of this application.

[0021] Figure 2-1 This is a flowchart illustrating a process for determining a reference matrix for constant false alarm rate detection based on a distance-Doppler matrix, as provided in an embodiment of this application.

[0022] Figure 2-2 This is a schematic diagram illustrating a process for obtaining element values ​​from each submatrix of a distance Doppler matrix, as provided in an embodiment of this application.

[0023] Figure 3 This is a flowchart illustrating a process for determining a reference matrix for constant false alarm rate detection based on a distance-Doppler matrix, as provided in an embodiment of this application.

[0024] Figure 4 This is a flowchart illustrating a process for determining the test matrix for constant false alarm rate detection based on the distance Doppler matrix, as provided in an embodiment of this application.

[0025] Figure 5-1 This is a flowchart illustrating a target detection process based on a reference matrix and a test matrix, as provided in an embodiment of this application.

[0026] Figure 5-2 This is a schematic diagram illustrating a process for determining reference elements from a reference matrix, as provided in an embodiment of this application.

[0027] Figure 6 This is a flowchart of a target detection method provided in an embodiment of this application.

[0028] Figure 7-1 This is a schematic diagram of RDM under DDM mode provided in an embodiment of this application.

[0029] Figure 7-2 This is a schematic diagram illustrating the process of executing the CFAR algorithm using the related technologies provided in the embodiments of this application.

[0030] Figure 7-3 This is a schematic diagram illustrating a process for constructing a test matrix and a reference matrix, as provided in an embodiment of this application.

[0031] Figure 7-4 This is a schematic diagram illustrating the process of executing the CFAR algorithm based on RDM, as provided in the embodiments of this application.

[0032] Figure 8 This is a structural block diagram of a processing chip provided in an embodiment of this application.

[0033] Figure 9 This is a structural block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0034] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0035] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0036] As described in the background section, the Constant False Alarm Rate (CFAR) algorithm is a target detection and tracking algorithm widely used in vehicle-mounted millimeter-wave radar signal processing. Its core idea is to detect target signals in background noise while maintaining a constant false detection probability. By adaptively adjusting the threshold, the CFAR algorithm can maintain a consistent false alarm rate in different environments, improving the performance and robustness of vehicle-mounted millimeter-wave radar systems.

[0037] Generally, the transmitted waveforms of vehicle-mounted millimeter-wave radars use both Time Division Multiplexing (TDM) Multiple Input Multiple Output (MIMO) and Doppler Division Multiplexing (DDM) MIMO. In DDM mode, multiple transmitting antennas can transmit simultaneously, achieving higher transmission gain compared to TDM. However, in DDM mode, the millimeter waves transmitted simultaneously by multiple transmitting antennas belong to multiple sub-bands, resulting in the Range-Doppler Matrix (RDM) of the millimeter waves in DDM mode comprising sub-matrices corresponding to multiple sub-bands. During the execution of the CFAR algorithm based on the RDM, the CFAR algorithm is first executed on each of the multiple sub-matrices, and then the results of multiple CFAR executions are fused to analyze whether a target exists within the range of the millimeter waves received by the vehicle-mounted millimeter-wave radar. This method of executing the CFAR algorithm multiple times on the RDM in DDM mode leads to the entire target detection process consuming a large amount of storage and computing resources, resulting in poor performance.

[0038] In a target detection method provided in this application embodiment, a range-Doppler matrix in Doppler submultiplexing mode is obtained; based on the range-Doppler matrix, a reference matrix and a test matrix for constant false alarm rate (CFAR) detection are determined; target detection is performed based on the reference matrix and the test matrix; wherein the number of elements in the reference matrix is ​​less than the number of elements in the range-Doppler matrix; and the number of elements in the test matrix is ​​less than the number of elements in the range-Doppler matrix. Thus, by determining a reference matrix and a test matrix with fewer elements than the range-Doppler matrix based on the range-Doppler matrix in Doppler submultiplexing mode, and then performing target detection based on the reference matrix and the test matrix for CFAR detection, compared to the method of performing CFAR detection using the original range-Doppler matrix, using a reference matrix and a test matrix with fewer elements than the range-Doppler matrix reduces the computational load for CFAR detection, thereby significantly saving storage and computational resources.

[0039] It should be understood that all target detection methods provided in the embodiments of this application can be executed by electronic devices. The electronic devices may include vehicle-mounted sensors such as millimeter-wave radar. Electronic chips may be installed within the electronic devices, and these chips can be used to execute the CFAR algorithm. The embodiments of this application do not limit the specific hardware deployment environment.

[0040] The methods for processing abnormal flash memory data provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0041] Please see Figure 1 , Figure 1 A flowchart of a target detection method provided in an embodiment of this application is shown below. Figure 1 As shown, the method includes the following steps:

[0042] Step 110: Obtain the range-Doppler matrix in Doppler multiplexing mode.

[0043] In this embodiment, before obtaining the range-Doppler matrix in Doppler Division Multiplexing (DDM) mode, a detection signal can be transmitted via multiple transmitting antennas in DDM mode, and echo signals can be received. Then, a two-dimensional Fast Fourier Transform (2D-FFT) is performed on the echo signals, i.e., FFT is performed on the range dimension and the Doppler velocity dimension of the echo signals respectively, to obtain the range-Doppler matrix (RDM) of the echo signals in DDM mode. The RDM is a two-dimensional matrix, with the horizontal and vertical axes representing range and Doppler velocity, respectively. The velocity dimension of the DDM RDM is continuous, while the velocity dimension of the DDM RDM is divided according to the number of sub-bands and is continuous within each sub-band. The velocity ambiguity order needs to be obtained by de-interpreting the non-empty sub-bands to determine the velocity value of a target falling within a certain sub-band.

[0044] Specifically, since the echo signal in DDM mode belongs to multiple sub-bands, the RDM of the echo signal includes sub-matrices corresponding to multiple sub-bands. Specifically, the range-Doppler matrix can include N sub-matrices, each sub-matrice corresponding to one sub-band, and the number of elements in each sub-matrice is the same; N is a positive integer greater than 1.

[0045] Step 120: Based on the range-Doppler matrix, determine the reference matrix and the test matrix for constant false alarm rate detection; wherein the number of elements in the reference matrix is ​​less than the number of elements in the range-Doppler matrix; and the number of elements in the test matrix is ​​less than the number of elements in the range-Doppler matrix.

[0046] In this embodiment, the range-Doppler matrix may include N sub-matrices, each sub-matrice corresponding to a sub-frequency band. The number of elements in the reference matrix determined based on the range-Doppler matrix for constant false alarm rate (CFRR) detection can be the same as the number of elements in any one of the N sub-matrices. Correspondingly, the number of elements in the test matrix determined based on the range-Doppler matrix for CFRR detection can be the same as the number of elements in any one of the N sub-matrices, and the number of elements in the test matrix is ​​the same as the number of elements in the reference matrix. In other words, the number of elements in both the reference matrix and the test matrix can be the same as the number of elements in any one of the N sub-matrices.

[0047] Step 130: Perform target detection based on the reference matrix and the matrix to be tested.

[0048] In this embodiment, a range-Doppler matrix in Doppler submultiplexing mode is obtained; based on the range-Doppler matrix, a reference matrix and a test matrix for constant false alarm rate (CFAR) detection are determined; target detection is performed based on the reference matrix and the test matrix; wherein the number of elements in the reference matrix is ​​less than the number of elements in the range-Doppler matrix; and the number of elements in the test matrix is ​​less than the number of elements in the range-Doppler matrix. Thus, based on the range-Doppler matrix in Doppler submultiplexing mode, a reference matrix and a test matrix with fewer elements than the range-Doppler matrix are obtained for target detection. This reduces the computational load of CFAR detection compared to methods using the original range-Doppler matrix, significantly saving storage and computational resources.

[0049] In this embodiment, the range Doppler matrix may include N sub-matrices, and each of the N sub-matrices may contain M elements, where M is a positive integer greater than 1. In determining the reference matrix for constant false alarm rate detection based on the range Doppler matrix, the k-th element in the reference matrix can be obtained based on the k-th element of each of the N sub-matrices, where k is a positive integer less than or equal to M. Specifically, the k-th element of each of the N sub-matrices can be obtained to obtain N elements, and the k-th element in the reference matrix is ​​determined based on these N elements. Correspondingly, in determining the test matrix for constant false alarm rate detection based on the range Doppler matrix, the k-th element in the test matrix can be obtained based on the k-th element of each of the N sub-matrices. Specifically, the k-th element of each of the N sub-matrices can be obtained to obtain N elements, and the k-th element in the test matrix is ​​determined based on these N elements.

[0050] In one embodiment of this application, the element value of the k-th element in the reference matrix can be obtained by: obtaining the element value of the k-th element of each of the N sub-matrices, resulting in N element values; calculating the average of the N element values, and using the average as the element value of the k-th element in the reference matrix. In another embodiment of this application, the element value of the k-th element in the reference matrix can be obtained by: obtaining the element value of the k-th element of each of the N sub-matrices, resulting in N element values; sorting the N element values ​​by size, resulting in a sorting result; and selecting the element value in the middle position from the sorting result as the element value of the k-th element in the reference matrix.

[0051] The following is combined Figure 2-1 , Figure 2-2 and Figure 3 To elaborate.

[0052] Please see Figure 2-1 , Figure 2-1 A flowchart illustrating a process for determining a reference matrix for constant false alarm rate detection based on a range-Doppler matrix, as provided in this application embodiment, is shown below. Figure 2-1 As shown, the process includes the following steps:

[0053] Step 210: Obtain the element value of the k-th element of each of the N submatrices in the distance Doppler matrix, and obtain N element values.

[0054] In this embodiment, each of the N sub-matrices contains M elements, where M is a positive integer greater than 1. The value of each element in each sub-matrice can be the accumulation of an approximation of the signal energy at the same Doppler velocity at a corresponding distance within the sub-frequency band corresponding to the current sub-matrice. The value of the k-th element of each of the N sub-matrices is obtained, resulting in N element values, where 1 ≤ K ≤ M, and M is the number of elements in each of the N sub-matrices of the distance-Doppler matrix. For example... Figure 2-2 As shown, taking a range-Doppler matrix comprising four sub-matrices as an example, the element value of the k-th element of each of the four sub-matrices A, B, C, and D is obtained, resulting in four element values, namely A... k B k C k and D k . Figure 2-2 In the diagram, A1 represents the first element of submatrix A, B1 represents the first element of submatrix B, C1 represents the first element of submatrix C, and D1 represents the first element of submatrix D. 16 B represents the 16th element of submatrix A. 16C represents the 16th element of submatrix B. 16 D represents the 16th element of submatrix C. 16 Let k represent the 16th element of submatrix D. If each submatrix contains 16 elements, then k is a positive integer less than or equal to 16. It should be understood that the embodiments in this application use submatrixes containing 16 elements as an example, and are not intended to be limiting. Unless otherwise specified, the submatrixes in the accompanying drawings of this application can be interpreted as follows: Figure 2-2 We can understand this through the interpretation of the elements.

[0055] Step 220: Calculate the average of the N element values ​​and use this average as the element value of the k-th element in the reference matrix used for constant false alarm rate detection. For example, when obtaining A... k B k C k and D k After 4 element values, based on A k B k C k and D k Calculate the average value and use it as the element value of the k-th element in the reference matrix used for constant false alarm rate detection.

[0056] Step 230: Obtain the reference matrix based on the element value of the k-th element in the reference matrix.

[0057] In this embodiment, the element value of the (k+1)th element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. Steps 210-230 are repeated until the element value of the Mth element in the reference matrix used for constant false alarm rate detection is determined, i.e., the last element value of the reference matrix. The reference matrix can be obtained based on the element values ​​of the M elements in the reference matrix.

[0058] In this embodiment, the element value of the kth element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. The average value of the N elements is used as the element value of the kth element in the reference matrix used for constant false alarm rate detection. By averaging, a reference matrix that is more suitable for characterizing background noise is obtained, avoiding the situation where extreme cases exist in the element values ​​of the reference matrix, which may prevent the background noise estimation from being better obtained through the reference matrix when executing the CFAR detection algorithm.

[0059] Please see Figure 3 , Figure 3 A flowchart illustrating a process for determining a reference matrix for constant false alarm rate detection based on a range-Doppler matrix, as provided in this application embodiment, is shown below. Figure 3 As shown, the process includes the following steps:

[0060] Step 310: Obtain the element value of the k-th element of each of the N submatrices in the distance Doppler matrix, and obtain N element values.

[0061] Step 320: Sort the N element values ​​in order of size to obtain the sorted result. For example, when obtaining A... k B k C k and D k After 4 element values, for A k B k C k and D k Sort by size to get the sorted result.

[0062] Step 330: Select an element value in the middle position from the sorting results and use it as the element value of the kth element in the reference matrix used for constant false alarm rate detection.

[0063] In this embodiment, an element value in the middle position can be selected from the sorting results. For example, from a sorting result including N element values, the Gth largest element value can be selected, and this selected element value can be used as the element value of the kth element in the reference matrix used for constant false alarm rate detection. For example, after obtaining A... k B k C k and D k The sorting result among the four element values ​​is B. k C k、 A k and D k After 4, the third largest element value is selected as the element value of the kth element in the reference matrix, that is, A is selected. k As the element value used for the k-th element in the reference matrix.

[0064] Step 340: Obtain the reference matrix based on the element value of the k-th element in the reference matrix.

[0065] In this embodiment, the element value of the (k+1)th element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. Steps 310-340 are repeated until the element value of the Mth element in the reference matrix, i.e., the last element value of the reference matrix, is determined. The reference matrix can be obtained based on the element values ​​of the M elements in the reference matrix.

[0066] In this embodiment, the element value of the kth element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. These N elements are then sorted by size to obtain a sorting result. The element value in the middle position of the sorting result is then selected as the element value of the kth element in the reference matrix used for constant false alarm rate detection. By finding the element value in the middle position of the sorting, a reference matrix that is more suitable for characterizing background noise is obtained. This avoids the situation where extreme cases exist in the element values ​​of the reference matrix, which would prevent the background noise estimation from being better obtained through the reference matrix when executing the CFAR detection algorithm.

[0067] In this embodiment, the element value of the k-th element of each of the N sub-matrices in the distance Doppler matrix can be obtained to obtain N element values; the maximum value among the N element values ​​is obtained, and the maximum value is used as the element value of the k-th element in the test matrix used for constant false alarm rate detection; based on the element value of the k-th element in the test matrix, the test matrix is ​​obtained. The following is combined with... Figure 4 To elaborate.

[0068] Please see Figure 4 , Figure 4 A flowchart illustrating the process of determining the test matrix for constant false alarm rate detection based on the range Doppler matrix, as provided in this application embodiment, is shown below. Figure 4 As shown, the process includes the following steps:

[0069] Step 410: Obtain the element value of the k-th element of each of the N submatrices in the distance Doppler matrix, and obtain N element values.

[0070] Step 420: Obtain the maximum value among the N element values, and use the maximum value as the element value of the k-th element in the test matrix used for constant false alarm rate detection;

[0071] In this embodiment of the application, after obtaining N element values, the maximum value among the N element values ​​can be obtained. Specifically, the N element values ​​can be sorted according to their size to obtain a sorting result. For example, when obtaining A... k B k C k and D k After 4 element values, for A k B k C k and D k Sort the data by size, obtain the sorted results, and retrieve A. k B k C k and D k The maximum value in the matrix is ​​used as the element value of the k-th element in the matrix to be tested for constant false alarm rate detection.

[0072] Step 430: Obtain the matrix to be tested based on the element value of the k-th element in the matrix to be tested.

[0073] In this embodiment, after obtaining the maximum value among N element values ​​and using it as the element value of the k-th element in the test matrix for constant false alarm rate detection, the element value of the (k+1)-th element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. Steps 410-430 are repeated until the element value of the M-th element in the test matrix for constant false alarm rate detection, i.e., the last element value of the test matrix, is determined. The test matrix can be obtained based on the element values ​​of the M elements in the test matrix.

[0074] In this embodiment, the element value of the kth element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. The maximum value among the N element values ​​is used as the element value of the kth element in the test matrix for constant false alarm rate detection. By finding the maximum element value, the obtained test matrix can more easily detect the target when executing the CFAR detection algorithm.

[0075] Please see Figure 5-1 , Figure 5-1 A flowchart illustrating a target detection process based on a reference matrix and a test matrix, provided for embodiments of this application, is shown below. Figure 5-1 As shown, the process includes the following steps:

[0076] Step 510: Obtain the i-th element from the matrix to be tested as the test element; i is a positive integer and i is less than or equal to the total number of elements in the matrix to be tested.

[0077] In this embodiment of the application, the matrix to be tested may include M elements, such as Figure 5-2 As shown, the i-th element T can be obtained from the matrix to be tested. i As a test element.

[0078] Step 520: Obtain the target element associated with the test element in the reference matrix as the reference element. The target element includes the element adjacent to the i-th element in the reference matrix.

[0079] In this embodiment, the number of elements in the reference matrix is ​​the same as the number of elements in the matrix to be tested. After obtaining the i-th element from the matrix to be tested as the test element, as follows... Figure 5-2 As shown, a target element R associated with the test element can be obtained from the reference matrix as a reference element. The target element can be any number of elements related to the i-th element R in the reference matrix. i Adjacent elements.

[0080] Step 530: Calculate the reference threshold for the test element based on the reference element.

[0081] In this embodiment, the element values ​​of reference elements can be obtained, and a reference threshold for the test element can be calculated based on the element values ​​of the reference elements. Specifically, after obtaining the element adjacent to the i-th element in the reference matrix as the reference element, the reference threshold for the test element can be calculated based on the element values ​​of the reference elements. For example, the average value of the element values ​​of the reference elements can be calculated, and the average value can be used as the reference threshold for the test element.

[0082] Step 540: Perform target detection based on the reference threshold and test element.

[0083] In this embodiment, after determining the reference threshold of the test element, the element value of the test element can be obtained, and target detection can be performed based on the element value of the test element and the reference threshold. Specifically, if the element value of the test element is greater than the reference threshold of the test element, it can be determined that a target has been detected.

[0084] In this embodiment, after obtaining the i-th element from the matrix to be tested as a test element, obtaining the target element associated with the test element from the reference matrix as a reference element, calculating the reference threshold of the test element based on the reference element, and performing target detection based on the reference threshold and the test element, the (i+1)-th element from the matrix to be tested can be obtained as a test element, and steps 510-540 are repeated until the M-th element (i.e., the last element of the matrix to be tested) is obtained from the matrix to be tested as a test element, obtaining the target element associated with the test element from the reference matrix as a reference element, calculating the reference threshold of the test element based on the reference element, and performing target detection based on the reference threshold and the test element. During the process of sequentially determining M test elements based on the M elements of the matrix to be tested, obtaining reference elements from the reference matrix, calculating the reference threshold of the test elements, and performing target detection based on the reference threshold and the test elements, if the result of any one of the M target detections determines that a target exists, then a target is determined to be detected; conversely, if the results of all M target detections determine that a target does not exist, then a target is determined not to be detected. Ultimately, all existing targets were detected, and their corresponding distances and Doppler velocity values ​​were obtained.

[0085] In this embodiment, based on the range-Doppler matrix in the Doppler multiplexing mode, a reference matrix with fewer elements than the range-Doppler matrix and a test matrix with fewer elements than the range-Doppler matrix are determined. Then, based on the reference matrix and the test matrix used for constant false alarm rate detection, target detection is performed. Compared with the method of constant false alarm rate detection using the original range-Doppler matrix, using the reference matrix and the test matrix with fewer elements than the range-Doppler matrix for target detection can reduce the amount of computation required for constant false alarm rate detection, thereby significantly saving storage and computing resources.

[0086] Please see Figure 6 , Figure 6 A flowchart of a target detection method provided in an embodiment of this application is shown below. Figure 6 As shown, the method includes the following steps:

[0087] Step 610: Obtain the range-Doppler matrix in Doppler multiplexing mode.

[0088] In this embodiment of the application, before obtaining the range-Doppler matrix in the Doppler division multiplexing mode, the detection signal can be transmitted through multiple transmitting antennas in the Doppler division multiplexing (DDM) mode and the echo signal can be received. Then, a two-dimensional fast Fourier transform (2D-FFT) is performed on the echo signal, that is, the range dimension and the Doppler velocity dimension of the echo signal are respectively performed to obtain the range-Doppler matrix (RDM) of the echo signal in the DDM mode.

[0089] Specifically, since the echo signal in DDM mode belongs to multiple sub-frequencys, the RDM of the echo signal includes sub-matrices corresponding to multiple sub-frequency bands. Specifically, the range-Doppler matrix can include N sub-matrices, each sub-matrice corresponding to a sub-frequency band; N is a positive integer greater than 1; and the number of elements in each of the N sub-matrices is the same.

[0090] Step 613: Obtain the element value of the k-th element of each of the N submatrices in the distance Doppler matrix, and obtain N element values.

[0091] For details of step 613, please refer to the description of step 210.

[0092] Step 616: Calculate the average of the N element values ​​and use the average as the element value of the k-th element in the reference matrix used for constant false alarm rate detection.

[0093] For details of step 616, please refer to the description of step 220.

[0094] Step 619: Obtain the reference matrix based on the element value of the kth element in the reference matrix.

[0095] In this embodiment, the element value of the (k+1)th element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. Steps 613-619 are repeated until the element value of the Mth element in the reference matrix used for constant false alarm rate detection is determined, i.e., the last element value of the reference matrix. The reference matrix can be obtained based on the element values ​​of the M elements in the reference matrix.

[0096] In this embodiment, the element value of the k-th element of each of the N sub-matrices in the Doppler matrix can also be obtained, resulting in N element values. These N element values ​​are then sorted by size to obtain a sorting result. Specifically, after obtaining the N element values, they can be sorted by size to obtain a sorting result. For example, when obtaining A... k B k C k and D k After 4 element values, for A k B k C k and D k Sort the values ​​according to their size to obtain a sorted result. Select the middle element from the sorted result as the k-th element in the reference matrix used for constant false alarm rate detection. Specifically, after sorting the N element values ​​according to their size, select the middle element from the sorted result. For example, select the G-th largest element from the sorted result containing N element values, and use this selected element as the k-th element in the reference matrix used for constant false alarm rate detection. For example, after obtaining A... k B k C k and D k The sorting result among the 4 element values ​​is B. k C k、 A k and D k After step 4, the third largest element value is selected as the element value of the k-th element in the reference matrix used for constant false alarm rate detection, i.e., A is selected. k The value of the k-th element in the reference matrix used for constant false alarm rate detection is used as the element value. The reference matrix is ​​obtained based on the value of the k-th element in the reference matrix.

[0097] Step 622: Obtain the maximum value among the N element values, and use the maximum value as the element value of the k-th element in the test matrix used for constant false alarm rate detection.

[0098] For details of step 622, please refer to the description of step 420.

[0099] Step 625: Obtain the matrix to be tested based on the element value of the k-th element in the matrix to be tested.

[0100] In this embodiment, after obtaining the maximum value among N element values ​​and using it as the element value of the k-th element in the test matrix for constant false alarm rate detection, the element value of the (k+1)-th element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. Steps 622-625 are repeated until the element value of the M-th element in the test matrix for constant false alarm rate detection, i.e., the last element value of the test matrix, is determined. The test matrix can be obtained based on the element values ​​of the M elements in the test matrix.

[0101] Step 628: Obtain the i-th element from the matrix to be tested as the test element; i is a positive integer and i is less than or equal to the total number of elements in the matrix to be tested.

[0102] In this embodiment of the application, the matrix to be tested may include M elements.

[0103] Step 631: Obtain the target element associated with the test element in the reference matrix as the reference element. The target element includes the element adjacent to the i-th element in the reference matrix.

[0104] For details of step 631, please refer to the description of step 520.

[0105] Step 634: Calculate the reference threshold for the test element based on the reference element.

[0106] For details of step 634, please refer to the description of step 530.

[0107] Step 637: Perform target detection based on the reference threshold and test elements.

[0108] In this embodiment, after determining the reference threshold of the test element, the element value of the test element can be obtained, and target detection can be performed based on the element value of the test element and the reference threshold. Specifically, if the element value of the test element is greater than the reference threshold of the test element, it can be determined that a target has been detected.

[0109] In this embodiment, after obtaining the i-th element from the matrix to be tested as a test element, obtaining the target element associated with the test element from the reference matrix as a reference element, calculating the reference threshold of the test element based on the reference element, and performing target detection based on the reference threshold and the test element, the (i+1)-th element from the matrix to be tested can be obtained as a test element, and steps 628-637 are repeated until the M-th element (i.e., the last element of the matrix to be tested) is obtained from the matrix to be tested as a test element, obtaining the target element associated with the test element from the reference matrix as a reference element, calculating the reference threshold of the test element based on the reference element, and performing target detection based on the reference threshold and the test element. During the process of sequentially determining M test elements based on the M elements of the matrix to be tested, obtaining reference elements from the reference matrix, calculating the reference threshold of the test elements, and performing target detection based on the reference threshold and the test elements, if the result of any one of the M target detections determines that a target exists, then a target is determined to be detected; conversely, if the results of all M target detections determine that a target does not exist, then a target is determined not to be detected.

[0110] In this embodiment, a range-Doppler matrix in Doppler multiplexing mode is obtained; based on the range-Doppler matrix, a reference matrix and a test matrix for constant false alarm rate (CFAR) detection are determined; target detection is performed based on the reference matrix and the test matrix; wherein the number of elements in the reference matrix is ​​less than the number of elements in the range-Doppler matrix; and the number of elements in the test matrix is ​​less than the number of elements in the range-Doppler matrix. Thus, by determining a reference matrix and a test matrix with fewer elements than the range-Doppler matrix based on the range-Doppler matrix in Doppler multiplexing mode, and then performing target detection based on the reference matrix and the test matrix for CFAR detection, compared to the method of performing CFAR detection using the original range-Doppler matrix, using a reference matrix and a test matrix with fewer elements than the range-Doppler matrix reduces the computational load for CFAR detection, thereby significantly saving storage and computational resources.

[0111] To better understand the method for processing abnormal flash memory data provided in the embodiments of this application, further explanation is provided below. It should be understood that the following discussion is merely exemplary.

[0112] like Figure 7-1 As shown, in DDM mode, the Doppler velocity dimension of the RDM in DDM is divided according to the number of sub-bands. The RDM contains multiple sub-matrices corresponding to multiple sub-bands. When performing the CFAR algorithm on the RDM in DDM mode, as follows... Figure 7-2As shown, the CFAR algorithm is executed on the sub-matrix corresponding to each sub-frequency band, and the results of multiple executions of the CFAR algorithm are then fused to analyze the target detection results. This method consumes a lot of storage and computing power.

[0113] In a target detection method provided in this application embodiment, the target detection method includes the following steps: 1. Transmitting detection signals in Doppler division multiplexing (DDM) mode through multiple transmitting antennas; 2. Performing 2D-FFT on the echo signals to obtain Doppler spectra at different distances; 3. Generating RDM based on the Doppler spectra, wherein the RDM includes sub-matrices corresponding to multiple sub-frequency bands; 4. Determining the non-empty elements in each sub-matrix; 5. Constructing the test matrix and the reference matrix; 6. Using the reference matrix to estimate the background noise and calculating the reference threshold for the test elements; 7. Determining whether a target has been detected based on the reference threshold and the test elements.

[0114] Step 4 can be completed in any of the above-mentioned process steps or in any subsequent steps. Executing it in the above-mentioned steps can achieve the goal of improving computational efficiency by performing step 4 simultaneously with the construction of the matrix to be tested and the reference matrix.

[0115] In this embodiment of the application, the example RDM includes four sub-matrices, namely A, B, C, and D, each sub-matrix including 16 elements, namely A1-A2. 16 B1-B 16 C1-C 16 and D1-D 16 Two elements with the same index are elements located at the same position in different submatrices.

[0116] In DDM mode, the velocity ambiguity order at each position is typically obtained by solving for non-empty elements in each submatrix to resolve the velocity ambiguity problem. Specifically, the element value of the i-th element in each of the N submatrices is obtained, resulting in N element values. These N element values ​​are then permuted and summed to obtain the accumulated subband energy value of the i-th element in the N submatrices. Combinations with larger accumulated subband energy values ​​indicate larger energy, suggesting a lower probability that the i-th element in the N submatrices contains a non-empty element. Conversely, combinations with the smallest accumulated subband energy values ​​indicate the smallest energy, suggesting that the i-th element in the N submatrices contains a non-empty element.

[0117] Specifically, the non-empty elements of the solution at each position of each submatrix can be obtained in the following way: Obtain the element value of the i-th element of each of the N submatrices, resulting in N element values. For example, obtaining the second element of each of the four submatrices A, B, C, and D yields four element values: A2, B2, C2, and D2. Then, permutate and combine these N element values, and calculate the sum S of the element values ​​in each permutation and combination. For example, permuting and combining the four element values ​​A2, B2, C2, and D2... Combine the elements and calculate the sum of the element values ​​for each combination using the following formulas: S1 = A2 + B2 + C2, S2 = B2 + C2 + D2, S3 = C2 + D2 + A2, S4 = D2 + A2 + B2. Find the maximum sum of the element values ​​for each combination, for example, by finding the maximum value among S1, S2, S3, and S4 using max(S1, S2, S3, S4). If S3 is the maximum, then A2, C2, and D2 are the non-empty elements at that position. Repeat this process of finding non-empty elements for each position in each submatrix; in this example, it requires 16 iterations.

[0118] During the process of solving non-empty elements, since the entire RDM is traversed and read, the maximum, minimum, mean and sort values ​​of the elements at each position can be calculated at the same time. This method does not affect the flow of the entire object detection method and will not significantly increase the additional computational resource burden.

[0119] In this embodiment, the element value of the k-th element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. The maximum value among these N element values ​​is then used as the element value of the k-th element in the test matrix for constant false alarm rate detection. This process is repeated for each of the M elements in each sub-matrix to obtain the element values ​​of the M elements in the test matrix for constant false alarm rate detection, thus obtaining a test matrix containing M elements. Correspondingly, the element value of the k-th element of each of the N sub-matrices in the distance Doppler matrix is ​​obtained, resulting in N element values. The average value or the P-th largest value among these N element values ​​is then obtained, and this average value or the P-th largest value is used as the element value of the k-th element in the reference matrix for constant false alarm rate detection. This process is repeated for each of the M elements in each sub-matrix to obtain the element values ​​of the M elements in the reference matrix for constant false alarm rate detection, thus obtaining a reference matrix containing M elements. The number of elements in the test matrix is ​​the same as the number of elements in any submatrix of the RDM, making the size of the test matrix equivalent to the size of any submatrix in the RDM, which is 1 / N of the RDM size, where N is the number of submatrices. The same applies to the reference matrix, where the number of elements is the same as the number of elements in any submatrix of the RDM, making the size of the reference matrix equivalent to the size of any submatrix in the RDM, which is 1 / N of the RDM size. This reduces storage requirements, and the CFAR algorithm is executed based on the test matrix and the reference matrix for target detection, avoiding the need to execute the CFAR algorithm on multiple submatrices separately, reducing computational power requirements by N times. Furthermore, it eliminates the step of fusing and analyzing the results of the CFAR algorithm executed on each submatrix, further reducing computational power requirements and significantly improving efficiency.

[0120] The principle of target detection based on the CFAR algorithm is to obtain background noise estimates from the elements of the RDM. However, some elements in the RDM are affected by other target signals, resulting in abnormal element values, such as extreme cases of being too large or too small. This makes the background noise estimate obtained based on abnormal RDM elements inaccurate, affecting the final target detection performance of the CFAR algorithm. In this embodiment, the element value of the k-th element of each of the N sub-matrices in the range Doppler matrix is ​​obtained, resulting in N element values. The average value of the N elements or the value in the middle of the sorted order of the N elements is used as the element value of the k-th element in the reference matrix for constant false alarm rate detection. By averaging, a reference matrix that is more suitable for representing background noise is obtained, avoiding the situation where extreme values ​​in the reference matrix prevent the CFAR detection algorithm from obtaining a better background noise estimate. Since averaging and sorting to take the middle value can mitigate the influence of outliers in the reference matrix, and avoid some elements in the reference matrix not representing the background well, it helps to obtain a better background noise estimate.

[0121] In the embodiments of this application, a reference matrix can be constructed by averaging or by sorting and taking the median value. Then, the CFAR algorithm is executed based on the reference matrix. For example, reference units (i.e., reference elements) can be constructed by averaging, and then the reference threshold can be calculated by sorting CFAR; or reference units can be constructed by sorting and taking the median value, and then the reference threshold can be calculated by averaging CFAR. This combines the advantages of sorting and averaging in background noise estimation, and improves the accuracy and robustness of the CFAR algorithm for target detection.

[0122] like Figure 7-3 As shown, in constructing the test matrix and reference matrix in the example, each element T in the test matrix and each element R in the reference matrix can be calculated using the following formulas:

[0123] T k =max(A k B k C k D k ), where T k A is the k-th element in the matrix to be tested. k B is the value of the k-th element of submatrix A in RDM. k C is the value of the k-th element of submatrix B in RDM. k D is the value of the k-th element of submatrix C in RDM. k It is the value of the k-th element of submatrix D in RDM;

[0124] R k =ave(A k Bk C k D k ), where R k It is the k-th element in the reference matrix, A k B is the value of the k-th element of submatrix A in RDM. k C is the value of the k-th element of submatrix B in RDM. k D is the value of the k-th element of submatrix C in RDM. k It is the value of the k-th element of submatrix D in RDM, ave(A k B k C k D k To find A k B k C k D k A function of the average values ​​between. Correspondingly, A can also be expressed as a function of the average values ​​between. k B k C k D k Sort the results and find A. k B k C k D k The Pth largest value among them is taken as R k .

[0125] Choose to find A. k B k C k D k The maximum value in the middle is used as the T of the matrix to be tested. k The reason for obtaining the matrix to be tested is that elements at the same position in each submatrix of the RDM represent the same Doppler velocity. Therefore, A is calculated. k B k C k D k The operation for the maximum value was chosen by A. k B k C k D k The element with the highest energy in the medium, which can characterize the element that most closely approximates the target at the same Doppler velocity.

[0126] In this embodiment, during target detection using the CFAR algorithm based on the reference matrix and the matrix to be tested, each of the M elements of the matrix to be tested is sequentially used as a test element T. For example, the i-th element of the M elements of the matrix to be tested is used as the test element T. i And from the M elements of the reference matrix, obtain the element T that is the same as the test element. iThe associated target element is used as the reference element R. For example, the target element adjacent to the i-th element in the reference matrix is ​​taken as the reference element R. The CFAR algorithm is then applied to the reference element R to calculate the test element T. i The reference threshold is determined by comparing the test element T. i The value of an element is compared with a reference threshold to determine whether a target has been detected.

[0127] In the embodiments of this application, such as Figure 7-4 As shown, the relevant techniques typically use each element in the RDM as a test element T in sequence. i And obtain the test element T in the RDM. i Adjacent elements are used as reference elements, and the test element T is calculated based on the reference elements. i The reference threshold is determined by comparing the test element T. i The relative values ​​of the elements and the reference threshold are used to determine whether a target has been detected. In related technologies, both the reference and test elements originate from the RDM (Reference Matrix Determination). However, in the target detection method provided in this application, a test matrix and a reference matrix with fewer elements than the RDM are first determined based on the RDM. Then, test elements are determined from the test matrix, and reference elements are determined from the reference matrix. Thus, in this application embodiment, the test and reference elements originate from the test matrix and the reference matrix, respectively.

[0128] As described above, the target detection method provided in this application can solve the problems of high computing power requirements and low efficiency in CFAR in DDM mode. Specifically, in traditional TDM mode, the velocity dimension of TDM RDM is continuous, and CFAR is applied to the entire RDM; in DDM mode, RDM contains multiple sub-matrices corresponding to multiple sub-bands, and the velocity dimension of DDM RDM is divided according to the number of sub-bands, and is only continuous within the sub-bands. CFAR needs to be performed separately in each sub-band, and then fused to find effective target points, consuming a large amount of storage and computing power. In this embodiment, based on the range-Doppler matrix in the Doppler multiplexing mode, a reference matrix with fewer elements than the range-Doppler matrix and a test matrix with fewer elements than the range-Doppler matrix are determined. Then, based on the reference matrix and the test matrix used for constant false alarm rate detection, target detection is performed. Compared with the method of constant false alarm rate detection using the original range-Doppler matrix, using the reference matrix and the test matrix with fewer elements than the range-Doppler matrix for target detection can reduce the amount of computation required for constant false alarm rate detection, thereby significantly saving storage and computing resources.

[0129] The target detection method provided in this application can be applied to at least the following scenarios.

[0130] Scenario 1: Vehicle-mounted millimeter-wave radar has high frame rate requirements, typically 20fps, with each frame needing to be processed within 50ms. CFAR, as the most common point cloud target detection method, consumes a significant portion of this time. This application reduces the number of test units (i.e., test elements) from the entire RDM to the size of a sub-band. Under the same CFAR computing power, the processing time is reduced to (1 / number of sub-bands), and the CFAR computing power requirement is reduced to (1 / number of sub-bands) for the same processing time. Since CFAR detection is not required for each sub-band, the original RDM can be discarded to free up memory after obtaining the new RDM, while avoiding the bandwidth consumption of reading data from different sub-bands for CFAR detection.

[0131] Scenario 2: When multiple targets exist simultaneously, if the reference cell (i.e., reference element) happens to be the larger value of the alignment position of another target in each sub-band when performing CFAR using the original RDM within a sub-band, this reference cell may incorrectly lead to an overestimation of the background, affecting the target detection results of the test unit. This invention obtains a new reference cell by averaging the alignment positions (or taking the median value after sorting), which can improve the accuracy and robustness of subsequent CFAR detection.

[0132] Figure 8 This is a structural block diagram of a processing chip 800 provided in an embodiment of this application. (Refer to...) Figure 8 The processing chip 800 provided in this application embodiment includes:

[0133] The acquisition module 810 is used to acquire the range-Doppler matrix in the Doppler multiplexing mode;

[0134] The determination module 820 is used to determine, based on the range Doppler matrix, a reference matrix for constant false alarm rate detection and a test matrix for constant false alarm rate detection;

[0135] The detection module 830 is used to perform target detection based on the reference matrix and the matrix to be tested;

[0136] The reference matrix has fewer elements than the range-Doppler matrix; the test matrix has fewer elements than the range-Doppler matrix.

[0137] In this embodiment, a range-Doppler matrix in Doppler multiplexing mode is obtained; based on the range-Doppler matrix, a reference matrix and a test matrix for constant false alarm rate (CFAR) detection are determined; target detection is performed based on the reference matrix and the test matrix; wherein the number of elements in the reference matrix is ​​less than the number of elements in the range-Doppler matrix; and the number of elements in the test matrix is ​​less than the number of elements in the range-Doppler matrix. Thus, by determining a reference matrix and a test matrix with fewer elements than the range-Doppler matrix based on the range-Doppler matrix in Doppler multiplexing mode, and then performing target detection based on the reference matrix and the test matrix for CFAR detection, compared to the method of performing CFAR detection using the original range-Doppler matrix, using a reference matrix and a test matrix with fewer elements than the range-Doppler matrix reduces the computational load for CFAR detection, thereby significantly saving storage and computational resources.

[0138] In one embodiment of this application, the range Doppler matrix includes N sub-matrices, each sub-matrix corresponding to a sub-frequency band; N is a positive integer greater than 1; the number of elements in each of the N sub-matrices is the same; the number of elements in the reference matrix is ​​the same as the number of elements in any of the N sub-matrices; the number of elements in the matrix to be measured is the same as the number of elements in the reference matrix.

[0139] In one embodiment of this application, each of the N sub-matrices has M elements, where M is a positive integer greater than 1; the k-th element in the reference matrix is ​​obtained based on the k-th element of each of the N sub-matrices; the k-th element in the matrix to be tested is obtained based on the k-th element of each of the N sub-matrices; where k is a positive integer less than or equal to M.

[0140] In one embodiment of this application, during the process of determining a reference matrix for constant false alarm rate detection based on the range Doppler matrix, the determining module 820 is specifically configured to: obtain the element value of the k-th element of each of the N sub-matrices in the range Doppler matrix, thereby obtaining N element values; calculate the average value of the N element values, and use the average value as the element value of the k-th element in the reference matrix for constant false alarm rate detection; and obtain the reference matrix based on the element value of the k-th element in the reference matrix.

[0141] In one embodiment of this application, during the process of determining the reference matrix for constant false alarm rate detection based on the range Doppler matrix, the determining module 820 is specifically configured to: obtain the element value of the k-th element of each of the N sub-matrices in the range Doppler matrix, thereby obtaining N element values; sort the N element values ​​according to their size, thereby obtaining a sorting result; select an element value in the middle position from the sorting result as the element value of the k-th element in the reference matrix for constant false alarm rate detection; and obtain the reference matrix based on the element value of the k-th element in the reference matrix.

[0142] In one embodiment of this application, during the process of determining the test matrix for constant false alarm rate detection based on the range Doppler matrix, the determining module 820 is specifically configured to: obtain the element value of the kth element of each of the N sub-matrices in the range Doppler matrix, to obtain N element values; obtain the maximum value among the N element values, and use the maximum value as the element value of the kth element in the test matrix for constant false alarm rate detection; and obtain the test matrix based on the element value of the kth element in the reference matrix.

[0143] In one embodiment of this application, during the target detection process based on the reference matrix and the test matrix, the detection module 830 is specifically configured to: obtain the i-th element from the test matrix as a test element; i is a positive integer and i is less than or equal to the total number of elements in the test matrix; obtain a target element associated with the test element from the reference matrix as a reference element, the target element including elements adjacent to the i-th element in the reference matrix; calculate a reference threshold for the test element based on the reference element; and perform target detection based on the reference threshold and the test element.

[0144] like Figure 9As shown in the illustration, this application embodiment also provides an electronic device 900, which can be various types of computers, etc. The electronic device 900 includes a processor 910 and a memory 920. The memory 920 stores programs or instructions, which, when executed by the processor 910, implement the steps of any of the methods described above. The processor may include a processing chip. For example, when the program is executed by the processor 910, it implements the following process: In this application embodiment, a range-Doppler matrix in Doppler multiplexing mode is obtained; based on the range-Doppler matrix, a reference matrix for constant false alarm rate (CFAR) detection and a test matrix for CFAR detection are determined; target detection is performed based on the reference matrix and the test matrix; wherein the number of elements in the reference matrix is ​​less than the number of elements in the range-Doppler matrix; and the number of elements in the test matrix is ​​less than the number of elements in the range-Doppler matrix. Thus, based on the range-Doppler matrix in the Doppler multiplexing mode, a reference matrix with fewer elements than the range-Doppler matrix and a test matrix with fewer elements than the range-Doppler matrix are determined. Then, based on the reference matrix and the test matrix used for constant false alarm rate detection, target detection is performed. Compared with the method of constant false alarm rate detection using the original range-Doppler matrix, using the reference matrix and the test matrix with fewer elements than the range-Doppler matrix for target detection can reduce the amount of computation required for constant false alarm rate detection, thereby significantly saving storage and computing resources.

[0145] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the steps of the target detection method provided in any of the above embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0146] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0147] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above method embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0148] This application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above method embodiments and achieve the same technical effects. To avoid repetition, it will not be described again here.

[0149] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0150] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0151] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A target detection method characterized by, The method comprises: obtaining a range-Doppler matrix in a Doppler submultiplexing mode; determining, based on the range-Doppler matrix, a reference matrix for constant false alarm rate detection and a to-be-tested matrix for constant false alarm rate detection; performing target detection based on the reference matrix and the to-be-tested matrix; wherein the number of elements in the reference matrix is less than the number of elements in the range-Doppler matrix; the number of elements in the to-be-tested matrix is less than the number of elements in the range-Doppler matrix.

2. The method of claim 1, wherein, The range-Doppler matrix comprises N submatrices, each of which corresponds to a subband, and the number of elements in each of the submatrices is the same; N is a positive integer greater than 1; the number of elements in the reference matrix and the number of elements in the to-be-tested matrix are the same as the number of elements in any one of the N submatrices.

3. The method of claim 2, wherein, The number of elements in each of the N submatrices is M, and M is a positive integer greater than 1; the kth element in the reference matrix is obtained based on the kth element in each of the N submatrices; the kth element in the to-be-tested matrix is obtained based on the kth element in each of the N submatrices; wherein k is a positive integer less than or equal to M.

4. The method of claim 3, wherein, The element value of the kth element in the reference matrix is obtained by: obtaining the element values of the kth elements in each of the N submatrices to obtain N element values; calculating the average of the N element values, and taking the average as the element value of the kth element in the reference matrix.

5. The method of claim 3, wherein, The element value of the kth element in the reference matrix is obtained by: obtaining the element values of the kth elements in each of the N submatrices to obtain N element values; sorting the N element values according to size to obtain a sorting result; selecting an element value at a middle position from the sorting result as the element value of the kth element in the reference matrix.

6. The method of claim 3, wherein, The element value of the kth element in the to-be-tested matrix is obtained by: obtaining the element values of the kth elements in each of the N submatrices in the range-Doppler matrix to obtain N element values; obtaining the maximum value of the N element values, and taking the maximum value as the element value of the kth element in the to-be-tested matrix.

7. The method according to any one of claims 1 to 6, characterized in that, The target detection based on the reference matrix and the to-be-tested matrix comprises: obtaining an ith element from the to-be-tested matrix as a test element; i is a positive integer and i is less than or equal to the total number of elements in the to-be-tested matrix; obtaining a target element associated with the test element in the reference matrix as a reference element, the target element comprising an element adjacent to the ith element in the reference matrix; calculating a reference threshold value of the test element based on the reference element; performing target detection based on the reference threshold value and the test element.

8. A processing chip, comprising: The method comprises: an obtaining module, which obtains a range-Doppler matrix in a Doppler submultiplexing mode; a determining module, which determines, based on the range-Doppler matrix, a reference matrix for constant false alarm rate detection and a to-be-tested matrix for constant false alarm rate detection; performing target detection based on the reference matrix and the to-be-tested matrix. a detection module configured to perform target detection based on the reference matrix and the to-be-detected matrix; wherein the number of elements in the reference matrix is less than the number of elements in the range-Doppler matrix; wherein the number of elements in the to-be-detected matrix is less than the number of elements in the range-Doppler matrix.

9. An electronic device, comprising: a processor and a memory, the memory storing a program or instructions that are run on the processor, the program or instructions being executed by the processor to implement the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, a program or instructions stored on the medium, the program or instructions being executed to implement the steps of the method according to any one of claims 1-7.

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