A frequency diversity array multiple-input multiple-output radar target detection system

Abstract

The present application relates to the field of radar technology, provide a kind of frequency diversity array multiple-input multiple-output radar target detection system.The system includes detection statistics construction module, detection optimization module, detection threshold determination module and target determination module;Wherein: the detection statistics construction module is used to construct detection statistics;According to the detection statistics, the optimization model of semi-definite programming is constructed;The detection optimization module is used to construct the optimization model of semi-definite programming according to the detection statistics;The detection optimization module is also used to solve the optimization model, obtain the optimal value of detection statistics;The target determination module is used to compare the optimal value of detection statistics with detection threshold, to detect whether target exists, realize the promotion of frequency diversity array multiple-input multiple-output radar target detection probability and anti-interference ability under complex environment.

Description

Technical Field

[0001] This invention relates to the field of radar technology, and in particular to a frequency diversity array multi-input multi-output radar target detection system. Background Technology

[0002] Frequency diversity array (FDI) multiple-input multiple-output (MIMO) radars have been proposed and attracted considerable research attention due to their additional degrees of freedom in the range domain. Compared to traditional phased array, frequency-controlled array, or MIMO radars, FDI significantly improves target resolution and anti-jamming performance. Current research on this radar system covers multiple areas: deceptive jamming suppression, range ambiguity clutter suppression, synthetic aperture radar imaging, and parameter estimation. Only a few studies have addressed the detection problem of FDI.

[0003] Frequency diversity array multi-input multi-output radar combines the range dimension control capability of frequency diversity array with the spatial processing advantages of multi-input multi-output technology. It achieves beam range correlation through carrier frequency increment and, together with the "time-range-angle-Doppler" four-dimensional joint processing capability formed by virtual array expansion, exhibits unique technical advantages in complex electromagnetic environments.

[0004] However, existing frequency diversity array multiple-input multiple-output (MIMO) radar target detection technology faces two major challenges: first, the unknown incremental target range can lead to parameter mismatch, which significantly degrades system detection performance; second, the stability of conventional detection methods is difficult to guarantee in complex electromagnetic environments. These two issues severely restrict the application effectiveness of frequency diversity array MIMO radar in real-world environments.

[0005] Therefore, overcoming the shortcomings of the existing technology is an urgent problem to be solved in this technical field. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a frequency diversity array multi-input multi-output radar target detection system.

[0007] The present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a frequency diversity array multi-input multi-output radar target detection system, characterized in that it includes a detection statistics construction module, a detection optimization module, a detection threshold determination module, and a target determination module; wherein:

[0009] The detection statistics construction module is used to construct detection statistics. ;in, For the sampling covariance matrix, Represents the mean vector of the training sample matrix. This indicates the conjugate transpose. For joint transmit / receive steering vector, The azimuth angle of the far-field point source. The target incremental delay; wherein, the mean vector of the training sample matrix. It is pre-built;

[0010] The detection optimization module is used to optimize the detection based on the detection statistics. Construct a semidefinite programming optimization model;

[0011] The detection optimization module is also used to solve the optimization model to obtain the optimal value of the detection statistics;

[0012] The target determination module is used to compare the optimal value of the detection statistics with the detection threshold to detect whether the target exists.

[0013] Furthermore, the sampling covariance matrix , For the training sample matrix, This represents the number of training samples; where the training sample matrix... It is pre-built.

[0014] Furthermore, the optimization model is as follows: ;

[0015] in, express The maximum value, Represents the set of real numbers. and express and All are positive semi-definite matrices, and and For Hermitian matrices, The number of elements in the transmitting array. and Describes the constructed matrix. , , , , ; This indicates the construction of a diagonal matrix. It represents the Hadamah accumulation. , This represents the vector of triangular polynomial coefficients in the numerator of the detection statistic. This represents the vector of trigonometric polynomial coefficients in the denominator of the detection statistic. , , This indicates the radar baseband bandwidth.

[0016] Furthermore, the triangular polynomial coefficient vector of the numerator of the detection statistic ;

[0017] in, , Representation matrix of OK The elements of the column.

[0018] Furthermore, the triangular polynomial coefficient vector of the denominator of the detection statistic ;

[0019] in, , This indicates the conjugate operation. Representing vectors of One element, , This represents the spatiotemporal modulation process of the transmitted signal in the angle-range domain. , , Indicates the receiving guide vector. For the number of receiving array elements, The number of elements in the transmitting array. For the spacing between array elements, Indicates the reference carrier wavelength.

[0020] Furthermore, it also includes a detection threshold determination module, which is used to: solve the optimization model using a convex optimization method and run it several times to obtain... Optimal value vector of detection statistics under the assumption and Optimal value vector of detection statistics under the assumption ;

[0021] in, , , for Assume and Number of runs under the assumption; for Assuming the following operation is performed The optimal value of the test statistic for the second test. for Assuming the following operation is performed The optimal value of the test statistic for the second test. .

[0022] Furthermore, the detection threshold is ;in, Indicates in Assuming the following Arranged in descending order, This indicates that the data is rounded up; PFA represents the preset false alarm probability. This indicates that the data is sorted in descending order.

[0023] Furthermore, the target determination module is specifically used to: if the detection statistic has the optimal value Greater than or equal to the detection threshold If the detection statistic is optimal, then the target is determined to exist; Less than the detection threshold If the target does not exist, then it is determined that the target does not exist.

[0024] Furthermore, the characteristic is that the expression of the data matrix of the unit to be detected is: ;in, Represents the complex amplitude of the target signal. express Gaussian interference noise vector, For the target incremental delay, , Indicates the radar baseband bandwidth. For joint transmit / receive steering vector;

[0025] The expression for the mean vector of the training sample matrix is: ;in, The number of training samples, .

[0026] Furthermore, the joint transmit / receive steering vector ;

[0027] in, Indicates the Kronecker product. It represents the Hadamah accumulation. Indicates the receiving guide vector. The superscript indicates the guide vector representing the distance offset of the target within the cell. Indicates transpose. represents an imaginary number, Indicates the reference carrier wavelength. For the frequency to increase, This represents the spatiotemporal modulation process of the transmitted signal in the angle-range domain. , From elements Composition, and , Indicates the first The matched filter pair for the _th The output response of each transmitted waveform This represents the transmitted signal waveform of a frequency diversity array multiple-input multiple-output radar. , This indicates the conjugate operation. Indicates the pulse width. The number of elements in the transmitting array. For the number of receiving array elements, The distance between array elements.

[0028] Secondly, the present invention also provides a frequency diversity array multiple-input multiple-output radar target detection device for implementing the frequency diversity array multiple-input multiple-output radar target detection system described in the first aspect, the device comprising:

[0029] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor for performing the frequency diversity array multiple-input multiple-output radar target detection system described in the first aspect.

[0030] Thirdly, the present invention also provides a non-volatile computer storage medium storing computer-executable instructions that are executed by one or more processors to perform the method described in the first aspect.

[0031] Fourthly, a computer program product comprising instructions is provided, which, when executed on a computer or processor, cause the computer or processor to perform the methods of the first aspect and any one thereof.

[0032] This invention constructs a detection statistic and uses it to build a semidefinite programming optimization model. Solving the model yields the optimal value of the detection statistic, which is then used to detect the presence of a target at a corresponding azimuth angle. This improves the target detection probability and anti-jamming capability of a frequency diversity array multi-input multi-output radar in complex environments. Furthermore, this invention ensures robust detection of unknown target locations while maintaining a high detection probability in strong interference environments, thus enhancing the detection probability in complex electromagnetic environments. It provides a unified technical approach for subsequent research on complex scenarios such as anti-clutter and anti-non-Gaussian interference, possessing both theoretical universality and engineering feasibility. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0034] Figure 1This is a schematic diagram of the overall flow of a frequency diversity array multi-input multi-output radar target detection system module provided in an embodiment of the present invention;

[0035] Figure 2 This is a flowchart illustrating a comparison and detection statistic and detection threshold provided by an embodiment of the present invention;

[0036] Figure 3 This is a flowchart illustrating a frequency diversity array multi-input multi-output radar target detection method provided in an embodiment of the present invention;

[0037] Figure 4 This is a schematic diagram of a frequency diversity array multi-input multi-output radar target detection method provided in an embodiment of the present invention;

[0038] Figure 5 This is a schematic diagram of the architecture of a frequency diversity array multi-input multi-output radar target detection system provided in an embodiment of the present invention;

[0039] Figure 6 This is a schematic diagram illustrating the detection probability of a frequency diversity array multi-input multi-output radar target detection method provided by an embodiment of the present invention compared with existing technologies;

[0040] Figure 7 This is a schematic diagram of the architecture of a frequency diversity array multi-input multi-output radar target detection device provided in an embodiment of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0042] Unless the context otherwise requires, throughout the specification and claims, the term "comprising" is interpreted as openly inclusive, meaning "including, but not limited to." In the description of the specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this disclosure. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics mentioned may be included in any suitable manner in any one or more embodiments or examples; that is, although they may be incorporated into embodiments or examples using the above terms for reasons such as order and position, it does not limit them to be incorporated in combination by a single embodiment or example.

[0043] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of this disclosure, unless otherwise stated, "a plurality of" means two or more. Furthermore, for example, the description may use the prefix "A" or "B" to describe the same type of nouns as two independent entities. In this case, the corresponding features defined with "A" and "B" are used only to distinguish between similar entities and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features.

[0044] In the description of this invention, the expression “A and / or B” (where A and B are used to formally represent specific features) will be used. The corresponding expression includes the following three combinations: only A, only B, and a combination of A and B.

[0045] As used in this invention, “about,” “approximately,” or “approximately” includes the stated value and the average value within an acceptable range of deviation from a particular value, wherein the acceptable range of deviation is determined by a person skilled in the art taking into account the measurement under discussion and the error associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0046] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0047] Example 1:

[0048] Embodiment 1 of the present invention provides a frequency diversity array multi-input multi-output radar target detection system, such as... Figure 1 As shown, it includes:

[0049] The detection statistics construction module is used to construct detection statistics. ;in, For the sampling covariance matrix, Represents the mean vector of the training sample matrix. This indicates the conjugate transpose. For joint transmit / receive steering vector, The azimuth angle of the far-field point source. The target incremental delay; wherein, the mean vector of the training sample matrix. It is pre-built.

[0050] In one embodiment, the frequency diversity array multi-input multi-output radar target detection system of the present invention may further include a data matrix construction module, which constructs a correlation matrix based on information and determines the target space-time steering vector, the sampling covariance matrix, and the data matrix of the unit to be detected.

[0051] The detection statistics construction module is used to construct detection statistics with adjustable parameters using the data matrix of the units to be detected and the Wald criterion.

[0052] The detection optimization module is used to optimize the detection based on the detection statistics. We construct a semidefinite programming optimization model.

[0053] The detection optimization module is also used to solve the optimization model to obtain the optimal value of the detection statistics.

[0054] In one embodiment, the detection optimization module is used to convert the detection statistics into a convex optimization form, construct an optimization problem about semidefinite programming, and determine the optimal value of the detection statistics.

[0055] In one embodiment, the detection optimization module may include a detection threshold determination module; alternatively, the frequency diversity array multi-input multi-output radar target detection system of this embodiment may further include a detection threshold determination module. The detection threshold determination module is used to determine a detection threshold value using system parameters, a preset false alarm probability, and the optimal value of the aforementioned detection statistics. This module will be described below.

[0056] The target determination module is used to compare the optimal value of the detection statistics with the detection threshold to detect whether the target exists.

[0057] In one embodiment, the target determination module compares the optimal value of the detection statistic with the detection threshold to determine whether a target exists. If the detection statistic is less than the detection threshold, the target is determined not to exist; if the detection statistic is greater than or equal to the detection threshold, the target is determined to exist. The detection threshold value is determined by system parameters, a preset false alarm probability, and an optimization model based on semidefinite programming.

[0058] In existing technologies, the unknown and uncertain nature of the incremental target distance leads to parameter mismatch, making it difficult to accurately obtain the incremental distance and significantly reducing the performance of traditional detectors. Furthermore, in noise-suppressed interference environments, radar signals are susceptible to complex Gaussian interference, and their covariance matrix needs to be estimated based on training samples. The statistical characteristics of the interference signal are often unknown and time-varying, causing a significant degradation in the performance of traditional detection algorithms based on fixed interference models. The stability of traditional detection methods in complex electromagnetic environments is difficult to guarantee. In addition, the estimation of the target position parameters suffers from high computational complexity and a difficulty in balancing real-time performance and accuracy.

[0059] This invention constructs a detection statistic and uses it to build a semidefinite programming optimization model. The optimal value of the detection statistic is obtained by solving the model, and then compared with a detection threshold to determine the presence of a target. This enables target detection in a frequency diversity array multi-input multi-output radar under complex environments. This invention also ensures robust detection of unknown target locations while maintaining a high detection probability in environments with strong interference, thus improving the detection probability in complex electromagnetic environments. It provides a unified technical approach for subsequent research on complex scenarios such as anti-clutter and anti-non-Gaussian interference, possessing both theoretical universality and engineering feasibility.

[0060] Furthermore, by adjusting parameters, the detector in this embodiment of the invention can optimize the waveform design and "space-distance" degree of freedom allocation of the frequency diversity array multi-input multi-output radar, thereby adapting to the needs of different detection scenarios and ensuring detection stability.

[0061] It should be noted that the detector in this embodiment of the invention is suitable for large-sample, stationary interference scenarios; it is also suitable for problems where the interference covariance matrix and target parameters are unknown, and can significantly improve robustness.

[0062] Wherein, the sampling covariance matrix , For the training sample matrix, , The number of training samples and the data matrix of the units to be detected represent the total number of training samples. and training sample matrix Both have a dimension of 1. ,in, This refers to the number of transmit elements in a frequency diversity array multiple-input multiple-output radar. For the number of receiving array elements, This represents the number of training samples; where the data matrix of the units to be detected is... and training sample matrix All of them were pre-built.

[0063] In one optional implementation, the optimization model is: ;in, Indicates the detection statistic The maximum value, Represents the set of real numbers. and express and All are positive semi-definite matrices, and and For Hermitian matrices, The number of elements in the transmitting array. and Describes the constructed matrix. , , , , ; This indicates the construction of a diagonal matrix. It represents the Hadamah accumulation. , This represents the vector of triangular polynomial coefficients in the numerator of the detection statistic. This represents the vector of trigonometric polynomial coefficients in the denominator of the detection statistic. , , This indicates the radar baseband bandwidth.

[0064] Wherein, the triangular polynomial coefficient vector of the numerator of the detection statistic ;in, , Representation matrix of OK Column elements, The number of elements in the launch array.

[0065] The trigonometric polynomial coefficient vector of the denominator of the detection statistic ;in, , This indicates the conjugate operation. Representing vectors of One element, , This represents the spatiotemporal modulation process of the transmitted signal in the angle-range domain. , , Indicates the receiving guide vector. For the number of receiving array elements, The number of elements in the transmitting array. For the spacing between array elements, Indicates the reference carrier wavelength.

[0066] In practical applications, the detection optimization module solves the optimization model to obtain the optimal value of the detection statistics, specifically:

[0067] The detection threshold determination module uses a convex optimization method to solve the optimization model and runs it several times to obtain... Optimal value vector of detection statistics under the assumption and Optimal value vector of detection statistics under the assumption .

[0068] in, , , for Assume and Number of runs under the assumption; for Assuming the following operation is performed The optimal value of the test statistic for the second test. for Assuming the following operation is performed The optimal value of the test statistic for the second test. .

[0069] In some embodiments, detection threshold ;in, Indicates in Assuming the following Arranged in descending order, This indicates that the data is rounded up; PFA represents the preset false alarm probability. This indicates that the data is sorted in descending order.

[0070] In practical use, the target determination module is specifically used to: compare the optimal value of the detection statistic with the detection threshold to detect whether the target exists, such as... Figure 2 As shown, it specifically includes:

[0071] In step 301, if the detection statistic is optimal... Greater than or equal to the detection threshold If so, then the target is determined to exist.

[0072] In step 302, if the detection statistic is optimal... Less than the detection threshold If the target does not exist, then it is determined that the target does not exist.

[0073] In a practical application scenario, the data matrix of the unit to be detected Training sample matrix and training sample matrix It is pre-constructed; specifically, the expression for the data matrix of the unit to be detected is: ;in, Represents the complex amplitude of the target signal. express Gaussian interference noise vector, For the target incremental delay, , Indicates the radar baseband bandwidth. This is the joint transmit / receive steering vector. ;in, Indicates the Kronecker product. It represents the Hadamah accumulation. Indicates the receiving guide vector. The superscript indicates the guide vector representing the distance offset of the target within the cell. Indicates transpose. represents an imaginary number, Indicates the reference carrier wavelength. For the frequency to increase, This represents the spatiotemporal modulation process of the transmitted signal in the angle-range domain. , From elements Composition, and , Indicates the first The matched filter pair for the _th The output response of each transmitted waveform This represents the transmitted signal waveform of a frequency diversity array multiple-input multiple-output radar. , This indicates the conjugate operation. Indicates the pulse width. The number of elements in the transmitting array. For the number of receiving array elements, The distance between array elements.

[0074] The frequency diversity array multi-input multi-output radar target detection method provided in this embodiment does not require independent filtering and constant false alarm rate (CFAR) processing steps, and has adaptive detection capability for targets with unknown positions within the range cell. It maintains good detection performance even under strong noise suppression interference environments. This method significantly improves the target detection capability of radar systems in complex electromagnetic environments and can also ensure robust detection of unknown target positions; it is suitable for large-sample, stable interference scenarios, ensuring that the detector achieves target detection with a high probability.

[0075] Example 2:

[0076] Based on the method described in Embodiment 1, this invention combines specific application scenarios and uses technical descriptions in relevant scenarios to illustrate the implementation process of the features of this invention in those scenarios.

[0077] Due to noise suppression interference, the transmitted and received signals of frequency diversity array multi-input multi-output radar are easily affected by interference. Its covariance matrix needs to be estimated based on training samples, and the statistical characteristics of the interference signal are often unknown and time-varying, significantly degrading the performance of traditional detection algorithms based on fixed interference models. Furthermore, the uncertainty of target position parameters makes it difficult to accurately obtain incremental distance, further reducing the performance of traditional detectors. To address the adaptive detection problem of frequency diversity array multi-input multi-output radar under noise suppression interference conditions, this invention provides a target detection method for frequency diversity array multi-input multi-output radar, illustrated by the following application scenario:

[0078] Assume the number of transmitting array elements in a frequency diversity array multiple-input multiple-output radar system is . The number of receiving array elements is The spacing between array elements is A far-field point source is located at the azimuth angle. In this case, when the data to be detected contains both targets and noise, the data to be detected can be used. A dimensional vector is represented as:

[0079]

[0080] in, Represents the complex amplitude of the target signal. express Gaussian interference noise vector, For the target incremental delay, , Indicates the radar baseband bandwidth. For joint transmit / receive steering vector, and , Indicates the Kronecker product. It represents the Hadamah accumulation. Indicates the receiving guide vector. The superscript indicates the guide vector representing the distance offset of the target within the cell. Indicates transpose. represents an imaginary number, Indicates the reference carrier wavelength. For the frequency to increase, This represents the spatiotemporal modulation process of the transmitted signal in the angle-range domain. , From elements Composition, and , Indicates the first The matched filter pair for the _th The output response of each transmitted waveform This represents the transmitted signal waveform of a frequency diversity array multiple-input multiple-output radar. , Indicates the pulse width.

[0081] The frequency diversity array multi-input multi-output radar target detection method provided in this embodiment, such as Figure 3 and Figure 4 As shown, it includes:

[0082] In step 401, the target space-time steering vector, the sampling covariance matrix, and the data matrix of the unit to be detected are determined.

[0083] In step 402, the detection statistics of the Wald criterion are designed and processed in an integrated manner.

[0084] In step 403, the detection problem is transformed into a convex optimization problem, and an optimization model based on semidefinite programming is constructed.

[0085] In step 404, the optimization problem is solved to obtain the optimal value of the detection statistic.

[0086] In step 405, the detection threshold is determined based on system parameters, the system's preset false alarm probability, and the optimization model based on semidefinite programming.

[0087] In step 406, the optimal value of the detection statistic is compared with the detection threshold to determine whether the target exists. If the detection statistic is less than the detection threshold, the target is determined not to exist; if the detection statistic is greater than or equal to the detection threshold, the target is determined to exist.

[0088] The constructed data matrix of the unit to be detected and the training sample matrix are respectively represented as follows: and ( Both have a dimension of 1. ,in, This refers to the number of transmit elements in a frequency diversity array multiple-input multiple-output radar. For the number of receiving array elements, This indicates the number of training samples.

[0089] The sampling covariance matrix constructed using the training samples is denoted as ,for superscript This indicates the conjugate transpose.

[0090] The detection statistic with adjustable parameters and based on the Wald criterion is: In the formula, This indicates the absolute value operation.

[0091] The optimization model of the semidefinite programming is as follows: .

[0092] In the formula, Indicates the detection statistic The maximum value, Represents the set of real numbers. and express and All are positive semi-definite matrices, and and For Hermitian matrices, and Let these be the trigonometric polynomial coefficient vectors of the numerator and denominator of the detection statistic, respectively, and their expressions are as follows: , , and They are respectively represented as , , Representation matrix of OK Column elements, This indicates the conjugate operation. Representing vectors of One element, , This represents the spatiotemporal modulation process of the transmitted signal in the angle-range domain. , , ; and The two expressions are: , ,in , , ; This indicates the construction of a diagonal matrix. , , .

[0093] Step 405 specifically involves obtaining the detection statistic using a convex optimization tool. maximum value , respectively obtained Assume and The optimal value under the assumption, and That is, the Wald detection statistic based on semidefinite programming optimization;

[0094] When in Assume and Run them separately under the following assumptions At this time, the dimensions are all obtained. Statistical vector and superscript Indicates running the first Second-rate, ;exist Under the following assumptions, calculate the detection threshold: , , indicating in Assuming the following Arranged in descending order; This indicates that the data is rounded up; PFA represents the preset false alarm probability. This indicates that the data is sorted in descending order.

[0095] The step of comparing the optimal value of the detection statistic with the detection threshold to determine whether the target exists specifically involves: setting the optimal value of the detection statistic... With the detection threshold A comparison is made to determine whether the target exists. Specifically: if the detection statistic is optimal... Greater than or equal to the detection threshold If the detection statistic is optimal, then the target is determined to exist; Less than the detection threshold If the target does not exist, then it is determined that the target does not exist.

[0096] The method and system provided in this embodiment not only improve the theoretical framework of frequency diversity array multi-input multi-output radar detection, but also provide key technical support for practical system design, serving as fundamental work for radar target detection in complex environments. By solving the point target detection problem in Gaussian noise, it lays a methodological foundation for subsequent research on complex scenarios such as clutter and interference resistance, possessing significant theoretical and practical application value. The method described in this embodiment, by adjusting parameters, can optimize the waveform design and array configuration of frequency diversity array multi-input multi-output radar, applicable to large-sample, stationary interference scenarios, and particularly suitable for problems where the interference covariance matrix and target parameters are unknown, significantly improving robustness.

[0097] Figure 6 This is the method of this embodiment (actually, the detector that applies the method described in this embodiment). Figure 6 The curve with circles in it) and the existing 1S-GLRT-based detector ( Figure 6 (The curves marked with asterisks) are schematic diagrams illustrating the detection probability at different signal-to-interference-plus-noise ratios. It can be seen that, under suitable parameters, the method in this embodiment has a higher detection probability than the existing 1S-GLRT detector.

[0098] Example 3:

[0099] like Figure 7 The diagram shown is a schematic representation of the architecture of a frequency diversity array multi-input multi-output radar target detection device according to an embodiment of the present invention. The frequency diversity array multi-input multi-output radar target detection device of this embodiment includes one or more processors 21 and a memory 22. Figure 7 Take a processor 21 as an example.

[0100] Processor 21 and memory 22 can be connected via a bus or other means. Figure 7 Taking the example of a connection between China and Israel via a bus.

[0101] The memory 22, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs and non-volatile computer-executable programs, such as the frequency diversity array multi-input multi-output radar target detection method and / or the frequency diversity array multi-input multi-output radar target detection system in Embodiment 1. The processor 21 executes the frequency diversity array multi-input multi-output radar target detection method and / or implements the frequency diversity array multi-input multi-output radar target detection system in Embodiment 1 by running the non-volatile software programs and instructions stored in the memory 22.

[0102] Memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 22 may optionally include memory remotely located relative to processor 21, which can be connected to processor 21 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0103] The program instructions / modules are stored in the memory 22. When executed by one or more processors 21, they execute the frequency diversity array multi-input multi-output radar target detection method in Embodiment 1 above, and / or implement the frequency diversity array multi-input multi-output radar target detection system in Embodiment 1.

[0104] It is worth noting that the information interaction and execution process between the modules and units in the above-mentioned device and system are based on the same concept as the processing method embodiment of the present invention. For details, please refer to the description in the method embodiment of the present invention, and will not be repeated here.

[0105] Those skilled in the art will understand that all or part of the steps in the various methods of the embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0106] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A frequency diversity array multi-input multi-output radar target detection system, characterized in that, It includes a detection statistics construction module, a detection optimization module, a detection threshold determination module, and a target determination module; among which: The detection statistics construction module is used to construct detection statistics using the data matrix of the unit to be detected and the Wald criterion. ;in, For the sampling covariance matrix, Represents the mean vector of the training sample matrix. This indicates the conjugate transpose. For joint transmit / receive steering vector, The azimuth angle of the far-field point source. The target incremental delay; wherein, the mean vector of the training sample matrix. It is pre-built; The detection optimization module is used to optimize the detection based on the detection statistics. Construct a semidefinite programming optimization model; the optimization model is as follows: ; in, Indicates the detection statistic The maximum value, Represents the set of real numbers. and express and All are positive semi-definite matrices, and and For Hermitian matrices, The number of elements in the transmitting array. and Describes the constructed matrix. , , , , ; This indicates the construction of a diagonal matrix. It represents the Hadamah accumulation. , This represents the vector of triangular polynomial coefficients in the numerator of the detection statistic. This represents the vector of trigonometric polynomial coefficients in the denominator of the detection statistic. , , Indicates the radar baseband bandwidth; The detection threshold determination module is used to: solve the optimization model using a convex optimization method, and run it several times to obtain... Optimal value vector of detection statistics under the assumption and Optimal value vector of detection statistics under the assumption ;in, , , for Assume and Number of runs under the assumption; for Assuming the following operation is performed The optimal value of the test statistic for the second test. for Assuming the following operation is performed The optimal value of the test statistic for the second test. ; The target determination module is used to compare the optimal value of the detection statistics with the detection threshold to detect whether the target exists.

2. The frequency diversity array multi-input multi-output radar target detection system according to claim 1, characterized in that, The sampling covariance matrix , For the training sample matrix, This represents the number of training samples; where the training sample matrix... It is pre-built.

3. The frequency diversity array multi-input multi-output radar target detection system according to claim 1, characterized in that, The triangular polynomial coefficient vector of the numerator of the detection statistic ; in, , Representation matrix of OK The elements of the column.

4. The frequency diversity array multi-input multi-output radar target detection system according to claim 1, characterized in that, The trigonometric polynomial coefficient vector of the denominator of the detection statistic ; in, , This indicates the conjugate operation. Representing vectors of One element, , This represents the spatiotemporal modulation process of the transmitted signal in the angle-range domain. , , Indicates the receiving guide vector. For the number of receiving array elements, The number of elements in the transmitting array. For the spacing between array elements, Indicates the reference carrier wavelength.

5. The frequency diversity array multi-input multi-output radar target detection system according to claim 1, characterized in that, The detection threshold is ;in, Indicates in Assuming the following Arranged in descending order, This indicates that the data is rounded up; PFA represents the preset false alarm probability. This indicates that the data is sorted in descending order.

6. The frequency diversity array multi-input multi-output radar target detection system according to claim 5, characterized in that, The target determination module is specifically used for: if the detection statistic is optimal... Greater than or equal to the detection threshold If the detection statistic is optimal, then the target is determined to exist; Less than the detection threshold If the target does not exist, then it is determined that the target does not exist.

7. The frequency diversity array multi-input multi-output radar target detection system according to claim 1, characterized in that, The expression for the data matrix of the unit to be detected is: ;in, Represents the complex amplitude of the target signal. express Gaussian interference noise vector, For the target incremental delay, , Indicates the radar baseband bandwidth. For joint transmit / receive steering vector; The expression for the mean vector of the training sample matrix is: ;in, The number of training samples, .

8. The frequency diversity array multi-input multi-output radar target detection system according to claim 7, characterized in that, The joint transmit / receive steering vector ; in, Indicates the Kronecker product. It represents the Hadamah accumulation. Indicates the receiving guide vector. The superscript indicates the guide vector representing the distance offset of the target within the cell. Indicates transpose. represents an imaginary number, Indicates the reference carrier wavelength. For the frequency to increase, This represents the spatiotemporal modulation process of the transmitted signal in the angle-range domain. , From elements Composition, and , Indicates the first The matched filter pair for the _th The output response of each transmitted waveform This represents the transmitted signal waveform of a frequency diversity array multiple-input multiple-output radar. , This indicates the conjugate operation. Indicates the pulse width. The number of elements in the transmitting array. For the number of receiving array elements, The distance between array elements.

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