An air moving target positioning method, device, medium and product based on a ground-based distributed passive detection system

Abstract

The application discloses an air moving target positioning method and device based on a ground-based distributed passive detection system, a medium and a product, and relates to the field of target positioning. The method comprises the following steps: optimizing the layout of receiving stations in the ground-based distributed passive detection system by using a genetic algorithm to obtain an optimal non-uniform receiving station deployment structure; determining a spatial Doppler signal history based on signals radiated by an air moving target and received by each receiving station in the optimal non-uniform receiving station deployment structure; dividing a space to be measured into spatial grids according to slant range, azimuth angle and pitch angle, calculating the theoretical propagation distance of a grid point to a receiving station, and constructing a corresponding theoretical Doppler signal history; performing coherent accumulation on the theoretical Doppler signal history and the spatial Doppler signal history, constructing a spatial positioning cost function, searching for the peak position of the spatial positioning cost function, and determining the position of the air moving target. The application can realize high-precision and high-robustness positioning of the air moving target under the condition of a single fast shot.

Description

Technical Field

[0001] This application relates to the field of target positioning, and in particular to a method, device, medium and product for locating aerial moving targets based on a ground-based distributed passive detection system. Background Technology

[0002] Traditional multi-station passive localization methods are typical geometric localization systems, whose accuracy is highly dependent on the spatial configuration of the observation stations. Under poor geometric conditions, they are prone to a large GDOP (Geometric Dilution of Precision) effect. For moving targets, since the target state changes rapidly over time, traditional multi-station passive localization often needs to complete the localization within a short observation window, resulting in a single-shot or few-shot localization problem. Under these conditions, traditional algorithms struggle to obtain stable statistical properties, making them highly sensitive to noise, synchronization errors, and model mismatch, and significantly reducing localization robustness. Summary of the Invention

[0003] The purpose of this application is to provide a method, device, medium and product for locating aerial moving targets based on a ground-based distributed passive detection system, which can achieve high-precision and robust positioning of aerial moving targets under single-shot conditions.

[0004] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a method for locating aerial moving targets based on a ground-based distributed passive detection system, including: The optimal non-uniform receiver station deployment structure in the ground-based distributed passive detection system was obtained by optimizing the receiver station layout using a genetic algorithm. The spatial Doppler signal history is determined based on the signals radiated by airborne moving targets received by each receiving station in the optimal non-uniform receiving station deployment structure. The airspace to be measured is divided into spatial grids according to slant range, azimuth angle and elevation angle. The theoretical propagation distance from the grid point to the receiving station is calculated, and the corresponding theoretical Doppler signal history is constructed. By coherently accumulating the theoretical Doppler signal history with the spatial Doppler signal history at the same moment, a spatial positioning cost function is constructed. By searching for the peak position of the spatial positioning cost function, the position of the airborne moving target is determined, thus achieving the positioning of the airborne moving target.

[0005] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for locating aerial moving targets based on a ground-based distributed passive detection system.

[0006] Thirdly, this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for locating aerial moving targets based on a ground-based distributed passive detection system.

[0007] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for locating aerial moving targets based on a ground-based distributed passive detection system.

[0008] According to the specific embodiments provided in this application, this application has the following technical effects: (1) This application obtains the optimal non-uniform receiving station deployment through global optimization using a genetic algorithm, which reduces the sidelobe level of the spatial response, reduces positioning ambiguity, and improves positioning reliability under complex geometric conditions.

[0009] (2) This application uses the theoretical Doppler signal history and the spatial Doppler signal history at the same time to coherently accumulate and construct a spatial positioning cost function. By searching for the peak position of the spatial positioning cost function, high-precision and high-robust positioning of aerial moving targets is achieved under single snapshot conditions. It solves the problems that the positioning accuracy of traditional multi-station passive positioning methods is limited by the spatial configuration of the observation station, and the problems that the single snapshot positioning statistical stability is poor and the robustness is insufficient in scenarios where moving targets change rapidly. It improves the accuracy and reliability of moving target positioning in complex environments. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 A flowchart illustrating an aerial moving target localization method based on a ground-based distributed passive detection system, provided as an embodiment of this application; Figure 2 This is a geometric model diagram of a ground-based distributed passive detection system for locating moving targets in the air. Detailed Implementation

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. 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.

[0013] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0014] In one exemplary embodiment, such as Figure 1 As shown, an aerial moving target localization method based on a ground-based distributed passive detection system is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is described using a server as an example, and includes the following steps S1 to S4.

[0015] S1: The optimal non-uniform receiving station deployment structure is obtained by optimizing the receiving station layout in the ground-based distributed passive detection system using a genetic algorithm.

[0016] Specifically, this includes: using the planar coordinate parameters of each receiving station as genetic code individuals to initialize the population; for each individual in the current population corresponding to the receiving station layout, calculating the main lobe peak and the maximum sidelobe peak based on the spatial array response formed by the receiving station layout, and constructing the peak sidelobe level; with minimizing the peak sidelobe level as the optimization objective, sequentially performing fitness evaluation, selection, crossover, and mutation operations to iteratively optimize the receiving station layout and obtain the optimal non-uniform receiving station deployment structure.

[0017] For each individual in the current population and the corresponding receiver layout, a spatial array response is constructed, and the peak value of the main lobe and the peak value of the maximum sidelobe are calculated. The peak-sidelobe level (PSLL) is used as the fitness evaluation index. Based on this, the individuals in the population are ranked by fitness, and a selection operation is performed to retain individuals with high fitness. A crossover operation is performed on the selected individuals to generate new receiver layout individuals. At the same time, a mutation operation is introduced to perturb the coordinate parameters of the individuals to enhance the population diversity. The fitness evaluation, selection, crossover, and mutation iteration process is repeated until the convergence condition is met or the maximum number of iterations is reached. Finally, the receiver spatial layout corresponding to the minimum PSLL is obtained, which is the optimal non-uniform receiver deployment structure.

[0018] Assume the number of receiving stations N in the ground-based distributed radar system is 36, and the aperture is... The minimum distance between receiving stations is 30m.

[0019] Let the location of the receiving station be To ensure the aperture and minimum spacing, , The distance between any two stations This creates the population of individuals. If the number of individuals V in the population is 100, then the population can be represented as: .

[0020] The peak sidelobe level is: in, The main lobe peak value, This represents the maximum sidelobe peak value.

[0021] individual The fitness function is in These are the fitness function adjustment parameters.

[0022] Sort individuals by fitness and retain those with high fitness. Assume a crossover probability of 0.9 and a mutation probability of 0.05. Generate new individuals through crossover and mutation operations to form a new population. Repeat this process until the convergence condition is met or the maximum number of iterations is reached to obtain the optimal non-uniform receiving station deployment structure. in, This represents the optimal non-uniform receiving station deployment structure. This represents the set of receiving station locations.

[0023] S2: Determine the spatial Doppler signal history based on the signals radiated by moving targets in the air received by each receiving station in the optimal non-uniform receiving station deployment structure.

[0024] Specifically, this includes: downconverting the signals radiated by moving targets in the air received by each receiving station in the optimal non-uniform receiving station deployment structure to obtain baseband signals; and for each positioning time, modulating the baseband signals of each receiving station and recombining them into a space Doppler signal history.

[0025] like Figure 2 As shown, assume a drone carrying a radiation source (i.e., an aerial moving target) is maneuvering at a speed of 200 m / s. The number of receiving stations N in the ground-based distributed passive detection system is 36, and the aperture is... The minimum distance between receiving stations is 30m. (Radiation source carrier frequency) The frequency is 2GHz. At the initial moment, the UAV is 10km away from the ground reference station, and the azimuth and elevation angles of the reference station are 30° and 45°, respectively. Figure 2 middle, , , ... These are the coordinates of the receiving station.

[0026] The coordinates of the nth receiving station Coordinates of moving targets in the air The instantaneous distance from the moving aerial target to the receiving station is : in, Let m be the instantaneous distance from the moving target in space to the nth receiving station at positioning time. In this embodiment, the positioning period is... .

[0027] The baseband signals of each receiving station are modulated based on the instantaneous distance from the moving target in the air to the receiving station to obtain the spatial Doppler signal history: in, The spatial Doppler signal history at the nth receiving station at positioning time m. It is the speed of light.

[0028] S3: Divide the airspace to be measured into a spatial grid according to slant range, azimuth angle and elevation angle, calculate the theoretical propagation distance from the grid point to the receiving station, and construct the corresponding theoretical Doppler signal history.

[0029] Specifically, arbitrarily select a receiving station. Using the reference station, the target space to be searched (i.e., the airspace to be measured) is discretized into a grid according to slant range, azimuth angle, and elevation angle. The T-th grid point is... , These are the slope distance, azimuth, and elevation angles of the T-th grid point, respectively. The rectangular coordinates corresponding to the T-th grid point are... The relationship between the two is as follows: In this embodiment, the slant range corresponding to the spatial domain to be measured The search range is 8000 meters to 12000 meters, with a search step size of 1 meter; azimuth angle The search range is 25° to 35°, pitch angle The search range is 35° to 45°, and the search step size is 0.01°.

[0030] The theoretical propagation distance from the grid point to the receiving station is: in, Let T be the theoretical propagation distance from the T-th grid point to the n-th receiving station.

[0031] Construct the corresponding theoretical Doppler signal history in, This represents the theoretical Doppler signal history of the nth receiving station for the Tth grid point.

[0032] S4: By coherently accumulating the theoretical Doppler signal history with the spatial Doppler signal history at the same moment, a spatial positioning cost function is constructed. By searching for the peak position of the spatial positioning cost function, the position of the moving target in the air is determined, thus realizing the positioning of the moving target in the air.

[0033] The spatial positioning cost function is expressed as: in, Let T be the spatial location cost function corresponding to the T-th grid point. It is the conjugate of the theoretical Doppler signal history of the nth receiving station for the Tth grid point.

[0034] By searching for the peak position of the localization cost function, the position of the spatially moving target at the current localization time can be obtained. in, Let m be the position of the spatially moving target at time m.

[0035] By constructing a spatial positioning cost function, high-precision and robust positioning of aerial moving targets is achieved under single-shot conditions. This solves the problems of positioning accuracy being limited by the spatial configuration of the observation station in traditional multi-station passive positioning methods, as well as the poor statistical stability and insufficient robustness of single-shot positioning in scenarios with rapidly changing moving targets. It significantly improves the accuracy and reliability of moving target positioning in complex environments.

[0036] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments. The computer device can be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, memory, and I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device stores data to be processed. The I / O interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with an external terminal via a network connection. When the computer program is executed by the processor, it implements the steps in the above-described method embodiments.

[0037] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0038] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0039] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0040] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0041] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0042] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0043] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for locating aerial moving targets based on a ground-based distributed passive detection system, characterized in that, include: The optimal non-uniform receiver station deployment structure in the ground-based distributed passive detection system was obtained by optimizing the receiver station layout using a genetic algorithm. The spatial Doppler signal history is determined based on the signals radiated by airborne moving targets received by each receiving station in the optimal non-uniform receiving station deployment structure. The airspace to be measured is divided into spatial grids according to slant range, azimuth angle and elevation angle. The theoretical propagation distance from the grid point to the receiving station is calculated, and the corresponding theoretical Doppler signal history is constructed. By coherently accumulating the theoretical Doppler signal history with the spatial Doppler signal history at the same moment, a spatial positioning cost function is constructed. By searching for the peak position of the spatial positioning cost function, the position of the airborne moving target is determined, thus achieving the positioning of the airborne moving target.

2. The method for locating aerial moving targets based on a ground-based distributed passive detection system according to claim 1, characterized in that, The distribution of receiving stations in a ground-based distributed passive detection system is optimized using a genetic algorithm to obtain the optimal non-uniform receiving station deployment structure, specifically including: The population was initialized using the planar coordinate parameters of each receiving station as genetically encoded individuals; For each individual in the current population, the main lobe peak value and the maximum side lobe peak value are calculated based on the spatial array response formed by the receiver station layout, and the peak side lobe level is constructed. With minimizing peak sidelobe levels as the optimization objective, fitness evaluation, selection, crossover, and mutation operations are performed sequentially to iteratively optimize the receiver layout and obtain the optimal non-uniform receiver deployment structure.

3. The method for locating aerial moving targets based on a ground-based distributed passive detection system according to claim 1, characterized in that, The spatial Doppler signal history is determined based on the signals radiated by airborne moving targets received by each receiving station in an optimal non-uniform receiving station deployment structure, specifically including: The signals radiated by moving aerial targets received by each receiving station in the optimal non-uniform receiving station deployment structure are down-converted to obtain baseband signals; For each positioning time, the baseband signals of each receiving station are modulated and recombined into a spatial Doppler signal history.

4. The method for locating aerial moving targets based on a ground-based distributed passive detection system according to claim 2, characterized in that, The expression for the spatial Doppler signal history is: in, The spatial Doppler signal history at the nth receiving station at positioning time m. Let m be the instantaneous distance from the moving target in space to the nth receiving station at positioning time m. The carrier frequency of the radiation source carried by the aerial moving target. It is the speed of light.

5. The method for locating aerial moving targets based on a ground-based distributed passive detection system according to claim 1, characterized in that, The theoretical propagation distance from the grid point to the receiving station is expressed as: in, Let T be the theoretical propagation distance from the T-th grid point to the n-th receiving station. Let these be the coordinates of the nth receiving station. Let T be the rectangular coordinates of the T-th grid point.

6. The method for locating aerial moving targets based on a ground-based distributed passive detection system according to claim 5, characterized in that, The theoretical Doppler signal history is expressed as: in, The theoretical Doppler signal history of the nth receiving station for the Tth grid point is given. The carrier frequency of the radiation source carried by the aerial moving target. It is the speed of light.

7. The method for locating aerial moving targets based on a ground-based distributed passive detection system according to claim 1, characterized in that, The spatial positioning cost function is expressed as: in, Let T be the spatial location cost function corresponding to the T-th grid point. These are the slant range, azimuth, and elevation angle of the T-th grid point, respectively. For the conjugate of the theoretical Doppler signal history of the nth receiving station with respect to the Tth grid point, Let N be the spatial Doppler signal history corresponding to the nth receiving station, where N is the number of receiving stations.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the aerial moving target localization method based on a ground-based distributed passive detection system as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the aerial moving target localization method based on a ground-based distributed passive detection system as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the aerial moving target localization method based on a ground-based distributed passive detection system as described in any one of claims 1-7.

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