Zero-power target positioning method based on unmanned swarm

Abstract

The present invention relates to the technical field of distributed unmanned cluster target positioning, and provides a zero-power target positioning method based on unmanned clusters, comprising: calculating baseline distances between different unmanned cluster receiving nodes and opportunistic radiation sources, then constructing baseline distance differences between different unmanned cluster receiving nodes using the unmanned cluster receiving node with the closest baseline distance as a reference, and then solving for the position of an unknown opportunistic radiation source based on a measurement set of baseline distance differences; calculating bistatic distances corresponding to different opportunistic radiation source-target-unmanned cluster receiving node pairs based on the position of the unknown opportunistic radiation source, and then constructing bistatic distance differences between different unmanned cluster receiving nodes using the unmanned cluster receiving node with the closest baseline distance as a reference, and then solving for the target position based on the measurement set of bistatic distance differences. The present invention can achieve target positioning without the target itself radiating any electromagnetic signals.

Description

Technical Field

[0001] The present invention relates to the technical field of target positioning of distributed unmanned clusters, and in particular to a zero-power target positioning method based on unmanned clusters. Background Art

[0002] Currently, in many fields such as maritime patrol, traffic control, and disaster emergency rescue, the use of drones and unmanned boats equipped with video, infrared, and laser ranging sensors to monitor key areas of concern has become an important means of obtaining environmental and target information. However, in complex environments, the problem of situational monitoring based on unmanned platforms has become extremely complex due to various factors such as the diversity of tasks and limited time, the limited resources of unmanned platforms and the uncertainty of targets, and the increasingly complex environment of the mission area. As a result, the mission execution efficiency of a single unmanned platform will be extremely limited, and the efficient collaborative cooperation model of unmanned swarms will inevitably emerge. Clustering is also a key development direction for unmanned systems.

[0003] In an information-based and networked environment, the traditional "platform-centric" situational awareness model has shifted to a "network-centric" multi-platform distributed collaborative awareness model. Regarding the target positioning problem in unmanned swarms, numerous solutions have been proposed in public literature, primarily based on hyperbolic and elliptical cross-localization. The former relies on measuring the time difference of arrival (TDOA) of signals (radar or communication signals) emitted by the target of interest, sending these measurements to a fusion center for centralized target positioning. The latter, commonly referred to as passive coherent localization in the passive radar field, primarily relies on receiving signals emitted by secondary scattered opportunistic emitters to determine the target's bistatic range. Cross-localization is then performed using different measurements from different opportunistic emitter-receiver pairs to determine the target's position. It is important to note that this localization method requires the known position of the opportunistic emitter and the aid of intercepting the arrival time of the direct wave signal at all receiving nodes. Therefore, when the position of the opportunistic emitter cannot be determined in advance or when line-of-sight limitations make it difficult for all receiving nodes to reliably obtain the direct wave signal, the problem of locating zero-power targets that do not emit any electromagnetic signals becomes a major challenge in the situational awareness of unmanned swarms. Summary of the Invention

[0004] The purpose of the present invention is to solve at least one technical problem in the background technology and provide a zero-power target positioning method based on unmanned clusters.

[0005] To achieve the above objectives, the present invention provides a zero-power target positioning method based on unmanned clusters, comprising:

[0006] Calculate the baseline distances between different unmanned cluster receiving nodes and the opportunistic radiator. Then, using the unmanned cluster receiving node with the closest baseline distance as a reference, construct the baseline distance difference between different unmanned cluster receiving nodes. Then, based on the measurement set of baseline distance differences, solve the position of the unknown opportunistic radiator.

[0007] Based on the position of the unknown opportunistic emitter, the bistatic distances corresponding to different opportunistic emitter-target-unmanned cluster receiving node pairs are calculated. Then, with the unmanned cluster receiving node with the closest baseline distance as a reference, the bistatic distance differences between different unmanned cluster receiving nodes are constructed. The target position is then calculated based on the measurement set of the bistatic distance differences.

[0008] According to one aspect of the present invention, the step of calculating baseline distances between different unmanned cluster receiving nodes and the opportunistic radiation source, and then constructing baseline distance differences between different unmanned cluster receiving nodes using the unmanned cluster receiving node with the closest baseline distance as a reference, includes:

[0009] The computer will pair the radiation source with the jth unmanned cluster receiving node The corresponding baseline distance is , where t is the opportunity radiation source, For the j Unmanned cluster receiving nodes, express The model;

[0010] Receive the node with the first unmanned cluster As the reference node, the baseline distance difference between different nodes is obtained for:

[0011]

[0012] Square both sides of equation (1) and simplify it to get:

[0013]

[0014] According to one aspect of the present invention, the method of calculating the position of an unknown source of opportunity based on a measurement set of baseline distance differences includes:

[0015] Receive the node with the first unmanned cluster As the reference node, the arrival time of the direct wave received between the unmanned cluster receiving nodes is used. , calculate the baseline distance difference between different nodes containing measurement errors for:

[0016]

[0017] Where, , is the measurement error of the baseline distance difference; The mean is zero and the variance is And independent and identically distributed Gaussian random noise; further use the baseline distance difference of the measurement error The true value of the baseline distance difference for:

[0018]

[0019] The true value of the baseline distance difference Substitute into equation (2) and ignore the square term of the measurement error of the baseline distance difference ,get , and further expressed in matrix form:

[0020]

[0021] Where, , , , , ,and is a zero-mean Gaussian vector;

[0022] Based on the least squares criterion, the position of the unknown opportunity radiation source t is solved using formula (5):

[0023] .

[0024] According to one aspect of the present invention, the step of calculating the bistatic distances corresponding to different opportunistic radiation source-target-unmanned cluster receiving node pairs based on the position of the unknown radiation source, and then constructing the bistatic distance differences between different unmanned cluster receiving nodes with the unmanned cluster receiving node closest to the baseline distance as a reference, includes:

[0025] Based on the calculated position of the unknown opportunity radiation source t, calculate the first opportunity radiation source-target-unmanned cluster receiving node pair The corresponding bistatic distance is ,in express The model, express The model is obtained with the target The position of ;

[0026] Calculate the i-th opportunity radiation source-target-unmanned cluster receiving node pair The corresponding bistatic distance is , where express The difference between the dual-base distance between the i-th unmanned cluster receiving node and the first unmanned cluster receiving node is obtained by taking the modulus of for:

[0027] ,

[0028] Square both sides of equation (7) and simplify it to get:

[0029] .

[0030] According to one aspect of the present invention, the step of calculating the target position based on a measurement set of a bistatic range difference comprises:

[0031] Receive the node with the first unmanned cluster As the reference node, the arrival time of the target scattered echo received by the unmanned cluster receiving nodes is used. , calculate the difference in the bistatic distance containing the measurement error between the i-th unmanned cluster receiving node and the first unmanned cluster receiving node for:

[0032]

[0033] Where c is the speed of light; ; The mean is zero and the variance is And the Gaussian random noise is independent and identically distributed, then the difference between the bistatic distances of the i-th unmanned cluster receiving node and the first unmanned cluster receiving node is The analytical expression can be expressed as:

[0034]

[0035] The formula (10) is obtained Substitute into equation (8) and ignore the square term of the measurement error ,get , and further expressed in matrix form:

[0036]

[0037] Where, , , , , , is a zero-mean Gaussian vector;

[0038] Based on the least squares criterion, the target is obtained by using formula (11) The location is:

[0039]

[0040] Where, .

[0041] To achieve the above objectives, the present invention further provides a zero-power target positioning system based on unmanned clusters, comprising:

[0042] The unknown opportunistic emitter position calculation module calculates the baseline distances between different unmanned cluster receiving nodes and the opportunistic emitter. It then uses the unmanned cluster receiving node with the closest baseline distance as a reference to construct the baseline distance difference between different unmanned cluster receiving nodes. Based on the measurement set of the baseline distance difference, it calculates the position of the unknown opportunistic emitter.

[0043] The target position calculation module calculates the bistatic distances corresponding to different pairs of opportunity radiation sources, targets, and unmanned cluster receiving nodes based on the position of the unknown opportunity radiation source. It then constructs the bistatic distance differences between different unmanned cluster receiving nodes with the unmanned cluster receiving node closest to the baseline distance as a reference, and then calculates the target position based on the measurement set of the bistatic distance differences.

[0044] To achieve the above-mentioned objectives, the present invention also provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and runnable on the processor, wherein when the computer program is executed by the processor, the zero-power target positioning method based on unmanned cluster as described above is implemented.

[0045] To achieve the above objectives, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the zero-power target positioning method based on unmanned cluster is implemented as described above.

[0046] According to the solution of the present invention, compared with the traditional unmanned cluster target positioning method, the zero-power target positioning method based on unmanned cluster provided by the present invention can realize target positioning under the premise that the target itself does not radiate any electromagnetic signals, and does not require the position information of the opportunity radiation source to be mastered in advance. The opportunity radiation source platform can be stationary or moving, and its transmitting antenna can be omnidirectional or mechanically scanned. At the same time, it is not required that all receiving nodes can receive the direct wave signal emitted by the opportunity radiation source. It is suitable for complex electromagnetic confrontation conditions, and uses suppressive interference sources as opportunity radiation sources to solve the real-time positioning problem of interference sources and their shielded targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A flowchart schematically illustrates a zero-power target positioning method based on an unmanned cluster according to an embodiment of the present invention;

[0048] Figure 2 A topological diagram schematically illustrates unmanned cluster target positioning under the condition that the position of the opportunity radiation source is unknown according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only intended to enable those skilled in the art to better understand and implement the present invention, rather than to imply any limitation on the scope of the present invention.

[0050] As used herein, the term "including" and variations thereof are to be interpreted as open-ended terms meaning "including, but not limited to." The term "based on" is to be interpreted as "based, at least in part, on." The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment."

[0051] Figure 1 The flowchart of the zero-power target positioning method based on unmanned cluster according to one embodiment of the present invention is schematically shown. Figure 1 As shown, in this embodiment, the zero-power target positioning method based on unmanned cluster includes:

[0052] Calculate the baseline distances between different unmanned cluster receiving nodes and the opportunistic radiator. Then, using the unmanned cluster receiving node with the closest baseline distance as a reference, construct the baseline distance difference between different unmanned cluster receiving nodes. Then, based on the measurement set of baseline distance differences, solve the position of the unknown opportunistic radiator.

[0053] Based on the position of the unknown opportunistic emitter, the bistatic distances corresponding to different opportunistic emitter-target-unmanned cluster receiving node pairs are calculated. Then, with the unmanned cluster receiving node with the closest baseline distance as a reference, the bistatic distance differences between different unmanned cluster receiving nodes are constructed. The target position is then calculated based on the measurement set of the bistatic distance differences.

[0054] Further, according to one embodiment of the present invention, Figure 2 As shown in the figure, the unmanned cluster system includes N passive sensor nodes (i.e., unmanned cluster receiving nodes, hereinafter referred to as unmanned cluster receiving nodes), where , the location of each unmanned cluster receiving node is ; The zero-power target itself does not emit any electromagnetic signal, and the corresponding position is ; The position of the antenna mechanical scanning opportunity radiation source is , where the position of the opportunity radiator is unknown, but the signal emitted by the main lobe of the opportunity radiator antenna is secondary scattered by the zero-power target and can be intercepted by N nodes in the unmanned cluster. However, due to the limitation of line-of-sight propagation, only some nodes can receive the direct wave signal emitted by the opportunity radiator and measure the arrival time of the corresponding target secondary scattered signal and direct signal. Without loss of generality, assume that M unmanned cluster receiving nodes can receive the direct wave signal radiated by the side lobe of the opportunity radiator antenna, where , and the number of non-collinear nodes on any plane at the same time is greater than or equal to 3, and no one cluster receives nodes It can simultaneously intercept the echo of the secondary scattering of the zero-power target and the direct wave emitted by the opportunity radiation source, with the shortest baseline distance and an unmanned cluster receiving node. is the reference node.

[0055] Furthermore, according to an embodiment of the present invention, the baseline distances between different unmanned cluster receiving nodes and the opportunistic radiation source are calculated, and then the baseline distance differences between different unmanned cluster receiving nodes are constructed using the unmanned cluster receiving node with the closest baseline distance as a reference, including:

[0056] The computer will pair the radiation source with the jth unmanned cluster receiving node The corresponding baseline distance is , where t is the opportunity radiation source, is the jth unmanned cluster receiving node, express The model;

[0057] Receive the node with the first unmanned cluster As the reference node, the baseline distance difference between different nodes is obtained for:

[0058]

[0059] Square both sides of equation (1) and simplify it to get:

[0060] .

[0061] Furthermore, according to one embodiment of the present invention, the position of an unknown opportunistic radiator is calculated based on a set of baseline distance difference measurements, including:

[0062] Receive the node with the first unmanned cluster As the reference node, the arrival time of the direct wave received between the unmanned cluster receiving nodes is used. , calculate the baseline distance difference between different nodes containing measurement errors for:

[0063]

[0064] Where, , is the measurement error of the baseline distance difference; The mean is zero and the variance is And independent and identically distributed Gaussian random noise; further use the baseline distance difference of the measurement error The true value of the baseline distance difference for:

[0065]

[0066] The true value of the baseline distance difference Substitute into equation (2) and ignore the square term of the measurement error ,get , and further expressed in matrix form:

[0067]

[0068] Where, , , , , ,and is a zero-mean Gaussian vector;

[0069] Based on the least squares criterion, the position of the unknown opportunity radiation source t is solved using formula (5):

[0070] .

[0071] Furthermore, according to an embodiment of the present invention, based on the location of the unknown radiation source, the bistatic distances corresponding to different opportunistic radiation source-target-unmanned cluster receiving node pairs are calculated, and then the bistatic distance differences between different unmanned cluster receiving nodes are constructed using the unmanned cluster receiving node with the closest baseline distance as a reference, including:

[0072] Based on the calculated position of the unknown opportunity radiation source t, calculate the first opportunity radiation source-target-unmanned cluster receiving node pair The corresponding bistatic distance is ,in express The model, express The model is obtained by The position of ;

[0073] Calculate the i-th opportunity radiation source-target-unmanned cluster receiving node pair The corresponding bistatic distance is , where express The difference between the dual-base distance between the i-th unmanned cluster receiving node and the first unmanned cluster receiving node is obtained by taking the modulus of for:

[0074]

[0075] Square both sides of equation (7) and simplify it to get:

[0076] .

[0077] Furthermore, according to one embodiment of the present invention, obtaining the position of a target based on a measurement set of a bistatic range difference includes:

[0078] Receive the node with the first unmanned cluster As the reference node, the arrival time of the target scattered echo received by the unmanned cluster receiving nodes is used. , calculate the difference in the bistatic distance containing the measurement error between the i-th unmanned cluster receiving node and the first unmanned cluster receiving node for:

[0079]

[0080] Where c is the speed of light; ; The mean is zero and the variance is And the Gaussian random noise is independent and identically distributed, then the difference between the bistatic distances of the i-th unmanned cluster receiving node and the first unmanned cluster receiving node is The analytical expression can be expressed as:

[0081]

[0082] The formula (10) is obtained Substitute into equation (8) and ignore the square term of the measurement error ,get , and further expressed in matrix form:

[0083]

[0084] Where, , , , , , is a zero-mean Gaussian vector;

[0085] Based on the least squares criterion, the target is obtained by using formula (11) The location is:

[0086]

[0087] Where, .

[0088] According to the above scheme of the present invention, compared with the traditional unmanned cluster target positioning method, the zero-power target positioning method based on unmanned cluster provided by the present invention can realize target positioning under the premise that the target itself does not radiate any electromagnetic signals, and does not require the position information of the opportunity radiation source to be mastered in advance. The opportunity radiation source platform can be stationary or moving, and its transmitting antenna can be omnidirectional or mechanically scanned. At the same time, it is not required that all receiving nodes can receive the direct wave signal emitted by the opportunity radiation source. It is suitable for complex electromagnetic confrontation conditions, and uses suppressive interference sources as opportunity radiation sources to solve the real-time positioning problem of interference sources and their shielded targets.

[0089] Furthermore, to achieve the above objectives, the present invention also provides a zero-power target positioning system based on unmanned clusters, comprising:

[0090] The unknown opportunistic emitter position calculation module calculates the baseline distances between different unmanned cluster receiving nodes and the opportunistic emitter. It then uses the unmanned cluster receiving node with the closest baseline distance as a reference to construct the baseline distance difference between different unmanned cluster receiving nodes. Based on the measurement set of the baseline distance difference, it calculates the position of the unknown opportunistic emitter.

[0091] The target position calculation module calculates the bistatic distances corresponding to different pairs of opportunity radiation sources, targets, and unmanned cluster receiving nodes based on the position of the unknown opportunity radiation source. It then constructs the bistatic distance differences between different unmanned cluster receiving nodes with the unmanned cluster receiving node closest to the baseline distance as a reference, and then calculates the target position based on the measurement set of the bistatic distance differences.

[0092] The above-mentioned zero-power target positioning system based on unmanned cluster according to the present invention can implement the above-mentioned zero-power target positioning method based on unmanned cluster. The specific process steps are as described above and will not be repeated here.

[0093] Furthermore, to achieve the above-mentioned purpose, the present invention also provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the zero-power target positioning method based on the unmanned cluster as described above is implemented.

[0094] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the zero-power target positioning method based on unmanned cluster as described above is implemented.

[0095] Those skilled in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented using electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0096] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method implementation methods and will not be repeated here.

[0097] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0098] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the embodiments of the present invention.

[0099] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0100] If the functions are implemented as software modules and sold or used as standalone products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the energy-saving signal transmission / reception method according to various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, ROM, RAM, a magnetic disk, or an optical disk.

[0101] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

[0102] It should be understood that the size of the serial numbers of each step in the content of the invention and the implementation methods of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation methods of the present invention.

Claims

1. A zero-power target positioning method based on unmanned clusters, characterized in that: include: Calculate the baseline distances between different unmanned cluster receiving nodes and the opportunistic radiator. Then, using the unmanned cluster receiving node with the closest baseline distance as a reference, construct the baseline distance difference between different unmanned cluster receiving nodes. Then, based on the measurement set of baseline distance differences, solve the position of the unknown opportunistic radiator. Based on the position of the unknown opportunistic emitter, the bistatic distances corresponding to different opportunistic emitter-target-unmanned cluster receiving node pairs are calculated. Then, with the unmanned cluster receiving node with the closest baseline distance as a reference, the bistatic distance differences between different unmanned cluster receiving nodes are constructed. The target position is then calculated based on the measurement set of the bistatic distance differences.

2. The zero-power target positioning method based on unmanned cluster according to claim 1 is characterized in that: The calculation of the baseline distances between different unmanned cluster receiving nodes and the opportunity radiation source, and then constructing the baseline distance differences between different unmanned cluster receiving nodes with the unmanned cluster receiving node closest to the baseline distance as a reference, includes: The computer will pair the radiation source with the jth unmanned cluster receiving node The corresponding baseline distance is , where t is the opportunity radiation source, is the jth unmanned cluster receiving node, express The model; Receive the node with the first unmanned cluster As the reference node, the baseline distance difference between different nodes is obtained for: ， in, M For the M Unmanned cluster receiving nodes; Square both sides of equation (1) and simplify it to get: 。 3. The zero-power target positioning method based on unmanned cluster according to claim 2 is characterized in that: The measurement set based on the baseline distance difference is used to calculate the position of the unknown opportunistic radiation source, including: Receive the node with the first unmanned cluster As the reference node, the arrival time of the direct wave received between the unmanned cluster receiving nodes is used. , calculate the baseline distance difference between different nodes containing measurement errors for: ， Where, , is the measurement error of the baseline distance difference; The mean is zero and the variance is And independent and identically distributed Gaussian random noise; further use the baseline distance difference of the measurement error The true value of the baseline distance difference for: ， The true value of the baseline distance difference Substitute into equation (2) and ignore the square term of the measurement error of the baseline distance difference ,get , and further expressed in matrix form: ， Where, , , , , ,and is a zero-mean Gaussian vector; Based on the least squares criterion, the position of the unknown opportunity radiation source t is solved using formula (5): 。 4. The zero-power target positioning method based on unmanned cluster according to claim 3 is characterized in that: The method of calculating the bistatic distances corresponding to different pairs of opportunistic radiation sources, targets, and unmanned cluster receiving nodes based on the position of the unknown opportunistic radiation source, and then constructing the bistatic distance differences between different unmanned cluster receiving nodes with the unmanned cluster receiving node closest to the baseline distance as a reference, includes: Based on the calculated position of the unknown opportunity radiation source t, calculate the first opportunity radiation source-target-unmanned cluster receiving node pair The corresponding bistatic distance is ,in express The model, express The model is obtained by The position of ; Calculate the i-th opportunity radiation source-target-unmanned cluster receiving node pair The corresponding bistatic distance is , where express The difference between the dual-base distance between the i-th unmanned cluster receiving node and the first unmanned cluster receiving node is obtained by taking the modulus of for: ， in, N For the N Unmanned cluster receiving nodes; Square both sides of equation (7) and simplify it to get: 。 5. The zero-power target positioning method based on unmanned cluster according to claim 4 is characterized in that: The target position is obtained by solving the measurement set based on the bistatic range difference, including: Receive the node with the first unmanned cluster As the reference node, the arrival time of the target scattered echo received by the unmanned cluster receiving nodes is used. , calculate the difference in the bistatic distance containing the measurement error between the i-th unmanned cluster receiving node and the first unmanned cluster receiving node for: ， Where c is the speed of light; ; The mean is zero and the variance is And the Gaussian random noise is independent and identically distributed, then the difference between the bistatic distances of the i-th unmanned cluster receiving node and the first unmanned cluster receiving node is The analytical expression can be expressed as: ， The formula (10) is obtained Substitute into equation (8) and ignore the square term of the measurement error ,get , and further expressed in matrix form: ， Where, , , , , , is a zero-mean Gaussian vector; Based on the least squares criterion, the position of the target u is calculated using formula (11): ， Where, .

6. The zero-power target positioning system based on unmanned cluster is characterized by: include: The unknown opportunistic emitter position calculation module calculates the baseline distances between different unmanned cluster receiving nodes and the opportunistic emitter. It then uses the unmanned cluster receiving node with the closest baseline distance as a reference to construct the baseline distance difference between different unmanned cluster receiving nodes. Based on the measurement set of the baseline distance difference, it calculates the position of the unknown opportunistic emitter. The target position calculation module calculates the bistatic distances corresponding to different pairs of opportunity radiation sources, targets, and unmanned cluster receiving nodes based on the position of the unknown opportunity radiation source. It then constructs the bistatic distance differences between different unmanned cluster receiving nodes with the unmanned cluster receiving node closest to the baseline distance as a reference, and then calculates the target position based on the measurement set of the bistatic distance differences.

7. An electronic device, characterized in that The invention comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the zero-power target positioning method based on an unmanned cluster is implemented as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the zero-power target positioning method based on an unmanned cluster is implemented according to any one of claims 1 to 5.

Images