Station layout optimization and system under non-cooperative target angle measurement positioning

Abstract

An embodiment of the present invention provides a station layout optimization method system for non-cooperative target angular positioning. The method includes: constructing an index for evaluating the positioning accuracy of a station layout configuration based on index elements for evaluating positioning accuracy; determining the optimal weights corresponding to the index elements of the cooperative target trajectory by optimizing the constructed index based on historical measurement data of the cooperative target trajectory; obtaining a motion direction vector of the non-cooperative target trajectory, using the optimal weights corresponding to the index elements of the optimized trajectory as the optimal weights corresponding to the index elements of the non-cooperative target trajectory; obtaining actual measurement data obtained based on the motion direction vector of the non-cooperative target trajectory, and using the preliminary station layout configuration corresponding to the minimum index value as the optimal station layout configuration for positioning the non-cooperative target; and locating and tracking the non-cooperative target using the station layout solution within the optimal station layout configuration. The station layout optimization can be completed using only the direction vector connecting the target's starting point and end point, without relying on a theoretical trajectory.

Description

Technical Field

[0001] The present invention relates to the field of station layout configuration, and in particular to a station layout optimization and system under non-cooperative target angle measurement and positioning. Background Art

[0002] With the continuous advancement of modern information technology, warfare environments are increasingly adopting a new trend towards informatization, and electronic countermeasures are gradually emerging in modern warfare. Using active positioning to locate targets can easily expose one's position, making it vulnerable to targeted attacks. Passive positioning, on the other hand, offers advantages such as high concealment, low bandwidth requirements, and long range. With the continuous improvement of measurement technology, signal interception and processing capabilities are also increasing simultaneously, and the application of passive positioning technology in the field of electronic countermeasures is becoming increasingly widespread.

[0003] In passive positioning systems, there are generally two types of target positioning methods: direct and indirect. Direct positioning methods are more difficult to obtain target signals in complex environments, so passive positioning systems generally use indirect positioning methods to locate targets. Indirect positioning methods measure a series of parameters related to the target's position and use these parameters to locate the target. Depending on the type of sensor measurement value, indirect positioning methods in passive positioning can be divided into single-station / multi-station positioning technologies based on angle of arrival (AOA), multi-station positioning technologies based on time of arrival (TOA), and multi-station time difference positioning technologies based on time difference of arrival (TDOA). Compared with other indirect positioning methods, AOA requires fewer measurement devices and has simpler time alignment preprocessing. Therefore, research on AOA and its application scenarios are increasing.

[0004] Key AOA technologies primarily include target positioning and site selection (hereafter referred to as site placement). While positioning technology has been extensively researched and mature, site placement, particularly for non-cooperative target positioning, has been less studied. Site placement optimization involves establishing a reasonable site geometry and topology within certain constraints to improve the effectiveness of the measurement system. When equipment errors and target trajectory are largely determined, site geometry becomes the sole factor influencing target positioning accuracy.

[0005] Currently, there are many methods for determining the optimal positioning configuration for passive angle-based positioning systems. These methods can be broadly categorized as analytical methods and intelligent optimization methods. Analytical methods are generally used for special or regular positioning schemes, and theoretical derivation leads to optimal positioning schemes for several special positioning configurations. For example, the positioning node selection problem is transformed into a non-convex optimization problem, and a semi-positive programming method is used under rectangular positioning conditions to study the optimal positioning node selection problem in TDOA. For example, the relationship between the intersection angle and the circular error radius (COE) is analyzed for a triangular positioning system. By calculating the optimal intersection angle for different positioning accuracies, an optimal positioning method is proposed. For example, the positioning results of eight regular positioning systems are presented, demonstrating the need for different positioning configurations based on the actual environment and target trajectory. Furthermore, the Cramer-Rao lower bound (CRLB) is derived, concluding that an optimal sensor layout can be achieved by forming a equiangular polygon surrounding the target with any number of sensors. Since most analytical methods only consider special positioning scenarios, and the complex spatial environment of real-world positioning systems generally makes it impossible to achieve an ideal regular positioning system, analytical positioning methods are not universally applicable.

[0006] With the development of intelligent algorithms, an increasing number of researchers are utilizing intelligent optimization methods to solve the optimal station layout problem, primarily including evolutionary algorithms, particle swarm optimization (PSO), and neural networks. For example, genetic algorithms are used to search for optimal station locations, with the positioning accuracy metric being the trace of the CRLB. Obtaining the optimal station location is transformed into an optimal solution problem, with the positioning accuracy of the entire target area as the objective function, and the optimal solution is sought. Alternatively, using the trace of the CRLB as the accuracy metric, a particle swarm algorithm is used to study the optimal station layout for different numbers of stations. Alternatively, using genetic algorithms with the geometric dilution precision (GDOP) as the positioning accuracy metric, a station layout optimization method based on the simulated annealing algorithm is proposed. Compared to traditional analytical methods, using intelligent algorithms to solve the optimal station layout configuration is more universally applicable, with simple principles and convenient computations. However, intelligent algorithms often suffer from drawbacks such as slow convergence, poor convergence performance, and combinatorial explosion. These algorithms require practical improvements to achieve better results.

[0007] In summary, the accuracy metrics used to evaluate station configurations are constantly evolving. These metrics range from analytically determining the optimal intersection angle for station configurations to using metrics such as the CRLB trace or GDOP. With the advancement of intelligent optimization methods in station configuration, station optimization has evolved from specific station configurations, such as rectangular and diamond-shaped ones, to more general station optimization problems covering entire large-scale measurement areas. However, both the CRLB trace and GDOP require prior information about the target trajectory, making them applicable only to cooperative target positioning. In non-cooperative target tracking and positioning under an angle measurement system, the true position of non-cooperative targets is difficult to obtain, and their true trajectory is unknown, making it impossible to calculate accuracy metrics such as the geometric dilution of precision (GDOP). Therefore, traditional methods such as the geometric dilution of precision (GDOP) cannot be used to evaluate the quality of station configurations. Summary of the Invention

[0008] The embodiments of the present invention provide a station layout optimization and system under non-cooperative target angular measurement positioning, which can solve the technical problem in the prior art that "in non-cooperative target tracking and positioning under the angular measurement system, since the true position of the target is difficult to obtain and the true trajectory is unknown, accuracy indicators such as the geometric dilution of precision (GDOP) cannot be calculated, and therefore the pros and cons of the station layout plan cannot be evaluated by traditional methods such as the geometric dilution of precision (GDOP)."

[0009] To achieve the above objectives, in a first aspect, an embodiment of the present invention provides a method for optimizing station layout under non-cooperative target angular positioning, comprising:

[0010] Before optimizing the station configuration for tracking and positioning a non-cooperative target, an indicator for evaluating the positioning accuracy of the station configuration is constructed based on the indicator elements for evaluating positioning accuracy. The station configuration refers to the process of selecting multiple measuring devices from existing measuring devices to perform the measurement and positioning task of the target. The process of selecting measuring devices is called station configuration, the selected measuring devices are called station configuration scheme, and the geometric configuration of the selected measuring devices in space is called station configuration.

[0011] Obtain historical measurement data for each cooperative target trajectory in the historical trajectory library, calculate the values ​​of various indicator elements of an indicator for evaluating the positioning accuracy of the station configuration corresponding to the cooperative target trajectory based on the historical measurement data of each cooperative target trajectory, construct corresponding indicators based on the various indicator elements corresponding to the cooperative target trajectory, and determine the optimal weights corresponding to the various indicator elements of the cooperative target trajectory by optimizing the constructed indicators;

[0012] When positioning and tracking a non-cooperative target, a motion direction vector of the non-cooperative target trajectory is obtained, multiple cooperative target trajectories in a historical trajectory library are obtained, the non-cooperative target trajectory is rotationally offset to obtain a first offset trajectory, and the non-cooperative target trajectory is translationally offset to obtain a second offset trajectory, and a cooperative target trajectory with the same starting point or end point that the first offset trajectory can fall into is used as the optimization trajectory, or a parallel cooperative target trajectory that the second offset trajectory can fall into is used as the optimization trajectory, and the optimal weight corresponding to each indicator element of the optimized trajectory is used as the optimal weight corresponding to each indicator element of the non-cooperative target trajectory, wherein the motion direction vector of the non-cooperative target trajectory refers to a line connecting the starting point and the end point of the non-cooperative target;

[0013] Acquire actual measurement data obtained from the motion direction vector of the non-cooperative target's trajectory, construct multiple sets of preliminary station configurations from existing measurement equipment, calculate the index value of each index element of each set of preliminary station configurations based on the weights corresponding to each index element of the optimized trajectory and the actual measurement data of the non-cooperative target, and use the preliminary station configuration corresponding to the minimum index value as the optimal station configuration for positioning the non-cooperative target;

[0014] The non-cooperative target is positioned and tracked through a station layout plan within the optimal station layout configuration.

[0015] In a second aspect, an embodiment of the present invention provides a station layout optimization system under non-cooperative target angular positioning, including:

[0016] An indicator element construction unit is used to construct an indicator for evaluating the positioning accuracy of the station configuration based on the indicator elements for evaluating positioning accuracy before optimizing the station configuration for tracking and positioning a non-cooperative target. The station configuration refers to the process of selecting multiple measuring devices from existing measuring devices to perform a target measurement and positioning task. The process of selecting measuring devices is called station configuration, the selected measuring devices are called station configuration scheme, and the geometric configuration of the selected measuring devices in space is called station configuration.

[0017] A cooperative target weight optimization unit is configured to obtain historical measurement data for each cooperative target trajectory in the historical trajectory library, calculate, based on the historical measurement data for each cooperative target trajectory, the values ​​of various index elements of an indicator for evaluating the positioning accuracy of a station configuration corresponding to the cooperative target trajectory, construct corresponding indicators based on the various index elements of the indicator corresponding to the cooperative target trajectory, and determine the optimal weight corresponding to each index element of the cooperative target trajectory by optimizing the constructed indicators;

[0018] A weight optimization unit for a non-cooperative target is configured to, when positioning and tracking a non-cooperative target, obtain a motion direction vector of the non-cooperative target trajectory, obtain multiple cooperative target trajectories in a historical trajectory library, rotationally offset the non-cooperative target trajectory to obtain a first offset trajectory, and translationally offset the non-cooperative target trajectory to obtain a second offset trajectory, using a cooperative target trajectory with the same starting point or end point that the first offset trajectory can fall into as an optimization trajectory, or using a parallel cooperative target trajectory that the second offset trajectory can fall into as an optimization trajectory, and using the optimal weights corresponding to each indicator element of the optimized trajectory as the optimal weights corresponding to each indicator element of the non-cooperative target trajectory, wherein the motion direction vector of the non-cooperative target trajectory refers to a line connecting the starting point and the end point of the non-cooperative target;

[0019] A station layout optimization unit is configured to obtain actual measurement data obtained based on the motion direction vector of the non-cooperative target trajectory, construct multiple sets of preliminary station layout configurations from existing measurement equipment, calculate the index value of each index element of each set of preliminary station layout configurations based on the weights corresponding to each index element of the optimized trajectory and the actual measurement data of the non-cooperative target, and use the preliminary station layout configuration corresponding to the minimum index value as the optimal station layout configuration for positioning the non-cooperative target;

[0020] A positioning unit is used to locate and track the non-cooperative target through a station layout plan within the optimal station layout configuration.

[0021] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores one or more programs. When the one or more programs are executed by a computer device, the computer device executes the aforementioned station layout optimization method under non-cooperative target angular positioning.

[0022] In a fourth aspect, an embodiment of the present invention provides a computer device, including:

[0023] A processor; and a memory arranged to store computer-executable instructions, which, when executed, cause the processor to perform the aforementioned station layout optimization method under non-cooperative target angular positioning.

[0024] The above technical solution has the following beneficial effects: constructing the positioning accuracy evaluation index and corresponding elements of the station layout optimization method for positioning non-cooperative targets, and proposing a new station layout optimization simulation method based on the positioning accuracy evaluation index, which only uses the direction vector connecting the starting point and end point of the target, without relying on the theoretical trajectory, to complete the station layout optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0026] Figure 1 This is a flow chart of a station layout optimization method under non-cooperative target angular positioning according to an embodiment of the present invention;

[0027] Figure 2 This is a structural diagram of a station layout optimization system under non-cooperative target angle measurement positioning according to an embodiment of the present invention;

[0028] Figure 3 is a schematic diagram of angle measurement and positioning according to an embodiment of the present invention;

[0029] Figure 4 This is a schematic diagram of a two-station intersection according to an embodiment of the present invention;

[0030] Figure 5 These are the various stages of non-cooperative target positioning under the range angle measurement system of an embodiment of the present invention;

[0031] Figure 6 This is a flow chart of a station layout optimization simulation method according to an embodiment of the present invention;

[0032] Figure 7 This is a diagram of a four-station intersection positioning according to an embodiment of the present invention;

[0033] Figure 8 is the theoretical trajectory of an embodiment of the present invention;

[0034] Figure 9 is the station layout optimization accuracy result of the cooperative target positioning according to the embodiment of the present invention;

[0035] Figure 10 is a non-cooperative target trajectory that conforms to two biases according to an embodiment of the present invention;

[0036] Figure 11 is the applicability experimental result of the new indicator of the embodiment of the present invention under the rotation bias of the oblique flight trajectory;

[0037] Figure 12 is the applicability experimental result of the indicators of the embodiment of the present invention under the translation bias of the oblique flight trajectory;

[0038] Figure 13 This is a simulated trajectory of the level flight phase according to an embodiment of the present invention;

[0039] Figure 14 These are the test results of the applicability of the indicators of the embodiment of the present invention under two biases of the level flight trajectory. DETAILED DESCRIPTION

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0041] like Figure 1 As shown, in combination with an embodiment of the present invention, a station layout optimization method under non-cooperative target angular positioning is provided, comprising:

[0042] S101: Before optimizing a station configuration for tracking and positioning a non-cooperative target, construct an indicator for evaluating the positioning accuracy of the station configuration based on an indicator element for evaluating positioning accuracy; wherein the station configuration refers to performing a target measurement and positioning task by selecting multiple measuring devices from existing measuring devices. The process of selecting measuring devices is called station configuration, the selected measuring devices are called a station configuration plan, and the geometric configuration of the selected measuring devices in space is called the station configuration.

[0043] S102: Obtain historical measurement data for each cooperative target trajectory in the historical trajectory library, calculate the values ​​of various index elements of an indicator for evaluating the positioning accuracy of a station configuration corresponding to the cooperative target trajectory based on the historical measurement data of each cooperative target trajectory, construct corresponding indicators based on the various index elements corresponding to the cooperative target trajectory, and determine the optimal weights corresponding to the various index elements of the cooperative target trajectory by optimizing the constructed indicators;

[0044] S103: When positioning and tracking a non-cooperative target, a motion direction vector of the non-cooperative target trajectory is obtained, multiple cooperative target trajectories in a historical trajectory library are obtained, the non-cooperative target trajectory is rotationally offset to obtain a first offset trajectory, and the non-cooperative target trajectory is translationally offset to obtain a second offset trajectory. The cooperative target trajectory with the same starting point or end point that the first offset trajectory can fall into is used as the optimization trajectory, or the parallel cooperative target trajectory that the second offset trajectory can fall into is used as the optimization trajectory. The optimal weights corresponding to the various indicator elements of the optimized trajectory are used as the optimal weights corresponding to the various indicator elements of the non-cooperative target trajectory. The motion direction vector of the non-cooperative target trajectory refers to the line connecting the starting point and the end point of the non-cooperative target.

[0045] S104: Acquire actual measurement data obtained based on the motion direction vector of the non-cooperative target trajectory, construct multiple sets of preliminary station configurations from existing measurement equipment, calculate the index value of each index element of each set of preliminary station configurations based on the weights corresponding to each index element of the optimized trajectory and the actual measurement data of the non-cooperative target, and use the preliminary station configuration corresponding to the minimum index value as the optimal station configuration for positioning the non-cooperative target;

[0046] S105: Positioning and tracking the non-cooperative target through the station layout plan within the optimal station layout configuration.

[0047] Preferably, the index elements include: angle difference, sight line distance, baseline intersection angle, consistency of target trajectory data and encounter data, and consistency of aircraft data and missile data when the target is launched. The target refers to a cooperative target or a non-cooperative target. Among them, consistency of target trajectory data and encounter data, and consistency of aircraft data and missile data when the target is launched belong to data consistency.

[0048] Angle differential refers to the difference between the angle measurement data of the jth measuring device at the i-th moment and the angle measurement data of the target at the i-1-th moment. The angle measurement data includes azimuth and elevation. The angle differential includes the second-order difference of azimuth and the second-order difference of elevation.

[0049] The sight line distance refers to the distance from the measuring device to the target;

[0050] The baseline is the line between the measuring device and the target, and the baseline intersection angle is the angle between the baselines corresponding to two different measuring devices;

[0051] The consistency of the target's ballistic segment data and encounter segment data refers to the following: in an "air-to-air" confrontation scenario, the target movement is divided into three different stages: the clockwork segment, the ballistic segment, and the encounter segment. The target includes the carrier aircraft and / or the missile carried by the carrier aircraft. The clockwork segment is the stage in which the carrier aircraft and the missile it carries fly together. At the end of the clockwork segment, the missile separates from the carrier aircraft and flies independently towards the target aircraft. At this time, the measured target becomes the missile and enters the ballistic segment. The encounter segment is the end of the ballistic segment. The measurement equipment can observe the missile and the target aircraft simultaneously until the missile hits the target aircraft. When multiple measurement stations are used to measure the missile and the target aircraft, there will be a measurement overlap segment target position in the encounter segment. By comparing the measurement overlap segment target positions of different measurement stations, the ballistic position data obtained is used as the consistency of the target's ballistic segment data and the encounter segment data;

[0052] The consistency of the carrier aircraft data and the missile data when the target is launched means that: during the winding stage, the missile has not yet separated from the carrier aircraft, and the measuring equipment will simultaneously measure the carrier aircraft position and the missile position. The difference between the carrier aircraft position and the missile position is less than 1 / 2 of the carrier aircraft's own structural length, 1 / 2 of the width, and 1 / 2 of the height.

[0053] Preferably, S102: historical measurement data of each cooperative target trajectory in the historical trajectory library is obtained; for each cooperative target trajectory, the values ​​of various index elements of an indicator for evaluating the positioning accuracy of the station configuration corresponding to the cooperative target trajectory are calculated; corresponding indicators are constructed based on the various index elements corresponding to the cooperative target trajectory; and optimal weights corresponding to the various index elements of the cooperative target trajectory are determined by optimizing the constructed indicators, including:

[0054] S102-1: Determine the initial weights of each indicator element corresponding to the cooperation target trajectory;

[0055] S102-2: Calculate the historical measurement data Y of the trajectory of the cooperative target based on the station configuration for positioning the cooperative target to obtain a trajectory calculation result for the cooperative target. Calculate the values ​​of various indicator elements corresponding to the cooperative target based on the trajectory calculation result.

[0056] S102-3: Construct an index for evaluating the positioning accuracy of the corresponding station configuration based on the values ​​of each index element and the corresponding initial weight, and converge the index value to the minimum;

[0057] S102-4: Compare the historical measurement data of the station configuration when the index value is minimum with the theoretical trajectory of the cooperative target to obtain the measurement accuracy of the cooperative target;

[0058] S102-5: When the cooperative target measurement accuracy value is optimized to a minimum by the adaptive genetic algorithm, the weights corresponding to the indicator elements when the cooperative target measurement accuracy value is optimized to the minimum are used as the optimal weights corresponding to the indicator elements of the cooperative target trajectory.

[0059] Preferably, S102-4: comparing the historical measurement data of the station configuration when the index value is minimum with the theoretical trajectory of the cooperative target to obtain the measurement accuracy of the cooperative target includes:

[0060] For the historical measurement data of the cooperative target trajectory, the decision variable refers to the weight λ corresponding to each indicator element i , the geometric precision factor GDOP of the station configuration corresponding to the minimum index J value is recorded as The station configuration with the minimum geometric dilution of precision GDOP is taken as the optimal station configuration, and the geometric dilution of precision GDOP of the optimal station configuration is recorded as GDOP min , construct the objective function f to be optimized, construct the objective function f to be optimized is the station configuration corresponding to the maximum value of index J GDOP of the optimal station configuration min The difference between , and the measurement accuracy of the cooperative target is expressed by the difference;

[0061] S102-5: When the cooperative target measurement accuracy value is optimized to a minimum by the adaptive genetic algorithm, the weights corresponding to the indicator elements when the cooperative target measurement accuracy value is optimized to the minimum are used as the optimal weights corresponding to the indicator elements of the cooperative target trajectory, including:

[0062] For the objective function f to be optimized, the adaptive genetic algorithm achieves the trade-off between searching for solutions and randomness in different ways, and adaptively changes the values ​​of crossover and mutation probabilities according to the fitness value. When the population constituting the solution tends to stay at the local optimum, the fitness of the population constituting the solution is concentrated, and the diversity is relatively poor, the crossover and mutation probabilities increase. When the population constituting the solution is scattered in the solution space, the crossover and mutation probabilities decrease. When the population constituting the solution tends to stay at the global optimum, the cooperative target measurement accuracy is determined to be the highest. When the population constituting the solution tends to stay at the global optimum, the weight corresponding to the indicator element is given as the optimal weight.

[0063] Preferably, S103: when positioning and tracking a non-cooperative target, obtaining a motion direction vector of the non-cooperative target trajectory, obtaining multiple cooperative target trajectories in a historical trajectory library, rotating and offsetting the non-cooperative target trajectory to obtain a first offset trajectory, and translating and offsetting the non-cooperative target trajectory to obtain a second offset trajectory, using the cooperative target trajectory with the same starting point as the first offset trajectory as the trajectory for optimization, or using the parallel cooperative target trajectory as the trajectory for optimization, and using the optimal weights corresponding to the various indicator elements of the optimized trajectory as the optimal weights corresponding to the various indicator elements of the non-cooperative target trajectory, including:

[0064] S103-1: If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical trajectory library is within a threshold range, and the distance between the end point of the motion direction vector of the non-cooperative target trajectory and the end point of the cooperative target trajectory is outside the threshold range, then the non-cooperative target trajectory is rotated and offset about the starting point to obtain a first offset trajectory at a varying angle to the non-cooperative target trajectory. The cooperative target trajectory whose starting point coincides with the first offset trajectory and at which the first offset trajectory forms the smallest angle with the non-cooperative target trajectory is selected as the optimization trajectory. The optimal weights corresponding to the various indicator elements of the optimization trajectory are used as the weights corresponding to the various indicator elements of the non-cooperative target trajectory.

[0065] S103-2: If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical ballistic library is outside the threshold range, and the closest distance between the end point of the motion direction vector of the non-cooperative target trajectory and the cooperative target trajectory is outside the threshold range, then the non-cooperative target trajectory is translated and offset to obtain multiple second offset orbits, and the parallel cooperative target trajectory into which the second offset orbit can fall and the cooperative target trajectory with the smallest distance between the second offset orbit and the non-cooperative target trajectory at this time is used as the trajectory used for optimization, and the optimal weights corresponding to the various indicator elements of the optimized trajectory are used as the weights corresponding to the various indicator elements of the non-cooperative target trajectory.

[0066] Preferably, S104: obtaining actual measurement data obtained based on the motion direction vector of the non-cooperative target trajectory, constructing multiple groups of preliminary station configurations from existing measurement equipment, calculating the index value constructed by each index element of each group of preliminary station configurations based on the weights corresponding to each index element of the optimized trajectory and the actual measurement data of the non-cooperative target, and using the preliminary station configuration corresponding to the minimum index value as the optimal station configuration for positioning the non-cooperative target, including:

[0067] Acquire actual measurement data based on the motion direction vector of the non-cooperative target's trajectory and construct multiple sets of preliminary station configurations from existing measurement equipment. The actual measurement data includes: angle difference, sight line distance, baseline intersection angle, consistency between the target's ballistic segment data and the encounter segment data, and consistency between the carrier aircraft data and the missile data at the time of target launch.

[0068] For each set of preliminary station configurations, the following constraints are imposed:

[0069] Constrain the second-order difference of azimuth and elevation angles to the minimum;

[0070] Make the sight line distance of each measuring device in the preliminary station configuration as small as possible;

[0071] Make the intersection angle of each baseline in the preliminary station configuration as close to 90 degrees as possible;

[0072] In the set of preliminary station configurations, the target position of each measurement overlap segment in the consistency between the target's trajectory segment data and the encounter segment data is minimized;

[0073] Within this group of preselected station configurations, the consistency between aircraft data and missile data during launch of non-cooperative targets is met;

[0074] The index of the group of preliminary station configurations is constructed by the weights corresponding to the above constraints and the index elements of the track used for optimization, and the preliminary station configuration corresponding to the minimum index value is used as the optimal station configuration for positioning the non-cooperative target.

[0075] Preferably, S103 further includes:

[0076] S103-3: When the motion direction vector of the non-cooperative target trajectory is an oblique flight trajectory, a target cooperative trajectory whose rotation offset change in the celestial direction relative to the non-cooperative target trajectory is less than an angle threshold is selected as the trajectory used for optimization;

[0077] S103-4: If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical ballistic library is outside the threshold range, and the closest distance between the end point of the motion direction vector of the non-cooperative target trajectory and the cooperative target trajectory is within the threshold range, then the non-cooperative target trajectory is rotated and offset around the end point to obtain a third offset trajectory with a varying angle to the non-cooperative target trajectory, and the cooperative target trajectory with the same end point that the third offset trajectory can fall into and the cooperative target trajectory with the smallest angle between the third offset trajectory and the non-cooperative target trajectory is used as the trajectory used for optimization.

[0078] like Figure 2 As shown, in combination with an embodiment of the present invention, a station layout optimization system under non-cooperative target angular positioning is provided, comprising:

[0079] An indicator element construction unit 21 is configured to construct an indicator for evaluating the positioning accuracy of the station configuration based on the indicator elements for evaluating positioning accuracy before optimizing the station configuration for tracking and positioning a non-cooperative target. The station configuration refers to the process of selecting multiple measuring devices from existing measuring devices to perform a target measurement and positioning task. The process of selecting measuring devices is referred to as station configuration, the selected measuring devices are referred to as a station configuration plan, and the geometric configuration of the selected measuring devices in space is referred to as the station configuration.

[0080] The cooperative target weight optimization unit 22 is configured to obtain historical measurement data for each cooperative target trajectory in the historical trajectory library, calculate the values ​​of various index elements of an indicator for evaluating the positioning accuracy of the station configuration corresponding to the cooperative target trajectory based on the historical measurement data of each cooperative target trajectory, construct corresponding indicators based on the various index elements of the indicator corresponding to the cooperative target trajectory, and determine the optimal weight corresponding to each index element of the cooperative target trajectory by optimizing the constructed indicators;

[0081] The non-cooperative target weight optimization unit 23 is used to obtain the motion direction vector of the non-cooperative target trajectory when positioning and tracking the non-cooperative target, obtain multiple cooperative target trajectories in the historical trajectory library, rotate and offset the non-cooperative target trajectory to obtain a first offset trajectory, and translate and offset the non-cooperative target trajectory to obtain a second offset trajectory, use the cooperative target trajectory with the same starting point or end point that the first offset trajectory can fall into as the optimization trajectory, or use the parallel cooperative target trajectory that the second offset trajectory can fall into as the optimization trajectory, and use the optimal weights corresponding to each indicator element of the optimized trajectory as the optimal weights corresponding to each indicator element of the non-cooperative target trajectory, wherein the motion direction vector of the non-cooperative target trajectory refers to the line connecting the starting point and the end point of the non-cooperative target;

[0082] The station layout optimization unit 24 is configured to obtain actual measurement data obtained based on the motion direction vector of the non-cooperative target trajectory, construct multiple sets of preliminary station layout configurations from existing measurement equipment, calculate the index value of each index element of each set of preliminary station layout configurations based on the weights corresponding to each index element of the optimized trajectory and the actual measurement data of the non-cooperative target, and select the preliminary station layout configuration corresponding to the minimum index value as the optimal station layout configuration for positioning the non-cooperative target;

[0083] The positioning unit 25 is configured to locate and track the non-cooperative target using a station layout plan within the optimal station layout configuration.

[0084] Preferably, the index elements include: angle difference, sight line distance, baseline intersection angle, consistency of target trajectory data and encounter data, and consistency of aircraft data and missile data when the target is launched. The target refers to a cooperative target or a non-cooperative target. Among them, consistency of target trajectory data and encounter data, and consistency of aircraft data and missile data when the target is launched belong to data consistency.

[0085] Angle differential refers to the difference between the angle measurement data of the jth measuring device at the i-th moment and the angle measurement data of the target at the i-1-th moment. The angle measurement data includes azimuth and elevation. The angle differential includes the second-order difference of azimuth and the second-order difference of elevation.

[0086] The sight line distance refers to the distance from the measuring device to the target;

[0087] The baseline is the line between the measuring device and the target, and the baseline intersection angle is the angle between the baselines corresponding to two different measuring devices;

[0088] The consistency of the target's ballistic segment data and encounter segment data refers to the following: in an "air-to-air" confrontation scenario, the target movement is divided into three different stages: the clockwork segment, the ballistic segment, and the encounter segment. The target includes the carrier aircraft and / or the missile carried by the carrier aircraft. The clockwork segment is the stage in which the carrier aircraft and the missile it carries fly together. At the end of the clockwork segment, the missile separates from the carrier aircraft and flies independently towards the target aircraft. At this time, the measured target becomes the missile and enters the ballistic segment. The encounter segment is the end of the ballistic segment. The measurement equipment can observe the missile and the target aircraft simultaneously until the missile hits the target aircraft. When multiple measurement stations are used to measure the missile and the target aircraft, there will be a measurement overlap segment target position in the encounter segment. By comparing the measurement overlap segment target positions of different measurement stations, the ballistic position data obtained is used as the consistency of the target's ballistic segment data and the encounter segment data;

[0089] The consistency of the carrier aircraft data and the missile data when the target is launched means that: during the winding stage, the missile has not yet separated from the carrier aircraft, and the measuring equipment will simultaneously measure the carrier aircraft position and the missile position. The difference between the carrier aircraft position and the missile position is less than 1 / 2 of the carrier aircraft's own structural length, 1 / 2 of the width, and 1 / 2 of the height.

[0090] Preferably, the cooperation goal weight optimization unit 22 is specifically used to:

[0091] The assignment subunit is used to determine the initial weights of each indicator element corresponding to the cooperation target trajectory;

[0092] The settlement subunit is used to solve the historical measurement data Y of the cooperative target's trajectory in combination with the station configuration for positioning the cooperative target, obtain the trajectory solution result of the cooperative target, and calculate the values ​​of various indicator elements corresponding to the cooperative target based on the trajectory solution result;

[0093] The convergence subunit is used to construct an index for evaluating the positioning accuracy of the corresponding station configuration based on the values ​​of each index element and the corresponding initial weight, and converge the index value to the minimum;

[0094] a comparison subunit, configured to compare historical measurement data of the station configuration when the index value is minimum with the theoretical trajectory of the cooperative target to obtain the measurement accuracy of the cooperative target;

[0095] The weight optimization subunit is used to optimize the cooperative target measurement accuracy value to the minimum through the adaptive genetic algorithm, and use the weights corresponding to the various indicator elements when the cooperative target measurement accuracy value is optimized to the minimum as the optimal weights corresponding to the various indicator elements of the cooperative target trajectory.

[0096] Preferably, the weight optimization subunit is specifically used to:

[0097] For the historical measurement data of the cooperative target trajectory, the decision variable refers to the weight λ corresponding to each indicator element i, the geometric precision factor GDOP of the station configuration corresponding to the minimum index J value is recorded as The station configuration with the minimum geometric dilution of precision GDOP is taken as the optimal station configuration, and the geometric dilution of precision GDOP of the optimal station configuration is recorded as GDOP min , construct the objective function f to be optimized, construct the objective function f to be optimized is the station configuration corresponding to the maximum value of index J GDOP of the optimal station configuration min The difference between , and the measurement accuracy of the cooperative target is expressed by the difference;

[0098] When the cooperative target measurement accuracy value is optimized to a minimum by an adaptive genetic algorithm, the weights corresponding to the various indicator elements when the cooperative target measurement accuracy value is optimized to a minimum are used as the optimal weights corresponding to the various indicator elements of the cooperative target trajectory, including:

[0099] For the objective function f to be optimized, the adaptive genetic algorithm achieves the trade-off between searching for solutions and randomness in different ways, and adaptively changes the values ​​of crossover and mutation probabilities according to the fitness value. When the population constituting the solution tends to stay at the local optimum, the fitness of the population constituting the solution is concentrated, and the diversity is relatively poor, the crossover and mutation probabilities increase. When the population constituting the solution is scattered in the solution space, the crossover and mutation probabilities decrease. When the population constituting the solution tends to stay at the global optimum, the cooperative target measurement accuracy is determined to be the highest. When the population constituting the solution tends to stay at the global optimum, the weight corresponding to the indicator element is given as the optimal weight.

[0100] Preferably, the non-cooperative objective weight optimization unit 23 is specifically configured to:

[0101] If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical trajectory library is within a threshold range, and the distance between the end point of the motion direction vector of the non-cooperative target trajectory and the end point of the cooperative target trajectory is outside the threshold range, then the non-cooperative target trajectory is rotated and offset around the starting point; a first offset trajectory having a varying angle with the non-cooperative target trajectory is obtained; the cooperative target trajectory whose starting point is consistent with the first offset trajectory and at which the angle between the first offset trajectory and the non-cooperative target trajectory is minimized is used as the trajectory for optimization; and the optimal weight corresponding to each indicator element of the optimized trajectory is used as the weight corresponding to each indicator element of the non-cooperative target trajectory;

[0102] If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical ballistic library is outside the threshold range, and the closest distance between the end point of the motion direction vector of the non-cooperative target trajectory and the cooperative target trajectory is outside the threshold range, then the non-cooperative target trajectory is translated and offset to obtain multiple second offset orbits, and the parallel cooperative target trajectory into which the second offset orbit can fall and the cooperative target trajectory with the smallest distance between the second offset orbit and the non-cooperative target trajectory at this time is used as the trajectory used for optimization, and the optimal weights corresponding to each indicator element of the optimized trajectory are used as the weights corresponding to each indicator element of the non-cooperative target trajectory.

[0103] The station layout optimization unit 24 is specifically used to:

[0104] Acquire actual measurement data based on the motion direction vector of the non-cooperative target's trajectory and construct multiple sets of preliminary station configurations from existing measurement equipment. The actual measurement data includes: angle difference, sight line distance, baseline intersection angle, consistency between the target's ballistic segment data and the encounter segment data, and consistency between the carrier aircraft data and the missile data at the time of target launch.

[0105] For each set of preliminary station configurations, the following constraints are imposed:

[0106] Constrain the second-order difference of azimuth and elevation angles to the minimum;

[0107] Make the sight line distance of each measuring device in the preliminary station configuration as small as possible;

[0108] Make the intersection angle of each baseline in the preliminary station configuration as close to 90 degrees as possible;

[0109] In the set of preliminary station configurations, the target position of each measurement overlap segment in the consistency between the target's trajectory segment data and the encounter segment data is minimized;

[0110] Within this group of preliminary station configurations, the consistency between the aircraft data and the missile data during launch of non-cooperative targets is met;

[0111] The index of the group of preliminary station configurations is constructed by the weights corresponding to the above constraints and the index elements of the track used for optimization, and the preliminary station configuration corresponding to the minimum index value is used as the optimal station configuration for positioning the non-cooperative target.

[0112] Preferably, the non-cooperative objective weight optimization unit 23 is specifically configured to:

[0113] When the motion direction vector of the non-cooperative target trajectory is an oblique flight trajectory, the target cooperative trajectory whose rotation offset change in the celestial direction relative to the non-cooperative target trajectory is less than the angle threshold is selected as the trajectory used for optimization;

[0114] If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical ballistic library is outside the threshold range, and the closest distance between the end point of the motion direction vector of the non-cooperative target trajectory and the cooperative target trajectory is within the threshold range, then the non-cooperative target trajectory is rotated and offset around the end point to obtain a third offset trajectory with a varying angle to the non-cooperative target trajectory. The cooperative target trajectory on which the third offset trajectory can fall, and the cooperative target trajectory with the smallest angle between the third offset trajectory and the non-cooperative target trajectory at this time, is used as the trajectory used for optimization.

[0115] In combination with an embodiment of the present invention, a computer-readable storage medium is provided, which stores one or more programs. When the one or more programs are executed by a computer device, the computer device executes any one of the aforementioned station optimization methods under non-cooperative target angular positioning.

[0116] In accordance with an embodiment of the present invention, a computer device is provided, including:

[0117] A processor; and a memory arranged to store computer-executable instructions, wherein when the executable instructions are executed, the processor executes any one of the aforementioned station layout optimization methods under non-cooperative target angular positioning.

[0118] The beneficial technical effects achieved by the embodiments of the present invention are as follows:

[0119] A new optimization evaluation metric for station placement schemes and its corresponding factors are constructed. Based on this metric, a new station placement optimization simulation method is proposed. This method, which uses only the directional vector connecting the target's starting and ending points, eliminates theoretical trajectories and achieves optimal station placement. This approach aims to address the inability of traditional station placement methods to be applied to non-cooperative targets. A new station placement optimization evaluation metric is constructed to address the issue of actual data consistency in air-to-air confrontation scenarios in target positioning and tracking, specifically the consistency of data from the trajectory phase to the encounter phase and from the aircraft to the missile phase. This metric only requires the directional vector of the non-cooperative target's motion, eliminating reliance on theoretical trajectories. Combining historical cooperative trajectories, an adaptive genetic algorithm is used to determine the optimal weights for each factor. This weighted weight is then applied to the positioning of non-cooperative targets, resulting in a more optimal station placement scheme for non-cooperative target positioning.

[0120] The beneficial technical effects achieved by the embodiments of the present invention are as follows:

[0121] For the optimization of station placement in passive angle measurement systems, a new station placement optimization evaluation metric and corresponding factors, distinct from traditional evaluation metrics such as GDOP and CRLB, are constructed. Based on this metric, a new station placement optimization simulation method is proposed. This method, independent of theoretical trajectories, utilizes only the direction vector connecting the target's starting and ending points to achieve optimal placement. This approach addresses the inability of traditional station placement methods to be applied to non-cooperative targets. A new station placement optimization evaluation metric is constructed to address the issue of actual data consistency in air-to-air confrontation scenarios in target positioning and tracking, specifically the consistency of data from the trajectory to the encounter phase and from the aircraft to the missile. This metric only requires the direction vector of the non-cooperative target's motion, eliminating reliance on theoretical trajectories. Using historical test trajectories, an adaptive genetic algorithm is used to determine the optimal weights for each factor. This weighted weight is then applied to the positioning of non-cooperative targets, resulting in a more optimal station placement solution for non-cooperative targets.

[0122] In the experimental phase, the proposed method was applied to the positioning of cooperative targets. The station combination selected when the global optimal metric value was minimized was consistent with the station combination selected using GDOP, verifying the effectiveness of the metric and the feasibility of the method. Secondly, in simulation experiments for the positioning of non-cooperative targets, the sensitivity of the new metric to two types of biases was analyzed, demonstrating the metric's applicability: when the non-cooperative target's direction vector is an oblique flight trajectory, historical cooperative trajectories based on rotational bias are preferred; and compared with oblique flight trajectories, the metric is more applicable to level flight trajectories. This method is independent of prior trajectory information and does not require theoretical trajectory support. It simply obtains the line connecting the non-cooperative target's starting point and end point in the positioning space and compares it with historical trajectories. By calculating the magnitude of the metric, the station placement optimization problem for non-cooperative targets can be solved.

[0123] The above technical solutions of the embodiments of the present invention are described in detail below with reference to specific application examples. For technical details not introduced during the implementation process, please refer to the relevant description above.

[0124] The embodiment of the present invention constructs a new station layout optimization index and proposes a new station layout optimization method under a passive angle measurement system. This method does not rely on theoretical trajectory and only uses the direction vector connecting the target starting point and end point to complete station layout optimization. Based on the factors affecting positioning accuracy such as angle difference, baseline intersection angle and sight line distance under the angle measurement system, combined with the actual data consistency problem in the "air-to-air" confrontation scenario in non-cooperative target positioning and tracking, that is, the "trajectory segment-encounter segment" data consistency and "carrier-missile" data consistency and other factors, a new station layout optimization evaluation index is constructed. This index only needs to obtain the direction vector of the non-cooperative target movement and is free from dependence on theoretical trajectory. Combined with the historical cooperative trajectory, the optimal weight of each factor is determined by an adaptive genetic algorithm and used in the positioning of non-cooperative targets. In this way, a better station layout scheme for non-cooperative target positioning is obtained, providing a new approach to the station layout optimization problem in non-cooperative target positioning. Simulation experiments verify the effectiveness of the new indicator under cooperative target positioning, analyze the sensitivity of the new indicator to two types of biases under non-cooperative target tracking and positioning, and evaluate the applicability of the new indicator for station layout optimization.

[0125] 1. Station layout optimization simulation model

[0126] 1.1 Traditional station layout optimization simulation model

[0127] When using the angle measurement positioning system to measure the trajectory outside the shooting range, the measuring equipment usually used is the optical theodolite. The angle measurement positioning method mainly revolves around the intersection of multiple optical theodolites (hereinafter referred to as optical measurement equipment or measurement stations), such as Figure 3 As shown in Figure 2, the station layout optimization problem under this measurement system is considered.

[0128] The traditional station layout optimization model optimizes the station locations with the goal of minimizing the positioning accuracy index value (at this time, the positioning accuracy is the highest). First, the calculation method of the traditional optimization model is discussed in the two-station angle measurement positioning scenario, taking GDOP as an example. Figure 4 , measure the target point X d The coordinates of the target are [x, y, z]. The coordinates of the target are different in different station systems. The coordinates in the i-th station system are X ci =[x ci ,y ci ,z ci ] T ,i=1,2; Assume that the coordinates of the i-th station in the center of the target are [x i ,y i ,z i ], the geocentric coordinate of the i-th station is X 0i , two optical measuring devices are aligned with the target X d The measured azimuth and elevation angles are A i and E i ,like Figure 4As shown, the intersection angle of the two stations is φ 12 .

[0129] When measuring stations are deployed over a large area, the station systems corresponding to different stations (with the station location as the origin) can differ significantly in the east, north, and celestial directions. Consequently, the target positions obtained by measuring in each station system can differ significantly. Therefore, the station systems to which the stations belong must be converted to the same coordinate system. This option is used to convert the station system to the geocentric system, then solve for the target position. The GDOP is then calculated based on the solved information.

[0130] Assume that the geocentric coordinates of the i-th station are X 0i , M is the rotation matrix, which can uniformly transform the coordinates of different station systems into the geocentric coordinates:

[0131] X ci =M(-B i ,L i )(X d -X 0i ) (1)

[0132] in:

[0133]

[0134] Notation function s ci =sign(xx ci ), azimuth A i , pitch angle E i The measurement equation is:

[0135]

[0136] Remember D i is the horizontal projection length of the line connecting station i and the target, that is:

[0137]

[0138] R i is the distance from the target to station i:

[0139]

[0140] The angle measurement Jacobian matrix of a single measuring station in the measuring station system is:

[0141]

[0142] Since the geocentric coordinate X 0i and M are constants, according to formula (1):

[0143]

[0144] Since the rotation matrices are all orthogonal matrices and the determinant is equal to 1, the angle measurement Jacobian matrix of each measuring station in the geocentric system can be obtained based on the composite differential formula:

[0145]

[0146] Among them, J ci Referring to formula (6), the multi-station angle measurement Jacobian matrix J is obtained from formula (8): d for:

[0147]

[0148] Taking two-station intersection positioning (positioning by two measuring stations) as an example, the multi-station angle measurement Jacobian matrix obtained by formula (9) is:

[0149]

[0150] For simplicity, x1, y1, z1 are the coordinates of the first measuring station in the bull's eye system, and x2, y2, z2 are the coordinates of the second measuring station in the bull's eye system.

[0151] Assuming D1=D2=R, we can get GDOP, sight distance R, and intersection angle φ 12 Relationship:

[0152]

[0153] Equation (11) shows that the target position directly affects the accuracy of the geometric dilution of precision (GDOP) by affecting the line-of-sight distance and the line-of-sight intersection angle. Traditional optimization models need to minimize GDOP to evaluate the pros and cons of station placement solutions, thereby achieving the goal of station placement optimization. Since the position of non-cooperative targets cannot be accurately located and their theoretical trajectory cannot be obtained, the GDOP indicator is invalid and GDOP cannot be used to optimize the evaluation of station placement solutions for non-cooperative target tracking and positioning.

[0154] 1.2 Station Layout Optimization Simulation Model of the Embodiment of the Present Invention

[0155] In the station layout optimization simulation model, the construction of positioning accuracy evaluation indicators is the core of the station layout optimization method. The selection of each element in the indicator is directly related to the reliability of the station layout evaluation criteria. Therefore, the selection of indicators requires multi-dimensional and multi-angle considerations. It is generally believed that the main factors affecting target positioning accuracy include the measurement accuracy of the measurement equipment and the station layout configuration. Therefore, the construction of indicators in the embodiments of the present invention needs to address these two influencing factors.

[0156] Considering the measurement accuracy of the measuring equipment, the station optimization evaluation index adds angle difference and sight line distance as index elements. In addition, the intersection difference and the baseline intersection angle are the main index factors affecting the station configuration, and the baseline intersection angle and the intersection difference are highly correlated, so only the baseline intersection angle is included in the index. On the other hand, in the "air-to-air" confrontation scenario in non-cooperative target positioning and tracking, due to the particularity and complexity of the environment, the consistency of the ballistic segment data and the encounter segment data, as well as the consistency of the carrier data and the missile data at the time of launch, will affect the target positioning accuracy from the algorithm, so they need to be used as index elements. Let Y be the actual measurement data (specifically including azimuth and pitch angles), is the trajectory position parameter (or target settlement result, i.e., the specific position of the target in the range system). The index element set φ(Y) of the embodiment of the present invention includes the above five index elements, specifically including: (1) angle difference, (2) sight line distance, (3) station baseline intersection angle, (4) consistency of trajectory segment data and encounter segment data, and (5) consistency of carrier aircraft data and missile data at launch, which are respectively recorded as:

[0157]

[0158] Among them, φ1(Y) represents the angle difference, φ2(Y) represents the sight line distance, and φ3(Y) represents the baseline intersection angle. Indicates the consistency between the trajectory segment data and the encounter segment data, Indicates the consistency between the carrier aircraft data and the missile data at launch.

[0159] 1.2.1 Angle difference

[0160] The angle difference is defined as the difference between the angle measured by the jth device at the i-th moment and the angle measured at the i-1-th moment.

[0161] Let ma and na be the total number of measurement points (which can be understood as the sum of measurement times) and the total number of measurement equipment respectively; A ij ,E ij Indicates the azimuth and elevation angles measured by the equipment in the range system (the coordinate system with the measuring equipment as the origin); dA ij ,dE ij Respectively represent the first-order difference of azimuth angle and the first-order difference of elevation angle; d 2 A ij ,d 2 E ij Respectively represent the second-order differential of azimuth angle and the second-order differential of elevation angle. Angle differential includes: the first-order differential of azimuth angle dA ij , first-order difference of pitch angle dE ij 、Second-order difference of azimuth d 2 A ij , the second-order difference of the pitch angle d2 E ij ; dA ij ,dE ij ,d 2 A ij ,d 2 E ij The calculation formulas are expressed as:

[0162]

[0163] The size of the angular differential depends on the device sampling frequency and the target's motion amplitude. During target tracking and measurement, the angular velocity and angular acceleration of the observation device must not exceed their respective limits. Otherwise, the target may be lost or dynamic hysteresis errors may increase. It is generally believed that the first-order differential primarily reflects the target's motion state, while the second-order differential primarily reflects the measurement accuracy of the measurement device during target measurement. Therefore, it is necessary to constrain the angular differential (second-order differential) to be as small as possible:

[0164] φ1(Y)=min(d 2 A ij +d 2 E ij ) (14)

[0165] 1.2.2 Viewing line distance

[0166] The sight line distance is the line of sight distance between different measuring devices in the shooting range (station) observing the target, that is, the distance from the station to the target.

[0167] The sight line distance reflects the measurement accuracy of the measuring device, which changes continuously during the measurement process. Let D be the sight line distance of different measuring devices. It is easy to see that the smaller the sight line distance, the higher the accuracy and the smaller the error. Therefore, it is necessary to constrain the sight line distance values ​​of different devices to be as small as possible:

[0168] φ2(Y)=min(D) (15)

[0169] 1.2.3 Baseline intersection angle

[0170] The baseline is the line connecting the measuring station and the target position, and the baseline intersection angle is the angle between two different baselines.

[0171] Let α be the baseline intersection angle. According to formula (11), the closer the baseline intersection angle is to 90 degrees, the higher the accuracy is. Therefore, it is necessary to constrain the baseline intersection angle to be close to 90 degrees:

[0172]

[0173] 1.2.4 Conformity between trajectory data and encounter data

[0174] In the "air-to-air" confrontation scenario, the movement of non-cooperative targets can be divided into three stages: the clockwork stage, the ballistic stage, and the encounter stage. Figure 5 As shown in the figure, non-cooperative targets include the carrier aircraft and the missile carried by the carrier aircraft. The clockwork segment is the stage where the carrier aircraft and the missile fly together. At the end of the clockwork segment, the missile separates from the carrier aircraft and flies alone towards the target aircraft (the target to be attacked). At this time, the positioned cooperative target becomes the missile, and the measurement and positioning ballistic segment begins. The encounter segment is the end of the ballistic segment. When the missile and the target aircraft are simultaneously observed in the measurement image of the optical measurement equipment, until the missile hits the target aircraft (the target to be attacked), this segment is the encounter segment.

[0175] Since different measurement equipment is usually responsible for measuring the missile of the carrier aircraft and the target aircraft in the shooting range, there is a measurement overlap section in the encounter section. At this time, the ballistic position data obtained by different measurement equipment during the measurement overlap section is compared to determine the data consistency.

[0176] Assume (x DD ,y DD ,z DD ) is the ballistic segment, the target position of the measurement overlap segment measured by the measuring equipment, (x XY ,y XY ,z XY ) is the encounter segment. The target position of the measurement overlap segment measured by the measuring device can constrain the position difference between the target position of the measurement overlap segment of the trajectory segment and the target position of the measurement overlap segment of the encounter segment, so that the position difference between the target position of the measurement overlap segment of the trajectory segment and the target position of the measurement overlap segment of the encounter segment is minimized. The position difference between the target position of the measurement overlap segment of the trajectory segment and the target position of the measurement overlap segment of the encounter segment is expressed as:

[0177]

[0178] 1.2.5 Compatibility of aircraft data and missile data at launch

[0179] When in the winding stage, the missile has not yet separated from the carrier aircraft. The measuring equipment will simultaneously measure and locate the carrier aircraft position and the missile position. The measured difference between the carrier aircraft position and the missile position should be less than 1 / 2 of the carrier aircraft's own structural length, width, and height.

[0180] Assume that the length of the carrier aircraft is a meter, the width is b meters, and the height is c meters. The coordinate position (x ZJ ,y ZJ ,z ZJ ), the coordinate position of the target aircraft in the range system (x BB ,y BB ,z BB ):

[0181]

[0182] In summary, in the embodiment of the present invention, after determining the indicator element set, different weights are assigned to each indicator element. Since the dimensions of each indicator element are different, the indicator J is the linear weighted sum of each indicator element after standardization, that is:

[0183]

[0184] Based on this indicator J, the present invention proposes a new station placement optimization simulation model. This model offers two advantages over traditional models: First, it eliminates the need for theoretical trajectory analysis and only requires comparing the similarity between the motion direction vectors of non-cooperative targets and historical cooperative targets to achieve station placement optimization simulation for tracking and positioning non-cooperative targets under a passive angle measurement system. Second, the model's indicators consider data consistency in real-world scenarios, which increases its credibility compared to traditional models by considering more factors.

[0185] 2 Station layout optimization simulation method based on the new model

[0186] 2.1 Station Layout Optimization Simulation Method Process

[0187] In the target positioning of the shooting range angle measurement system, the angle measurement data includes azimuth and elevation. The relationship between the angle measurement data and the unknown true target position is:

[0188] Y=F(X)+ε (20)

[0189] Where Y is the actual measurement data, X is the unknown true target position, F(X) is the angle measurement equation, and ε is the noise. Target positioning station optimization refers to selecting several stations that meet the mission requirements from existing sites based on traditional station optimization evaluation metrics such as GDOP to achieve the highest positioning accuracy for the unknown true target. The positioning accuracy of each measurement point (at the time of measurement) is:

[0190]

[0191] in, is the target solution result. The target positioning accuracy is the mean of the accuracy of all measurement points. When positioning non-cooperative targets, X is unknown. Traditional station placement evaluation and optimization metrics cannot measure P (a precision metric). Therefore, traditional station placement evaluation and optimization metrics cannot guide station placement for non-cooperative target positioning.

[0192] In summary, in cooperative target positioning, since the actual position can be replaced by a theoretical trajectory, the size of the accuracy measurement index can reflect the quality of the station layout scheme; while in non-cooperative target positioning, there is no theoretical trajectory. Since traditional accuracy measurement indicators are invalid in non-cooperative target positioning, it is impossible to judge the quality of the station layout scheme in non-cooperative target positioning.

[0193] To address this issue, in an embodiment of the present invention, when positioning a non-cooperative target, the direction vector of the non-cooperative target's movement is used as the target's true position instead of the theoretical trajectory, and a station layout optimization simulation method is constructed based on the indicator J. The specific process of the station layout optimization simulation method based on the indicator J is as follows: Figure 6 .

[0194] First, for cooperative target positioning, the station layout optimization simulation method based on indicator J ultimately needs to determine its optimal weight in cooperative target positioning, which specifically includes the six steps shown below. In this station layout optimization simulation method based on indicator J, the initial weight, theoretical trajectory, actual measurement data and station location are input, and the optimal weight under each cooperative target trajectory positioning is output. That is: Input: the initial weight λ of each indicator element in the indicator i0 , theoretical trajectory X, actual measurement data (historical measurement data) Y, measurement station location (CZ1, CZ2, ..., CZ N ); Output: optimal weight The six steps are as follows:

[0195] Step 1: Construct an index element set: angle difference, sight line distance, baseline intersection angle, consistency between trajectory segment data and encounter segment data, and consistency between aircraft data and missile data at launch, denoted as: φ(Y) = {φ1(Y), φ2(Y), φ3(Y), φ4(Y), φ5(Y)}

[0196] Step 2: Select a set of station sites (CZ k1 ,CZ k2 ,...,CZ kn ), belongs to (CZ1,CZ2,...,CZ N ), the trajectory calculation is performed through the actual measurement data Y to obtain the Kth group of trajectory calculation results According to the ballistic calculation results Calculate the value of each indicator element within the indicator

[0197]

[0198] Step 3: Through λ i0 and indicator elements Calculate the indicator J:

[0199]

[0200] Step 4: Minimize the index J value and select the station site with the minimum index J value;

[0201] Step 5: Based on the station location and theoretical trajectory X where the J value is the smallest, calculate the positioning accuracy: in, Indicates the result of trajectory calculation.

[0202] Step 6: Optimize the optimal indicator weights with the highest accuracy through adaptive genetic algorithm

[0203] The measuring station is determined, and a cooperative target trajectory (historical test trajectory) corresponds to a set of optimal weights. In non-cooperative target positioning, when there are enough sets of optimal weights, that is, there are enough historical test trajectories in the historical trajectory library of the shooting range, the non-cooperative target is compared with the historical test trajectory. Under the two offsets (rotation and translation) of the historical test trajectory, the optimal weights of these historical test trajectories can be obtained. Directly used for non-cooperative target site optimization simulation, such as Figure 10 As shown in Figure 2, two offsets are possible between the trajectory of a non-cooperative target and a historical mission: if the starting point of the non-cooperative target trajectory l is close to the starting point of any trajectory l1 in the historical mission library, but the end points are different, the angle between the two trajectories is defined as θ; if the starting point of the non-cooperative target trajectory l and any trajectory in the historical mission library are completely different, and the direction of the trajectory is also significantly different, but l is nearly parallel to any trajectory l2 in the historical mission library, the distance between the two trajectories is defined as d.

[0204] For non-cooperative targets, by selecting several devices from the existing measurement equipment to perform measurement and positioning tasks, each group of station layout plans only differs from each other in the positions of the devices. The different configurations of the station layout plans directly affect the positioning accuracy. Therefore, it is necessary to select the optimal station layout configuration to achieve the minimum accuracy measurement index and the highest positioning accuracy.

[0205] 2.1 Station Layout Optimization Simulation Algorithm

[0206] In the above-mentioned non-cooperative target station layout optimization simulation method, an intelligent optimization algorithm is required to obtain the optimal weights that maximize the cooperative target accuracy, that is, minimize the accuracy measurement index value. However, the algorithm iteration process is prone to falling into local optimality, so it is necessary to balance the algorithm's local and global search capabilities. The adaptive genetic algorithm can adjust the crossover and mutation probabilities according to the fitness value, improving the common problem of traditional genetic algorithms in the lack of local search for optimal solutions in the later stages of the algorithm. It can improve the diversity of the population (solution) while ensuring population convergence, and can better solve the weight optimization problem of the embodiment of the present invention. Therefore, the adaptive genetic algorithm is used to optimize and obtain the optimal weights for the highest accuracy.

[0207] The adaptive genetic algorithm aims to achieve a trade-off between search and randomness by using different methods (the ability to adjust the probability of crossover and mutation with iterations), adaptively changing the value of crossover and mutation probability according to the fitness value. When the group tends to stay in the local optimum (when the group fitness is concentrated and the diversity is relatively poor), the crossover and mutation probability increases, and when the group spreads in the solution space (when the group fitness is dispersed and the diversity is relatively high), the probability decreases. Therefore, the adaptive genetic algorithm designs a calculation formula for the crossover and mutation probability to make it conform to dynamic changes. The crossover probability P c and mutation probability P m They are:

[0208]

[0209] Among them, f' is the larger fitness value in crossover, f is the fitness value in mutation, and f max is the maximum fitness in the population, f min is the minimum fitness of the population, f avg is the average fitness of the population. are constants in the range [0,1], The value of is 1, The value of is 0.5. When using the adaptive genetic algorithm to optimize the simulation station configuration, a chromosome is needed to represent the weight of each factor in the indicator. Therefore, the weights of the five factors in the indicator must be converted into binary codes, the selected population size is 100, and the upper limit of iteration is 100 times.

[0210] The optimization functions of cooperative and non-cooperative objectives are different. Under cooperative objectives, an adaptive genetic algorithm needs to be used to optimize the optimal weights, while for non-cooperative objectives, the offset size of the trajectory needs to be compared with that of historical tests, and the appropriate optimal weights need to be selected according to the applicability of the indicators to minimize the indicator values.

[0211] In the case of cooperative target positioning, the optimized decision variable is the indicator weight λ i , the objective function f is the GDOP of the station configuration when the index J value is minimum, denoted as Compared with the optimal station configuration GDOP, the GDOP is the smallest at this time, recorded as GDOP min , calculate the difference between the two, that is:

[0212]

[0213] When choosing the optimal weight After that, the optimization objective function of the non-cooperative objective is:

[0214] f=min(J) (24)

[0215] 3 Simulation and Analysis

[0216] 3.1 Scenario Design

[0217] Based on the actual mission requirements of the shooting range, it is now necessary to select 4 optical theodolites from the 30 high-precision optical theodolites with fixed positions and known locations in the shooting range to locate and measure cooperative targets with known theoretical trajectories and non-cooperative targets with unknown theoretical trajectories. Figure 7 A four-station intersection measurement model of optical measurement equipment is given.

[0218] O-XYZ is the geocentric system, measuring the target point X d The coordinates of the target are [x, y, z], and the coordinates of the target in the i-th station system are X ci =[x ci ,y ci ,z ci ] T ,i=1,2,3,4; Assume that the coordinates of the i-th station in the center of the target are [x i ,y i ,z i ], the geocentric coordinate of the i-th station is X 0i , the geodetic coordinates latitude and longitude are [B i ,L i ,H i ], the projections on the horizontal plane are O1, O2, O3, O4, four optical measurement devices on the target X d The measured azimuth and elevation angles are A i (i=1,2,3,4) and E i (i=1,2,3,4).

[0219] After constructing the above four-station rendezvous model, the theoretical ballistic data of the real mission in the range (such as Figure 8 ), the trajectory is in the descent phase. The range layout is 40 km x 40 km. Thirty stations are randomly generated within this layout through simulation, with the distance between each simulated station being at least 200 meters. The new aircraft dimensions for the experiment are a = 14, b = 12, and c = 4.

[0220] 3.2 Results Analysis

[0221] 3.2.1 Cooperation Target Positioning

[0222] The theoretical trajectory of the cooperative target is known and the position of the simulation station in the station layout space is known. The verification experiment of the cooperative target using the above station layout optimization simulation method is as follows: Figure 9 As shown. Assume that the conditions for the algorithm to complete convergence are:

[0223] f I -f I-1 ≤10-6 (25)

[0224] Where I is the number of iterations. In this cooperative case, the algorithm completes convergence and reaches the global optimum after 11 iterations. Figure 9 It can be seen that the GDOP of the station configuration optimized by the method decreased from 13799.6 to 12038.1, and the accuracy increased by nearly 12.76%. After reaching the global optimum, the station combination selected when the index is minimum is consistent with the station combination selected by the minimum GDOP, and the optimal weight λ of the theoretical trajectory is obtained. *i .

[0225] The following experiment demonstrates that the aforementioned station placement optimization simulation method does not result in a combinatorial explosion. In this simulation, the theoretical trajectory of the actual mission described above is used within the station placement space to simulate varying station positions within the range. Assume that the total number of stations N in the range varies, with N = 10, 20, 30, 40, 50, and 70, respectively. Four stations are selected from these stations to perform the positioning task, with the spacing between them remaining constant. The following shows the number of iterations required to select the optimal station placement configuration using the aforementioned algorithm from the total number of stations.

[0226] Depend on Figure 9 It can be seen that when the total number of stations in the range is 70, the average number of iterations required for the algorithm to converge is still less than 10. However, this number of 70 stations already exceeds the maximum number of devices that can be accommodated in a 40km*40km range under realistic conditions. Therefore, the non-cooperative target station placement optimization simulation method of this embodiment of the present invention will not cause combinatorial explosion under realistic range conditions. These conclusions demonstrate that the station placement optimization simulation method can be extended to solve optimization problems with larger ranges and more stations. Furthermore, this method requires fewer iterations to converge, effectively improving the efficiency of station optimization in target positioning scenarios.

[0227] 3.2.2 Applicability of indicators for non-cooperative targeting

[0228] The following discusses the applicability of the metrics used in the methods of this embodiment of the present invention, specifically, the circumstances under which this metric can be used when observing the start and end points of a non-cooperative target within the range measurement space. Let l be the line connecting the start and end points of the non-cooperative target. Below, we consider two offsets between the non-cooperative target and the historical mission trajectory.

[0229] If the starting point of the non-cooperative target trajectory l is close to the starting point of any trajectory l1 in the historical task library, but the end points are different, the angle between the two trajectories is defined as θ; if the starting point of the non-cooperative target trajectory l is completely different from the starting point of any trajectory l1 in the historical task library, and the landing direction is also very different, but l is almost parallel to any trajectory l2 in the historical task library, the distance between the two trajectories is defined as d.

[0230] In order to analyze the sensitivity of the indicators to the two types of biases, this section conducts simulation experiments in the following two scenarios.

[0231] First, the applicability of the test indicator to the non-cooperative trajectory with an angle θ with the historical trajectory. Figure 10 ) changes only in the north and celestial directions and remains unchanged in the east direction. Therefore, in the simulation, the theoretical trajectory is rotated around the trajectory starting point on a plane with an unchanged east direction, with rotation angles ranging from 1 to 30 degrees, and each rotation angle is 1 degree. After obtaining 30 different simulated trajectories, the trajectory is solved and the minimum geometric dilution of precision (GDOP) is obtained by calculating the optimal station configuration for each simulated trajectory, which is recorded as GDOP min ; Use the optimal index weight λ obtained from the theoretical trajectory in the above experiment *i , change λ *i Substitute the result of each new simulation trajectory into the settlement result to obtain the geometric precision factor GDOP value corresponding to the station configuration of each simulation trajectory with the minimum index, which is recorded as Then, the applicability of the constructed station layout optimization evaluation index A under the non-cooperative target with the same starting point but different rotation angles is tested by formula (26). θ :

[0232]

[0233] Repeat the above experiment 10 times, and each time only the station position is randomly selected. The experimental results are as follows Figure 11 , the horizontal axis is the rotation angle θ, and the vertical axis is the applicability of the indicator on the rotation trajectory A θ It can be seen that the optimal weight λ obtained using the theoretical trajectory *i , applied to each new simulation trajectory, the minimum index value GDOP calculated Jmin The corresponding station layout plan, relative to the theoretical optimal value GDOP min The average degradation degree of the indicator when it rotates 1 to 30 degrees in the east direction is about 0.2.

[0234] Next, we consider the second type of bias and examine the applicability of the indicator to a parallel non-cooperative trajectory at a distance d from the historical trajectory. In the simulation, the theoretical trajectory is translated left and right on a plane with an unchanging east direction, with a distance of 3000 meters to the left and 3000 meters to the right, with each translation distance of 100 meters. After obtaining 60 different simulated trajectories, the trajectory is solved and the minimum GDOP value obtained by calculating the optimal station configuration for each simulated trajectory is recorded as GDOP. min ; Use the optimal index weight obtained through theoretical trajectory in the above experiment Will Substitute the settlement results of each new simulation trajectory to obtain the GDOP value corresponding to the station configuration with the minimum index for each simulation trajectory, which is recorded as Then, the applicability of the constructed station layout optimization evaluation index A under the non-cooperative target with the same starting point but different rotation angles is tested by formula (27). d :

[0235]

[0236] Repeat the above experiment 10 times, and the results are as follows Figure 12 , the horizontal coordinate is the translation distance d, leftward movement is negative and rightward movement is positive, and the vertical coordinate is A d The further to the right (north), Relative to GDOP min The lower the degradation degree, the better the indicator effect, and vice versa. Under the non-cooperative target with translation bias, the indicator effect is poor, even if it is translated to the right by 3000 meters, Relative to GDOP min The degree of degradation is still close to 0.4.

[0237] The following conclusions can be drawn from the above experiments: (1) When the line connecting the starting point and the end point of the non-cooperative target is an oblique flight trajectory, try to select the historical cooperative trajectory based on the rotation offset, and optimize the station layout plan through the optimal weight of the historical trajectory; (2) When there is no suitable cooperative trajectory consistent with the starting point or end point of the non-cooperative target in the historical database, when using the station layout optimization simulation method of the embodiment of the present invention to select the historical test trajectory based on the translation offset to optimize the station layout plan, the historical trajectory located in the south direction of the non-cooperative trajectory should be selected.

[0238] In order to further test the applicability of the indicators under different trajectories, the following experiment will test the applicability of the indicators on non-cooperative targets in level flight. First, a level flight simulation trajectory (such as Figure 13 ), that is, the trajectory remains unchanged in the celestial direction, and the inspection method is the same as that of the oblique flight segment.

[0239] The simulated trajectory of the horizontal flight segment is rotated around the starting point of the trajectory on a plane with a constant celestial direction, with a rotation angle of 1 to 30 degrees, and each rotation angle is 1 degree, to obtain 30 different simulated trajectories. The simulated trajectory of the horizontal flight segment is translated left and right on a plane with a constant celestial direction, with a distance of 3000 meters to the left and 3000 meters to the right, and each translation distance is 100 meters, to obtain 60 different simulated trajectories. After obtaining these simulated trajectories, the applicability of the indicator A is tested. θ With A d , Figure 14 The graph shows the experimental results of 10 repeated experiments.

[0240] Depend on Figure 14As can be seen, for rotations of 0 to 30 degrees and translations of -3000 to 3000 meters, the indicator output based on historical trajectory shows the degree of degradation of the station plan's GDOP relative to the theoretical optimal value. The average degradation for rotation angle is 0.0498, and the average degradation for translation is 0.0637, indicating good applicability of the indicator.

[0241] The above experiments can draw the following conclusions: (1) In the rotation range of 0 to 30 degrees and the translation range of [-3000, 3000] in the level flight phase, the difference between the station layout scheme obtained by the station layout optimization simulation method and the theoretical optimal value when the trajectory is completely known is less than 5%; (2) Compared with the oblique flight phase trajectory, the indicator has better applicability in the level flight phase trajectory.

[0242] The beneficial technical effects achieved by the embodiments of the present invention are as follows:

[0243] For the optimization of station placement in passive angle measurement systems, a new station placement optimization evaluation metric and corresponding factors, distinct from traditional evaluation metrics such as GDOP and CRLB, are constructed. Based on this metric, a new station placement optimization simulation method is proposed. This method, independent of theoretical trajectories, utilizes only the direction vector connecting the target's starting and ending points to achieve optimal placement. This approach addresses the inability of traditional station placement methods to be applied to non-cooperative targets. A new station placement optimization evaluation metric is constructed to address the issue of actual data consistency in air-to-air confrontation scenarios in target positioning and tracking, specifically the consistency of data from the trajectory to the encounter phase and from the aircraft to the missile. This metric only requires the direction vector of the non-cooperative target's motion, eliminating reliance on theoretical trajectories. Using historical test trajectories, an adaptive genetic algorithm is used to determine the optimal weights for each factor. This weighted weight is then applied to the positioning of non-cooperative targets, resulting in a more optimal station placement solution for non-cooperative targets.

[0244] In the experimental phase, the proposed method was applied to the positioning of cooperative targets. The station combination selected when the global optimal metric value was minimized was consistent with the station combination selected using GDOP, verifying the effectiveness of the metric and the feasibility of the method. Secondly, in simulation experiments for the positioning of non-cooperative targets, the sensitivity of the new metric to two types of biases was analyzed, demonstrating the metric's applicability: when the non-cooperative target's direction vector is an oblique flight trajectory, historical cooperative trajectories based on rotational bias are preferred; and compared with oblique flight trajectories, the metric is more applicable to level flight trajectories. This method is independent of prior trajectory information and does not require theoretical trajectory support. It simply obtains the line connecting the non-cooperative target's starting point and end point in the positioning space and compares it with historical trajectories. By calculating the magnitude of the metric, the station placement optimization problem for non-cooperative targets can be solved.

[0245] It should be understood that the specific order or hierarchy of steps in the disclosed processes is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process can be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy described.

[0246] In the foregoing detailed description, various features are grouped together in a single embodiment to simplify the disclosure. This method of disclosure should not be interpreted as reflecting an intention that embodiments of the claimed subject matter require more features than are expressly recited in each claim. On the contrary, as reflected in the appended claims, the invention comprises less than all the features of any individual disclosed embodiment. The appended claims are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.

[0247] The above description of the disclosed embodiments is intended to enable any person skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the spirit and scope of the present disclosure. Therefore, the present disclosure is not limited to the embodiments presented herein but is intended to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0248] The foregoing description includes examples of one or more embodiments. Of course, it is not possible to describe all possible combinations of components or methods for the purposes of describing the above embodiments, but one of ordinary skill in the art will recognize that the various embodiments may be further combined and arranged. Therefore, the embodiments described herein are intended to encompass all such changes, modifications and variations that fall within the scope of the appended claims. Furthermore, to the extent the term "comprising" is used in the specification or claims, the term is intended to be encompassed in a manner similar to the term "including," as explained in terms of "including," used as a transitional word in the claims. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or."

[0249] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A station layout optimization method under non-cooperative target angular positioning, characterized in that: include: Before optimizing the station configuration for tracking and positioning a non-cooperative target, an indicator for evaluating the positioning accuracy of the station configuration is constructed based on the indicator elements for evaluating positioning accuracy. The station configuration refers to the process of selecting multiple measuring devices from existing measuring devices to perform the measurement and positioning task of the target. The process of selecting measuring devices is called station configuration, the selected measuring devices are called station configuration scheme, and the geometric configuration of the selected measuring devices in space is called station configuration. Obtain historical measurement data for each cooperative target trajectory in the historical trajectory library, calculate the values ​​of various indicator elements of an indicator for evaluating the positioning accuracy of the station configuration corresponding to the cooperative target trajectory based on the historical measurement data of each cooperative target trajectory, construct corresponding indicators based on the various indicator elements corresponding to the cooperative target trajectory, and determine the optimal weights corresponding to the various indicator elements of the cooperative target trajectory by optimizing the constructed indicators; When positioning and tracking a non-cooperative target, a motion direction vector of the non-cooperative target trajectory is obtained, multiple cooperative target trajectories in a historical trajectory library are obtained, the non-cooperative target trajectory is rotationally offset to obtain a first offset trajectory, and the non-cooperative target trajectory is translationally offset to obtain a second offset trajectory, and a cooperative target trajectory with the same starting point or end point that the first offset trajectory can fall into is used as the optimization trajectory, or a parallel cooperative target trajectory that the second offset trajectory can fall into is used as the optimization trajectory, and the optimal weight corresponding to each indicator element of the optimized trajectory is used as the optimal weight corresponding to each indicator element of the non-cooperative target trajectory, wherein the motion direction vector of the non-cooperative target trajectory refers to a line connecting the starting point and the end point of the non-cooperative target; Acquire actual measurement data obtained from the motion direction vector of the non-cooperative target's trajectory, construct multiple sets of preliminary station configurations from existing measurement equipment, calculate the index value of each index element of each set of preliminary station configurations based on the weights corresponding to each index element of the optimized trajectory and the actual measurement data of the non-cooperative target, and use the preliminary station configuration corresponding to the minimum index value as the optimal station configuration for positioning the non-cooperative target; The non-cooperative target is positioned and tracked through a station layout plan within the optimal station layout configuration.

2. The station layout optimization method under non-cooperative target angular positioning according to claim 1 is characterized in that: The index elements include: angle difference, sight line distance, baseline intersection angle, consistency of target trajectory data and encounter data, and consistency of aircraft data and missile data at the time of target launch. The target can be a cooperative target or a non-cooperative target. Among them, consistency of target trajectory data and encounter data, and consistency of aircraft data and missile data at the time of target launch belong to data consistency. Angle differential refers to the difference between the angle measurement data of the jth measuring device at the i-th moment and the angle measurement data of the target at the i-1-th moment. The angle measurement data includes azimuth and elevation. The angle differential includes the second-order difference of azimuth and the second-order difference of elevation. The sight line distance refers to the distance from the measuring device to the target; The baseline is the line between the measuring device and the target, and the baseline intersection angle is the angle between the baselines corresponding to two different measuring devices; The consistency of the target's ballistic segment data and encounter segment data refers to the following: in an air-to-air confrontation scenario, the target's motion is divided into three different phases: the spring segment, the ballistic segment, and the encounter segment. The target includes the carrier aircraft and / or the missile carried by the carrier aircraft. The spring segment is the phase in which the carrier aircraft and the missile on board fly together. At the end of the spring segment, the missile separates from the carrier aircraft and flies independently toward the target aircraft. At this time, the target being measured becomes the missile and enters the ballistic segment. The encounter segment is the end of the ballistic segment, when the measurement equipment can simultaneously observe the missile and the target aircraft until the missile impacts the target aircraft. When multiple measurement stations are used to measure the missile and the target aircraft, there will be overlapping target positions in the encounter segment. By comparing the target positions in the overlapping segments measured by different measurement stations, the ballistic position data obtained is used to determine the consistency of the target's ballistic segment data and the encounter segment data. The consistency of the carrier aircraft data and the missile data when the target is launched means that: during the winding stage, the missile has not yet separated from the carrier aircraft, and the measuring equipment will simultaneously measure the carrier aircraft position and the missile position. The difference between the carrier aircraft position and the missile position is less than 1 / 2 of the carrier aircraft's own structural length, 1 / 2 of the width, and 1 / 2 of the height.

3. The station layout optimization method under non-cooperative target angular positioning according to claim 2 is characterized in that: The steps of obtaining historical measurement data of each cooperative target trajectory in the historical trajectory library, calculating, for each historical measurement data of each cooperative target trajectory, values ​​of various index elements of an indicator for evaluating the positioning accuracy of a station configuration corresponding to the cooperative target trajectory, constructing corresponding indicators based on the various index elements corresponding to the cooperative target trajectory, and determining the optimal weights corresponding to the various index elements of the cooperative target trajectory by optimizing the constructed indicators include: Determine the initial weights of each indicator element corresponding to the cooperation target trajectory; Combined with the station configuration for positioning the cooperative target, the historical measurement data Y of the cooperative target's trajectory is solved to obtain the trajectory solution result of the cooperative target. Based on the trajectory solution result, the values ​​of various indicator elements corresponding to the cooperative target are calculated; According to the values ​​of each index element and the corresponding initial weight, an index for evaluating the positioning accuracy of the corresponding station configuration is constructed, and the index value is converged to the minimum; Comparing the historical measurement data of the station configuration when the index value is minimum with the theoretical trajectory of the cooperative target to obtain the measurement accuracy of the cooperative target; When the cooperative target measurement accuracy value is optimized to a minimum by an adaptive genetic algorithm, the weights corresponding to the various indicator elements when the cooperative target measurement accuracy value is optimized to a minimum are used as the optimal weights corresponding to the various indicator elements of the cooperative target trajectory.

4. The station layout optimization method under non-cooperative target angular positioning according to claim 3 is characterized in that: Compare the historical measurement data of the station configuration when the index value is minimum with the theoretical trajectory of the cooperative target to obtain the cooperative target measurement accuracy, including: For the historical measurement data of the cooperative target trajectory, the decision variable refers to the weight λ corresponding to each indicator element i , the geometric dilution of precision GDOP of the station configuration corresponding to the minimum value of index J is recorded as GDOP Jmin , the station configuration with the minimum geometric precision factor GDOP is taken as the optimal station configuration, and the geometric precision factor GDOP of the optimal station configuration is recorded as GDOP min , construct the objective function f to be optimized, the objective function f to be optimized is the GDOP of the station configuration corresponding to the maximum value of index J Jmin GDOP of the optimal station configuration min The difference between , and the measurement accuracy of the cooperative target is expressed by the difference; When the cooperative target measurement accuracy value is optimized to a minimum by an adaptive genetic algorithm, the weights corresponding to the various indicator elements when the cooperative target measurement accuracy value is optimized to a minimum are used as the optimal weights corresponding to the various indicator elements of the cooperative target trajectory, including: For the objective function f to be optimized, the adaptive genetic algorithm achieves the trade-off between searching for solutions and randomness in different ways, and adaptively changes the values ​​of crossover and mutation probabilities according to the fitness value. When the population constituting the solution tends to stay at the local optimum, the fitness of the population constituting the solution is concentrated, and the diversity is relatively poor, the crossover and mutation probabilities increase. When the population constituting the solution is scattered in the solution space, the crossover and mutation probabilities decrease. When the population constituting the solution tends to stay at the global optimum, the cooperative target measurement accuracy is determined to be the highest. When the population constituting the solution tends to stay at the global optimum, the weight corresponding to the indicator element is given as the optimal weight.

5. The station layout optimization method under non-cooperative target angular positioning according to claim 3 is characterized in that: When positioning and tracking a non-cooperative target, a motion direction vector of the non-cooperative target trajectory is obtained, multiple cooperative target trajectories in a historical trajectory library are obtained, the non-cooperative target trajectory is rotationally offset to obtain a first offset trajectory, and the non-cooperative target trajectory is translationally offset to obtain a second offset trajectory, a cooperative target trajectory with the same starting point or end point that the first offset trajectory can fall into is used as an optimization trajectory, or a parallel cooperative target trajectory that the second offset trajectory can fall into is used as an optimization trajectory, and the optimal weight corresponding to each indicator element of the optimization trajectory is used as the optimal weight corresponding to each indicator element of the non-cooperative target trajectory, including: If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical trajectory library is within a threshold range, and the distance between the end point of the motion direction vector of the non-cooperative target trajectory and the end point of the cooperative target trajectory is outside the threshold range, then the non-cooperative target trajectory is rotated and offset around the starting point; a first offset trajectory having a varying angle with the non-cooperative target trajectory is obtained; the cooperative target trajectory whose starting point is consistent with the first offset trajectory and at which the angle between the first offset trajectory and the non-cooperative target trajectory is minimized is used as the trajectory for optimization; and the optimal weight corresponding to each indicator element of the optimized trajectory is used as the weight corresponding to each indicator element of the non-cooperative target trajectory; If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical ballistic library is outside the threshold range, and the closest distance between the end point of the motion direction vector of the non-cooperative target trajectory and the cooperative target trajectory is outside the threshold range, then the non-cooperative target trajectory is translated and offset to obtain multiple second offset orbits, and the parallel cooperative target trajectory into which the second offset orbit can fall and the cooperative target trajectory with the smallest distance between the second offset orbit and the non-cooperative target trajectory at this time is used as the trajectory used for optimization, and the optimal weights corresponding to each indicator element of the optimized trajectory are used as the weights corresponding to each indicator element of the non-cooperative target trajectory.

6. The station layout optimization method under non-cooperative target angular positioning according to claim 5 is characterized in that: Acquire actual measurement data obtained from the motion direction vector of the non-cooperative target trajectory, construct multiple groups of preliminary station configurations from existing measurement equipment, calculate the index value of each index element of each group of preliminary station configurations based on the weights corresponding to each index element of the optimized trajectory and the actual measurement data of the non-cooperative target, and use the preliminary station configuration corresponding to the minimum index value as the optimal station configuration for positioning the non-cooperative target, including: Acquire actual measurement data based on the motion direction vector of the non-cooperative target's trajectory and construct multiple sets of preliminary station configurations from existing measurement equipment. The actual measurement data includes: angle difference, sight line distance, baseline intersection angle, consistency between the target's ballistic segment data and the encounter segment data, and consistency between the carrier aircraft data and the missile data at the time of target launch. For each set of preliminary station configurations, the following constraints are imposed: Constrain the second-order difference of azimuth and elevation angles to the minimum; Make the sight line distance of each measuring device in the preliminary station configuration as small as possible; Make the intersection angle of each baseline in the preliminary station configuration as close to 90 degrees as possible; In the set of preliminary station configurations, the target position of each measurement overlap segment in the consistency between the target's trajectory segment data and the encounter segment data is minimized; Within this group of preliminary station configurations, the consistency between the aircraft data and the missile data during launch of non-cooperative targets is met; The index of the group of preliminary station configurations is constructed by the weights corresponding to the above constraints and the index elements of the track used for optimization, and the preliminary station configuration corresponding to the minimum index value is used as the optimal station configuration for positioning the non-cooperative target.

7. The station layout optimization method under non-cooperative target angular positioning according to claim 5, characterized in that: When positioning and tracking a non-cooperative target, a motion direction vector of the non-cooperative target trajectory is obtained, multiple cooperative target trajectories in a historical trajectory library are obtained, the non-cooperative target trajectory is rotationally offset to obtain a first offset trajectory, and the non-cooperative target trajectory is translationally offset to obtain a second offset trajectory, a cooperative target trajectory with the same starting point or end point that the first offset trajectory can fall into is used as an optimization trajectory, or a parallel cooperative target trajectory that the second offset trajectory can fall into is used as an optimization trajectory, and the optimal weight corresponding to each indicator element of the optimization trajectory is used as the optimal weight corresponding to each indicator element of the non-cooperative target trajectory, including: When the motion direction vector of the non-cooperative target trajectory is an oblique flight trajectory, the target cooperative trajectory whose rotation offset change in the celestial direction relative to the non-cooperative target trajectory is less than the angle threshold is selected as the trajectory used for optimization; If the distance between the starting point of the motion direction vector of the non-cooperative target trajectory and the starting point of any cooperative target trajectory in the historical ballistic library is outside the threshold range, and the closest distance between the end point of the motion direction vector of the non-cooperative target trajectory and the cooperative target trajectory is within the threshold range, then the non-cooperative target trajectory is rotated and offset around the end point to obtain a third offset trajectory with a varying angle to the non-cooperative target trajectory. The cooperative target trajectory on which the third offset trajectory can fall, and the cooperative target trajectory with the smallest angle between the third offset trajectory and the non-cooperative target trajectory at this time, is used as the trajectory used for optimization.

8. A station layout optimization system under non-cooperative target angle measurement positioning, characterized in that: include: An indicator element construction unit is used to construct an indicator for evaluating the positioning accuracy of the station configuration based on the indicator elements for evaluating positioning accuracy before optimizing the station configuration for tracking and positioning a non-cooperative target. The station configuration refers to the process of selecting multiple measuring devices from existing measuring devices to perform a target measurement and positioning task. The process of selecting measuring devices is called station configuration, the selected measuring devices are called station configuration scheme, and the geometric configuration of the selected measuring devices in space is called station configuration. A cooperative target weight optimization unit is configured to obtain historical measurement data for each cooperative target trajectory in the historical trajectory library, calculate, based on the historical measurement data for each cooperative target trajectory, the values ​​of various index elements of an indicator for evaluating the positioning accuracy of a station configuration corresponding to the cooperative target trajectory, construct corresponding indicators based on the various index elements of the indicator corresponding to the cooperative target trajectory, and determine the optimal weight corresponding to each index element of the cooperative target trajectory by optimizing the constructed indicators; A weight optimization construction unit for a non-cooperative target is used to, when positioning and tracking a non-cooperative target, obtain a motion direction vector of the non-cooperative target trajectory, obtain multiple cooperative target trajectories in a historical trajectory library, rotate and offset the non-cooperative target trajectory to obtain a first offset trajectory, and translate and offset the non-cooperative target trajectory to obtain a second offset trajectory, use the cooperative target trajectory with the same starting point that the first offset trajectory can fall into as the trajectory used for optimization, or use the parallel cooperative target trajectory that the second offset trajectory can fall into as the trajectory used for optimization, and use the optimal weights corresponding to each indicator element of the optimized trajectory as the optimal weights corresponding to each indicator element of the non-cooperative target trajectory, wherein the motion direction vector of the non-cooperative target trajectory refers to the line connecting the starting point to the end point of the non-cooperative target; A station layout optimization unit is configured to obtain actual measurement data obtained based on the motion direction vector of the non-cooperative target trajectory, construct multiple sets of preliminary station layout configurations from existing measurement equipment, calculate the index value of each index element of each set of preliminary station layout configurations based on the weights corresponding to each index element of the optimized trajectory and the actual measurement data of the non-cooperative target, and use the preliminary station layout configuration corresponding to the minimum index value as the optimal station layout configuration for positioning the non-cooperative target; The positioning unit is used to locate and track the non-cooperative target through a station layout plan within the optimal station layout configuration.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores one or more programs, which, when executed by a computer device, enable the computer device to execute the station layout optimization method under non-cooperative target angular positioning as described in any one of claims 1 to 7.

10. A computer device, characterized in that: include: processor; And, a memory arranged to store computer-executable instructions, which, when executed, cause the processor to execute the station layout optimization method under non-cooperative target angular positioning as described in any one of claims 1-7.

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