Optimization method for high-precision missile target detection and positioning

Abstract

The present invention relates to the field of target detection and positioning, and specifically to an optimization method for high-precision missile target detection and positioning, wherein the method obtains N missiles deployed in a predetermined mission area, wherein the N missiles are equipped with target detection sensors and wireless communication modules; the actual position measurement data of the targets detected by the N missiles are sent to a central data processing center through a wireless communication module, and then fused and processed through a data fusion algorithm, and the precise position data of the target is obtained through data analysis; the precise position data is transmitted in real time to a missile group composed of the N missiles, and each missile of the missile group adjusts its flight trajectory according to the precise position data; the missile group transmits information through a self-organizing network method and an anti-interference encrypted communication protocol. The method solves the problem that when multiple missiles perform collaborative tasks, they cannot effectively use the detection information of other missiles for real-time adjustment to achieve more accurate target detection and positioning.

Description

Technical Field

[0001] The invention relates to the field of target detection and positioning, and in particular to an optimization method for high-precision missile target detection and positioning. Background Art

[0002] With the continuous development of modern warfare technology, missiles, as the core equipment for precision strikes, rely heavily on the precise control of target positioning and flight trajectory. At present, the target detection and positioning technology of missiles mainly relies on several key means, such as the global positioning system (GPS), inertial navigation system (INS), and detection by radar and infrared sensors.

[0003] However, current missile target detection and positioning methods still face many challenges, especially in complex battlefield environments. These systems may be seriously affected in complex battlefield environments, such as electronic interference, target maneuvers or signal shielding, resulting in a decrease in missile target positioning and navigation accuracy. Although existing technologies have met the needs of missile navigation and target positioning to a certain extent, there are still many deficiencies and challenges in complex battlefield environments. In particular, when multiple missiles are performing collaborative tasks, the information sharing capabilities between the missiles are limited, and it is impossible to effectively use the detection information of other missiles for real-time adjustments to achieve more accurate target detection and positioning. Summary of the invention

[0004] (1) Technical issues to be resolved

[0005] The purpose of the present invention is to provide an optimization method for high-precision missile target detection and positioning, so as to solve the problem that when multiple missiles are performing collaborative tasks, the information sharing capability between the missiles is limited, and the detection information of other missiles cannot be effectively used for real-time adjustment to achieve more accurate target detection and positioning.

[0006] (2) Technical solution

[0007] To achieve the above object, on the one hand, the present invention provides an optimization method for high-precision missile target detection and positioning, the method comprising:

[0008] S1. Acquire N missiles deployed in a predetermined mission area, wherein the N missiles are equipped with a target detection sensor and a wireless communication module; the target detection sensor is used to detect the actual position measurement data of the target in real time, and the wireless communication module is used to transmit wireless data;

[0009] S2, sending the actual position measurement data of the N missile detection targets to the central data processing center through the wireless communication module; fusing the actual position measurement data of the N missile detection targets through the data fusion algorithm in the central data processing center, and obtaining the accurate position data of the targets through data analysis;

[0010] S3, transmitting the precise position data in real time to the missile group consisting of the N missiles, and each missile of the missile group adjusts the flight trajectory according to the precise position data; the missile group transmits information through a self-organizing network method and an anti-interference encrypted communication protocol.

[0011] Furthermore, the method of fusing the actual position measurement data of the N missile detection targets by a data fusion algorithm in the central data processing center and obtaining the accurate position data of the targets by data analysis includes:

[0012] The actual position measurement data includes the distance, azimuth and elevation between the missile and the target, wherein the distance is the straight-line distance between the missile and the target, the azimuth is the horizontal angle of the target relative to the missile, and the elevation is the vertical angle between the target and the missile;

[0013] Theoretical position measurement data of the target is obtained through a nonlinear model, a position measurement model is constructed by combining the actual position measurement data and the theoretical position measurement data, and accurate position data of the target is obtained through a weighted least square method and a recursive algorithm.

[0014] Furthermore, the method of obtaining theoretical position measurement data of the target through a nonlinear model and constructing a position measurement model with the actual position measurement data and the theoretical position measurement data includes:

[0015] The nonlinear model includes a distance measurement model, an azimuth measurement model, and an elevation measurement model; assuming that the target The precise location data at the moment is , No. Missiles in The location data at the moment is ;

[0016] The position measurement model is:

[0017] ;

[0018] in, For the Missiles in Detect the actual position measurement data of the target at all times; is a nonlinear observation model, which represents the theoretical position measurement data obtained by nonlinear mapping of the distance measurement model, the azimuth angle measurement model, and the elevation angle measurement model, and is The geometric relationship between the missile and the target; For the Missiles in The noise vector at time t;

[0019] The distance measurement model is used to obtain Moment The distance from the missile to the target ; The azimuth angle measurement model is used to obtain Moment Missiles and target Azimuth on a plane ; The elevation angle measurement model is used to obtain Moment The elevation angle between the missile and the target ; then the nonlinear observation model , the position measurement model is expanded as:

[0020] ;

[0021] in, , , Respectively indicate distance , azimuth , Elevation exist The noise component at the moment;

[0022] The nonlinear model is linearized before the fusion process.

[0023] Furthermore, the method of performing linearization processing on the nonlinear model before performing fusion processing includes:

[0024] Get the target's initial estimated position data When the missile is observed for the first time, the observation data of the target detected by the missile's target detection sensor for the first time is used as the initial estimated position data; when the missile has historical observation data, the historical accurate position data of the target is used to obtain the initial estimated position data through data analysis;

[0025] The nonlinear observation model After linearization, the observation matrix is ​​obtained :

[0026] ;

[0027] Then the linearized position measurement model is:

[0028] .

[0029] Furthermore, the method of obtaining accurate position data of the target by weighted least squares method and recursive algorithm includes:

[0030] The actual position measurement data of the N missile detection targets are used to obtain the optimal position estimation data of the targets through the weighted least square method, and the accurate position data of the targets are obtained through the recursive algorithm through the optimal position estimation data;

[0031] Get the Missiles in The noise covariance matrix at time , the noise covariance matrix It is The matrix of the observation noise characteristics of the missile target detection sensor; the optimal position estimation data for:

[0032] ;

[0033] in, Represents the observation matrix of the N missiles and the noise covariance matrix The weighted sum of is used to obtain the inverse matrix of the cumulative weight matrix; Represents the actual position measurement data of the N missiles After weighted accumulation, the accumulated actual position measurement data is obtained.

[0034] Furthermore, the method further comprises:

[0035] Obtain the historical accurate position data and speed information of the target and build the target's motion model through data analysis;

[0036] The optimal position estimation data and the motion model of the target are used to obtain accurate position data through a recursive algorithm.

[0037] Furthermore, the method for the missile group to transmit information through a self-organizing network method and an anti-interference encrypted communication protocol includes:

[0038] A communication network is constructed by a self-organizing network method, wherein each missile is used as a network node; when the monitored missile enters a predetermined mission area, the missile is automatically connected to another missile for communication;

[0039] When the monitoring missile loses its communication function, other missiles will automatically bypass the network nodes of the missile and re-establish the communication network.

[0040] Furthermore, the method further comprises:

[0041] Acquire the precise position data of any two missiles in the missile group and obtain the distance between the missiles by a three-dimensional Euclidean distance calculation method, obtain the minimum communication range of the two missiles, and if the distance between the missiles is less than the minimum communication range, establish a communication link between the two missiles;

[0042] Through undirected graph representing a communication network of said missile group, is the collection of all missiles in the missile group, is the set of communication links between missiles; if the monitored missile loses its communication function and is recorded as a failed missile, the network node of the failed missile is deleted in the undirected graph, the latest adjacency list between the missiles is updated, and the shortest communication path between each missile in the missile group and other missiles is recalculated, and the communication network is updated according to the latest adjacency list and the shortest communication path.

[0043] Furthermore, the method further comprises:

[0044] When the signal strength of the monitored communication link is lower than the preset signal strength threshold data, the communication link is disconnected; when the monitored communication link is disconnected, the missile group executes a bypass strategy and starts a communication link repair mechanism. The bypass strategy is that the remaining missiles reorganize the communication links and bypass the disconnected communication links.

[0045] Furthermore, the method of the communication link repair mechanism includes:

[0046] The communication link repair mechanism includes constructing a relay node to maintain information transmission strategy and a signal strength enhancement strategy; the constructing a relay node to maintain information transmission strategy is to use the network nodes of one or more missiles of the remaining missiles in the missile group as intermediate network nodes and calculate a new communication path;

[0047] The signal strength enhancement strategy is to obtain a new signal strength by increasing the transmission power of the missile wireless communication module. If the new signal strength is greater than the preset signal strength threshold data, the communication link returns to normal.

[0048] (3) Beneficial effects

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. Effectively process measurement data from multiple missiles, improve the accuracy of target detection and update the target's position information in real time, which can reduce the error that may be caused by a single missile sensor, enhance the robustness of the system, and ensure that the target position estimation is more accurate and reliable.

[0051] 2. The self-organizing network mechanism and communication link repair mechanism were introduced, and a dynamic anti-interference communication network was built in the missile group to ensure that in the event of failure of individual missiles or link interruption, the missile group can still quickly adjust the communication path and maintain smooth data transmission, significantly improving the communication stability and anti-interference capability in complex environments, thereby achieving accurate target detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0053] Figure 1 This is a flowchart of an optimization method for high-precision missile target detection and positioning according to Example 1 of the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0055] Before giving examples, it is necessary to explain the application scenarios of the present invention. The present invention is applied to missile target detection and positioning optimization.

[0056] Example 1: Figure 1 As shown, this embodiment provides an optimization method for high-precision missile target detection and positioning, the method comprising:

[0057] S1. Obtain N missiles deployed in a predetermined mission area, wherein the N missiles are equipped with target detection sensors and wireless communication modules; the target detection sensors are used to detect the actual position measurement data of the target in real time, and the wireless communication modules are used to transmit wireless data; each missile is equipped with a target detection sensor, such as a radar sensor, an infrared sensor, etc., which can measure the distance, azimuth and elevation between the target and the missile in real time. The radar sensor can measure the distance and azimuth of the target. The infrared sensor is used to capture the heat source information of the target, and the angle and distance of the target can be obtained. The wireless communication module is used for wireless data exchange between missiles and with the central data processing center.

[0058] S2, sending the actual position measurement data of the target detected by the N missiles to the central data processing center through the wireless communication module; the actual position measurement data of the target detected by the N missiles are fused and processed by the data fusion algorithm in the central data processing center, and the accurate position data of the target is obtained through data analysis; each missile independently detects the target position from different angles, distances and directions through its sensor, including the three-dimensional coordinates, velocity vector, etc. of the target. The N missiles form multi-angle coverage of the target through their own different detection angles and positions, thereby improving the detection probability and accuracy of the target.

[0059] S3, transmitting the precise position data to the missile group composed of the N missiles in real time, and each missile of the missile group adjusts the flight trajectory according to the precise position data; the missile group transmits information through a self-organizing network method and an anti-interference encrypted communication protocol. After receiving the measurement data from multiple missiles, the central data processing center will integrate the measurement data provided by different missiles through a data fusion algorithm. In this embodiment, the weighted least squares method is used for data fusion. Each missile may produce different measurement errors due to sensor accuracy or interference. Therefore, the weighted fusion method can reduce the impact of a single measurement error and improve the overall measurement accuracy. The encrypted communication protocol includes an end-to-end encryption mechanism, and uses an advanced encryption standard (such as AES) to encrypt data to ensure the integrity and security of the data during transmission. For example: if missile 1 measures the target distance to 300 meters and missile 2 measures 295 meters, a weighted average of 298 meters may be obtained through the fusion algorithm as a more accurate distance estimate.

[0060] The method of fusing the actual position measurement data of the N missile detection targets by a data fusion algorithm at the central data processing center and obtaining the accurate position data of the targets by data analysis includes:

[0061] The actual position measurement data includes the distance, azimuth and elevation between the missile and the target, wherein the distance is the straight-line distance between the missile and the target, the azimuth is the horizontal angle of the target relative to the missile, and the elevation is the vertical angle between the target and the missile;

[0062] Theoretical position measurement data of the target is obtained through a nonlinear model, a position measurement model is constructed by combining the actual position measurement data and the theoretical position measurement data, and accurate position data of the target is obtained through a weighted least square method and a recursive algorithm.

[0063] The method of obtaining theoretical position measurement data of a target through a nonlinear model and constructing a position measurement model with the actual position measurement data and the theoretical position measurement data comprises:

[0064] The nonlinear model includes a distance measurement model, an azimuth measurement model, and an elevation measurement model; assuming that the target The precise location data at the moment is , No. Missiles in The location data at the moment is ;

[0065] The position measurement model is:

[0066] ;

[0067] in, For the Missiles in Detect the actual position measurement data of the target at all times; is a nonlinear observation model, which represents the theoretical position measurement data obtained by nonlinear mapping of the distance measurement model, the azimuth angle measurement model, and the elevation angle measurement model, and is The geometric relationship between the missile and the target; For the Missiles in The noise vector at time t;

[0068] The distance measurement model is used to obtain Moment The distance from the missile to the target ; The azimuth angle measurement model is used to obtain Moment Missiles and target Azimuth on a plane ; The elevation angle measurement model is used to obtain Moment The elevation angle between the missile and the target ; then the nonlinear observation model , the position measurement model is expanded as:

[0069] ;

[0070] in, , , Respectively indicate distance , azimuth , Elevation exist The noise component at the moment;

[0071] The nonlinear model is linearized before the fusion process. Noise is caused by the inaccuracy of the target detection sensor, signal interference or other external factors, which affects the observed data. The noise vector obeys a zero-mean Gaussian distribution.

[0072] The method of performing linearization processing on the nonlinear model before performing fusion processing includes:

[0073] Get the target's initial estimated position data When the missile is observed for the first time, the observation data of the target detected by the missile's target detection sensor for the first time is used as the initial estimated position data; when the missile has historical observation data, the historical accurate position data of the target is used to obtain the initial estimated position data through data analysis;

[0074] The nonlinear observation model After linearization, the observation matrix is ​​obtained :

[0075] ;

[0076] Then the linearized position measurement model is:

[0077] .

[0078] The nonlinear observation model is linearized by Taylor expansion, which facilitates the application of linear estimation methods. For example, when the missile is observed for the first time, the distance detected by the sensor is , azimuth , Elevation The initial estimated position data of the target is obtained through mathematical transformation , the mathematical transformation uses polar coordinates to Cartesian coordinates conversion, , , .

[0079] The method for obtaining accurate position data of a target by using a weighted least square method and a recursive algorithm comprises:

[0080] The actual position measurement data of the N missile detection targets are used to obtain the optimal position estimation data of the targets through the weighted least square method, and the accurate position data of the targets are obtained through the recursive algorithm through the optimal position estimation data;

[0081] Get the Missiles in The noise covariance matrix at time , the noise covariance matrix It is The matrix of the observation noise characteristics of the missile target detection sensor; the optimal position estimation data for:

[0082] ;

[0083] in, Represents the observation matrix of the N missiles and the noise covariance matrix The weighted sum of is used to obtain the inverse matrix of the cumulative weight matrix; Represents the actual position measurement data of the N missiles The accumulated actual position measurement data is obtained after weighted accumulation. The weighted least squares method is used to merge the observation data of N missiles. The least squares method uses the noise covariance matrix of each missile measurement data to perform weighted calculations to obtain the optimal position estimate of the target. The inverse matrix of the accumulated weight matrix is ​​used to correct and adjust the observation data. The measurement noise covariance matrix is ​​a characteristic parameter of the missile measurement system, which reflects the performance of the missile target detection sensor and the influence of the external environment (such as interference signals). It is used to measure the noise size of the missile observation data. The larger the noise covariance, the greater the measurement data error. The noise covariance matrix can be used to calculate the noise covariance from the experimental data through statistical analysis methods, and is updated in real time through a recursive algorithm during real-time operation. The inverse matrix of the noise covariance matrix is ​​used to adjust the weights of different missile observation data in the weighted least squares method. The larger the noise of the missile, the smaller the weight; the smaller the noise, the larger the weight, so that the observation data with higher accuracy contributes more to the final estimation result.

[0084] The method also includes: obtaining historical precise position data and speed information of the target and constructing a motion model of the target through data analysis; the historical precise position data and speed information can provide the trajectory and trend of the target's motion, and this information can construct a motion model of the target, such as a uniform linear motion or acceleration model.

[0085] The optimal position estimation data and the motion model of the target are combined through a recursive algorithm to obtain accurate position data. At each moment, the new measurement data of each missile is combined with the motion model, so that the target position is further corrected through the recursive algorithm. The recursive algorithm uses the optimal position estimate to continuously correct and update the position of the target, which can eliminate the noise influence of data between different missiles as much as possible. This embodiment uses Kalman filtering to obtain the precise position of the target. In the central data processing center, the Kalman filter combines the actual position measurement data from multiple missiles, recursively estimates the state of the target through two steps of prediction and observation update, and corrects the target position estimate in real time in multi-missile collaborative target detection. In addition, the combination of the target's motion model and sensor observation data can effectively handle the noise influence, thereby improving the positioning accuracy and robustness of the entire system.

[0086] The method for the missile group to transmit information through a self-organizing network method and an anti-interference encrypted communication protocol includes:

[0087] A communication network is constructed by a self-organizing network method, wherein each missile is used as a network node; when the monitored missile enters a predetermined mission area, the missile is automatically connected to another missile for communication;

[0088] When the monitoring missile loses its communication function, other missiles will automatically bypass the network nodes of the missile and re-establish the communication network. Each missile in the missile group has a wireless communication module that can automatically establish a communication link. When the missile group enters the mission area, the missiles will establish a communication network with each other through self-organizing network technology to ensure that data can be transmitted quickly. When one of the missiles loses its communication function, the network can also automatically bypass the faulty node to re-establish the connection. During the execution of the mission, some missiles may lose their communication function and become failed nodes due to interference or hardware failure. For example, when missile 1 fails, other missiles in the missile group automatically reorganize the communication network to ensure that information transmission is not interrupted.

[0089] The method further includes: obtaining accurate position data of any two missiles in the missile group and obtaining the distance between the missiles by a three-dimensional Euclidean distance calculation method, obtaining a minimum communication range between the two missiles, and if the distance between the two missiles is less than the minimum communication range, establishing a communication link between the two missiles;

[0090] Through undirected graph representing a communication network of said missile group, is the collection of all missiles in the missile group, is the set of communication links between missiles; if the monitored missile loses its communication function and is recorded as a failed missile, the network node of the failed missile is deleted in the undirected graph and the latest adjacency list between missiles is updated, and the shortest communication path between each missile in the missile group and other missiles is recalculated, and the communication network is updated according to the latest adjacency list and the shortest communication path. Each missile in the missile group is regarded as a network node and has its own location information and communication capability; the communication link between each two missiles depends on the distance between them and the communication range. The adjacency list is the communication link established by the missiles adjacent to one of the missile network nodes. For example, if the K network node in the missile group fails, the remaining missiles will delete the communication links related to the K network node in the undirected graph to obtain a new undirected graph. The adjacency list update is that all missiles adjacent to the K network node recalculate the adjacency list and find the communication link with other missiles. The Dijkstra algorithm or Bellman-Ford algorithm is used to perform path optimization calculation on the new undirected graph.

[0091] The method further includes: when the signal strength of the monitored communication link is lower than the preset signal strength threshold data, the communication link is disconnected; when the monitored communication link is disconnected, the missile group executes a bypass strategy and starts a communication link repair mechanism, wherein the bypass strategy is that the remaining missiles reorganize the communication link and bypass the disconnected communication link. If the signal strength is too low, it will affect the continuous stability of the overall communication and the smooth execution of the task. Therefore, in order to ensure the normal communication network, it is necessary to monitor the signal strength of the communication link and dynamically adjust the network topology to ensure that the missile group maintains effective communication.

[0092] The method of the communication link repair mechanism includes:

[0093] The communication link repair mechanism includes constructing a relay node to maintain information transmission strategy and a signal strength enhancement strategy; the constructing a relay node to maintain information transmission strategy is to use the network nodes of one or more missiles of the remaining missiles in the missile group as intermediate network nodes and calculate a new communication path;

[0094] The signal strength enhancement strategy is to obtain a new signal strength by increasing the transmission power of the missile wireless communication module. If the new signal strength is greater than the preset signal strength threshold data, the communication link returns to normal. When the communication link is interrupted, the missile group will start a bypass strategy or build a relay node. The bypass strategy refers to other missiles bypassing the disconnected communication link by reorganizing the network. The relay node strategy maintains communication by allowing nearby missiles to serve as relay points. If the relay node strategy cannot restore communication, the missile can also increase the transmission power to enhance the signal strength, thereby restoring the communication link. For example, after the communication link between missile 2 and missile 3 is disconnected, missile 4 takes over the transmission task as a relay node. If missile 4 cannot serve as a relay node, then missile 2 or 3 increases the signal transmission power to restore communication.

[0095] Finally, it should be noted that: Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An optimization method for high-precision missile target detection and positioning, characterized in that: The method comprises: Acquire N missiles deployed in a predetermined mission area, wherein the N missiles are equipped with a target detection sensor and a wireless communication module; the target detection sensor is used to detect the actual position measurement data of the target in real time, and the wireless communication module is used to transmit wireless data; The actual position measurement data of the N missile detection targets are sent to a central data processing center through a wireless communication module; the actual position measurement data of the N missile detection targets are fused and processed by a data fusion algorithm in the central data processing center, and the precise position data of the targets are obtained through data analysis; The precise location data is transmitted in real time to the missile group consisting of the N missiles, and each missile of the missile group adjusts its flight trajectory according to the precise location data; the missile group transmits information through a self-organizing network method and an anti-interference encrypted communication protocol; The method of fusing the actual position measurement data of the N missile detection targets by a data fusion algorithm at the central data processing center and obtaining the accurate position data of the targets by data analysis includes: The actual position measurement data includes the distance, azimuth and elevation between the missile and the target, wherein the distance is the straight-line distance between the missile and the target, the azimuth is the horizontal angle of the target relative to the missile, and the elevation is the vertical angle between the target and the missile; Obtain theoretical position measurement data of the target through a nonlinear model, construct a position measurement model with the actual position measurement data and the theoretical position measurement data, and obtain accurate position data of the target through a weighted least square method and a recursive algorithm; The method of obtaining theoretical position measurement data of a target through a nonlinear model and constructing a position measurement model with the actual position measurement data and the theoretical position measurement data comprises: The nonlinear model includes a distance measurement model, an azimuth measurement model, and an elevation measurement model; The precise location data at the moment is , No. Missiles in The location data at the moment is ; The position measurement model is: ; in, For the Missiles in Detect the actual position measurement data of the target at all times; is a nonlinear observation model, which represents the theoretical position measurement data obtained by nonlinear mapping of the distance measurement model, the azimuth angle measurement model, and the elevation angle measurement model, and is The geometric relationship between the missile and the target; For the Missiles in The noise vector at time instant; The distance measurement model is used to obtain Moment The distance from the missile to the target ; The azimuth angle measurement model is used to obtain Moment Missiles and target Azimuth on a plane ; The elevation angle measurement model is used to obtain Moment The elevation angle between the missile and the target ; then the nonlinear observation model , the position measurement model is expanded as: ； in, , , Respectively indicate distance , azimuth , Elevation exist The noise component at the moment; The nonlinear model is linearized before the fusion process.

2. The optimization method for high-precision missile target detection and positioning according to claim 1 is characterized in that: The method of performing linearization processing on the nonlinear model before performing fusion processing includes: Get the target's initial estimated position data When the missile is observed for the first time, the observation data of the target detected by the missile's target detection sensor for the first time is used as the initial estimated position data; when the missile has historical observation data, the historical accurate position data of the target is used to obtain the initial estimated position data through data analysis; The nonlinear observation model After linearization, the observation matrix is ​​obtained : ； Then the linearized position measurement model is: 。 3. The optimization method for high-precision missile target detection and positioning according to claim 2 is characterized in that: The method for obtaining accurate position data of a target by using a weighted least square method and a recursive algorithm comprises: The actual position measurement data of the N missile detection targets are used to obtain the optimal position estimation data of the targets through the weighted least square method, and the accurate position data of the targets are obtained through the recursive algorithm through the optimal position estimation data; Get the Missiles in The noise covariance matrix at time , the noise covariance matrix It is The matrix of the observation noise characteristics of the missile target detection sensor; the optimal position estimation data for: ； in, Represents the observation matrix of the N missiles and the noise covariance matrix The weighted sum of is used to obtain the inverse matrix of the cumulative weight matrix; Represents the actual position measurement data of the N missiles After weighted accumulation, the accumulated actual position measurement data is obtained.

4. The optimization method for high-precision missile target detection and positioning according to claim 3 is characterized in that: The method further comprises: Obtain the historical accurate position data and speed information of the target and build the target's motion model through data analysis; The optimal position estimation data and the motion model of the target are used to obtain accurate position data through a recursive algorithm.

5. The optimization method for high-precision missile target detection and positioning according to claim 1 is characterized in that: The method for the missile group to transmit information through a self-organizing network method and an anti-interference encrypted communication protocol includes: A communication network is constructed by a self-organizing network method, wherein each missile is used as a network node; when the monitored missile enters a predetermined mission area, the missile is automatically connected to another missile for communication; When the monitoring missile loses its communication function, other missiles will automatically bypass the network nodes of the missile and re-establish the communication network.

6. The optimization method for high-precision missile target detection and positioning according to claim 5 is characterized in that: The method further comprises: Acquire the precise position data of any two missiles in the missile group and obtain the distance between the missiles by a three-dimensional Euclidean distance calculation method, obtain the minimum communication range of the two missiles, and if the distance between the missiles is less than the minimum communication range, establish a communication link between the two missiles; Through undirected graph representing a communication network of said missile group, is the collection of all missiles in the missile group, is the set of communication links between missiles; if the monitored missile loses its communication function and is recorded as a failed missile, the network node of the failed missile is deleted in the undirected graph, the latest adjacency list between the missiles is updated, and the shortest communication path between each missile in the missile group and other missiles is recalculated, and the communication network is updated according to the latest adjacency list and the shortest communication path.

7. The optimization method for high-precision missile target detection and positioning according to claim 6 is characterized in that: The method further comprises: When the signal strength of the monitored communication link is lower than the preset signal strength threshold data, the communication link is disconnected; when the monitored communication link is disconnected, the missile group executes a bypass strategy and starts a communication link repair mechanism. The bypass strategy is that the remaining missiles reorganize the communication links and bypass the disconnected communication links.

8. The optimization method for high-precision missile target detection and positioning according to claim 7 is characterized in that: The method of the communication link repair mechanism includes: The communication link repair mechanism includes constructing a relay node to maintain information transmission strategy and a signal strength enhancement strategy; the constructing a relay node to maintain information transmission strategy is to use the network nodes of one or more missiles of the remaining missiles in the missile group as intermediate network nodes and calculate a new communication path; The signal strength enhancement strategy is to obtain a new signal strength by increasing the transmission power of the missile wireless communication module. If the new signal strength is greater than the preset signal strength threshold data, the communication link returns to normal.

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