Integrated Navigation Method and System for Surface Ship Formations Based on Distributed Networks

Abstract

This invention provides an integrated navigation method and system for surface warship formations based on a distributed network, comprising the following steps: Distributed network construction step: constructing a distributed network for the formation; Navigation system construction step: constructing an integrated navigation system for the formation based on the distributed network; Fusion step: fusing collaborative navigation data of the formation based on the integrated navigation system. This invention significantly improves the anti-interference and anti-damage capabilities of formation navigation. The application of this distributed network-based integrated navigation method for surface warship formations ensures the navigation capability of the entire formation even when the navigation of any single ship is normal.

Description

Technical Field

[0001] This invention relates to the technical field of positioning and navigation, specifically to an integrated navigation method and system for surface ship formations based on a distributed network. Background Technology

[0002] With the development of modern science and technology such as information technology, aerospace technology, and artificial intelligence, traditional platform-centric warfare is evolving towards networked and system-of-systems warfare. Major military powers worldwide, led by the United States, are strengthening the system-of-systems combat capabilities of their naval formations, striving to enhance the robustness and flexibility of these formations through the dynamic connection of operational nodes, fully releasing combat power and achieving a leapfrog improvement in combat effectiveness, based on existing combat resources. Future naval warfare will be system-of-systems operations at the formation level. In system-of-systems warfare, establishing reliable navigation benchmarks is the foundation for achieving key system-of-systems combat capabilities such as spatiotemporal unification, situational awareness integration, integrated command and control, and distributed fire strike / interception.

[0003] Chinese invention patent document CN112947447A discloses an autonomous navigation method for unmanned surface vessels based on a synchronous planning-control strategy. It belongs to the field of unmanned surface vessel control. Based on the idea of ​​synchronous planning-control, it uses an improved artificial potential field method based on grid map for obstacle avoidance path planning and a model predictive control method for tracking the reference trajectory. The two methods are executed alternately to achieve autonomous navigation control.

[0004] In view of the above-mentioned prior art, the inventors considered that in complex combat environments such as electromagnetic interference and equipment damage, a single navigation data source and navigation equipment are insufficient to guarantee the navigation needs of naval formations. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this invention is to provide an integrated navigation method and system for surface warship formations based on distributed networks.

[0006] An integrated navigation method for surface warship formations based on a distributed network, provided by the present invention, includes the following steps:

[0007] Distributed network construction steps: Build a queued distributed network;

[0008] Navigation system construction steps: Build an integrated formation navigation system based on a formation-distributed network;

[0009] Integration steps: Integrate formation collaborative navigation data based on the formation integrated navigation system.

[0010] Preferably, in the distributed network construction step, a surface warship formation distributed network {S} is constructed using ships as nodes. iEach node is interconnected and shares navigation information. Adjacent nodes conduct relative navigation measurements through shipborne radar or laser ranging equipment, forming a distributed cooperative navigation network.

[0011] Preferably, the distributed network construction step includes the following steps:

[0012] The steps for constructing a cooperative navigation network are as follows: When nodes perform relative navigation measurements through shipborne radar or laser ranging equipment, they have an adjacency relationship. Based on the adjacency matrix, a cooperative navigation network structure is constructed.

[0013] For a group {S1, S2, ..., S...} consisting of N nodes, N The cooperative navigation relationship between nodes at time t is represented by the adjacency matrix A(t):

[0014]

[0015] Among them, a ij (t) represents node S i To node S j The adjacency relationship is {i = 1, 2, ..., N}, {j = 1, 2, ..., N}; when i = j, a ij (t) = 0;

[0016] For surface warship formations, a can be calculated based on the effective distance measured by relative navigation from shipborne radar or laser ranging equipment. ij (t):

[0017]

[0018] Where, r ij (t) represents node S i To node S j distance; r i0 For node S j Shipborne radar or laser ranging equipment for node S i The effective distance for relative navigation measurements;

[0019] The steps for finding the shortest path are as follows: Based on the adjacency matrix A(t), the Floyd algorithm based on dynamic programming is used to find the shortest path; the shortest path distance matrix D(t) and the routing matrix P(t) contain the path information of the cooperative navigation network structure.

[0020]

[0021]

[0022] Where, d ij (t) represents the shortest path distance from node i to node j, p ij(t) represents the intermediate points traversed by the shortest path from node i to node j, {i = 1, 2, ..., N}, {j = 1, 2, ..., N}; when i = j, a ij (t) = 0;

[0023] D(t) is obtained by iterating with A(t) as the initialization matrix according to equation (5); P(t) is obtained by iterating with P0 as the initialization matrix according to equation (6), where P0 is shown in equation (7);

[0024] if d ij (t)>d ik (t)+d kj (t),thend ij (t)=d ik (t)+d kj (t) (5)

[0025] if d ij (t)>d ik (t)+d kj (t),thenp ij (t)=p ik (t) (6)

[0026]

[0027] Where i is the starting point; j is the ending point; k is the intermediate point; if means if; then means then.

[0028] Preferably, the navigation system construction steps include the following steps:

[0029] Raw navigation data acquisition steps: At the equipment level of the integrated navigation system of the formation, each node navigation device outputs raw navigation data, while the shipborne radar or laser ranging equipment performs auxiliary positioning measurements on adjacent nodes to obtain relative navigation data;

[0030] Steps for acquiring node-independent navigation data: At the system level of the integrated formation navigation system, each node navigation system uses a federated Kalman filter to filter and fuse the raw navigation data, and outputs node-independent navigation data.

[0031] Steps for acquiring node collaborative navigation data: At the system level of the formation integrated navigation system, dynamic baseline transmission is achieved through relative navigation data between nodes, and node collaborative navigation data is generated by dynamic baseline transformation based on the independent navigation data of each node.

[0032] Preferably, the fusion step includes the following steps:

[0033] Steps for establishing observation equations: Establish observation equations;

[0034] Fusion output steps: Based on the observation equation, the weighted least squares method is used to fuse the collaborative navigation data of multiple nodes and output the formation collaborative navigation data.

[0035] An integrated navigation system for surface warship formations based on a distributed network, according to the present invention, includes the following modules:

[0036] Distributed network building module: Builds arrayed distributed networks;

[0037] Navigation system construction module: Constructing an integrated formation navigation system based on a formation distributed network;

[0038] Fusion Module: Based on the formation integrated navigation system, it integrates formation collaborative navigation data.

[0039] Preferably, in the distributed network construction module, a surface warship formation distributed network {S} is constructed using warships as nodes. i Each node is interconnected and shares navigation information. Adjacent nodes conduct relative navigation measurements through shipborne radar or laser ranging equipment, forming a distributed cooperative navigation network.

[0040] Preferably, the distributed network construction module includes the following modules:

[0041] Cooperative navigation network construction module: When nodes perform relative navigation measurements through shipborne radar or laser ranging equipment, they have adjacency relationships. Based on the adjacency matrix, a cooperative navigation network structure is constructed.

[0042] For a group {S1, S2, ..., S...} consisting of N nodes, N The cooperative navigation relationship between nodes at time t is represented by the adjacency matrix A(t):

[0043]

[0044] Among them, a ij (t) represents node S i To node S j The adjacency relationship is {i = 1, 2, ..., N}, {j = 1, 2, ..., N}; when i = j, a ij (t) = 0;

[0045] For surface warship formations, a can be calculated based on the effective distance measured by relative navigation from shipborne radar or laser ranging equipment. ij (t):

[0046]

[0047] Where, r ij (t) represents node S i To node S jdistance; r i0 For node S j Shipborne radar or laser ranging equipment for node S i The effective distance for relative navigation measurements;

[0048] The shortest path solution module: Based on the adjacency matrix A(t), the Floyd algorithm based on dynamic programming is used to solve for the shortest path; the shortest path distance matrix D(t) and the routing matrix P(t) contain the path information of the cooperative navigation network structure;

[0049]

[0050]

[0051] Where, d ij (t) represents the shortest path distance from node i to node j, p ij (t) represents the intermediate points traversed by the shortest path from node i to node j, {i = 1, 2, ..., N}, {j = 1, 2, ..., N}; when i = j, a ij (t) = 0;

[0052] D(t) is obtained by iterating with A(t) as the initialization matrix according to equation (5); P(t) is obtained by iterating with P0 as the initialization matrix according to equation (6), where P0 is shown in equation (7);

[0053] if d ij (t)>d ik (t)+d kj (t),thend ij (t)=d ik (t)+d kj (t) (5)

[0054] if d ij (t)>d ik (t)+d kj (t),thenp ij (t)=p ik (t) (6)

[0055]

[0056] Where i is the starting point; j is the ending point; k is the intermediate point; if means if; then means then.

[0057] Preferably, the navigation system construction module includes the following modules:

[0058] Raw navigation data acquisition module: At the equipment level of the integrated navigation system of the formation, each node navigation device outputs raw navigation data, while shipborne radar or laser ranging equipment performs auxiliary positioning measurements on adjacent nodes to obtain relative navigation data;

[0059] Node-independent navigation data acquisition module: At the system level of the integrated formation navigation system, each node navigation system uses a federated Kalman filter to filter and fuse the raw navigation data, and outputs node-independent navigation data.

[0060] Node collaborative navigation data acquisition module: At the system level of the formation integrated navigation system, dynamic baseline transmission is achieved through relative navigation data between nodes, and node collaborative navigation data is generated by dynamic baseline transformation based on the independent navigation data of each node.

[0061] Preferably, the fusion module includes the following modules:

[0062] Observation Equation Establishment Module: Establishes observation equations;

[0063] Fusion output module: Based on the observation equation, the weighted least squares method is used to fuse the collaborative navigation data of multiple nodes and output the formation collaborative navigation data.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] 1. This invention significantly improves the anti-interference and anti-damage capabilities of formation navigation. The application of the integrated navigation method for surface ship formations based on distributed networks in this invention can ensure the navigation capability of the entire formation as long as the navigation of any single ship is normal.

[0066] 2. This invention effectively improves formation navigation accuracy. The integrated surface vessel formation navigation method based on a distributed network effectively improves formation navigation accuracy through multi-node navigation fusion.

[0067] 3. This invention optimizes navigation resource allocation. The integrated navigation method for surface ship formations based on distributed networks in this invention can support low-cost navigation resource allocation of "a single high-precision node + multiple low-precision nodes". Attached Figure Description

[0068] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0069] Figure 1 A schematic diagram of a distributed network for surface ships;

[0070] Figure 2 A schematic diagram of integrated navigation for surface ships;

[0071] Figure 3This is a schematic diagram of node collaborative navigation.

[0072] Figure 4 A schematic diagram of the typical composition and combat formation of an aircraft carrier battle group;

[0073] Figure 5 A diagram of a formation-based distributed cooperative navigation network (a = 10km, b = 35km);

[0074] Figure 6 A diagram of a formation-based distributed cooperative navigation network (a = 15km, b = 45km);

[0075] Figure 7 The diagram shows the movement trajectory of the formation (double column → single line).

[0076] Figure 8 The diagram shows the formation movement trajectory (diamond formation → circular formation);

[0077] Figure 9 A diagram showing the distribution of formation navigation errors (double column → single line).

[0078] Figure 10 This is a diagram showing the distribution of formation navigation errors (diamond formation → circular formation). Detailed Implementation

[0079] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0080] This invention discloses an integrated navigation method for surface warship formations based on distributed networks, such as... Figure 1 and Figure 2 As shown, Figure 1 For a distributed network of surface warship formations, Figure 2 For an integrated navigation system for surface warship formations, the integrated navigation method for surface warship formations based on distributed networks includes the following steps:

[0081] Distributed network construction steps (Step 1): Construct a formation distributed network. Using ships as nodes, construct a surface ship formation distributed network {S1, S2, ..., S...}. N Each node is interconnected and shares navigation information. Adjacent nodes conduct relative navigation measurements through shipborne radar or laser ranging equipment, forming a distributed cooperative navigation network.

[0082] Specifically, this involves constructing a distributed network for surface ships, which means: ignoring ship identities, and using ships as general nodes to construct a distributed network {S1, S2, ..., S} for the surface ship formation. N},like Figure 1 As shown, each node is interconnected and shares navigation information. Adjacent nodes conduct relative navigation measurements through shipborne radar or laser ranging equipment, forming a distributed cooperative navigation network.

[0083] The steps involved in building a distributed network include the following:

[0084] Cooperative navigation network construction steps (Step 1.1): When nodes perform relative navigation measurements through shipborne radar or laser ranging equipment, they have adjacency relationships. Based on the adjacency matrix, the cooperative navigation network structure is constructed. That is, based on the adjacency matrix (when nodes can perform relative navigation measurements through shipborne radar or laser ranging equipment, they have adjacency relationships), the cooperative navigation network structure is constructed.

[0085] For a group {S1, S2, ..., S...} consisting of N nodes, N The cooperative navigation relationship between nodes at time t is represented by the adjacency matrix A(t).

[0086]

[0087] Among them, a ij (t) represents node S i To node S j The adjacency relationship is given by {i = 1, 2, ..., N}, {j = 1, 2, ..., N}. When i = j, a ij (t) = 0.

[0088] For surface warship formations, a can be calculated based on the effective distance measured by relative navigation from shipborne radar or laser ranging equipment. ij (t):

[0089]

[0090] Where, r ij (t) represents node S i To node S j distance; r i0 For node S j Shipborne radar or laser ranging equipment for node S i The effective distance for relative navigation measurements.

[0091] Shortest path solution steps (step 1.2): Solve for the shortest path. Based on the adjacency matrix A(t), the Floyd algorithm based on dynamic programming is used to solve for the shortest path. The shortest path distance matrix D(t) and the routing matrix P(t) contain all the path information of the cooperative navigation network structure, as shown in equations (3) and (4).

[0092]

[0093]

[0094] Where, d ij (t) represents the shortest path distance from node i to node j, p ij (t) represents the intermediate points traversed by the shortest path from node i to node j, where {i = 1, 2, ..., N} and {j = 1, 2, ..., N}. When i = j, a ij (t) = 0.

[0095] D(t) is obtained by iterating with A(t) as the initialization matrix according to equation (5). P(t) is obtained by iterating with P0 as the initialization matrix according to equation (6), where P0 is shown in equation (7).

[0096] if d ij (t)>d ik (t)+d kj (t),thend ij (t)=d ik (t)+d kj (t) (5)

[0097] if d ij (t)>d ik (t)+d kj (t),thenp ij (t)=p ik (t) (6)

[0098]

[0099] Where i is the starting point; j is the ending point; k is the intermediate point; if means if; then means then.

[0100] Navigation System Construction Steps (Step 2): Constructing an Integrated Navigation System for the Formation. The integrated navigation system for the formation is constructed based on a distributed network. Specifically, the integrated navigation system design for the surface warship formation adopts a distributed network divided into three layers: device level, system level, and architecture level. Nodes can dynamically join or leave, as shown in the structure below. Figure 2 As shown.

[0101] The steps involved in building a navigation system are as follows:

[0102] Raw navigation data acquisition steps (step 2.1): At the equipment level of the integrated navigation system of the formation, each node navigation device outputs raw navigation data, while the shipborne radar or laser ranging equipment performs auxiliary positioning measurements on adjacent nodes to obtain relative navigation data.

[0103] Specifically, at the equipment level, each node's GNSS / INS navigation equipment outputs raw navigation data, while shipborne radar or laser ranging equipment performs auxiliary positioning measurements on adjacent nodes to obtain relative navigation data. GNSS stands for Global Navigation Satellite System; INS stands for Inertial Navigation System.

[0104] The relative navigation data obtained includes the following: Let S i It is S j The adjacent nodes satisfy the condition that element a in the adjacency matrix A(t) is a ij (t)≠∞. Node S i Positioning is assisted by radar or laser ranging equipment, and S is measured. i →S j Relative navigation data r ij (t) and v(t) ij Among them, r ij v(t) is the relative position vector. ij This is a relative velocity vector. → indicates "to" or "to".

[0105] Step 2.2: At the system level of the formation integrated navigation system, each node navigation system uses a federated Kalman filter to filter and fuse the original navigation data, and outputs node-independent navigation data.

[0106] Specifically, at the system level, each node's navigation system uses a federated Kalman filter to filter and fuse the original navigation data, outputting node-independent navigation data.

[0107] The relative navigation data is filtered and denoised to generate a dynamic baseline, including the following:

[0108] At time t, let the observation Z(t) = [r ij (t) v(t) ij ] T T represents transpose. Take the state variable. State equations and observation equations are established under the assumption of local uniform linear motion. The state variables are represented by the symbol "-" to distinguish them from the observation variables; this is a common representation method used in Kalman filtering.

[0109] X(t+1)=F(t+1)X(t) (8)

[0110] Z(t+1)=X(t+1)+υ(t+1) (9)

[0111] in,

[0112]

[0113] In the formula: F(t+1) is the state transition matrix; υ(t+1) is the observation noise; Δt=1 / f, f is the data rate.

[0114] Based on the state equation and the observation equation, the Kalman filter equation is obtained as follows:

[0115] State prediction equation: X(t+1|t)=F(t+1)X(t|t) (11)

[0116] In the formula: X(t|t) is the optimal estimate at time t; X(t+1|t) is the state prediction at time t+1.

[0117] Covariance prediction equation: P(t+1|t)=F(t+1)P(t|t)F(t+1) T +Q(t) (12)

[0118] In the formula: Q(t) is the process excitation noise covariance matrix at time t; P(t|t) is the covariance matrix at time t; P(t+1|t) is the covariance prediction matrix at time t+1.

[0119] Gain equation: K(t+1)=P(t+1|t) / (P(t+1|t)+R(t)) (13)

[0120] In the formula: R(t) is the observation noise covariance matrix at time t; K(t+1) is the gain matrix at time t+1.

[0121] State update equation: X(t+1|t+1)=X(t+1|t)+K(t+1)(Z(t+1)-X(t+1|t))(14)

[0122] In the formula: Z(t+1) is the observation at time t+1; X(t+1|t+1) = is the optimal estimate at time t+1.

[0123] Covariance update equation: P(t+1|t+1)=(IK(t+1))P(t+1|t) (15)

[0124] In the formula: P(t+1|t+1) is the covariance matrix at time t+1.

[0125] Equations (11) to (15) are the state prediction equation, covariance prediction equation, gain equation, state update equation, and covariance update equation, respectively. Based on equations (11) to (15), the optimal estimate of the state variable X(t+1|t+1) (dynamic baseline) can be obtained when the observed quantity Z(t+1) is known, thus achieving filtering and noise reduction. ~ indicates to or to.

[0126] Step 2.3: At the system level of the formation integrated navigation system, dynamic baseline transmission is achieved through relative navigation data between nodes, and node collaborative navigation data is generated by dynamic baseline transformation based on the independent navigation data of each node.

[0127] Specifically, at the system level, dynamic baseline transfer is achieved through relative navigation data between nodes, and node collaborative navigation data is generated by dynamic baseline transformation based on the independent navigation data of each node.

[0128] To achieve dynamic baseline transfer and generate node-based collaborative navigation data, the following is included:

[0129] Suppose that, based on the shortest path distance matrix D(t) and the routing matrix P(t), the shortest path between node Si and node Sj is Si→Sk→Sj. If the independent navigation data of node Sj and the dynamic baseline from node Si to node Sj are known, then... Figure 3 Dynamic baseline transformation is performed to generate node-based collaborative navigation data. Let be the relative position vector from node Si to node Sj; Let r be the relative position vector from node Sk to node Sj; Oj (t) represents the independent navigation and positioning vector of node Sj; r Oi←j (t) is the cooperative navigation positioning vector of node Si with reference to node Sj.

[0130] According to geometric relations, r Oi←j (t) satisfies

[0131]

[0132] Fusion Step (Step 3): Fusion of formation collaborative navigation data based on the formation integrated navigation system. The formation collaborative navigation data is fused and output as collaborative navigation data.

[0133] The fusion process includes the following steps:

[0134] Steps for establishing the observation equation (Step 3.1): Establish the observation equation.

[0135] Assume that node Si has a baseline transfer relationship with m nodes at time t, meaning that node Si can obtain node cooperative navigation data from m nodes through baseline transformation. The observation equations are established as follows:

[0136]

[0137] In the formula: r Oi (t) T This is the independent navigation and positioning vector for node Si. and The node cooperative navigation positioning vector generated by node Si with reference to other nodes; υ(t) is the formation cooperative navigation positioning vector of node Si; H is an all-one vector; υ(t) is noise.

[0138] Fusion output step (step 3.2): Based on the observation equation, the weighted least squares method is used to fuse the collaborative navigation data of multiple nodes and output the formation collaborative navigation data.

[0139] Weighted least squares method is used to fuse data from multiple nodes to output formation collaborative navigation data.

[0140] remember Solve using the recursive weighted least squares method as follows

[0141]

[0142] In the formula: W(t) is the weight matrix.

[0143] From equation (18), it can be seen that the formation cooperative navigation positioning vector of node Si is... It integrates independent navigation data from this node and collaborative navigation data from all nodes. Based on Markov estimation, the weight matrix is ​​constructed as follows:

[0144] W(t)=(R1+R2) -1 (1)

[0145] In the formula: R1 is the cooperative navigation baseline transmission error covariance matrix, representing the error generated by the cooperative node navigation data in baseline transmission; R2 is the node-independent navigation error covariance matrix, representing the error of the local node S i and collaborative nodes GNSS / INS navigation output error.

[0146] Baseline transfer error is related to the transfer path distance and the relative measurement accuracy of radar / laser-assisted positioning. R1 is constructed as a diagonal matrix as follows:

[0147] R1=diag([0 (τ i D(i,j1)) 2 …(τ i D(i,j m )) 2 ] T (20)

[0148] In the formula: τ i For relative navigation ranging accuracy coefficients; D(i,j1), ..., D(i,j2) m ) is the node S i To the collaborative node Shortest path distance. diag represents a diagonal matrix.

[0149] The node-independent navigation error covariance matrix R2 can be expressed as:

[0150]

[0151] In the formula: σ(S) i ) represents the current node S i GNSS / INS navigation output accuracy; Represents a collaborative node GNSS / INS navigation output accuracy.

[0152] Equations (18) to (21) can be used to generate formation collaborative navigation data based on the independent navigation data of this node and the collaborative navigation data of each collaborative node, thereby realizing the fusion of surface ship formation navigation data based on distributed network.

[0153] The numerical simulation verification process of the integrated navigation method for surface ship formations based on distributed networks is as follows:

[0154] 1. Building a distributed collaborative network:

[0155] Considering the influence of three formation parameters—the distance between inner and outer ships, the forward distance of forward-departing ships, and the relative effective navigation distance—the formation parameters are shown in Table 1.

[0156] Table 1 Formation Parameters of Surface Ship Formations

[0157]

[0158]

[0159] Using the above-mentioned formation cooperative navigation network construction algorithm, in order to Figure 4 Taking formation and table parameters as an example, how to construct a distributed cooperative navigation network? Figure 5 , Figure 6 As shown. When the distance between ships is greater than the relative navigation effective distance, adjacency cannot be established, resulting in isolated nodes. Figure 6 The outer ships in part a) or the resulting fragmentation of the overall network structure. Figure 5 (The forward ships in Part a) Figure 5 Part a and Figure 6Part a is a local cooperative navigation network due to the presence of isolated nodes and network structure segmentation. Isolated nodes cannot obtain cooperative navigation data from other nodes, while cooperative navigation can occur within the segmented network but cannot obtain cooperative navigation data from other segmented networks. Figure 5 Part B of the middle section Figure 5 Part C Figure 6 Part b and Figure 6 Part C is a global collaborative navigation network, where independent navigation data from any node can be transmitted to all network nodes to provide collaborative navigation support, exhibiting the decentralized characteristics of a distributed network.

[0160] Comparative analysis shows that the tighter the formation, the greater the relative effective navigation distance, the more adjacency relationships a single ship can establish, and the more robust the distributed cooperative navigation network structure.

[0161] 2. Verify the effectiveness of the anti-interference algorithm of the formation cooperative navigation data fusion algorithm based on distributed network.

[0162] A surface warship formation consists of four ships equipped with radar, laser ranging equipment, and GNSS / INS integrated navigation equipment, possessing network communication capabilities and forming a distributed cooperative navigation network. Assuming a certain interference environment, the navigation capabilities of each ship are as shown in Table 2.

[0163] Table 2 Navigation Capabilities of Surface Ship Formations

[0164]

[0165] Navigation simulations were conducted using both node-independent navigation and formation cooperative navigation in two formation transformation scenarios: double column → single line and diamond → circular formation. The formation trajectories are as follows: Figure 7 , Figure 8 As shown. When the GNSS / INS equipment is subjected to strong interference or malfunction, resulting in the inability to effectively output navigation data, the independent navigation of the S2 local node is interrupted. Figure 7 Part a of the middle Figure 8 In part a), navigation and positioning are not possible. However, if swarm-based distributed cooperative navigation is used, after an independent node navigation interruption, S2 can acquire the cooperative navigation data from neighboring nodes S1 and S3 and fuse them to generate swarm-based cooperative navigation data, thus restoring normal navigation and positioning functionality. Furthermore, compared to independent node navigation, the motion trajectory using swarm-based cooperative navigation is smoother, indicating that through the fusion of multi-node, multi-source data, swarm-based cooperative navigation data achieves higher accuracy.

[0166] Navigation and positioning error distribution as follows Figure 9 , Figure 10As shown in Table 3, the error statistics parameters are as follows. From the dispersion of the error distribution and the error statistics parameters, it can be seen that the accuracy of the formation cooperative navigation of each node is higher than that of the node's independent navigation. The highest accuracy of formation cooperative navigation (28.6m) is better than the highest accuracy of the node's independent navigation (40m), indicating the effectiveness of formation cooperative navigation in improving accuracy through multi-node, multi-source data fusion. Among them, the navigation accuracy improvement of S2 and S4 under formation cooperative navigation is particularly significant, increasing from 150m and 100m to 29.0m–41.1m respectively, approaching or even exceeding the highest node independent navigation accuracy of 40m. This phenomenon reflects the decentralized nature of the distributed network; low-precision nodes in the network achieve accuracy support by acquiring cooperative navigation data from high-precision nodes. That is, only one or a few high-precision nodes are needed in the network to achieve high-precision navigation for all nodes, effectively reducing costs.

[0167] Table 3. Statistics on the accuracy of coordinated navigation in formations.

[0168]

[0169] In summary, numerical simulation results demonstrate that the integrated navigation data fusion algorithm for formation navigation can effectively construct a distributed cooperative navigation network based on formation parameters and achieve formation cooperative navigation through multi-node, multi-source navigation data fusion. Compared to independent node navigation, formation cooperative navigation, based on a distributed network, systematically integrates the navigation resources of each node, ensuring full formation navigation capability even when any node within the network is functioning normally independently, significantly improving the anti-interference capability of formation navigation. Simultaneously, the collaborative fusion of multi-node, multi-source data enables high-precision navigation resource support, effectively improving formation navigation accuracy and providing a low-cost navigation resource configuration scheme of "a single high-precision node + multiple low-precision nodes."

[0170] Therefore, it is necessary to conduct research on navigation data fusion methods for formation-based system warfare, and propose an integrated navigation method for surface ship formations based on distributed networks. This method can guarantee the navigation capability of the entire formation when the navigation of any ship is normal, and significantly improve the formation's anti-interference and anti-damage capabilities. At the same time, it can effectively improve the formation's navigation accuracy through multi-node navigation fusion, and can support low-cost navigation resource configuration of "a single high-precision node + multiple low-precision nodes".

[0171] This invention also discloses an integrated navigation system for surface warship formations based on a distributed network, such as... Figure 1 and Figure 2 As shown, it includes the following modules:

[0172] Distributed Network Construction Module: Constructs a distributed network for a surface warship formation. It uses ships as nodes to build a distributed network for a surface warship formation {S}. iEach node is interconnected and shares navigation information. Adjacent nodes conduct relative navigation measurements through shipborne radar or laser ranging equipment, forming a distributed cooperative navigation network.

[0173] The distributed network building module includes the following modules:

[0174] Cooperative navigation network construction module: When nodes perform relative navigation measurements through shipborne radar or laser ranging equipment, they have adjacency relationships. Based on the adjacency matrix, a cooperative navigation network structure is constructed.

[0175] For a group {S1, S2, ..., S...} consisting of N nodes, N The cooperative navigation relationship between nodes at time t is represented by the adjacency matrix A(t).

[0176]

[0177] Among them, a ij (t) represents node S i To node S j The adjacency relationship is given by {i = 1, 2, ..., N}, {j = 1, 2, ..., N}. When i = j, a ij (t) = 0.

[0178] For surface warship formations, a can be calculated based on the effective distance measured by relative navigation from shipborne radar or laser ranging equipment. ij (t):

[0179]

[0180] Where, r ij (t) represents node S i To node S j distance; r i0 For node S j Shipborne radar or laser ranging equipment for node S i The effective distance for relative navigation measurements;

[0181] The shortest path solution module: Based on the adjacency matrix A(t), the Floyd algorithm, based on dynamic programming, is used to find the shortest path. The shortest path distance matrix D(t) and the routing matrix P(t) contain all the path information of the cooperative navigation network structure.

[0182]

[0183]

[0184] Where, d ij (t) represents the shortest path distance from node i to node j, p ij(t) represents the intermediate points traversed by the shortest path from node i to node j, where {i = 1, 2, ..., N} and {j = 1, 2, ..., N}. When i = j, a ij (t) = 0.

[0185] D(t) is obtained by iterating with A(t) as the initialization matrix according to equation (5). P(t) is obtained by iterating with P0 as the initialization matrix according to equation (6), where P0 is shown in equation (7).

[0186] if d ij (t)>d ik (t)+d kj (t),thend ij (t)=d ik (t)+d kj (t) (5)

[0187] if d ij (t)>d ik (t)+d kj (t),thenp ij (t)=p ik (t) (6)

[0188]

[0189] Where i is the starting point; j is the ending point; k is the intermediate point; if means if; then means then.

[0190] Navigation system construction module: Construct an integrated navigation system based on a distributed formation network.

[0191] The navigation system construction module includes the following modules:

[0192] Raw navigation data acquisition module: At the equipment level of the integrated navigation system of the formation, each node navigation device outputs raw navigation data, while shipborne radar or laser ranging equipment performs auxiliary positioning measurements on adjacent nodes to obtain relative navigation data.

[0193] Node-independent navigation data acquisition module: At the system level of the integrated formation navigation system, each node navigation system uses a federated Kalman filter to filter and fuse the raw navigation data, and outputs node-independent navigation data.

[0194] Node collaborative navigation data acquisition module: At the system level of the formation integrated navigation system, dynamic baseline transmission is achieved through relative navigation data between nodes, and node collaborative navigation data is generated by dynamic baseline transformation based on the independent navigation data of each node.

[0195] Fusion Module: Based on the formation integrated navigation system, it integrates formation collaborative navigation data.

[0196] The fusion module includes the following modules:

[0197] Observation Equation Establishment Module: Establishes observation equations.

[0198] Fusion output module: Based on the observation equation, the weighted least squares method is used to fuse the collaborative navigation data of multiple nodes and output the formation collaborative navigation data.

[0199] This invention aims to enhance the robustness and flexibility of formation navigation in complex environments. It discloses an integrated navigation method and system for surface warship formations based on a distributed network. The integrated formation navigation system is divided into a device layer, a system layer, and an architecture layer. The device layer outputs raw navigation data, the system layer outputs independent navigation data from GNSS / INS nodes, and the architecture layer fuses and generates coordinated formation navigation data. To achieve coordinated formation navigation data fusion, a distributed coordinated formation navigation network is constructed using the Floyd algorithm. Based on the independent node navigation data, node coordinated navigation data is generated through dynamic baseline transmission. Subsequently, weighted least squares is used to fuse multiple node coordinated navigation data to output the overall coordinated formation navigation data. This method can guarantee the navigation capability of the entire formation under normal navigation conditions for any single ship, significantly improving the formation navigation's anti-interference and anti-damage capabilities. Simultaneously, multi-node navigation fusion effectively improves formation navigation accuracy and supports low-cost navigation resource configuration of "a single high-precision node + multiple low-precision nodes."

[0200] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0201] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. An integrated navigation method for surface warship formations based on distributed networks, characterized in that, Includes the following steps: Distributed network construction steps: Build a queued distributed network; Navigation system construction steps: Build an integrated formation navigation system based on a formation-distributed network; Fusion steps: Fusion of formation collaborative navigation data based on the formation integrated navigation system; The distributed network construction steps include the following steps: The steps for constructing a cooperative navigation network are as follows: When nodes perform relative navigation measurements through shipborne radar or laser ranging equipment, they have an adjacency relationship. Based on the adjacency matrix, a cooperative navigation network structure is constructed. For a group {S1, S2, ..., S...} consisting of N nodes, N The cooperative navigation relationship between nodes at time t is represented by the adjacency matrix A(t): Among them, a ij (t) represents node S i To node S j The adjacency relationship is {i = 1, 2, ..., N}, {j = 1, 2, ..., N}; when i = j, a ij (t) = 0; For surface warship formations, a is calculated based on the effective distance measured by relative navigation from shipborne radar or laser ranging equipment. ij (t): Where, r ij (t) represents node S i To node S j distance; r i0 For node S j Shipborne radar or laser ranging equipment for node S i The effective distance for relative navigation measurements; The steps for finding the shortest path are as follows: Based on the adjacency matrix A(t), the Floyd algorithm based on dynamic programming is used to find the shortest path; the shortest path distance matrix D(t) and the routing matrix P(t) contain the path information of the cooperative navigation network structure. Where, d ij (t) represents the shortest path distance from node i to node j, p ij (t) represents the intermediate points traversed by the shortest path from node i to node j, {i = 1, 2, ..., N}, {j = 1, 2, ..., N}; when i = j, a ij (t) = 0; D(t) is obtained by iterating with A(t) as the initialization matrix according to equation (5); P(t) is obtained by iterating with P0 as the initialization matrix according to equation (6), where P0 is shown in equation (7); if d ij (t)>d ik (t)+d kj (t), thend ij (t)=d ik (t)+d kj (t) (5) if d ij (t)>d ik (t)+d kj (t), thenp ij (t)=p ik (t) (6) Where i is the starting point; j is the ending point; k is the intermediate point; if means "if"; then means "then"; The navigation system construction steps include the following steps: Raw navigation data acquisition steps: At the equipment level of the integrated navigation system of the formation, each node navigation device outputs raw navigation data, while the shipborne radar or laser ranging equipment performs auxiliary positioning measurements on adjacent nodes to obtain relative navigation data; Steps for acquiring node-independent navigation data: At the system level of the integrated formation navigation system, each node navigation system uses a federated Kalman filter to filter and fuse the raw navigation data, and outputs node-independent navigation data. Steps for acquiring node collaborative navigation data: At the system level of the formation integrated navigation system, dynamic baseline transmission is achieved through relative navigation data between nodes, and node collaborative navigation data is generated by dynamic baseline transformation based on the independent navigation data of each node.

2. The integrated navigation method for surface warship formations based on distributed networks according to claim 1, characterized in that, In the distributed network construction step, a distributed network {S} for the surface warship formation is constructed using ships as nodes. i Each node is interconnected and shares navigation information. Adjacent nodes conduct relative navigation measurements through shipborne radar or laser ranging equipment, forming a distributed cooperative navigation network.

3. The integrated navigation method and system for surface warship formations based on distributed networks according to claim 1, characterized in that, The fusion step includes the following steps: Steps for establishing observation equations: Establish observation equations; Fusion output steps: Based on the observation equation, the weighted least squares method is used to fuse the collaborative navigation data of multiple nodes and output the formation collaborative navigation data.

4. An integrated navigation system for surface warship formations based on a distributed network, characterized in that, Includes the following modules: Distributed network building module: Builds arrayed distributed networks; Navigation system construction module: Constructing an integrated formation navigation system based on a formation distributed network; Fusion module: Based on the formation integrated navigation system, it fuses formation collaborative navigation data; The distributed network construction module includes the following modules: Cooperative navigation network construction module: When nodes perform relative navigation measurements through shipborne radar or laser ranging equipment, they have adjacency relationships. Based on the adjacency matrix, a cooperative navigation network structure is constructed. For a group {S1, S2, ..., S} consisting of N nodes, N The cooperative navigation relationship between nodes at time t is represented by the adjacency matrix A(t): Among them, a ij (t) represents node S i To node S j The adjacency relationship is {i = 1, 2, ..., N}, {j = 1, 2, ..., N}; when i = j, a ij (t) = 0; For surface warship formations, a can be calculated based on the effective distance measured by relative navigation from shipborne radar or laser ranging equipment. ij (t): Where, r ij (t) represents node S i To node S j distance; r i0 For node S j Shipborne radar or laser ranging equipment for node S i The effective distance for relative navigation measurements; The shortest path solution module: Based on the adjacency matrix A(t), the Floyd algorithm based on dynamic programming is used to solve for the shortest path; the shortest path distance matrix D(t) and the routing matrix P(t) contain the path information of the cooperative navigation network structure; Where, d ij (t) represents the shortest path distance from node i to node j, p ij (t) represents the intermediate points traversed by the shortest path from node i to node j, {i = 1, 2, ..., N}, {j = 1, 2, ..., N}; when i = j, a ij (t) = 0; D(t) is obtained by iterating with A(t) as the initialization matrix according to equation (5); P(t) is obtained by iterating with P0 as the initialization matrix according to equation (6), where P0 is shown in equation (7); if d ij (t)>d ik (t)+d kj (t), thend ij (t)=d ik (t)+d kj (t) (5) if d ij (t)>d ik (t)+d kj (t), thenp ij (t)=p ik (t) (6) Where i is the starting point; j is the ending point; k is the intermediate point; if means "if"; then means "then"; The navigation system construction module includes the following modules: Raw navigation data acquisition module: At the equipment level of the integrated navigation system of the formation, each node navigation device outputs raw navigation data, while shipborne radar or laser ranging equipment performs auxiliary positioning measurements on adjacent nodes to obtain relative navigation data; Node-independent navigation data acquisition module: At the system level of the integrated formation navigation system, each node navigation system uses a federated Kalman filter to filter and fuse the raw navigation data, and outputs node-independent navigation data. Node collaborative navigation data acquisition module: At the system level of the formation integrated navigation system, dynamic baseline transmission is achieved through relative navigation data between nodes, and node collaborative navigation data is generated by dynamic baseline transformation based on the independent navigation data of each node.

5. The integrated navigation system for surface warship formations based on a distributed network according to claim 4, characterized in that, In the distributed network construction module, a distributed network {S} for surface warship formations is constructed using ships as nodes. i Each node is interconnected and shares navigation information. Adjacent nodes conduct relative navigation measurements through shipborne radar or laser ranging equipment, forming a distributed cooperative navigation network.

6. The integrated navigation system and system for surface warship formations based on a distributed network according to claim 5, characterized in that, The fusion module includes the following modules: Observation Equation Establishment Module: Establishes observation equations; Fusion output module: Based on the observation equation, the weighted least squares method is used to fuse the collaborative navigation data of multiple nodes and output the formation collaborative navigation data.

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