Cooperative reconnaissance task allocation method and device based on consistent auction

Abstract

The invention discloses a cooperative reconnaissance task allocation method and device based on consistent auction, and the method comprises the steps: receiving a task information table, starting consistent auction processing, generating an auction information table and a bid-winning information table through a task auction stage by each node, and calculating a task benefit with a positioning error reciprocal as an index; in the consistent negotiation stage, the information table is interactively updated, the latest auction item and the maximum benefit bid winning result are reserved, when the auction information and the bid winning information are not changed continuously for multiple rounds or within the preset time, the bid winning node combination is determined to execute the task, and through distributed negotiation and dynamic benefit optimization, the radiation source positioning precision is improved, the communication overhead is reduced, and the efficiency is improved. The method is suitable for a multi-node cooperative reconnaissance scene in a complex environment, and a node combination with the optimal task benefit is dynamically optimized through a multi-round auction and negotiation mechanism in which multiple nodes participate equally, so that the task allocation problem in a centerless scene is solved.

Description

Technical Field

[0001] The present application relates to the technical field of collaborative reconnaissance task allocation, and in particular to a method and device for collaborative reconnaissance task allocation based on consistency auction. Background Art

[0002] In the field of collaborative reconnaissance task allocation, existing technologies are primarily categorized into centralized and decentralized approaches. However, both methods suffer from technical limitations and struggle to adapt to the complex and ever-changing demands of collaborative tasks. Centralized collaborative reconnaissance task allocation utilizes a centralized management architecture, where a management center globally coordinates the status information of all reconnaissance nodes and generates an optimal allocation plan based on task requirements. While this approach offers the advantages of high global optimization efficiency and strong resource synergy, it also suffers from significant drawbacks: First, the communication architecture is fragile. High-frequency state synchronization between the management center and nodes is required, which can easily lead to communication congestion when the number of nodes surges, and a failure of the management center can lead to system failure. Second, scalability is limited. Dynamic node entry and exit require the reconstruction of global information, making real-time performance difficult to guarantee.

[0003] In decentralized task allocation methods, each node, acting as an autonomous agent, implements task allocation through distributed negotiation, resulting in high system robustness and fault tolerance. However, existing decentralized methods are only applicable to situations where a single node independently completes a task or multiple nodes collaborate sequentially to complete a task, and the task value is known. For complex scenarios requiring synchronous multi-node collaboration and where the task value / benefit is dynamically unknown, existing technologies lack effective mechanisms for real-time collaborative decision-making between nodes. Specifically, they lack the ability to dynamically evaluate the nonlinear task benefits generated by multi-node collaboration, and they lack distributed optimization algorithms under collaborative constraints, making it difficult for task allocation schemes to meet spatiotemporal synchronization requirements.

[0004] Therefore, there is an urgent need for a new collaborative task allocation method that can realize real-time synchronous collaboration of multiple nodes under a decentralized architecture, while solving the problems of dynamic task value evaluation and distributed optimization decision-making, so as to meet the robustness and adaptability requirements of collaborative reconnaissance tasks in highly confrontational environments. Summary of the Invention

[0005] The purpose of this application is to overcome the existing technical defects and provide a collaborative reconnaissance task allocation method and device based on consistency bidding. Through a multi-round bidding and negotiation mechanism with equal participation of multiple nodes, the node combination with the best task efficiency is dynamically selected to solve the task allocation problem in a decentralized scenario.

[0006] The purpose of this application is achieved through the following technical solutions:

[0007] In a first aspect, the present application proposes a method for allocating collaborative reconnaissance tasks based on consistency bidding, which is applied to m distributed reconnaissance nodes and includes:

[0008] Receive and store a task information table, wherein the task information table includes a task ID, target characteristic parameters, target estimated position, task type, and task period;

[0009] Conduct multiple rounds of consistent bidding based on the task information table, generating a bidding information table and a winning bid information table during the task bidding phase. The consistent bidding process includes node resource matching analysis, dynamic calculation of task benefits, and a distributed negotiation mechanism.

[0010] During the consensus negotiation phase, nodes exchange bidding information tables and winning bid information tables, update and merge information to reach a consensus;

[0011] The termination condition is that the information table remains unchanged for multiple consecutive rounds or within a preset time, and the winning combination is determined to perform the task. The winning combination is the reconnaissance node combination composed of n nodes with the largest calculated task benefit, and the task benefit is the inverse of the radiation source positioning error.

[0012] In a possible implementation, when the target estimated position in the task information table is the coordinates of the vertices of a polygonal area, the target position coordinate point estimate is calculated: in are vertex coordinates, and b is the number of vertices in the polygonal area.

[0013] In one possible implementation, the auction information table includes task ID, node ID, node location, angle measurement error, site error, and auction time, and is managed in groups by task ID; during the auction phase, the node adds its own information to the auction information table and broadcasts updates.

[0014] In a possible implementation, the task auction stage includes:

[0015] The node determines whether to participate in the auction by judging idle resources and analyzing task compatibility;

[0016] The node is dynamically combined with other nodes in the auction information table to calculate the task benefits of all n-node combinations;

[0017] If the current maximum task benefit is higher than the historical value, update the bid winning information table and record the bid winning time;

[0018] Only the changes in the auction information table and the winning bid information table will be broadcast.

[0019] In a possible implementation, when calculating task benefits, the node is only combined with the nodes in the newly added or modified auction information table for calculation.

[0020] In one possible implementation, the consensus negotiation phase includes:

[0021] After receiving the auction information table, the node merges it by task ID and node ID, retaining the latest auction time entry;

[0022] After receiving the winning bid information table, keep the largest task benefit entry by task ID. If the benefits are the same, keep the earliest winning bid time.

[0023] In a possible implementation, the task package records multiple task IDs that have won bids for the node, and the number of task IDs does not exceed the maximum number of tasks that can be executed by the node.

[0024] In a second aspect, the present application proposes a collaborative reconnaissance task allocation device for implementing any of the methods described in the first aspect, comprising:

[0025] Task information storage module, used to manage task information table and task priority;

[0026] The bidding processing module is used to generate the bidding information table, calculate the task benefits and update the winning bid information table;

[0027] Communication module, used to broadcast the changed bidding information table and winning bid information table;

[0028] The negotiation decision module is used to merge external information tables and determine the auction termination conditions.

[0029] The above-mentioned main scheme of this application and its further options can be freely combined to form multiple schemes, all of which are schemes that can be adopted and protected by this application; and in this application, (non-conflicting options) can also be freely combined with each other and with other options. After understanding the scheme of this application, those skilled in the art will understand that there are many combinations based on existing technology and common knowledge, all of which are technical solutions to be protected by this application, and they are not exhaustive here.

[0030] The present application discloses a collaborative reconnaissance task allocation method and device based on consistency bidding, which receives a task information table and starts consistency bidding processing. Each node generates an auction information table and a winning information table through the task auction stage, and calculates the task benefit with the inverse of the positioning error as an indicator; in the consistent negotiation stage, the information table is interactively updated to retain the latest auction items and the maximum benefit winning result. When the auction information and the winning information do not change for multiple rounds or within a preset time, the winning node combination is determined to perform the task. Through distributed negotiation and dynamic benefit optimization, the radiation source positioning accuracy is improved and the communication overhead is reduced. The method is suitable for multi-node collaborative reconnaissance scenarios in complex environments. Through a multi-round auction and negotiation mechanism with equal participation of multiple nodes, the node combination with the best task benefit is dynamically selected to solve the task allocation problem in a decentralized scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 A flow chart of a method for allocating collaborative reconnaissance tasks based on consistency bidding proposed in an embodiment of the present application is shown.

[0033] Figure 2 A schematic diagram of a scenario in which a distributed reconnaissance node conducts reconnaissance, direction finding, and cross-positioning of a radiation source target is shown in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The following describes the embodiments of the present application through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0035] Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of this application.

[0036] In decentralized task allocation methods, each node is an equal, autonomous intelligent agent, participating in task bidding based on its own capabilities and status, resulting in strong robustness. Current decentralized task allocation methods are only suitable for scenarios where a single node can independently complete a task, or where multiple nodes collaborate to complete a task, and the value or benefits of the task are known. They are not suitable for scenarios where multiple nodes must collaborate simultaneously to complete a task, and the value or benefits of the task are unknown, such as multi-node collaborative reconnaissance, direction finding, and cross-localization tasks.

[0037] Due to limited reconnaissance and computing resources, it is not possible to use all distributed reconnaissance nodes to perform reconnaissance, direction finding, and cross-location of a single radiation source target signal. Therefore, the present application proposes a method and apparatus for allocating collaborative reconnaissance tasks based on consistency bidding. This method does not require a central management node; distributed reconnaissance nodes only need to negotiate with each other on a peer-to-peer basis to select the reconnaissance node combination with the highest mission efficiency to perform the collaborative reconnaissance task on the radiation source target, achieving the optimal pairing of the collaborative reconnaissance task with the distributed reconnaissance node combination.

[0038] Please refer to Figure 1 , Figure 1 A schematic diagram of a process flow of a collaborative reconnaissance task allocation method based on consistent bidding proposed in an embodiment of the present application is shown. The method is applied to a reconnaissance node combination consisting of n nodes selected from m distributed reconnaissance nodes. Figure 2 The schematic diagram of the distributed reconnaissance node reconnaissance direction finding and cross-positioning scenario for the radiation source target proposed in the embodiment of the present application is shown. Assuming that the estimated position of the radiation source target is X(x, y), there are m distributed reconnaissance nodes (m≥4), the position of the reconnaissance node i is Si(xi, yi), and the direction finding value of the reconnaissance node to the radiation source target signal is θi (with the positive direction of the X-axis as the azimuth reference), where i∈1,…,m. Due to the limited resources such as reconnaissance and computing, the m distributed reconnaissance nodes conduct interactive negotiations on an equal basis, and the reconnaissance node combination composed of n nodes (m>n≥2) with the greatest reconnaissance mission efficiency is preferably used to collaboratively perform the reconnaissance direction finding and cross-positioning tasks for the radiation source target. The angular measurement error of the reconnaissance node i has a mean of 0 and a variance of The normal distribution of the reconnaissance node i has a mean of 0 and a variance of Normal distribution.

[0039] A collaborative reconnaissance task allocation method based on consensus bidding includes the following steps:

[0040] Step S1, receiving and storing a task information table, wherein the task information table includes a task ID, target characteristic parameters, target estimated position, task type, and task period;

[0041] The task information table describes the task information that needs to be completed through consistent bidding, and is performed collaboratively by multiple reconnaissance nodes. The task information table includes: task ID, target ID, target characteristic parameters, target estimated position, task type, and task period. The task ID is the unique identifier of the task; the target ID is the unique identifier of the radiation source target; the target characteristic parameters are the operating frequency band, signal waveform and other parameters of the radiation source target; the target estimated position is the estimated value of the radiation source target position, which can be a location point coordinate or the vertex coordinate of a polygonal area; the task type specifies the number of reconnaissance nodes that perform the task and the positioning method. Task types include collaborative direction finding cross positioning of 2 reconnaissance nodes and collaborative direction finding cross positioning of 3 reconnaissance nodes; the task period specifies the start time and end time of the collaborative execution of the task by the reconnaissance nodes.

[0042] Each task corresponds to a task information table. When there are multiple tasks, the corresponding task information tables are arranged in order of importance. The order of the task information tables indicates the order of task bidding. The scout node performs consistency bidding for tasks according to the order of the task information tables. Table 1 shows the parameter names and descriptions in the task information table:

[0043] Table 1

[0044]

[0045] Assuming that the polygonal area has b vertices, the estimated position of the radiation source target is X(x,y). When the target estimated position in the mission information table is the coordinate of the polygonal area vertex, calculate the estimated value of the target position coordinate point: in are vertex coordinates, and b is the number of vertices in the polygonal area.

[0046] Step S2: Perform multiple rounds of consistency bidding based on the task information table. The consistency bidding process includes node resource matching analysis, dynamic calculation of task benefits, and distributed negotiation mechanism.

[0047] The consensus auction process consists of the task auction phase and the consensus negotiation phase. Each round of the consensus auction process begins with the task auction phase. Afterward, the scout nodes exchange winning bid information tables and auction information tables, and then proceed to the consensus negotiation phase. The task auction phase and consensus negotiation phase processes are identical for each scout node.

[0048] Among them, the node resource matching analysis can ensure that the reconnaissance nodes participating in the auction have the resources and capabilities to perform the tasks. First, the idle resources are judged. Each node determines whether there are idle resources to perform new tasks based on its current load (such as the number of tasks that have been bid, computing resource usage, etc.). For example, if the maximum number of tasks that a node can execute is 3, and there are already 2 tasks in the current task package, it is allowed to participate in the auction. Secondly, function and performance matching is performed. The node needs to verify whether its hardware capabilities (such as working frequency band coverage and signal waveform analysis capabilities) meet the requirements of the "target characteristic parameters" in the task information table. Finally, geographical matching is performed. If the "target estimated position" in the task information table is a polygonal area, the node needs to determine whether its own position is within the area or the adjacent area to ensure effective direction finding. For example, if the task requires the node to be located in a certain polygonal area, although node A meets the function parameters, it cannot participate in the auction because its location exceeds the area range.

[0049] When calculating task benefits, the node is only combined with the nodes in the newly added or modified auction information table for calculation.

[0050] Dynamic calculation of mission efficiency quantifies the positioning accuracy of different node combinations for the radiation source target and selects the combination with the highest mission efficiency. During each bidding round, nodes generate all possible n-node combinations based on the latest bidding information table. For example, if there are four nodes participating in the bidding (A, B, C, D) and the task type is two-node collaborative positioning, the efficiency of C(4,2)=6 combinations must be calculated. If only some node information is added or modified during a bidding round, only the efficiency of the combination containing D needs to be recalculated, avoiding repeated calculation of historical data.

[0051] The distributed negotiation mechanism ensures that all nodes ultimately reach consensus on the winning combination through information exchange and merging between nodes. First, the bidding information table is merged. Nodes receive bidding information tables broadcast by other nodes and group them by task ID. For the same node with the same task ID, only the entry with the most recent bidding time is retained. Next, the winning bid table is merged. For winning bids with the same task ID, the combination with the highest task benefit is retained. If the benefits are the same, the entry with the earliest winning time is retained. When all nodes' bidding and winning bid tables remain unchanged for m consecutive rounds or a preset time t, consensus is considered reached and the auction is terminated.

[0052] For example, when performing multiple rounds of consistency auction processing:

[0053] First round of bidding: Nodes A, B, C, and D all participate in the bidding and each calculates the benefits of all two-node combinations. Node A believes that (A, B) has the highest benefit, and node B believes that (B, C) has the highest benefit. They then broadcast their respective winning bids.

[0054] Negotiation and Update: After receiving information about winning bids from others, nodes recalculate the global optimal combination. Assuming (A, B) has the highest actual efficiency, all nodes update the winning bid information table.

[0055] Second round of bidding: Nodes recalculate the combined efficiency based on the updated bidding table (possibly including node E). If (A, E) is more efficient, the winning bid table is updated, and negotiations continue until the information stabilizes.

[0056] Step S3: Generate a bidding information table and a winning bid information table during the task bidding phase. During the consensus negotiation phase, nodes exchange the bidding information table and the winning bid information table, update and merge the information to reach a consensus.

[0057] The auction information table describes the information of reconnaissance nodes capable of executing tasks and participating in task auctions. The auction information table includes the task ID, node ID, node location, angle measurement error, site error, and auction time, and is grouped by task ID. During the auction phase, nodes add their own information to the auction information table and broadcast updates. The task ID uniquely identifies the task; the node ID uniquely identifies the reconnaissance node; the node location is the location coordinate of the reconnaissance node; the node angle measurement error is the root mean square error of the reconnaissance node's angle measurement in the target operating frequency band of the radiation source; the node site error is the root mean square error of the reconnaissance node's self-positioning; and the auction time is the time when the reconnaissance node confirms its participation in the auction for the task.

[0058] Multiple reconnaissance node auction tasks will have multiple auction information tables. Multiple auction information tables can be grouped and managed by task ID. The auction information tables with the same task ID are grouped together. Table 2 shows the parameter names and descriptions of the auction information table:

[0059] Table 2

[0060]

[0061]

[0062] The winning bid information table describes the reconnaissance node combination information of the winning task. The winning bid information table includes the task ID, winning bid combination, winning bid task benefit, and winning bid time. The task ID is the unique identifier of the task; the winning bid combination is a reconnaissance node combination composed of multiple winning reconnaissance nodes, which collaborates to perform the reconnaissance direction finding and positioning task of the radiation source target; the winning bid task benefit is the task benefit of the winning bid combination performing the reconnaissance direction finding and positioning task of the radiation source target, and the task benefit can be calculated. The winning bid time refers to the time it takes to form the reconnaissance node combination and calculate the winning bid task benefit. Table 3 shows the parameter names and descriptions of the winning bid information table:

[0063] Table 3

[0064]

[0065] The task auction phase includes:

[0066] The node determines whether to participate in the auction by judging idle resources and analyzing task compatibility;

[0067] The node is dynamically combined with other nodes in the auction information table to calculate the task benefits of all n-node combinations;

[0068] If the current maximum task benefit is higher than the historical value, update the bid winning information table and record the bid winning time;

[0069] Only the changes in the auction information table and the winning bid information table will be broadcast.

[0070] When scout node i receives a pending task, or updates its bid information table or winning bid information table during the consensus negotiation phase, a new round of consensus bidding begins. The task bidding phase includes determining idle resources, analyzing resource and task compatibility, calculating scout task benefits, updating the winning bid information table, updating the bid information table, and broadcasting information.

[0071] The task bidding phase is the core process in which each reconnaissance node independently processes the bidding logic. Its goal is to generate candidate node combinations and their task benefits through local computation and decision-making, and to update the bidding and winning bid tables. First, a resource availability check is performed to ensure that the node has the physical resources (such as computing power, communication bandwidth, and task slots) to execute the new task. Functional matching and geographic matching are then performed to verify that the node's hardware capabilities meet the task requirements. Geographic matching involves determining whether the node's own location is within or adjacent to a polygonal area if the estimated location of the task target is within that area.

[0072] Calculation of reconnaissance mission benefit: The reconnaissance node i is successively matched with all other reconnaissance nodes in the auction information table to form a reconnaissance node combination consisting of n nodes. The mission benefit calculation formula is used to calculate the mission benefit of each combination in performing the reconnaissance direction finding and cross-positioning missions of the radiation source target, and the maximum mission benefit and its corresponding reconnaissance node combination are found. When the number of other reconnaissance nodes in the auction information table is p, the number of reconnaissance node combinations consisting of n nodes formed by matching the reconnaissance node i with other reconnaissance nodes is The number of calculations according to the task benefit calculation formula is also To reduce the number of calculations, scout node i can record the newly added or modified auction information table in each round of consistency auction processing. When calculating the reconnaissance mission benefit, scout node i is only paired with other scout nodes in the newly added or modified auction information table to form a reconnaissance node combination consisting of n nodes. The reconnaissance mission benefit of each combination is calculated according to the mission benefit calculation formula to find the maximum mission benefit and its corresponding reconnaissance node combination.

[0073] Update of the winning bid information table: When the maximum task benefit found by the reconnaissance node i is greater than the winning task benefit in the corresponding task winning bid information table stored in it, the winning task benefit in the winning bid information table is updated to the maximum task benefit, the winning combination is updated to the reconnaissance node combination corresponding to the maximum task benefit, and the winning time is updated to the current system time.

[0074] Update the auction information table: Determine whether the auction information table already has information about the scout node i. If not, add the information about the scout node i to the auction information table. If so, skip this process.

[0075] Information broadcast: Scout node i broadcasts updated auction information tables and winning bid information tables to other scout nodes. To reduce the amount of information broadcast, scout node i can record changes in the winning bid information table and the auction information table during the winning bid information and auction information table updates, and only broadcast the updated auction information table and winning bid information table with changes to other scout nodes.

[0076] The consensus negotiation phase includes:

[0077] After receiving the auction information table, the node merges it by task ID and node ID, retaining the latest auction time entry;

[0078] After receiving the winning bid information table, retain the entry with the largest task benefit by task ID. If the benefits are the same, retain the earliest winning bid time.

[0079] After scout node i completes the task auction phase and receives the auction information table and winning bid information table from other scout nodes, it enters the consensus negotiation phase. This includes updating the auction information table and the winning bid information table.

[0080] Auction Information Table Update: Scout node i compares and merges the received auction information table with its stored auction information table. The new information in the auction information table is updated to the auction information table stored by scout node i. For auction information tables with the same task ID and node ID, scout node i only retains the auction information table with the latest auction time.

[0081] Update the winning bid information table: Scout node i compares and merges the received winning bid information table with its stored winning bid information table. For winning bid information tables with the same task ID, scout node i only retains the winning bid information for the task with the highest winning bid benefit, its corresponding winning bid combination, and winning bid time. For winning bid information tables with the same task ID and winning bid benefit, scout node i only retains the winning bid information table with the earliest winning bid time.

[0082] Step S4: The termination condition is that the information table remains unchanged for multiple consecutive rounds or within a preset time, and a winning combination is determined to perform the task. The winning combination is a reconnaissance node combination composed of n nodes with the largest calculated task benefit, and the task benefit is the inverse of the radiation source positioning error.

[0083] The reconnaissance mission benefit is expressed as the inverse of the theoretical positioning error of the multiple reconnaissance nodes in cross-locating the emitter target signal. The smaller the positioning error of the multiple reconnaissance nodes on the emitter target, the greater the mission benefit.

[0084] The calculation formula for the mission benefit of the reconnaissance node combination composed of n nodes to perform the reconnaissance and positioning mission of the radiation source target is: Where trace(A) represents the trace of matrix A,

[0085] θ i It represents the direction-finding value of the reconnaissance node i to the target signal of the radiation source (with the positive direction of the X axis as the azimuth reference). The number of nodes in the reconnaissance node combination is n, then i∈1,…,n, so θ i The values ​​of include θ1, θ2,…, θ n .

[0086] The task benefit is defined as the inverse of the radiation source positioning error, meaning that the higher the task benefit, the smaller the positioning error. The winning combination consists of the n nodes with the highest task benefits. Multiple rounds of bidding and negotiation are conducted first, with each node participating in the bidding based on its own resource matching and dynamically calculated task benefit. In each round, the node will update and broadcast its bidding information table and winning bid information table. Afterwards, a consistency convergence judgment is performed. If the bidding information table and winning bid information table of all nodes remain unchanged for multiple consecutive rounds (for example, three rounds), consensus is considered reached. Alternatively, if the information table remains unchanged within a preset time threshold t, the process will also be terminated. When the above termination conditions are met, the final confirmed winning combination will execute the task, and the remaining nodes will release resources or participate in other task auctions. This ensures efficient and accurate task allocation in a distributed environment, while also having good real-time and robustness.

[0087] During the consistency auction process, the main information that each reconnaissance node needs to process and store includes not only the task information table, auction information table, and winning bid information table, but also the task package. The task package records multiple task IDs that the node has won the bid for. The number of task IDs does not exceed the maximum number of tasks that the node can execute.

[0088] The task package describes the tasks that the scout node bids for and wins. The task package records one or more task IDs that the scout node wins. The number of task IDs does not exceed the maximum number of tasks that the scout node can execute. Table 4 shows the parameter names and descriptions of the task package:

[0089] Table 4

[0090]

[0091] In one possible embodiment, assuming there are four (m=4) distributed reconnaissance nodes and one radiation source target, a reconnaissance node combination consisting of two nodes with the highest mission efficiency is selected to perform the reconnaissance direction finding and cross-location tasks for the radiation source target. Information such as the ID, operating frequency band, functional capabilities, node location, node angle measurement rms error, and node site error rms of the four reconnaissance nodes is shown in Table 5 below:

[0092] Table 5

[0093]

[0094] At 01:00:00 on January 1, 20X0, the four reconnaissance nodes received the task information table shown in Table 6:

[0095] Table 6

[0096]

[0097] After the four scout nodes receive the task information table, they start the consistent bidding process. In the first round of task bidding, each scout node does not have the bidding information table of other nodes, so it only adds its node information to the bidding information table and broadcasts it. The bidding information table broadcast by node 1 is shown in Table 7:

[0098] Table 7

[0099]

[0100] The auction information broadcast by node 2 is shown in Table 8:

[0101] Table 8

[0102]

[0103]

[0104] The auction information table broadcast by node 3 is shown in Table 8:

[0105] Table 9

[0106]

[0107] The auction information table broadcast by node 4 is shown in Table 10:

[0108] Table 10

[0109]

[0110] Assume that nodes 1, 2, 3, and 4 can communicate directly with each other. After nodes 1, 2, 3, and 4 complete information exchange and transmission, they update the new bidding information table during the consensus negotiation phase. Nodes 1, 2, 3, and 4 update the same bidding information table as shown in Table 11:

[0111] Table 11

[0112]

[0113] Each node calculates the task benefit of itself and other nodes according to formula (1). The node combinations for calculating the task benefit of node 1 include <1,2>, <1,3>, and <1,4>; the node combinations for calculating the task benefit of node 2 include <2,1>, <2,3>, and <2,4>; the node combinations for calculating the task benefit of node 3 include <3,1>, <3,2>, and <3,4>; and the node combinations for calculating the task benefit of node 4 include <4,1>, <4,2>, and <4,3>. The reconnaissance node calculates the task benefit of each node combination separately. The task benefit of each node combination is shown in the following table (Table 12):

[0114] Table 12

[0115] Task ID Node combination (in no particular order) Mission Benefits 1 <1,2> / <2,1> 0.1331 1 <1,3> / <3,1> 0.6898 1 <1,4> / <4,1> 0.6385 1 <2,3> / <3,2> 0.6549 1 <2,4> / <4,2> 0.5935 1 <3,4> / <4,3> 0.2521

[0116] The scout node finds the maximum task benefit and its corresponding combination, and adds the node combination to the winning bid information table. After the task auction phase, the updated auction information table and winning bid information table are broadcast.

[0117] After multiple rounds of consistent bidding, nodes 1, 2, 3, and 4 finally complete the task bidding. The reconnaissance nodes all receive the same winning bid information, as shown in Table 13:

[0118] Table 13

[0119] Task ID Winning combination Mission Benefits Winning bid time 1 <1,3> 0.6898 January 1, 20X0, 1:02:00 AM

[0120] The task packages of node 1 and node 3 are shown in Table 14:

[0121] Table 14

[0122] Task ID 1

[0123] The task packages of nodes 2 and 4 are empty.

[0124] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0125] First, through the auction processing and interactive negotiation mechanism among distributed reconnaissance nodes, the best node combination for performing collaborative reconnaissance tasks is selected, avoiding the use of all available nodes to scout a single target, thereby saving limited reconnaissance and computing resources.

[0126] Second, there's no need for a designated central management node; all distributed reconnaissance nodes bid and negotiate on an equal footing. This approach reduces the risk of single points of failure and enhances system reliability and anti-interference capabilities. Even if some nodes fail or exit the system, the remaining nodes can still complete the assigned tasks.

[0127] Third, the method ensures that the selected distributed reconnaissance node combination can provide the best mission benefit, that is, the collaborative direction finding cross-positioning performance of the radiation source target is optimized, and the best match between the reconnaissance node combination and the mission requirements is achieved by maximizing the mission benefit.

[0128] A possible implementation of a collaborative reconnaissance task allocation device is provided below, which is used to execute the various execution steps and corresponding technical effects of the distributed reconnaissance node method shown in the above embodiment and possible implementation. The device includes:

[0129] Task information storage module, used to manage task information table and task priority;

[0130] The bidding processing module is used to generate the bidding information table, calculate the task benefits and update the winning bid information table;

[0131] Communication module, used to broadcast the changed bidding information table and winning bid information table;

[0132] The negotiation decision module is used to merge external information tables and determine the auction termination conditions.

[0133] In summary, the present application discloses a collaborative reconnaissance task allocation method and device based on consistency bidding, which receives a task information table and starts consistency bidding processing. Each node generates an auction information table and a winning information table through the task auction stage, and calculates the task benefit with the inverse of the positioning error as an indicator; in the consistent negotiation stage, the information table is interactively updated to retain the latest auction items and the maximum benefit winning result. When the auction information and the winning information do not change for multiple rounds or within a preset time, the winning node combination is determined to perform the task. Through distributed negotiation and dynamic benefit optimization, the radiation source positioning accuracy is improved and the communication overhead is reduced. It is suitable for multi-node collaborative reconnaissance scenarios in complex environments. Through a multi-round auction and negotiation mechanism with equal participation of multiple nodes, the node combination with the best task benefit is dynamically selected to solve the task allocation problem in a decentralized scenario.

[0134] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A collaborative reconnaissance task allocation method based on consistency bidding, characterized by: The method is applied to multiple distributed reconnaissance nodes, and the method includes: Receive and store a task information table, wherein the task information table includes a task ID, target characteristic parameters, target estimated position, task type, and task period; Perform multiple rounds of consistency auction processing based on the task information table, including node resource matching analysis, dynamic calculation of task benefits and distributed negotiation mechanism; During the task auction phase, a bidding information table and a winning bid information table are generated. During the consensus negotiation phase, the bidding information table and the winning bid information table are exchanged between nodes, and the information is updated and merged to reach a consensus. The termination condition is that the information table remains unchanged for multiple consecutive rounds or within a preset time, and the winning combination is determined to perform the task. The winning combination is the reconnaissance node combination composed of n nodes with the largest calculated task benefit, and the task benefit is the inverse of the radiation source positioning error.

2. The collaborative reconnaissance task allocation method according to claim 1, wherein: When the target estimated position in the task information table is the vertex coordinate of the polygon area, the target position coordinate point estimate is calculated: in are vertex coordinates, and b is the number of vertices in the polygonal area.

3. The collaborative reconnaissance task allocation method according to claim 1, wherein: The auction information table includes task ID, node ID, node position, angle measurement error, site error and auction time, and is grouped and managed by task ID; during the auction phase, the node adds its own information to the auction information table and broadcasts updates.

4. The collaborative reconnaissance task allocation method according to claim 1, wherein: The task auction stage includes: The node determines whether to participate in the auction by judging idle resources and analyzing task compatibility; The node is dynamically combined with other nodes in the auction information table to calculate the task benefits of all n-node combinations; If the current maximum task benefit is higher than the historical value, update the bid winning information table and record the bid winning time; Only the changes in the auction information table and the winning bid information table will be broadcast.

5. The collaborative reconnaissance task allocation method according to claim 4, characterized in that: When calculating task benefits, the node is only combined with the nodes in the newly added or modified auction information table for calculation.

6. The collaborative reconnaissance task allocation method according to claim 1, wherein: The consensus negotiation phase includes: After receiving the auction information table, the node merges it by task ID and node ID, retaining the latest auction time entry; After receiving the winning bid information table, retain the entry with the largest task benefit by task ID. If the benefits are the same, retain the earliest winning bid time.

7. The collaborative reconnaissance task allocation method according to claim 1, wherein: The task package records multiple task IDs that the node has won, and the number of task IDs does not exceed the maximum number of tasks that the node can execute.

8. A collaborative reconnaissance task allocation device based on consistency bidding, the device being used to implement the method according to any one of claims 1 to 7, characterized in that: The device comprises: Task information storage module, used to manage task information table and task priority; The bidding processing module is used to generate the bidding information table, calculate the task benefits and update the winning bid information table; Communication module, used to broadcast the changed bidding information table and winning bid information table; The negotiation decision module is used to merge external information tables and determine the auction termination conditions.

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