Sensor Optimized Deployment And Pursuit Game For Tactical Reconnaissance

The modern war environment is complex,the objectives are diverse,and the battlefield situation changes rapidly,which put higher requirements on the optimal deployment of multisensor resources.At the same time,reasonable deployment of multi-sensor resource is an important guarantee to improve the reconnaissance performance of sensor networks,and it is also the key basis for the sensors to play an important role.Based on this,this paper studies the key issues in the optimal deployment and reconnaissance of heterogeneous sensors in complex environments,which are mainly divided into three aspects: the static sensor deployment,dynamic sensor deployment and the pursuit game of UAVs in reconnaissance missions.Firstly,we study the static and dynamic optimization deployment of multi-sensors in complex environments,including problem modeling,problem analysis,algorithm design,and proposes a new game and optimization theory.Then,based on the deployment results,the multi-agent escape strategy is studied and a multi-agent differential strategy is proposed.The main work of this paper is as follows:Firstly,in order to provide theoretical support for multi-sensor optimization deployment,the distributed multi-objective optimization problem and algorithm are studied.A multi-agent distributed design method is used to design a discrete-time distributed optimization algorithm,and a rigorous theoretical proof is given.A Pareto optimal solution for distributed multiobjective optimization problems is obtained.On this basis,a distributed multi-target sensor deployment optimization model is established for static sensor deployment.At the same time,combined with the existence of multiple optimization objectives in sensor network:maintaining a certain formation,minimizing the probability of being discovered by the target,minimizing the reconnaissance consumption and maximizing the reconnaissance effect,the Pareto optimal solution for the multi-target static sensor deployment problem is obtained.The numerical simulations are given.Then,in view of the actual engineering needs,the sensor-target allocation problem composed of multiple indicators is considered.The threat area set by the enemy is regarded as the obstacle area where the sensor is not deployable.A dynamic network deployment strategy of the sensor network is designed,so that sensors can avoid the threat areas and the non-deployable areas while detecting the allocated target and ensure the connectivity of the network.Game theory is used to solve the optimal decision-making problem,and thus the dynamic optimization of sensor deployment in complex environments is obtained.Finally,the problem of pursuit in the battlefield deployment has been studied.We expand the existing two-person survival line strategy,and establish a model and analysis method for the three-way survival line countermeasures.Furthermore,the boundary barrier and escape strategy of the three-person survival line countermeasures in the pursuit problem are further studied.The decomposition method is used to decompose the three-person survival line strategy into two survival line sub-strategies,and the boundary between the two sub-strategies is obtained respectively.Then,the two boundary gates are integrated to form the boundary of the whole countermeasure problem,thereby depicting the corresponding capture zone and escape zone.On this basis,the strategies that escapers can take are analyzed,and different strategies that escapers can choose in different areas of the escape zone are given.