Research On Multi-sensor Scheduling Optimization In Complex Battlefield Environment

Taking the multi-sensor cluster control unit as the object of combat scheduling and deployment is an indispensable strategic scheme in the construction of perceptual defense system,and the selection of its scheduling and deployment mode is an important prerequisite for the launch of combat missions.Due to the lack of consideration of the reality battlefield environment in the existing combat simulation deployment,there are still problems such as uneven distribution of regional coverage,uneven resource and energy consumption,and weak coordination of node allocation.In order to improve the problems mentioned above,starting from the analysis of sensor perception models,coverage methods and scheduling planning modes,based on the theory of scheduling algorithm,the coverage,dormancy,and distribution technologies in multi-sensor scheduling model under complex battlefield environment are studied in-depth in this paper.Furthermore,a complete combat area perception defense system is further built,it can provide theoretical and technical support for the reasonable deployment of operational scheduling tasks.The main research contents of this paper are as follows:Firstly,in view of the complexity of the battlefield environment in the process of scheduling and deployment,the influence of severe weather on the sensor’s sensing radius and transmission loss is analyzed,and the adverse weather influence factors are normalized based on the perceived visibility as a unified measurement standard,complex battlefield weather interference model is established and the adaptation factors of the sensor detection distance under different weather types are obtained,which can provide an important reference for sensor deployment under complex battlefield weather.Secondly,aiming at the problem of uneven control in area coverage,the homogeneous sensor is selected as the research object of scheduling optimization,and a scheduling coverage algorithm based on hybrid improved virtual force is proposed to achieve efficient coverage deployment of scheduling sensors.Based on the optimization of the parameters and distribution of the virtual force,this algorithm combines the particle swarm optimization(PSO)algorithm and the constraint relationship of energy distribution to realize the optimal control of sensor node deployment,which solves the problem that PSO is easy to fall into local optimization.The experimental results show that the algorithm can make the sensor scheduling more uniform,improve the regional coverage rate and save energy.Thirdly,aiming at the problem of unbalanced energy consumption and early paralysis of nodes in the phenomenon of regional node coverage redundancy,the existing scheduling sleep algorithm has the disadvantages of long and fixed sleep time,which leads to excessive energy consumption.In this paper,a self-adaption dynamically dispatch dormancy-node Energy Strategy(SDDES)is proposed.Based on the hybrid scheduling coverage algorithm,a node scheduling sleep sequence within a complete cycle is constructed,and the remaining energy and redundant coverage state in the current node distribution state are used as the judgment basis to dynamically adjust the node mode and sleep period,so as to realize the optimal control of the number of multi-sensors.The experimental results show that the proposed strategy can reduce the consumption of perception energy and effectively prolong the operational life time of the combat scheduling space by sleeping a large number of redundant sensors in the premise of ensuring efficient coverage in the region.Finally,this paper also studies the problem that the objective function in multi-sensor target assignment is difficult to plan and restrict comprehensively,and the coordination is not high,which affects the monitoring effect.In order to effectively monitor the targets in the control area that appear in the perceptual overlapping domain,a scheduling optimization algorithm based on the target monitoring set is proposed.By enhancing the sensing coordination between sensors and targets,the algorithm integrates the sensor sensing region of distributed targets reasonably,constructs the optimal monitoring efficiency function with detection gain and monitoring life as constraints,thus realizing the collaborative allocation optimization between the sensors and monitoring targets.The experimental results show that the algorithm can effectively improve the monitoring efficiency of the cooperative allocation sensors under the target monitoring set,and it is suitable for the resource allocation between the multi-sensors and the targets under the multi deployment cases.