Optimal Deployment And Scheduling Of Heterogeneous Sensors In Battlefield Reconnaissance

Sensor networks have played an extremely important role in modern battlefields.Diversified target types,multi-dimensional information states,non-homogeneous reconnaissance environments,and divergent target threats pose many new challenges to the management of sensor resource in battlefield reconnaissance.With ideal sensor perception model,isomorphic deployment environment,and simple management strategy,most existing studies show limitations when applied to complex and changing battlefield reconnaissance.Based on above problems,this paper focuses on the optimal deployment and dynamic scheduling of heterogeneous sensors in battlefield reconnaissance.Types of sensors involved are: vehicle-mounted CCD,vehicle-mounted infrared camera,vehicle-mounted ground activity target reconnaissance radar,vehicle-mounted gun reconnaissance radar,airborne CCD,airborne infrared camera,airborne synthetic aperture radar and airborne electronic reconnaissance equipment.This paper mainly researches reconnaissance on individual soldiers,armored vehicles,radar vehicles,command posts,artillery positions,radar units,armored units and so on.Firstly,according to the practical working principle of each kind of heterogeneous sensor in the battlefield environment,heterogeneous sensor sensing range models,conforming to the reconnaissance needs,are established.Combining characteristics of reconnaissance missions and detection performance of heterogeneous sensors,reconnaissance efficiency factor is introduced on the basis of the probability perception model,to improve the calculation of traditional detection effectiveness.Due to the accessibility of ground platforms,breadth-first algorithm is used to obtain accessibility matrix of heterogeneous ground platforms under the influence of natural environment and enemy threats.In combination with the priority of mission areas,value distribution maps of non-isomorphic environments in the air and land are constructed separately.Taking into account the presence of terrain fluctuations in the reconnaissance area,the sensor-sensing range impact model under the cover of complex environment is improved.Through the analysis and modeling of the complexity of the reconnaissance environment,models that can better reflect the reality of battlefield reconnaissance are obtained.Then,considering differences in the role of the air and ground subsystems in battlefields,detection capabilities,and maneuverability of platforms,this paper proposes strategies for optimal deployment of airborne heterogeneous sensors and ground heterogeneous platforms.According to common points and differences between these two subsystems,indicator function models are established respectively,and multi-objective particle swarm algorithm(MOPSO)is used to optimize these models.Combining the characteristics of mission areas with the performance of heterogeneous sensors,we obtain a sensor multi-tasking zone allocation scheme,as well as the optimized deployment result of heterogeneous sensors(platforms)based on this scheme.In the airborne heterogeneous sensor deployment strategy,due to the non-circular nature of airborne sensor detection range,the UAV’s heading angle is optimized through coordinate transformation.Because of multiple working modes of some sensors,the working mode of a sensor at the certain position is marked in the deployment strategy by distinguishing the type of reconnaissance areas.In the strategy of deploying heterogeneous platforms on the ground,taking into account the constraints of platform loads,the concept of combining heterogeneous sensors with ground platforms is introduced,which converts the distribution of heterogeneous sensors among ground mission areas to the distribution of heterogeneous platforms,also the deployment of independent sensor nodes is transformed into the management of ground mobile platforms.These obtained deployment strategies are in line with the actual situation of battlefield and have practicality.What’s more,two kinds of dynamic scheduling strategies of heterogeneous platforms on the ground are designed to address different types and degrees of renewal in the battlefield environment.Using the mobile platform judgment method proposed in the paper,states of platforms in the area are counted.Depth-first algorithm,image dilation and erosion are used to process the reconnaissance performance matrix,and loophole region parameters in the environment are obtained based on k-means clustering algorithm.In combination with environmental situation,different scheduling schemes are used to modify the reconnaissance efficiency.In the scheduling process,A* algorithm is adopted to calculate movement distance during platform scheduling,so as to obtain a scheduling scheme,in which preparation time is as short as possible.While improving reconnaissance effectiveness,these strategies effectively extend the life cycle of the network.Finally,the heterogeneous sensor resource optimization management system software is designed,and these proposed algorithms are verified in a reconnaissance project.Use Matlab dynamic link library to call the Matlab program corresponding to each module,and use QT to visualize the output results in the results display interface.Verified by various scenarios and reconnaissance environments,the heterogeneous sensor resource management strategies proposed in this paper have achieved high reconnaissance effectiveness and global coverage rate.Simulation show that,the optimal deployment and scheduling strategies of heterogeneous sensors proposed in this paper can meet the requirements of battlefield reconnaissance,which are practical and effective.