Research On Collaborative Tracking Of Multiple Land Platforms In Battlefield Environment

Multi-platform collaborative detection,adapting to modern battlefield,is a new reconnaissance model,which mainly includes collaborative location,collaborative identification and collaborative tracking.The purpose of collaborative tracking is to accurately track the movement of the targets through the cooperation of reconnaissance resources and perceive battlefield situation.The collaborative tracking problem of multiple land platform in the battlefield environment is to study how to allocate and schedule tracking tasks for the existing land platforms,so as to ensure continuous target tracking,and maximize overall tracking performance.Based on the battlefield environment,this paper analyzes the situation of regional full coverage and radar silence,and researches on multi-platform multi-target collaborative tracking and mobile collaborative tracking problem.The main work of this article is as follows:First,in combination with battlefield environment,establish target and sensor model in the collaborative tracking system of multiple land platform,and introduce the characteristics of multi-platform collaborative tracking system in centralized decision-making and distributed data processing.According to ground target movement feature,interactive multi-model extended Kalman filter is adopted to track targets in open areas,and extended Kalman filter based on road information is used to track moving targets along the road,which can guarantee the rationality of the tracking process.Secondly,in order to initially establish the battlefield situation and guide the tracking system to reasonably allocate reconnaissance resources,conduct a study on the problem of ground target threat assessment.According to target type,target number,distance between the target and our important units,and the speed of the target heading towards our important units,combining the influence of road on ground targets’ maneuverability,use Bayesian network to dynamically assess the target threat and obtain reconnaissance priority of different targets.Thirdly,aiming at the scenes of full regional coverage and unchanging positions of reconnaissance platforms,the multi-objective collaborative tracking problem is studied.The problem of sensor management in collaborative tracking is transformed into the problem of multi-platform collaborative tracking task allocation.According to the target threat and sensor tracking performance of target prediction trajectory,set up an objective function of tracking task assignment.Constraints are established based on multi-platform collaborative tracking model,and genetic algorithm is used to solve the tracking task assignment problem.Simulations show that this method guarantees continuous tracking of the target and improve tracking effects of high threat targets.Finally,in light of the scenario of radar silence,collaborative tracking of photovoltaic platforms is studied.Considering that the optoelectronic platform can track while moving,the conditions for requesting handover in the platform mobile tracking process and the scheduling strategy of handover platforms are obtained.According to the tracking performance,the threat degree of target and the distance between the platform and the target,particle swarm optimization algorithm is used to assist path planning of tracking process and the handover process of the platform.Design simulation to achieve the tracking and handover process of the photovoltaic platform in the case of radar silence,completed the mobile collaborative tracking of the target.