Research On Sensor Management Algorithm For Multi-maneuvering Target Collaborative Traking In Airborne Platform

As the speedily development of science and technology,especially sensor technology and avionics technology,more and more sensors are being incorporated into the airborne sensor network,and that the urgent demand of target location in modern air combat,the increasingly complex in air combat environment and the wide application of electronic warfare,makes how to allocate the limited network resources of airborne sensor to a number of different targets to complete the collaborative tracking has become a hot spot in the field of sensor management,while under the conditions about improving the aircraft's survivability and anti-destructive performance under the principle of reduce the use of active radars at the same time.In this paper,we studied the multi-sensor management algorithm for multi-maneuvering target collaborative tracking.The main research results are summarized as follows:1.Researching on aerial target priority assessment method.When the linear programming method evaluates the target priority,the algorithm has high complexity and long computation time can not adapt to the complicated and changeable battlefield environment.In order to solve these problems,the support vector regression(SVR)is used in this paper to study the target priority assessment model,and transform the complex computational process into the target priority prediction problem,to realize the rapid assessment of the target priority within the allowable range of the evaluation error.2.Researching on single maneuvering target multi-sensor cooperative tracking technology.In collaborative tracking,the uncertainty of the covariance and the irrationality of the desired threshold setting make it easy to cause the frequent switching of the radar.What's more,the existing sensor management is carried out under the same tracking accuracy and does not meet the needs of the actual battlefield environment.In view of the above problems,We divided the tracking accuracy according into the different battlefield situation,and defined the synergy index which was managed by covariance and information increment collaboratively to improve the desired threshold.The above-mentioned study proposed in this paper solved the above problems while saving more sensor resources and improving the aircraft's combat capability and survivability.3.Researching on sensor resource allocation algorithm for multi-maneuvering targetcollaborative tracking.First,the multi-sensor is managed by the linear programming method,and the waste function is taken into account while maximizing the performance function.However,with the increase of the number of sensor targets,the multi-sensor target allocation problem becomes a Non-Deterministic Polynomial problem.In this paper,a genetic algorithm is used to solve the problem of sensor resource allocation,and then a genetic particle swarm optimization algorithm is proposed to solve the problem of sensor resource allocation in collaborative tracking,which is based on the advantages of simple design and fast convergence in particle swarm algorithm.