A Study Of Beam Resource Management And Optimization For Multi-target Tracking Mode In Phased Array Radar

Phased array radar, with flexible beam pointing and agility characteristic, can allocate time and energy resources for the airspace search, target tracking and other different tasks in reason, and timely adjust and arrange radar mode, to meet different functional requirements; It can meet the target tracking requirements while maintaining the ability to search specified surveillance airspace; It can cope with multi-batch, strong motorized and high speed object tracking-location demands; It can adaptively adjust task priority, target priority, in response to changes in the battlefield environment and the target state in real time, thus dynamically adjust system status and device parameter settings to optimize overall performance. Due to the phased array radar system resources are shared and different working conditions and mission requirements are different for resources, without allocation of resources in reason, it cannot guarantee its tracking capabilities and advantages to play fundamentally.Combined with research achievements and background of the issue at the present stage, this thesis focuses on the multibeam resource management and optimization of phased array radar in multi-target tracking state. The main topics are as follows:1. The thesis studies on the resource management method of multi-objective multi-beam phased array radar in tracking mode, that is how to allocate the radar beam, how reasonable dispatch between search and tracking. Focus on resource management in multi-target tracking under multi-beam architecture.1) In the multi-target scenes, each target threat assessment largely affect the allocation of tracking targets, while fast and accurate assessment of the threat level leads to better rational use of limited radar resources. This thesis combines fuzzy optimization theory with analytic hierarchy, using expert knowledge and prior knowledge of the target jointly determines target threat degree, it studies on an objectives threat criterion based on fuzzy optimization. With simulation it proved to provide accurate multi-target determination of threat in real time, which takes full advantage of expert knowledge and follows and simulates human thinking awareness and has good evaluate performance.2) The thesis studies an information theory- covariance theory fused resource management algorithm, which combines the advantages of two algorithms by taking into account both the independent expectation of tracking accuracy for each target and the incremental information brought by the maneuvering characteristics. With fusion improvements, considering the actual phased array applications in independent beam control case, the algorithm achieves a multi-target tracking and multi-beam jointly controlling radar resource management, which makes it more responsive to the multi-target scenes and further enhances the target capacity.2. Proceeding from the angle of optimizing radar emission parameters, the thesis focuses on independent beam power allocation optimization problems in multi-beam mode. By treat the Bayesian Cramer-Rao lower bound of tracking error as the cost function, it studies an effective optimization methods for allocation of limited power resources. In addition, for existing phased array radar multibeam resource management issues, namely multi-beam joint scheduling and task assignment, the thesis studies a Time- Power Joint Distribution Method. The simulation confirmed the effectiveness of optimal power allocation method in terms of improving tracking performance, and validated the feasibility and effectiveness of joint distribution method, compared with the traditional time- power average allocation method in detail.