基于半定规划的无源跟踪最佳传感器选择  

Optimal Sensor Selection for Passive Tracking System Based on Semi-definite Programming

作　　者：蔡立平 左燕[1] 王文光[2] CAI Li-ping;ZUO Yan;WANG Wen-guang(Institute of Information and Control, Hangzhou Dianzi University Hangzhou 310018,China;School of Electronic Information Engineering, Beihang University, Beijing 100191,China)

机构地区：[1]杭州电子科技大学自动化学院,杭州310018 [2]北京航空航天大学电子信息工程学院,北京100191

出　　处：《火力与指挥控制》2019年第9期49-54,共6页Fire Control & Command Control

基　　金：国家自然科学基金面上项目(61673146,61771028);浙江省自然科学基金面上资助项目(LY16F030009)

摘　　要：在多站测向定位系统中,观测站与目标的几何位置影响目标定位跟踪精度。以目标估计的克-劳美罗下界(CRLB)行列式最大值为优化指标,在考虑传感器自身的探测能力等实际约束的前提下,建立了无源协同跟踪下最佳传感器选择优化模型。提出了一种基于半定规划(SDP)算法将上述组合优化问题转换为凸优化问题,进行优化求解。仿真结果验证了算法的有效性,与松弛算法和随机选择算法相比,基于SDP的传感器选择可以进一步提高无源协同跟踪的精度。The tracking accuracy of passive AOA location system is affected by the relative geometry relationship between sensors and target. An optimal sensor selection formulation with minimizing maximum Cramer-Rao lower bound(CRLB) under detective capability constraints is proposed. The problem can be relaxed to a convex optimization problem using semi-definite programming(SDP). The simulation result shows that the SDP algorithm is effective and can improve the tracking accuracy comparing with the relaxation algorithm and random selection algorithm.

关 键 词：无源定位 半定规划(SDP) 传感器选择 克-劳美罗下界(CRLB) 

分 类 号：TN95[电子电信—信号与信息处理]