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.
作者
蔡立平
左燕
王文光
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)
出处
《火力与指挥控制》
CSCD
北大核心
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)
