【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。更多还原

【Abstract】 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.更多还原