一种可融合频差变化率的无源定位算法

A Passive Location Algorithm Using Derivative of FDOA

在时/频差双站无源定位中,窄带信号的到达时差估计误差较大会导致定位性能恶化。针对这一问题,提出梯度加权定位算法,该算法利用观测量对地理位置的敏感度作为加权系数,建立最大似然目标函数,可将多个观测量进行加权融合,由此引入频差变化率以增加观测的Fisher信息。仿真结果表明,对于窄带信号,该算法相对于传统的时/频差定位算法具有更高的精度,与Hough算法相比具有更小的搜索量,能有效提升对窄带辐射源的综合定位性能。

For TDOA/FDOA dual-station passive location,usually notable degradation could be caused by narrow-band emitter in location performance.A so-called Gradient-Weighting algorithm is proposed to solve this problem.Position sensitivity of measurements could be used as weight factor to construct a cost function,which can fuse different kinds of parameters,especially derivative of FDOA,to improve location performance of narrow-band emitter.Simulation results show the performance of algorithm is better than TDOA/FDOA passive location algorithm,and has less computation than existing weighting algorithm.