联合角度和时差的单站无源相干定位加权最小二乘算法

针对利用单个观测站接收多个外辐射源信号从而实现对目标定位的单站无源相干定位问题, 该文提出了一种联合角度和时差的加权最小二乘定位算法。首先, 将角度和时差的观测方程线性化处理, 考虑方程中的各项误差, 将定位问题建立为加权最小二乘模型。然后利用迭代方法对模型求解。最后, 对算法的定位性能进行了理论分析。仿真结果表明, 不同于仅时差定位方法至少需要3个外辐射源才能定位, 联合角度和时差定位方法仅需一个外辐射源即可定位, 且在同样数量外辐射源条件下估计精度高于仅时差定位；算法的均方误差低于最小二乘算法, 在时差测量噪声较大时定位精度仍然能逼近克拉美罗界。此外, 对系统几何精度因子图的分析表明, 目标及辐射源的位置对定位精度也有重要影响。 

Weighted Least Squares Algorithm for Single-observer Passive Coherent Location Using DOA and TDOA Measurements

In order to determine single-observer passive coherent locations using illuminators of opportunity, we propose a jointing angle and Time Difference Of Arrival (TDOA) Weighted Least Squares (WLS) location method. First, we linearize the DOA and TDOA measurement equations. We establish the localization problem as the WLS optimization model by considering the errors in the location equations. Then, we iteratively solve the WLS optimization. Finally, we conduct a performance analysis of the proposed method. Simulation results show that, unlike the TDOA-only method, which needs at least three illuminators to locate a target, the jointing DOA and TDOA method requires only one illuminator. It also has a higher localization accuracy than the TDOA-only method when using the same number of illuminators. The proposed method yields a lower mean square error than the least squares algorithm, which makes it possible to approach the Cramr-Rao lower bound at a relatively high TDOA noise level. Moreover, on the basis of the geometric dilution of precision, we conclude that the positions of the target and illuminators are also important factors affecting the localization accuracy.