提出一种新的基于总体最小二 乘 (Total Least Squares, TLS) 到达角 (Angle of Arrival, AOA) 和 到达时间差 (Time Difference of Arrival, TDOA) 目标运动分 析 (Target Motion Analysis, TMA) 算法. 首先给出了基于 AOA/TDOA 的混合变量含误差 TMA 模型, 并根据该模型提出 一种 AOA/TDOA 混合TLS算法, 并证明该算法的渐近最优性. 仿 真结果验证所提出算法的均方根误差在较小观测误差条件下可达 Cra\'{m}er-Rao 下界.

This paper presents a novel total least-squares (TLS) algorithm to solve the target motion analysis problem using angles of arrival (AOA) and time differences of arrival (TDOA). First we linearize the AOA/TDOA measurement equations and show that the new model fits a class of error in variables (EIV) models. Then a TLS method is proposed based on the EIV model and it is proved to be asymptotically optimal. The simulation results show the root-mean-square-error (RMSE) of the proposed estimator achieves the Cra\'{m}er-Rao lower bound with small observation error.