关键词: 无源定位, 到达时差, 到达频差, 最大似然, 牛顿迭代, 最小二乘

Abstract: To solve the single-observer passive location estimation using illuminators of opportunity, a jointing TDOA and FDOA location algorithm based on maximum likelihood is proposed. Firstly, according to the TDOA and FDOA measurement equations, the maximum likelihood model is constructed. Then Newton’s method is applied to solve the maximum likelihood model to obtain the estimation of the target position and velocity. The initial iteration value is given by a Least Squares（LS） algorithm. The Cramer-Rao Lower Bound（CRLB） and the theoretical error of the proposed algorithm are also derived and they are proved equal. Simulation results show that the proposed algorithm has higher estimation accuracy than the Two-Step Weighting Least Squares（TSWLS） algorithm and the Constrained Total Least Squares（CTLS） algorithm, which makes it possible to achieve the CRLB at moderate noise level before the threshold effect occurs. Moreover, from the Geometric Dilution Of Precision（GDOP） figure, it concludes target position, illuminator number and position are also important factors affecting the localization accuracy.

Key words: passive location, Time Difference Of Arrival（TDOA）, Frequency Difference Of Arrival（FDOA）, Maximum Likelihood（ML）, Newton’s method, Least Squares（LS）