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This paper discusses the localization problem for strictly noncircular sources based on Doppler shifts and angle of arrival (AOA). The conventional location methods, called two-step methods, first extract measurement parameters from the signals, and then estimate the position from these parameters. Unlike the conventional two-step methods, direct position determination (DPD) methods can locate emitter in a single step without estimating intermediate parameters, thereby receiving higher location accuracy. However, existing DPD algorithms focusing on moving receivers remain few, and ignore exploiting the noncircular property of sources to enhance the localization accuracy. To solve these problems, this paper develops a decoupled maximum likelihood (ML) DPD algorithm for strictly noncircular sources based on Doppler shifts and AOA. First, we reconstruct the DPD optimization model by exploiting the noncircular property of sources and using Doppler shifts to meet the moving receivers application. Then, since the prescribed ML DPD algorithm for multiple sources will suffer huge computation load, a decoupled iterative idea is applied to it. Compared with the straightforward implementation of ML estimators, our method substantially reduces the computation complexity via decoupling the position of each emitter from the other emitters in each iteration. In addition, we derive the Crame&#x0301;r-Rao Bound for strictly noncircular sources, and prove it is lower than that of circular sources. Simulation results demonstrate that the proposed algorithm achieves convergence through only a few iterations, and receives superior performance than other location methods in the test scenarios.

A Decoupled Direct Positioning Algorithm for Strictly Noncircular Sources Based on Doppler Shifts and Angle of Arrival