3D Passive Bearings-Only Emitter Localization Using Crude Angle-of-Arrival Measurements

Abstract. This paper derives three-dimensional passive bearings-only localization algorithms and examines their performance in the presence of large measurement noise by way of simulations. Among the algorithms studied, an iterative Gauss-Newton (GN) implementation of the maximum likelihood (ML) estimator is shown to have the best localization performance. In order to reduce the computational complexity of the GN algorithm to acceptable levels, a simple averaging technique is proposed whereby successive bearing measurements are averaged over non-overlapping finite-length windows. Extensive simulations are presented to illustrate the superior performance of the ML estimator in a radar localization application involving moving helicopters equipped with radar warning receivers.