ABSTRACT
This chapter considers an autonomous target motion analysis (TMA) problem. It describes the modeling of an autonomous TMA problem where a constant velocity target has to be tracked using bearing measurements which are noise corrupted. The chapter discusses the modeling of an autonomous TMA problem where a constant velocity target has to be tracked using bearing measurements which are noise corrupted. Since the measurement is only the noise corrupted bearing angle, the problem is highly nonlinear and challenging. A parametric study was carried out by varying the initial covariance, measurement noise covariance and sampling time to validate the filtering accuracy. The chapter discusses shifted Rayleigh filter is formulated to deal with Bearings-only tracking (BOT) problems where the process is represented by a stochastic differential equation and the measurement is discrete. BOT is one of the most challenging nonlinear filtering problems. BOT plays a very important role particularly in tracking enemy ships and submarines.
