Target Parameter Estimation in the Near Field with Two Sensors

A performance prediction procedure is developed for the evaluation of a passive tracking technique for the localization of targets in the near-field of the sensors. The target moves in a three-dimensional space with a constant velocity at a constant depth. The parameter vector is thus five-dimensional. Target localization parameter identifiability is established with the aid of the Fisher Information Matrix (FIM). The FIM is evaluated for various combinations of the following sequences of measurements: time difference of arrival (TDOA) between the two sensors, depression angles measured at the two sensors, and frequency measurements obtained separately with the two sensors. The FIM is used to determine bounds on localization performance, and the corresponding uncertainty ellipses associated with the target position are evaluated for various tracking scenarios. The theoretical results are corroborated by applying a maximum likelihood estimation algorithm to simulated data and observing the results for a series of Monte Carlo simulations.