Target Parameter Estimation with Passive Sensors in the Presence of False Detections

A method for target parameter estimation in the presence of false detections with two passive sensors is presented. The technique is based on the Maximum Likelihood Estimation. The measurement model is non-linear and includes false measurements. The algorithm is first developed for a single target and then extended to two targets. For multiple targets unresolved measurements are also considered to provide a realistic analysis of targets crossing in the measurement space. A modified Cramer-Rao Lower Bound (CRLB) is derived for the case of target parameter estimation in the presence of false measurements. The performance degradation due to the false measurements is illustrated in the examples.