Target Motion Analysis in the Presence of False Alarm
Claude Jauffret, Yaakov Bar‐Shalom · 1992
Usually, Target Motion Analysis (TMA) is based upon the Gaussian statistical assumption for the additive corrupting measurement noise. As a consequence, the Least Square Estimator (LSE) is equal to the Maximum Likelihood Estimator (MLE). In this paper, we propose a general formulation for TMA problems when the available measurement at each sampling time is either a true detection or a false alarm. By using realistic statistical assumptions, we compute the Cramer Rao Lower Bound. The case of bearing only TMA allows us to illustrate this new approach. A comparison is then made between LSE and MLE.