Maximum likelihood estimation of target acceleration

Maximum Likelihood Failure Detection (MLFD) theory is used to estimate the acceleration of a moving target performing an evasive maneuver during an air-to-air interception. Target acceleration is shown to introduce a bias in the residual of the navigation (Kalman) filter. The MLFD algorithm processes this biased residual to detect acceleration transitions, estimate the acceleration subsequent to the transition, and provide a correction term that approximately cancels the error due to target acceleration in estimating the projected miss distance. Also presented are simulation results demonstrating for a particular case that the rms terminal miss distance is reduced from 6.8 to 0.9 feet by application oF the MLFD algorithm.