Target maneuver detection algorithm

Using bearings only information, passive target tracking in under water scenario can be carried out for a target moving at a constant velocity. If the target changes its course or speed or both, the estimated parameters differ with those of actuals. Hence it is usual to find out target maneuver, before the solution diverges completely and appropriately the covariance matrix of target state vector is corrected. In general, the target maneuver is found out using chi-square test with normalized squared innovation process. J.L. Pirot and M.S. Smith used F-statistic to find out whether the target is stationary or not. In this paper, their work is extended to find out whether the target is maneuvering or not, as an alternate approach for chi-square test. The efficiency of the algorithm is demonstrated through Monte-Carlo simulation. The residuals generated from maximum likelihood estimator are used in sliding window format. The residuals are assumed to follow a second order polynomial. The mean squared errors of the innovations before and after maneuver is analyzed through F-statistic for deciding whether the target is maneuvering or not. Extensive simulation is carried out to evaluate the performance of the algorithm. For the purpose of evaluation, the results of two scenarios in Monte-Carlo simulation with and without target maneuver are presented.