An Algorithm for Underwater Target Motion Analysis(TMA) Based on Convergence Variance Tracking
Kang Wen-yu · 2005
Underwater TMA algorithm based on convergence variance tracking is presented in this paper. With Kalman filtering of azimuth-frequency, the asymptotic unbiased estimation of velocity is obtained to linearly estimate the target initial position and to further make the target motion estimation. Using the above algorithm, we can eliminate the initial position bias value resulted from using direct Kalman filtering algorithm of pseudo-linear estimation. Computer simulation results show that the method has a good estimation performance for the elements of target motion.