Maneuvering Target Tracking Algorithm Based on Improved Truncation Gaussian Probability Model

Maneuvering target model is a key element in underwater target tracking. Based on truncation Gaussian probability model for underwater target tracking, an improved maneuvering target tracking algorithm is presented in this paper. The algorithm utilizes the difference between observation value and state estimation of previous two sample positions to update the model′s self-adaptation of maneuvering acceleration and its variance, and avoids adverse influence of acceleration limit presupposition. Simulation result shows that this algorithm has good performance of tracking underwater maneuvering target with higher accuracy.