Research on Extended Target-Tracking Algorithms of Sea Surface Navigation Radar

To solve the problem of false tracks generated by breakdowns and clutter in point-target tracking polar coordinates, a fusion algorithm based on converted measurement Kalman filter random matrix expansion is proposed. The (CMKF) transforms coordinate data target at current time into Cartesian coordinates without bias. Based linear measurements states, position extended group was predicted updated using matrix, its track drawn combining nearest neighbors to realize size, shape azimuth target. Compared with tracking, accuracy multi-target increased 45.8% measured NAVICO navigation radar aboard ships sea. experimental results showed that improved method this paper could effectively reduce interference provide more information about motion features.