Joint Sigma-Point Kalman Filter Based Bearing-Only Tracking

These instructions give you the basic guidelines for preparing papers for WCICA/IEEE conference proceedings. Abstract - A novel joint sigma-point Kalman filter algorithm is proposed to solve the problems of slow convergence rate and biased state estimation when systematic error exists in bearing-only target tracking. The algorithm can eliminate the effect of systematic error to the state estimation as well as reduce linearization error. The simulation results demonstrate the validity of the proposed algorithm.