Bearing-only target tracking based on ellipsoidal outer-bounding set-membership estimation

For the problem of bearing-only maneuvering target tracking under the unknown-but-bounded noises, this paper proposes an ellipsoidal outer-bounding set-membership estimation (EOB-SME) algorithm. The EOB-SME algorithm has a prediction-correction structure in time update and observation update, which is similar to Kalman filter. For each update, there is a data-depending weighting factor. The observation weighting factor is computed by minimizing the upper bound on a Lyapunov function of the estimation error and the computation load is decreased. The linearization errors of nonlinear observation equation are bounded by an ellipsoid which is combined with the ellipsoid of observation noise to form a new ellipsoid of observation noise. The simulation results show that the proposed algorithm has higher tracking accuracy for bearing-only maneuvering target under the assumption of unknown-but-bounded noise.