Bearing-Only Ground Slow Target Localization with Unknown Relative Altitude

Abstract

AbstractA state-dependent extended Kalman filter (EKF) algorithm is proposed for bearing-only slow target tracking when the relative height between the observer and the target is unknown. Firstly, we establish the bearing-only target tracking model with unknown relative altitude. Secondly, we study the vinculum between the relative altitude and the target status and present a new Gauss-Helmert state transition model. The Gauss-Newton method is used to predict the state since the Gauss-Helmert model is nonlinear. Finally, we use EKF algorithm to jointly reckon the target location and the relative height. Compared with the augmented EKF algorithm, The algorithm proposed in this paper can predict the unknown state vector accurately.From the simulation result,the proposed state-dependent EKF algorithm has faster convergence speed and higher tracking accuracy.KeywordsSlow target trackingBearing-onlyUnknown relative altitudeState-dependentExtended Kalman filter