Improvement on Passive Location Algorithm Based on Extended Kalman Filter

Brings forward an improved bearing only location algorithm for airborne observers. Extended Kalman filter (EKF) is used to substitute the traditional least square location. Information about movement of the airborne platform is introduced into the observation equation to build up an observable system. Second order EKF algorithm is used to resolve the nonlinearity error produced by the nonlinearity observation function. The three methods of location are compared by Monte Carlo simulation. The results proved that second order EKF used in passive location problems led to better estimation precision. The estimation results appear in a smaller probability ellipse, which is reduced to 30% of the ellipse by LS estimation.