EXTENDED KALMAN FILTER FOR PASSIVE LOCALIZATION

Extented Kalman Filter （EKP） combined with Linear Minimum Variance method is utilized for post-processing of passive localization. The combination of the two methods reduces bias and variance seriously, and overcomes the shortcoming of poor initial condition causing big estimate error in EKF. A basic assumption concerning source motion is to consider it to-be of constant velocity over the successive observation intervals. The maneuvreing portions are modeled as random velocity perturbation. Adaptive technique is able to track maneuvering target. Computer simulation results show good performance to estimate range, speed, course of target, and the adaptation to target maneuvre.