Single observer bearings-only tracking with the unscented Kalman filter

The basic problem in target motion analysis (TMA) is to estimate the trajectory of an object from noise corrupted measurement data. The position and velocity of an emitter source can be determined from the bearing angle measurements of a passive observer. The paper introduces the recently developed unscented Kalman filter (UKF) in application to bearings-only tracking. What is more, the UKF is compared to the traditional extended Kalman filter (EKF). Simulation shows that the method performs very well even under the adverse circumstances of a noisy environment.

[1]  V. Aidala,et al.  Observability Criteria for Bearings-Only Target Motion Analysis , 1981, IEEE Transactions on Aerospace and Electronic Systems.

[2]  K. Gong,et al.  Position and Velocity Estimation Via Bearing Observations , 1978, IEEE Transactions on Aerospace and Electronic Systems.

[3]  V. Petridis A method for bearings-only velocity and position estimation , 1981 .

[4]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[5]  H.F. Durrant-Whyte,et al.  A new approach for filtering nonlinear systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[6]  V. Aidala Kalman Filter Behavior in Bearings-Only Tracking Applications , 1979, IEEE Transactions on Aerospace and Electronic Systems.