Iterated Modified Gain Extended Kalman Filter with Applications to Bearings Only Tracking

Abstract

A nonlinear filter called the iterated modified gain extended Kalman filter (IMGEKF) is presented in this paper. This filter uses bearings only measurements to estimate the target state in passive target tracking scenario. This work combines the MGEKF and the iteration method. The filter utilizes the updated state to re-linearize the measurement equation. Then the proposed work is tested in a two dimensional scenario. The simulation study compares the IMGEKF and some other filters to show the improvement. 

Bearing only Target Tracking using Single and Multisensor: A Review

“…It was initially proposed and derived by [84] and later the derivation of modified gain function was made simple by [22]. Huang et al [38] has presented the iterated MGEKF, which combines the MGEKF and iteration method. In IMGEKF the new updated state and its corresponding covariance are obtained by re-linearizing the measurement function.…”

“…The process of smoothing is applied to BOT and is discussed by few authors. In analogy to [38], Qian et al [73] has proposed a smoothing MGEKF (sMGEKF) based on Rauch-Tung-Stribel (RTS) smoothing. The authors stated that, RTS algorithm is a fixed interval smoothing and it has two steps forward filtering and backward propagation process.…”