Title : 
Improvement of bearings only target tracking using smoothing
         
        
            Author : 
Zhang Qian ; Taek Lyul Song
         
        
            Author_Institution : 
Dept. of Electron. Syst. Eng., Hanyang Univ., Seoul, South Korea
         
        
        
        
        
            Abstract : 
Bearings only target tracking is often addressed using linearized estimators such as the extended Kalman filter (EKF). Due to the erratic performance of the EKF algorithm in passive localization, a new filtering method, referred to as the smoothing modified gain EKF (sMGEKF), is proposed based on the modified gain EKF (MGEKF) and Rauch-Tung-Striebel (RTS) smoothing. Compared to the traditional approaches (e.g., the EKF and the iterated EKF) used in passive localization, the proposed method has potential advantages in tracking accuracy. A simulation study demonstrates the advantages of this approach.
         
        
            Keywords : 
Kalman filters; nonlinear filters; smoothing methods; target tracking; RTS smoothing; Rauch-Tung-Striebel smoothing; bearings only target tracking; extended Kalman filter; filtering method; iterated EKF; linearized estimators; passive localization; sMGEKF; smoothing modified gain EKF; tracking accuracy; Estimation error; Kalman filters; Mathematical model; Sensors; Smoothing methods; Target tracking; Time measurement; bearing only target tracking; modified gain extended Kalman filter; smoothing;
         
        
        
        
            Conference_Titel : 
Control Science and Systems Engineering (CCSSE), 2014 IEEE International Conference on
         
        
            Print_ISBN : 
978-1-4799-6396-6
         
        
        
            DOI : 
10.1109/CCSSE.2014.7224497