DocumentCode :
978445
Title :
Application of the Kalman-Levy Filter for Tracking Maneuvering Targets
Author :
Sinha, Aloka ; Kirubarajan, Thiagalingam ; Bar-Shalom, Y.
Author_Institution :
McMaster Univ., Hamilton
Volume :
43
Issue :
3
fYear :
2007
fDate :
7/1/2007 12:00:00 AM
Firstpage :
1099
Lastpage :
1107
Abstract :
Among target tracking algorithms using Kalman filtering-like approaches, the standard assumptions are Gaussian process and measurement noise models. Based on these assumptions, the Kalman filter is widely used in single or multiple filter versions (e.g., in an interacting multiple model (IMM) estimator). The oversimplification resulting from the above assumptions can cause degradation in tracking performance. In this paper we explore the application of Kalman-Levy filter to handle maneuvering targets. This filter assumes a heavy-tailed noise distribution known as the Levy distribution. Due to the heavy-tailed nature of the assumed distribution, the Kalman-Levy filter is more effective in the presence of large errors that can occur, for example, due to the onset of acceleration or deceleration. However, for the same reason, the performance of the Kalman-Levy filter in the nonmaneuvering portion of track is worse than that of a Kalman filter. For this reason, an IMM with one Kalman and one Kalman-Levy module is developed here. Also, the superiority of the IMM with Kalman-Levy module over only Kalman-filter-based IMM for realistic maneuvers is shown by simulation results.
Keywords :
Gaussian processes; Kalman filters; target tracking; Gaussian process; Kalman-Levy filter; Levy distribution; interacting multiple model; measurement noise models; noise distribution; target tracking; Filtering algorithms; Gaussian noise; Information filtering; Information filters; Kalman filters; Noise measurement; Phase noise; Probability distribution; State estimation; Target tracking;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/TAES.2007.4383597
Filename :
4383597
Link To Document :
بازگشت