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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sinha, A. Kirubarajan, T. Bar-Shalom, Y. |
| Copyright Year | 1965 |
| 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. |
| File Size | 1171156 |
| File Format | |
| ISSN | 00189251 |
| Volume Number | 43 |
| Issue Number | 3 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-07-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Target tracking Noise measurement Gaussian noise Kalman filters State estimation Information filtering Information filters Probability distribution Phase noise Filtering algorithms |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Aerospace Engineering |
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