Conference proceeding
Comparison of three Kalman filters for an indoor passive tracking system
2007 IEEE International Conference on Electro/Information Technology, pp.284-289
05/2007
DOI: 10.1109/EIT.2007.4374530
Abstract
Wireless sensor networks can be used for the localization and tracking of moving targets. However, the range measurements are noisy and Kalman filters are frequently used to improve the tracking accuracy. Three different tracking algorithms, namely, a standard Kalman filter (SKF), an extended Kalman filter (EKF), and a modified Kalman filter (MKF) are empirically studied in terms of accuracy and latency for a range-based indoor tracking system. The experimental results show that the filtering techniques improve the tracking accuracy when the target is moving rapidly. However, different forms of Kalman filters introduce different levels of latency which affects the real-time tracking performance.
Details
- Title: Subtitle
- Comparison of three Kalman filters for an indoor passive tracking system
- Creators
- Shuo Shen - Lincoln University - PennsylvaniaChen Xia - Lincoln University - PennsylvaniaR Sprick - University of Nebraska–LincolnL.C Perez - Dept. of Electrical Engineering, 209N WSEC, Lincoln, NE, USAS Goddard - University of Nebraska–Lincoln
- Resource Type
- Conference proceeding
- Publication Details
- 2007 IEEE International Conference on Electro/Information Technology, pp.284-289
- Publisher
- IEEE
- DOI
- 10.1109/EIT.2007.4374530
- ISSN
- 2154-0357
- eISSN
- 2154-0373
- Language
- English
- Date published
- 05/2007
- Academic Unit
- Computer Science
- Record Identifier
- 9984259471502771
Metrics
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