Expectation maximization algorithm for calibration of ground sensor networks using a road constrained particle filter
Target tracking in ground sensor networks requires an accurate calibration of sensor positions and orientations, as well as sensor offsets and scale errors. We present a calibration algorithm based on the EM (expectation maximization) algorithm, where the particle filter is used for target tracking...
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| Vydáno v: | 2012 15th International Conference on Information Fusion s. 771 - 778 |
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| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.07.2012
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| Témata: | |
| ISBN: | 1467304174, 9781467304177, 9780982443842, 0982443846 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Target tracking in ground sensor networks requires an accurate calibration of sensor positions and orientations, as well as sensor offsets and scale errors. We present a calibration algorithm based on the EM (expectation maximization) algorithm, where the particle filter is used for target tracking and a non-linear least squares estimator is used for estimation of the calibration parameters. The proposed algorithm is very simple to use in practice, since no ground truth of the target position and time synchronization are needed. In that way, opportunistic targets can also be used for calibration. For road-bound targets, a road-constrained particle filter is used to increase the performance. Tests on real data shows that a sensor position accuracy of a couple of meters is obtained from only one passing target. |
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| ISBN: | 1467304174 9781467304177 9780982443842 0982443846 |