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Two Stage Kalman Estimators with Probabilistically Weighted Average | ||
| Engineering and Technology Journal | ||
| Article 1, Volume 27, Issue 9, 2009, Pages 1847-1857 PDF (233.5 K) | ||
| DOI: 10.30684/etj.27.9.15 | ||
| Author | ||
| Hanady Abbas Jaber | ||
| Abstract | ||
| With spherical coordinate, the adaptive estimation using multiple model filtering is enhanced in this paper. The enhancement is achieved by using just two depended parallel Kalman filters, instead of multiple models, with the probabilistically weighted average, which provides the adaptive mechanism. The first filter is constant velocity filter (CVF) which is used to estimate the position and velocity of the moving target in non maneuvering course. The second filter calculates the acceleration and the new adjustment for the CVF. The second filter is referred as variable velocity filter (VVF). Monte Carlo computer simulation results are included to demonstrate the effectiveness of the proposed algorithm in enhancement the multiple model adaptive filtering. | ||
| Keywords | ||
| Estimation; Kalman Filter; two stages; probabilistically weighted average | ||
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