Abstract
Stand-alone GPS basted position estimation problem using GPS raw data, pseudo-range and Doppler shifts measurements are the concept of fusing noisy observations. A family of improved derivative nonlinear Kalman filters called Sigma Point Kalman filter (SPKF) are applied to a nonlinear model of GPS based position estimation in this paper. Simulations are made to compare the filter with the traditional Iterative Least Square (ILS) method and extended Kalman filter (EKF) method, results indicate that under same conditions, SPKF has higher filtering accuracy and more stable estimation performance.
| Original language | English |
|---|---|
| Title of host publication | 2005 Fifth International Conference on Information, Communications and Signal Processing |
| Pages | 213-217 |
| Number of pages | 5 |
| Publication status | Published - 2005 |
| Externally published | Yes |
| Event | 2005 Fifth International Conference on Information, Communications and Signal Processing - Bangkok, Thailand Duration: 6 Dec 2005 → 9 Dec 2005 |
Publication series
| Name | 2005 Fifth International Conference on Information, Communications and Signal Processing |
|---|---|
| Volume | 2005 |
Conference
| Conference | 2005 Fifth International Conference on Information, Communications and Signal Processing |
|---|---|
| Country/Territory | Thailand |
| City | Bangkok |
| Period | 6/12/05 → 9/12/05 |
Keywords
- Estimation
- GPS
- Kalman filter
- Sigma point
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Bo, T., Pingyuan, C., & Yangzhou, C. (2005). Sigma-point Kalman filters for GPS based position estimation. In 2005 Fifth International Conference on Information, Communications and Signal Processing (pp. 213-217). Article 1689037 (2005 Fifth International Conference on Information, Communications and Signal Processing; Vol. 2005).