Abstract
This paper addresses the Kalman filter divergence problem for Global Navigation Satellite System (GNSS)in Precise Point Positioning (PPP). Continuous improvement of precision of GNSS PPP makes it widely used in various fields, however the Kalman filter divergence resolutions for PPP signal attenuating and satellite missing condition are still insufficient. Kalman filter is a recursive, linear unbiased, minimum variance method. Compared with the standard Kalman filter, the dynamic Kalman filter with attenuation factor in this paper makes up for the Kalman filter divergence problem. The effectiveness of dynamic Kalman Filter is demonstrated via matlab simulation.
| Original language | English |
|---|---|
| Article number | 8484219 |
| Pages (from-to) | 4734-4738 |
| Number of pages | 5 |
| Journal | Chinese Control Conference, CCC |
| Volume | 2018-January |
| DOIs | |
| Publication status | Published - 2018 |
| Event | 37th Chinese Control Conference, CCC 2018 - Wuhan, China Duration: 25 Jul 2018 → 27 Jul 2018 |
Keywords
- Attenuation factor
- Kalman divergence
- Precise Point Positioning
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