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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Feng He Lenan Wu |
| Copyright Year | 2007 |
| Description | Author affiliation: Southeast Univ., Nanjing (Feng He; Lenan Wu) |
| Abstract | In this paper a computational Kalman smoothing algorithm framework -sequential dual filter (SDF) for the filtering of asynchronous measurements is studied. SDF having dual KFs constructs a sequential operating structure to compute the smoothed estimate of the state of an observed system. The performance comparison between SDF and classical R-T-S algorithm -forward backward filter (FBF) is researched with numerical experimentation. The smoother based on SDF can be suitably applied to an integrated navigation system (INS) to correct navigation information at every epoch using asynchronous measurements from digital TV broadcasting signals or other positioning sensors. The simulation results indicate the DTV/GPS integrated navigation system using SDF can be expected to achieve a high score in practical applications. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 1229370 |
| Page Count | 5 |
| File Format | |
| ISBN | 1424405882 |
| ISSN | 10915281 |
| DOI | 10.1109/IMTC.2007.379129 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-05-01 |
| Publisher Place | Poland |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Smoothing methods Navigation Digital TV Kalman filters Filtering algorithms State estimation Position measurement TV broadcasting Sensor systems Global Positioning System multisensor systems filtering smoothing methods Kalman filtering integrated navigation systems |
| Content Type | Text |
| Resource Type | Article |
| Subject | Instrumentation Electrical and Electronic Engineering |
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