Data Fusion of Multi Model with One Sensor
In this letter, a novel data fusion method, called the single sensor data fusion filter (SSDFF) was proposed. It differed from the existed multi sensor fusion algorithms. In the proposed SSDFF, a new process model using polynomial predictive filter by expanding the dimension of the state, was firstl...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IFSA Publishing, S.L.
2013-06-01
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| Series: | Sensors & Transducers |
| Subjects: | |
| Online Access: | http://www.sensorsportal.com/HTML/DIGEST/june_2013/Special%20Issue/P_SI_388.pdf |
| Summary: | In this letter, a novel data fusion method, called the single sensor data fusion filter (SSDFF) was proposed. It differed from the existed multi sensor fusion algorithms. In the proposed SSDFF, a new process model using polynomial predictive filter by expanding the dimension of the state, was firstly constructed. Then the local estimation results based on the original model and the proposed model were fused to get the global estimation. It was shown that the new process model could be presented whether the original state transition density was known exactly or not and the fusion result was better than the local ones. The demonstration results verified the effectiveness of the proposed method. |
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| ISSN: | 2306-8515 1726-5479 |