Name
Title | ||
|---|---|---|
A New Fusion Estimation Method for Multi-Rate Multi-Sensor Systems With Missing Measurements. |
Abstract | ||
|---|---|---|
A new fusion strategy is introduced in this article to estimate state for multi-rate multi-sensor systems with missing measurements. N sensors, which possess various sampling rates, render the measurements. Missing measurements with a certain probability pattern are also investigated. For these types of systems, Multi-rate Kalman filters are designed to estimate a target position at various sampling rates. Next, Ordered Weighted Averaging (OWA) operator is utilized to integrate multi-rate Kalman filters and improve the estimation quality. A new fusion strategy based on a real covariance matrix is introduced for updating the weighting factors, and proof of convergence is granted. Simulation studies on a tracking system verify the superior performance of the proposed fusion strategy in comparison with the Kalman filter, the multi-rate Kalman filters, and also the previous fusion methodology. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ACCESS.2020.2979222 | IEEE ACCESS |
Keywords | DocType | Volume |
Multi-rate Kalman filter,estimation,sensor data fusion,missing measurements,OWA operator | Journal | 8 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mojtaba Kordestani | 1 | 16 | 6.82 |
| Maryam Dehghani | 2 | 12 | 5.96 |
| Behzad Moshiri | 3 | 0 | 0.34 |
| Mehrdad Saif | 4 | 334 | 48.75 |