Abstract
In the case of multi-sensors weighted data fusion with unknown prior knowledge, a weighted data fusion method based on measurement traversal correction is proposed. The fusion accuracy of multi-sensors data fusion is influenced by both the measurement data accuracy and the data fusion weights of sensors. The measurement data of sensors is corrected through analyzing the reliability of different time data measured by sensors. The fusion weights of multi-sensors data fusion are optimal through depply analyzing the influence of weight distribution on multi-sensors data fusion accuracy. Typical examples are used to validate the proposed fusion algorithm, and the result shows that the fusion result is satisfying, and the algorithm is theoretical and practical.
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