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http://dx.doi.org/10.5370/KIEE.2014.63.11.1551

Asynchronous Sensor Fusion using Multi-rate Kalman Filter  

Son, Young Seop (Dept. of Electrical Engineering, Hanyang Universty, Korea and Global R&D Center, MANDO Corp.)
Kim, Wonhee (Dept. of Electrical Engineering, Dong-A University)
Lee, Seung-Hi (Div. of Electrical and Biomedical Engineering, Hanyang University)
Chung, Chung Choo (Div. of Electrical and Biomedical Engineering, Hanyang University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.63, no.11, 2014 , pp. 1551-1558 More about this Journal
Abstract
We propose a multi-rate sensor fusion of vision and radar using Kalman filter to solve problems of asynchronized and multi-rate sampling periods in object vehicle tracking. A model based prediction of object vehicles is performed with a decentralized multi-rate Kalman filter for each sensor (vision and radar sensors.) To obtain the improvement in the performance of position prediction, different weighting is applied to each sensor's predicted object position from the multi-rate Kalman filter. The proposed method can provide estimated position of the object vehicles at every sampling time of ECU. The Mahalanobis distance is used to make correspondence among the measured and predicted objects. Through the experimental results, we validate that the post-processed fusion data give us improved tracking performance. The proposed method obtained two times improvement in the object tracking performance compared to single sensor method (camera or radar sensor) in the view point of roots mean square error.
Keywords
Multi-rate; Kalman filter; Object vehicle tracking; Sensor fusion;
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