Cooperative Multi-Vehicle Localization Using Split Covariance Intersection Filter

Hao Li

doi:10.1109/MITS.2012.2232967

Cooperative Multi-Vehicle Localization Using Split Covariance Intersection Filter

2013-01-01

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AI

DOI：10.1109/MITS.2012.2232967

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Abstract

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Vehicle localization (ground vehicles) is an important task for intelligent vehicle systems and vehicle cooperation may bring benefits for this task. A new cooperative multi-vehicle localization method using split covariance intersection filter is proposed in this paper. In the proposed method, each vehicle maintains an estimate of a decomposed group state and this estimate is shared with neighboring vehicles; the estimate of the decomposed group state is updated with both the sensor data of the ego-vehicle and the estimates sent from other vehicles; the covariance intersection filter which yields consistent estimates even facing unknown degree of inter-estimate correlation has been used for data fusion. A comparative study based simulations demonstrate the effectiveness and the advantage of the proposed cooperative localization method.

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Cooperative Multi-Vehicle Localization Using Split Covariance Intersection Filter

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