A Reduced-Complexity Data-Fusion Algorithm Using Belief Propagation for Location Tracking in Heterogeneous Observations


This paper presents a low-complexity and high-accuracy algorithm to reduce the computational load of the traditional data-fusion algorithm with heterogeneous observations for location tracking. For the location-estimation technique with the data fusion of radio-based ranging measurement and speed-based sensing measurement, the proposed tracking scheme… (More)
DOI: 10.1109/TCYB.2013.2276749

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