Indoor Positioning Using Nonparametric Belief Propagation Based on Spanning Trees

• Nonparametric belief propagation (NBP) is one of the best-known methods for cooperative localization in sensor networks. It is capable of providing information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance measurement errors. However, the accuracy of NBP is questionable in loopy networks. Therefore, in this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST) created by breadth first search (BFS) method. In addition, we propose a reliable indoor model based on obtained measurements in our lab. According to our simulation results, NBP-ST performs better than NBP in terms of accuracy and communication cost in the networks with high connectivity (i.e., highly loopy networks). Furthermore, the computational and communication costs are nearly constant with respect to the transmission radius. However, the drawbacks of proposed method are a little bit higher computational cost and poor performance in low-connected networks.

Ämnesord

Engineering and Technology  (hsv)

Teknik och teknologier  (hsv)

Engineering and Technology  (hsv)

Electrical Engineering, Electronic Engineering, Information Engineering  (hsv)

Signal Processing  (hsv)

Teknik och teknologier  (hsv)

Elektroteknik och elektronik  (hsv)

Signalbehandling  (hsv)

Communication Systems  (hsv)

Kommunikationssystem  (hsv)

Nyckelord

belief propagation

spanning trees

cooperative localization

indoor positioning

breadth first search

loops