Asymmetric Event-Driven Localization Algorithm in Constrained Space

Abstract

Existing technologies are inapplicable to localization in constrained space, especially when considering environmental factors. These methods with low localization accuracy cannot meet the location requirements in constrained space, for they usually call for lots of computation time and process resources. Moreover, they are easily interfered by environmental factors and attacks from other users. Consequently, in order to improve location accuracy in constrained space, an asymmetric event-driven localization algorithm (AELA) is proposed in this paper, which is based on the combination of event distribution and anchor node achieving a distributed location estimation strategy, so that it can satisfy the localization requirement of constrained space and achieve the high-accuracy localization with a small amount of events and anchor nodes. Meanwhile, to improve the accuracy of the algorithm, a set of candidate events are adopted to prune the event which does not meet location accuracy requirements. We finally perform experiments in indoor corridors, and the results show that the proposed algorithm has higher performances not only on localization accuracy and energy consumption but also on anti-interference ability than RSSI and MSP.