Location-based Fingerprint Downhole Mobile Node Localization Algorithm

Abstract

Aiming at the problem that the wireless signal in coal mine is vulnerable to interference and the positioning accuracy of the node is low when moving, a positioning algorithm based on location fingerprint downhole mobile node is proposed. Firstly, based on the location fingerprint algorithm, the reference points with higher similarity are grouped, and KNN localization is performed respectively, and the position with large error is eliminated by the Grubbs criterion. Secondly, by generating a reasonable particle distribution and setting the particle collection method, the unscented particle filtering algorithm is improved, and the estimated position and state estimation are merged. The experimental results show that the algorithm of grouping KNN screening and improved unscented particle filtering algorithm improves the stability of the system and the positioning accuracy of the mobile node, and reduces the computational complexity of the algorithm.