Distance outlier detection with a mobile beacon in wireless sensor networks localisation

Abstract

Range-based localisation algorithms rely on distance measurements between nodes. If outlier distances exist, they make the estimated positions deviate from the true positions. Thus, it is important to detect and remove outlier distance measurements to achieve high localisation accuracy. In this paper, we propose a novel outlier detection approach called middle distance mobile beacon placement MDMP. Different from the traditional triangle-inequality-based approach that can detect only the existence of outlier distances but cannot distinguish which measurements are outliers, MDMP can exactly find which distances are outliers and exclude them from the localisation process. This prevents nodes from getting wrong position estimates caused by these outlier measurements. Simulation results show that MDMP improves the outlier detection accuracy by identifying more outliers than the traditional triangle inequality violation TIV-based method does. The evaluation results also show remarkable improvement in location accuracy by deleting outliers with MDMP.