A Distance Boundary with Virtual Nodes for the Weighted Centroid Localization Algorithm

Abstract

In wireless sensor networks, accurate location information is important for precise tracking of targets. In order to satisfy hardware installation cost and localization accuracy requirements, a weighted centroid localization (WCL) algorithm, which is considered a promising localization algorithm, was introduced. In our previous research, we proposed a test node-based WCL algorithm using a distance boundary to improve the localization accuracy in the corner and side areas. The proposed algorithm estimates the target location by averaging the test node locations that exactly match with the number of anchor nodes in the distribution map. However, since the received signal strength has large variability in real channel conditions, the number of anchor nodes is not exactly matched and the localization accuracy may deteriorate. Thus, we propose an intersection threshold to compensate for the localization accuracy in this paper. The simulation results show that the proposed test node-based WCL algorithm provides higher-precision location information than the conventional WCL algorithm in entire areas, with a reduced number of physical anchor nodes. Moreover, we show that the localization accuracy is improved by using the intersection threshold when considering small-scale fading channel conditions.

A New Distance Vector-Hop Localization Algorithm Based on Half-Measure Weighted Centroid

“…erefore, the cost of network construction can be reduced by using the algorithm. Hence, the authors proposed a new DV-Hop localization algorithm based on the half-measure weighted centroid [16].…”

Optimisation method with node selection and centroid algorithm in underwater received signal strength localisation

“…In order to improve the localisation accuracy, a weighted CL (WCL) method has been proposed [10, 11] that combines both CL and RSS. WCL improves the accuracy to an extent but we have identified that there exists two major deficiencies: (a) the accuracy deteriorates at the corners and sides of the geometric figure due to the centroid property [12] and (b) the localisation accuracy decreases significantly if an inappropriate node is selected. A number of improved weighted centroid algorithms are thus proposed to improve the localisation accuracy considering the first deficiency.…”

“…For instance, Kaur et al [13] proposed a localisation algorithm using weights that consider the influence of different factors such as the number of anchors, communication radius and nearest anchor to determine the position of the unknown node. While others used virtual concepts [12, 14–16] to improve the localisation accuracy. Kim and Shin [12] proposed a test node‐based WCL algorithm using a distance boundary to improve the localisation accuracy at the corner and side areas.…”

A Two-Stage Localization Scheme with Partition Handling for Data Tagging in Underwater Acoustic Sensor Networks

“…Underwater sensor networks (UWSNs) play a pivotal role in such studies by providing basic technical support for gathering, organizing, and reporting mission-critical data [7]. Besides some common characteristics between terrestrial and underwater sensor networks, such as large-scale deployment and energy constraints, UWSNs have some differences compared to their terrestrial counterparts [8,9,10]. For instance, unlike terrestrial sensor networks where radio waves are used as a medium of communication, UWSNs use acoustic waves predominantly [11,12].…”