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Abstract
Node position information is critical in wireless sensor networks (WSN). However, existing positioning algorithms commonly have the issue of low positioning accuracy due to noise interferences in communication. Hence, proposed in this paper is an iterative positioning algorithm based on distance correction to improve the positioning accuracy of target nodes in WSNs, with contributions including (1) a log-distance distribution model of received signal strength indication (RSSI) ranging which is built and from which is derived a noise impact factor based on the model, (2) the initial position coordinates of the target node obtained using a triangle centroid localization algorithm, via which the distance deviation coefficient under the influence of noise is calculated, and (3) the ratio of the distance measured by the log-distance distribution model to the median distance deviation coefficient which is taken as the new distance between the target node and the anchor node. Based on the new distance, the triangular centroid positioning algorithm is applied to calculate the coordinates of the target node, after which the iterative positioning model is constructed and the distance deviation coefficient updated repeatedly to update the positioning result until the criteria of iterations are reached. Experiment results show that the proposed iterative positioning algorithm is promising and effectively improves positioning accuracy.
Highlights
Wireless sensor networks have been widely applied in indoor scenarios where satellite or cellular signals do not work properly, primarily in fields of defense, industry, and social life due to the networks’advantages of low power consumption, low cost, and self-organization [1]
Construction of the iterative positioning algorithm based on distance correction The distance deviation coefficient median is used as an iteration factor for the iterative positioning algorithm
The basic principle of the iterative positioning algorithm based on distance correction is as follows: the distance deviation coefficient is introduced to evaluate the degree of deviation of the distance measured by the log-distance distribution model and the triangle centroid positioning algorithm, respectively
Summary
Wireless sensor networks have been widely applied in indoor scenarios where satellite or cellular signals do not work properly, primarily in fields of defense, industry, and social life due to the networks’advantages of low power consumption, low cost, and self-organization [1]. Wireless sensor networks have been widely applied in indoor scenarios where satellite or cellular signals do not work properly, primarily in fields of defense, industry, and social life due to the networks’. Node position information is the key to whether the information obtained is valuable or not in the WSN-based Zigbee protocol, especially for target surveillance and tracking in the fields of military work and anti-terrorism [4,5,6,7]. Wireless signals are inevitably interfered with by noises such as multi-path fading [8,9], diffraction [10], antenna gain [11], and non-line of sight [12] when propagating in actual physical environments, and uncertain propagation loss is produced, resulting in inaccuracies in ranging. It is known that the maximum ranging error rate is up to ±50% [13]
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