Dynamic Ring Structure Based Target Localization Algorithm in Wireless Sensor Networks

Author(s):  
Yu Pan ◽  
Qianqian Ren ◽  
Jinbao Li ◽  
Hu Jin
Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4455
Author(s):  
Seyoung Kang ◽  
Taehyun Kim ◽  
Wonzoo Chung

All existing hybrid target localization algorithms using received signal strength (RSS) and angle of arrival (AOA) measurements in wireless sensor networks, to the best of our knowledge, assume a single target such that even in the presence of multiple targets, the target localization problem is translated to multiple single-target localization problems by assuming that multiple measurements in a node are identified with their originated targets. Herein, we first consider the problem of multi-target localization when each anchor node contains multiple RSS and AOA measurement sets of unidentified origin. We propose a computationally efficient method to cluster RSS/AOA measurement sets that originate from the same target and apply the existing single-target linear hybrid localization algorithm to estimate multiple target positions. The complexity analysis of the proposed algorithm is presented, and its performance under various noise environments is analyzed via simulations.


Author(s):  
Amirhosein Hajihoseini ◽  
Seyed Ali Ghorashi

<p>Localization is an important issue for wireless sensor networks. Target localization has attracted many researchers who work on location based services such as navigation, public transportation and so on. Localization algorithms may be performed in a centralized or distributed manner. In this paper we apply diffusion strategy to the Gauss Newton method and introduce a new distributed diffusion based target localization algorithm for wireless sensor networks. In our proposed method, each node knows its own location and estimates the location of target using received signal strength. Then, all nodes cooperate with their neighbors and share their measurements to improve the accuracy of their decisions. In our proposed diffusion based algorithm, each node can localize target individually using its own and neighbor’s measurements, therefore, the power consumption decreases. Simulation results confirm that our proposed method improves the accuracy of target localization compared with alternative distributed consensus based target localization algorithms.  Our proposed algorithm is also shown that is robust against network topology and is insensitive to uncertainty of sensor nodes’ location.</p>


2015 ◽  
Vol 10 (10) ◽  
pp. 1062
Author(s):  
A. Mesmoudi ◽  
Mohammed Feham ◽  
Nabila Labraoui ◽  
Chakib Bekara

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 380-399
Author(s):  
Jiaxing Chen ◽  
Wei Zhang ◽  
Zhihua Liu ◽  
Rui Wang ◽  
Shujing Zhang

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