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Improved Recursive DV-Hop Localization Algorithm with RSSI Measurement for Wireless Sensor Networks
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As localization represents the main backbone of several wireless sensor networks applications, several localization algorithms have been proposed in the literature. There is a growing interest in the multi-hop localization algorithms as they permit the localization of sensor nodes even if they are several hops away from anchor nodes. One of the most famous localization algorithms is the Distance Vector Hop (DV-Hop). Aiming to minimize the large localization error in the original DV-Hop algorithm, we propose an improved DV-Hop algorithm in this paper. The distance between unknown nodes and anchors is estimated using the received signal strength indication (RSSI) and the polynomial approximation. Moreover, the proposed algorithm uses a recursive computation of the localization process to improve the accuracy of position estimation. Experimental results show that the proposed localization technique minimizes the localization error and improves the localization accuracy.
Title: Improved Recursive DV-Hop Localization Algorithm with RSSI Measurement for Wireless Sensor Networks
Description:
As localization represents the main backbone of several wireless sensor networks applications, several localization algorithms have been proposed in the literature.
There is a growing interest in the multi-hop localization algorithms as they permit the localization of sensor nodes even if they are several hops away from anchor nodes.
One of the most famous localization algorithms is the Distance Vector Hop (DV-Hop).
Aiming to minimize the large localization error in the original DV-Hop algorithm, we propose an improved DV-Hop algorithm in this paper.
The distance between unknown nodes and anchors is estimated using the received signal strength indication (RSSI) and the polynomial approximation.
Moreover, the proposed algorithm uses a recursive computation of the localization process to improve the accuracy of position estimation.
Experimental results show that the proposed localization technique minimizes the localization error and improves the localization accuracy.
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