Abstract

Since the sensor nodes are unevenly distributed, when the DV-Hop positioning algorithm counts the hop count, each hop with a different hop distance between the beacon nodes and the other nodes is considered to be equivalent, resulting in the calculated test metric. The node coordinates are quite inaccurate. In order to solve this error, a DV-Hop node localization algorithm based on received signal strength (RSSI) hops correction and improved artificial immune algorithm optimization is proposed. In this paper, firstly, the RSSI value received by the node is used to construct the correction coefficient to correct the hop count. On this basis, an improved artificial immune algorithm is introduced to improve the coordinates of the node to be measured by Gaussian mutation in the local search process. The Matlab simulation proves that compared with the original DV-Hop algorithm, the algorithm reduces the positioning error to different extents, improves the positioning accuracy, and improves the convergence speed.

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