A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for Wireless Sensor Networks

Wireless sensor networks (WSNs) are applied in many fields, among which node localization is one of the most important parts. The Distance Vector-Hop (DV-Hop) algorithm is the most widely used range-free localization algorithm, but its localization accuracy is not high enough. In this paper, to solve this problem, a hybrid localization algorithm for an adaptive strategy-based distance vector-hop and improved sparrow search is proposed (HADSS). First, an adaptive hop count strategy is designed to refine the hop count between all sensor nodes, using a hop count correction factor for secondary correction. Compared with the simple method of using multiple communication radii, this mechanism can refine the hop counts between nodes and reduce the error, as well as the communication overhead. Second, the average hop distance of the anchor nodes is calculated using the mean square error criterion. Then, the average hop distance obtained from the unknown nodes is corrected according to a combination of the anchor node trust degree and the weighting method. Compared with the single weighting method, both the global information about the network and the local information about each anchor node are taken into account, which reduces the average hop distance errors. Simulation experiments are conducted to verify the localization performance of the proposed HADSS algorithm by considering the normalized localization error. The simulation results show that the accuracy of the proposed HADSS algorithm is much higher than that of five existing methods.