Adaptive Cuckoo Optimization DV-HOP Localization Algorithm Based on Multi-Communication Radius and Error Correction

An adaptive cuckoo optimization DV-HOP localization algorithm based on multi-communication radius and error correction （MEACS-D）is proposed, aiming at addressing the problem of lager error in wireless sensor networks of range-free DV-HOP algorithms. Using the anchor nodes, which have the ability to broadcast multi-communication radius messages, and to decimalize a counted number of hops （to reduce error caused by different jump lengths）, the virtual intersecting circle geometric method was used to calculate the distance between unknown nodes and anchor nodes in one hop. When the unknown node was used to select the average jump distance, consideration was given to adding each anchor node weight to reduce error. To calculate the node coordinates in order to improve the localization accuracy, the cuckoo algorithm with adaptive search step was introduced instead of the maximum likelihood estimation method. In simulation, by varying the values for the anchor nodes, communication radius, and total node, the localization error of the MEACS-D algorithm was reduced by 39.7% and 10.6%, compared to the DV-HOP algorithm and the original cuckoo DV-HOP （CS-D） algorithm, respectively. These results confirm that the MEACS-D algorithm can reduce the localization error effectively.