Improved hybrid node localization using the wild horse optimization in the underwater environment

This paper introduces an improved DV-hop-based localization technique to solve the link failure problem without using extra hardware during the continuous localization process because of the uncertainty of the underwater channel, limited energy resources, and technical glitches. On the other hand, low accuracy and poor stability are the main problems of the traditional DV-hop technique. This paper also introduces a hybrid TDoA-DV hop algorithm to overcome these problems and evaluate the position of the target nodes. In this algorithm, the average hop distance is replaced with improved hop distance to suppress the hop distance error, and the Wild Horse Optimization (WHO) algorithm is used for position estimation to find out the best and fast optimum location of the target node and achieve better accuracy and stability. The experimental result of the proposed work is compared to existing works, including the traditional DV-hop, improved DV-hop, and improved shortest path +PSO. The simulation result shows that the proposed method improves the average accuracy by 67.9%, 56.24%, and 3.6%, and stability by 61.9%, 45.9%, and 5.15% approximately. The recommended technique is useful for localization in any static ad-hoc wireless or underwater sensor network due to its better accuracy and stability.