DV-Hop Localization Algorithm based on Improved Differential Evolution

Aiming at the shortcomings of the traditional DVHop algorithm in the node localization problem, we proposed a DV-Hop localization algorithm (IDEDV-Hop) with improved differential evolution. IDEDV-Hop utilizes the improved differential evolution to replace the least squares method for location estimation, and adaptively adjusts the crossover rate and mutation rate in a nonlinear manner, enabling the population can determine the probability of crossover and the degree of mutation according to the advantages and disadvantages of the current state, so as to reduce the error of node localization. Experimental results demonstrate that the localization error of IDEDV-Hop has been significantly reduced, and the localization accuracy has been improved by nearly 40% compared with DVHop. In addition, the proposed method demonstrates the state-of art performance under different communication radius of nodes, different anchor node ratios, and other restrictions.