A DV-Hop positioning algorithm based on the glowworm swarm optimisation of mixed chaotic strategy

DV-Hop, as a typical location algorithm without ranging, is widely used in node localisation of wireless sensor networks. However, in the third phase of DV-Hop, a least square method is used to solve the nonlinear equations. Using this method to locate the unknown nodes will produce large coordinates errors, poor stability of positioning accuracy, low location coverage and high energy consumption. An improved localisation algorithm based on hybrid chaotic strategy (MGDV-Hop) is proposed in this paper. Firstly, a glowworm swarm optimisation of hybrid chaotic strategy based on chaotic mutation and chaotic inertial weight updating (MC-GSO) is proposed. Then, MC-GSO is used to replace the least square method in estimating node coordinates. By establishing the error fitness function, the linear solution of coordinates is transformed into a two-dimensional combinatorial optimisation problem. Simulation results show that the average location error is reduced, while the location coverage is increased and the energy consumption is decreased.