Source Localization Algorithm Based on Cultural Modified Quantum Particle Swarm Optimization Algorithm for Wireless Sensor Networks
Maximum Likelihood Estimation is often used in the acoustic source localization based on energy in wireless sensor network,which transform localization problem into global optimization problem of nonlinear function. This paper presents a Cultural Modified quantum particle swarm optimization algorithm( CMQPSO) to solve this nonlinear optimization problem. First,on the basis of the quantum particle swarm( QPSO),combined with adaptive the variability ideas and RSNTO algorithm,the modified quantum particle swarm optimization( MQPSO) was proposed. Then,in order to further improve the global search ability and calculation accuracy of the algorithm and according to the dual evolutionary mechanisms of the cultural algorithm,we integrated MQPSO algorithm into cultural algorithm framework to form a CMQPSO algorithm proposed in this paper. Simulation results demonstrate that CMQPSO algorithm can achieve robust convergence performance and better localization accuracy.