An Efficient TDOA and GROA Localization Mechanism Based on GSO Algorithm with Flight Theory

10.3966/199115992017102805002

Dong-yao Zou；Bi-wei Liu；Wei Yang

flight mechanism ； gain ratios of arrival (GROA) ； glowworm swarm optimization (GSO) ； least squares ； particle swarm optimization (PSO) ； time differences of arrival (TDOA)

電腦學刊

28卷5期（2017 / 10 / 01）

11 - 25

英文

The positioning technology is of vital importance in Wireless Sensor Networks (WSNs), and its accuracy based on particle swarm optimization (PSO) is low. We propose an efficient time differences of arrival (TDOA) and gain ratios of arrival (GROA) localization algorithm with glowworm swarm optimization algorithm based on flight mechanism (Levy- GSO) for WSN in this paper. First, an improved positioning equation is introduced based on TDOA and GROA positioning model. And solve the equation by using correction two-step weighted least squares source localization method (TSWLS). To solve the nonlinear relationship between positioning equation and the target location by introducing the auxiliary variable and doing pseudo linear operation of nonlinear equation. Second, develop the GSO algorithm with flight mechanism to find the optimal solution under the same convergence speed and precision. Finally, test the proposed algorithm performance of ranging error, the number of reference nodes, Gaussian random variable variance and the root mean square error(RMSE). The simulation results indicate that the proposed localization mechanism has relative higher and stable localization accuracy compared with TDOA algorithm.