RANSAC based robust localization algorithm for visual sensor network - Bo ZHANG; Hai-yong LUO; Ji-wei LIU; Fang ZHAO (Tongxin xuebao)
Due to node failures or environmental changes,observed data on the target will be error in visual sensor network,so the least squares based multi-vision localization algorithm won’t be accurate.A centralized RANSAC based robust localization method was proposed,which can remove the error data and improve the positioning accuracy.Furthermore,to address this issue,energy imbalance of network nodes in centralized RANSAC where all computing load is executed in one single node,a robust localization algorithm based on distributed RANSAC was also proposed,which can distribute a large number of iterative calculations into each node averagely to ensure the network balance on calculation and energy without affecting the robustness.Finally,through comparing experiments on no-RANSAC,cen-RANSAC and dis-RANSAC,it’s verified that this algorithm can obtain robust and good positioning results in a predetermined probability,and the time complexity was analyzed via experiment.