Multi-target positioning for sensor network based on imaging strategy

In view of the multi-target positioning, this paper proposes a novel multi-target positioning method based on imaging strategy, which can overcome the solving difficulty, convergence problems, and the data association problem for multi-target. Since the sensor network is capable of receiving targets´ scattering information from different angles, we can transform the positioning problems in the geographic space into the peak value extracting in the imaging space by back projection algorithm. What´s more, given the sparse properties about the targets in the vast surveillance region and the layout of the sensors, one can reconstruct the multi-target and clear the false-target with the greed and clean algorithm. The performance of this positioning method is analyzed via a series of numerical experiments. We find that the positioning method can effectively capture the multiple targets without solving the non-linear equations.