Wireless Sensor Network Location Algorithm using Compressive Sensing and Multilateral Measurements

This thesis is mainly focused on the disadvantages of the traditional algorithm in the wireless location. Using the parameters of the received signal strength, we propose a wireless sensor networks positioning method combining compressed sensing technology with multilateral measurement method. Firstly, we transform grid-based targeting issues into compressed sensing technology, and determine whether the target is located in the center of the grid. If the target is not in the center of the grid, we adopt multilateral measurement method for accurate positioning of the target and overcome the effects of environmental factors on the positioning algorithm by using the station selection strategy of based on received signal strength. Compared with the traditional compressed sensing methods, this algorithm can overcome the limitations of an unknown target which can only be located in the center of grid, reduce the complexity of the algorithm and widen the application fields. Emulation results demonstrated that the localization performance and complexity of the algorithm we proposed have a huge advantage in comparison with the existing location algorithm.