利用压缩感知与多边测量技术的无线传感器网络定位算法

针对传统无线定位算法的缺点，该文提出了运用接收信号强度参数，将压缩感知技术和多边测量方法相结合的无线传感器网络定位方法。首先将基于网格的目标定位问题转化为压缩感知问题，判断目标是否位于网格中心。对于目标不在网格中心的情况，再用多边测量方法进行目标的精定位，并采用了基于接收信号强度的基站选择策略克服环境因素对定位算法的影响。与传统压缩感知方法相比，该文算法克服了未知目标只能在网格中心定位的局限性，降低了算法的复杂度，拓宽了算法的应用领域。仿真结果表明:与现有定位算法相比，该文算法在定位性能和算法复杂度上都体现了巨大优势。 

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.