基于RTI双重构的免携带设备目标无线定位

免携带设备定位是利用目标对无线通信链路产生的阴影衰落来估计目标的位置。针对现有算法定位精度有限、计算复杂度高等问题,在无线层析成像(radio tomographic imaging, RTI)的基础上提出了基于双重构的定位算法。该算法利用正则化快速重构的特点,首先对目标进行初步的定位;其次将粗定位区域进行像素精确划分,同时利用链路选择法减少链路个数,降低算法复杂度;最后提出补空间稀疏度自适应匹配重构算法,将目标位置转化为稀疏信号重构问题，完成定位。实验仿真结果表明,与基于RTI的单重构定位算法相比,所提双重构算法能达到较好的定位精度,且实时性更高。

Device-free localization based on RTI bi-reconstruction algorithm with wireless sensor networks

Device-free localization (DFL) is the estimation of target without carrying any electronic device by the shadow-fading of wireless communication links. However, current algorithms have some disadvantages of low positioning accuracy and large computation during positioning. A novel algorithm based on radio tomographic imaging(RTI), combining regularization and compressive sensing theory, called bi-reconstruction algorithm, is proposed to locate the target. The algorithm uses the characteristics of the fast reconstruction of regularization and first of all, it divides the location area into a plurality of grids to complete the initial positioning of the target. In order to achieve precise positioning, the possible location areas are divided into multiple small grids again, simultaneously the link selection method is used to decrease the number of links and reduce the algorithm complexity. Then, complementary sparsity adaptive matching pursuit (CMPs-SAMP) is adopted to locate the target and transform the localization problem to a sparse signal reconstruction problem. The simulation results show that the proposed bi reconstruction algorithm outperforms other single reconstruction algorithms.