基于稀疏重构的TOA定位估计算法  

Time-of-arrival positioning estimation algorithm based on sparse reconstruction

作　　者：胡进峰[1] 谢浩 李朝海[1] 李会勇[1] 谢菊兰[1] HU Jinfeng;XIE Hao;LI Chaohai;LI Huiyong;XIE Julan(School of Electronic Engineering, University of Electronic Science and Technology of China,Chengdu 611731, China)

机构地区：[1]电子科技大学电子工程学院,四川成都611731

出　　处：《系统工程与电子技术》2018年第4期746-750,共5页Systems Engineering and Electronics

基　　金：国家自然科学基金(61371184;61671137;61731006);四川省科技厅项目(2017GZ0344)资助课题

摘　　要：目标在定位空间中具有稀疏特性,基于该特点提出了一种稀疏重构的时延定位算法;已有的来波到达时间(time-of-arrival,TOA)算法大部分只利用了单次TOA进行估计,其定位结果受噪声影响较大,因此进一步提出对多样本的到达时间进行联合估计,从而提高算法对噪声的稳健性,并提高算法的定位精度。与已有算法相比,所提算法的优点是定位精度更高,对噪声有更强的稳健性。仿真结果验证了所提算法的有效性。Based on the feature that the targets are sparse in space,a positioning algorithm based on sparse reconstruction is proposed.Most of the existing time-of-arrival(TOA)algorithms use only one sample to estimate targets and they are sensitive to noise.The multi-sample joint estimation algorithm is further proposed to improve the noise robustness and the positioning accuracy of the algorithm.Compared with the existing algorithms,the proposed algorithm has a higher positioning accuracy and stronger noise robustness.Simulation results demonstrate the effectiveness of the proposed algorithm.

关 键 词：到达时间 稀疏重构 贝叶斯准则 多样本 

分 类 号：TN957[电子电信—信号与信息处理]