空间通信载波多普勒频偏捕获的两阶段稀疏算法  

Two-stage-sparse algorithm for carrier Doppler-shift acquisition in space communications

作　　者：张兆维 刘琳 刘慧 吴同 朱明蕾 潘甦[1] ZHANG Zhaowei;LIU Lin;LIU Hui;WU Tong;ZHU Minglei;PAN Su(School of Internet of Things,Nanjing University of Posts and Telecommunications,Nanjing 210003,China;State Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210023,China;School of Software Engineering,Jinling Institute of Technology,Nanjing 211169,China;School of Computer Engineering,Tongda College of Nanjing University of Posts and Telecommunications,Yangzhou 225127,China)

机构地区：[1]南京邮电大学物联网学院,江苏南京210003 [2]南京大学计算机软件新技术全国重点实验室,江苏南京210023 [3]金陵科技学院软件工程学院,江苏南京211169 [4]南京邮电大学通达学院计算机工程学院,江苏扬州225127

出　　处：《物联网学报》2024年第2期36-45,共10页Chinese Journal on Internet of Things

基　　金：国家自然科学基金项目(No.61801236);江苏省研究生科研与实践创新计划项目(No.SJCX23_0288);南京大学计算机软件新技术全国重点实验室资助项目(No.KFKT2024B41)。

摘　　要：在空间通信中,信号面临远距离传输和高动态相对运动,其中,远距离传输带来很低信噪比(SNR,signal-to-noise ratio),而高动态相对运动则引起载波高动态多普勒频偏。为解决低信噪比问题,传统捕获方法需要长时间累积很多接收信号。但是,在长时间累积过程中,高动态多普勒频偏会导致严重的能量扩散问题。针对上述问题,提出了一种两阶段稀疏(TSS, two-stage-sparse)算法来捕获载波多普勒频偏。该算法首先利用粗捕获结果构造粗稀疏搜索范围,然后选择若干个较大元素来构建精稀疏搜索范围,最后搜索最大元素作为捕获结果。由于稀疏范围仅覆盖很窄的频率区间,该算法能够滤除更多的噪声干扰,从而辅助信号元素成为最大元素。理论分析和仿真结果也表明,所提TSS算法能够显著提高多普勒频偏的捕获概率。In space communications,the signal faces long-distance transmission and a high-dynamic relative movement.The long-distance transmission results in a very low signal-to-noise ratio(SNR)and the high-dynamic relative movement causes a high-dynamic Doppler-shift on the carrier.To address the low SNR,the traditional acquisition method requires the long-time accumulation of many received signals.However,during the long-time accumulation,the high-dynamic Doppler-shift causes the serious energy dispersion problem.To solve the problem,a two-stage-sparse(TSS)algorithm was proposed to acquire the Doppler-shift.The proposed TSS algorithm firstly used the coarse acquisitions to construct a coarse sparse-search-range,then selected some large elements to construct a fine sparse-search-range,and finally searched the largest element as the acquisition result.Because the sparse-search-range only covers a narrow frequency range,the TSS algorithm excludes more noise elements,thus allowing the signal element to become the largest element.The theoretical analysis and simulation results show that the proposed TSS algorithm significantly increases the acquisition probability.

关 键 词：空间通信 低信噪比 高动态多普勒频偏 捕获 能量扩散 

分 类 号：TN929.5[电子电信—通信与信息系统]