高动态场景下频率估计器的设计与实现  

Design and Implementation of Frequency Estimator in High Dynamic Scenes

作　　者：税敏 苏泳涛[2,3] 曹欢 SHUI Min;SU Yong-tao;CAO Huan(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China;Beijing Key Laboratory of Mobile Computing and Pervasive Device,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065 [2]中国科学院计算技术研究所无线通信技术研究中心,北京100190 [3]移动计算与新型终端北京市重点实验室,北京100190 [4]中国科学院大学,北京100190

出　　处：《通信技术》2019年第1期239-245,共7页Communications Technology

基　　金：北京市科技计划项目(No.Z171100005217001)~~

摘　　要：针对卫星移动通信系统中高动态场景下频偏估计算法复杂度高和频偏捕获范围小的问题,设计了一种高动态场景下的频率估计器,并提出了经过优化的两级级联频偏估计算法。采用优化的M&M算法对大频偏进行捕获,并采用改进的ML估计算法对残余频偏进行补偿。同时,针对高动态场景下存在高阶多普勒频移变化率的问题,以扰动的形式对变化率引起的频偏进行模拟。粗估计基于最佳符号间隔优化算法复杂度,细估计利用Kay算法思想扩大算法估计范围。最后,MATLAB仿真结果表明,基于优化算法的频率估计器具有较低的复杂度、较高的精度和稳定的性能。Aiming at the high complexity of frequency offset estimation algorithm and small frequency offset acquisition range in high dynamic scenes in satellite mobile communication system, a frequency estimator in high dynamic scene is designed and an optimized two-stage cascaded frequency offset estimation algorithm is proposed. The optimized M&M algorithm is used to capture the large frequency offset, and the improved ML estimation algorithm is used to compensate the residual frequency offset. At the same time, for the problem of high-order Doppler shift rate of change in high dynamic scenes, the frequency offset caused by the rate of change is simulated in the form of disturbance. The rough estimation is based on the optimal symbol interval to optimize the algorithm complexity, and the fine estimation uses the Kay algorithm to expand the estimation range of the algorithm. Finally, the MATLAB simulation results indicate that the frequency estimator based on the optimization algorithm has lower complexity, higher precision and stable performance.

关 键 词：卫星移动通信 高动态场景 粗频率估计 细频率估计 

分 类 号：TN927.23[电子电信—通信与信息系统]