低信噪比高动态下基于卡尔曼滤波的码辅助载波同步算法  

Code-aided Carrier Synchronization Algorithm based on Kalman Filter at Low SNR and in High Dynamic Environment

作　　者：杨杰[1] 李广侠[1] 朱宏鹏 李飞龙 

机构地区：[1]解放军理工大学卫星通信重点实验室,江苏南京210007

出　　处：《通信技术》2017年第10期2167-2171,共5页Communications Technology

摘　　要：极低信噪比、高动态下的星地通信为卫星的小型化、移动化应用带来了可能,同时也对接收机同步特别对载波同步提出了更高要求。近年来,广泛研究的码辅助算法利用高增益编码特性,可在很少导频基础上利用译码反馈信息提高估计精度,但大部分算法建立在一帧中频偏恒定的假设,而对于动态较大的系统则不再适用,需要考虑反向结构。卡尔曼滤波以最小均方误差为准则解决最佳线性滤波问题,可以克服锁相结构带宽和动态的矛盾。因此,将Turbo码译码过程和卡尔曼滤波算法以迭代方式相结合,建立卡尔曼跟踪模型,给出了滤波跟踪算法。仿真结果表明,在低信噪比和一定动态下,所提算法可以较好地跟踪相位变化。Communications at very low signal-to-noise ratio（SNR） and in high-dynamic environment makes it possible for satellite miniaturization and mobile applications in the future.However,higher requirements for receiver synchronization,particularly for carrier synchronization,are put forward.In recent years,the widely-concerned code-aided algorithms,may improve the estimation performance at low SNR by using high-gain coding characteristics and a few pilot symbols.However,most of the algorithms are based on the assumption that the Doppler frequency is constant in one frame and no longer applicable to high dynamic system,so the closed-loop structure should be taken into consideration.Kalman filter,which could solve the problem of optimal linear filtering with minimum mean square error criterion,may overcome the contradiction of between bandwidth and dynamic in phase-locked structure.For this reason,the decoding process and the Kalman filtering algorithm are combined in iterative method,thus to establish the Kalman tracking model and at the same time,determine the filter tracking algorithm.Simulation results indicate that the proposed algorithm can track phase changes well at low signal-to-noise ratio（SNR） and in certain dynamic conditions.

关 键 词：低信噪比 高动态 卡尔曼滤波 编码辅助 同步 

分 类 号：TN911.7[电子电信—通信与信息系统]