移动条件下基于容积卡尔曼滤波的短波OFDM信道估计

针对移动短波通信场景下短波信道出现的时变性使得正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)系统不能精确估计信道状态信息导致通信质量下降的问题，提出了一种基于容积卡尔曼滤波(Cubature Kalman Filter,CKF)的信道估计方法。该方法基于球面径向积分准则，可更好地追踪信道的变化，提升信道估计的精度。建立了基于信道频域响应的非线性状态空间方程，并用容积卡尔曼滤波对每帧符号的信道频域响应进行估计。系统仿真结果表明，在静态短波通信场景到720 km/h的移动短波通信场景中，所提算法对信道有着更精确的估计精度，也可以有效抵抗多径时延所带来的影响。因此，所提算法更适用于移动短波通信场景。

HF OFDM Channel Estimation Based on Cubature Kalman Filter under Mobile Conditions

Because of time variation of shortwave channel in mobile shortwave communication,it is difficult to determine the channel state accurately by the orthogonal frequency division multiplexing(OFDM) system.To solve this problem,a channel estimation method based on the cubature Kalman filter(CKF) is proposed.Based on the spherical radial integration criterion,the method can better track channel changes and improve the accuracy of channel estimation.A nonlinear state-pace equation is established based on the channel frequency response and CKF is used to estimate the channel frequency response for each symbol.The system simulation results show that the proposed channel estimation algorithm based on CKF has higher accuracy than other algorithms in both static shortwave communication scenarios and mobile shortwave communication scenarios at speed up to 720 km/h,and can also combat the effects of multipath delay.Therefore,this algorithm is more suitable for the mobile shortwave communication scenario.