基于数据样本方差的正交频分复用水声通信多普勒频移估计方法

针对正交频分复用(OFDM)水声移动通信易受时变多普勒频移影响的缺点，该文提出一种基于数据样本方差的多普勒频移估计方法。利用前序符号的信道估计值恢复当前符号的有效数据序列及其频域分集副本，计算分集副本与数据序列的比值并搜索该比值序列在不同多普勒补偿因子下的方差，选取方差最小时对应的补偿因子作为多普勒频移估计值，利用稀疏贝叶斯学习和判决反馈信道估计算法获得修正后的信道频域响应并传递给后序符号，实现对多普勒频移的实时跟踪。数值仿真验证了该方法的可行性和优越性，海上试验证明，该方法实现了基于无人水下航行器的OFDM水声移动通信，能够对时变多普勒频移进行有效估计。

Doppler Frequency Shift Estimation Method for Orthogonal Frequency Division Multiplexing Underwater Acoustic Communication Based on Data Sample Variance

To overcome disadvantages of Orthogonal Frequency Division Multiplexing(OFDM) underwater acoustic mobile communication, a data variance-based Doppler frequency shift estimation method is proposed to estimate the time-varying Doppler shifts. The estimated channel response of previous OFDM symbol is utilized to recover the valid data sequence and its frequency-domain diversity. The variance of the ratio of data sequence and diversity copy are calculated under different Doppler compensation factors. Then the correct Doppler frequency shift factor is achieved by seeking the minimum of the variance. Sparse Bayesian learning and decision feedback channel estimation algorithm are used for calculating the revised channel frequency-domain response. The channel response is propagated to the follow-up symbol to track the time-varying Doppler shifts. The feasibility and superiority of the proposed method are verified by simulation. The sea trail demonstrates that the proposed algorithm can effectively estimate the Doppler shifts in underwater acoustic OFDM mobile communication for Unmanned Underwater Vehicle.