基于正交字典的全反馈信道函数估计

Channel function estimation using full feedback structure andorthogonal dictionary

为解决传统均衡算法和匹配算法在低信噪比情况下水声稀疏信道估计准确率低和计算量大的问题,提出一种基于正交字典的全反馈信道函数估计方法。通过信道参数估计公式分析,当训练序列与信道函数分量卷积构成正交字典集时,利用匹配算法便可获得最佳匹配结果,结合全反馈结构将信道参数反馈迭代计算,用数学归纳法证明该结构可进一步提高信道函数估计准确率。仿真结果表明,在低信噪比条件下,相比均衡类算法和匹配类算法,提出的信道估计算法可获得更高的估计准确率,具有更低的时间复杂度。

To solve the problems of low accuracy and large amount of calculation of underwater acoustic sparse channel estimation of traditional equalization and matching algorithms under the condition of low signal-to-noise ratio,a full feedback channel function estimation method based on orthogonal dictionary was proposed.The channel parameter estimation formula was adopted,when the training sequence and the channel function components were convolved to form an orthogonal dictionary set,the best matching result was obtained using the matching algorithm,and the channel parameters were iteratively calculated in combination with the full feedback structure,and the structure was further proved to be able to improve the channel function estimation accuracy by mathematical induction.The simulation results show that under the condition of low signal-to-noise ratio,compared with the equalization algorithm and the matching algorithm,the proposed channel estimation algorithm can obtain higher estimation accuracy and lower time complexity.