The performance of underwater acoustic communication system is affected seriously by inter-symbol interference caused by multipath effects. Therefore, a novel blind equalization algorithm based on constant modulus algorithm (CMA) and decision-directed least mean square (DD_LMS) is adopted to improve the equalization ability of the system. Firstly, the LMS algorithm is improved by introducing inverse hyperbolic sine function and three adjustment factors to control step-size and the appropriate parameter values are set through the simulation of three adjustment factors. Secondly, the error values of the step-size function are replaced with error expectations to improve the anti-noise performance. Finally, the improved step-size function is introduced into the CMA and DD_LMS algorithm and the difference of the iteration error of adjacent k times is used as the switching condition of the dual mode algorithm. The results show that the algorithm has good equalization and anti-noise performance at both high and low signal-to-noise ratio (SNR), especially at low SNR, its steady-state error is ~10 dB lower than the traditional CMA and its convergence speed is ~15% higher than the traditional CMA. This algorithm can be used to effectively improve the communication efficiency of the communication system of underwater robots, which has good application value.

中文翻译：

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水下声通信的新型CMA + DD_LMS盲均衡算法

多径效应引起的符号间干扰严重影响了水下声通信系统的性能。因此，采用了一种基于恒模算法（CMA）和决策平均最小均方（DD_LMS）的盲均衡算法，以提高系统的均衡能力。首先，通过引入反双曲正弦函数和三个调整因子来控制步长来改进LMS算法，并通过模拟三个调整因子来设置适当的参数值。其次，将步长函数的误差值替换为误差期望值，以提高抗噪性能。最后，将改进的步长函数引入到CMA和DD_LMS算法中，并将相邻步的迭代误差相加。k次用作双模式算法的切换条件。结果表明，该算法在高信噪比和低信噪比下均具有良好的均衡和抗噪性能，特别是在低信噪比时，其稳态误差比传统的CMA低约10 dB。收敛速度比传统的CMA高约15％。该算法可有效提高水下机器人通信系统的通信效率，具有良好的应用价值。