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首页> 外文期刊>IEEE sensors journal >A Kalman Filter-Based Blind Adaptive Multi-User Detection Algorithm for Underwater Acoustic Networks
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A Kalman Filter-Based Blind Adaptive Multi-User Detection Algorithm for Underwater Acoustic Networks

机译：基于卡尔曼滤波器的水下声网盲自适应多用户检测算法

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摘要

An underwater acoustic Kalman filter-based blind adaptive multi-user detection algorithm, suitable for underwater acoustic communication networks, is proposed in this paper. The algorithm can be employed to effectively improve the system capacity of multi-user communication in underwater acoustic sensor networks, reduce transmitting power and costs on power control, extend the multi-user communication distance, weaken or eliminate intersymbol interference, multiple access interference and near-far effect, thus effectively utilizing limited underwater frequency band resource. First, the dynamic model of underwater acoustic multi-user communication system and the optimal filter equation of the proposed algorithm are found. Second, computation complexity is analyzed, and convergence analysis is carried out in terms of excess mean output energy. Finally, pool, river, sea, and under-ice asynchronous communication experiments have been carried out for both the scalar and the vector hydrophones. Good experimental results verify the effectiveness of the proposed algorithm.
机译：提出了一种基于水声卡尔曼滤波的盲自适应多用户检测算法，适用于水声通信网络。该算法可有效提高水下声传感器网络中多用户通信的系统容量，降低发射功率和功率控制成本，延长多用户通信距离，减弱或消除符号间干扰，多址干扰和近距离干扰。远距离效应，从而有效利用有限的水下频段资源。首先，找到了水下声学多用户通信系统的动力学模型，并提出了该算法的最优滤波方程。其次，分析计算复杂度，并根据过剩的平均输出能量进行收敛分析。最后，已经针对标量和矢量水听器进行了池，河，海和冰下异步通信实验。良好的实验结果验证了该算法的有效性。

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