基于可变遗忘因子RLS 算法的水下激光雷达回波提取

抑制水体后向散射并提高目标分辨率是水下激光雷达探测的关键技术。基于最小递归二乘法(RLS)提出了一种对回波信号自适应滤波的方法。通过分析水下激光雷达探测信号特点，改进了传统RLS 中的遗忘因子，使其不仅可以区分回波信号和后向散射，还能根据不同距离目标回波的幅值变化进行动态调整。为了验证效果，在船池中进行了不同目标距离的水下探测实验。实验结果表明，提出的可变遗忘因子RLS 算法可以有效抑制水体后向散射，在目标信号出现时算法具有较快的收敛速度和跟踪速度，使目标回波信号凸显。与传统方法相比较，处理后的目标分辨率大大提升，在微弱目标回波信号的提取方面优势明显。最后，讨论了算法中滤波器阶数对于处理结果的影响。

Abstract

The restraining of water backscattering and increasing target resolution are the key technologies in underwater lidar detection. An adaptive filtering method of target echo based on recursive least- squares (RLS) algorithm is proposed. Through the feature analysis of underwater lidar detected signal, the forgetting factor in traditional RLS algorithm is improved to distinguish the target echo and water backscattering signal. The improved forgetting factor can also adapt the echo amplitude changes in different target distances. To estimate the effect of the method, the underwater detection experiments are carried out in water basin under different target distances. The results show that the backscattering signals are suppressed and the target echo are extracted with high tracking and convergence speed by using the proposed variable forgetting factor RLS algorithm. Compared with the traditional methods, the resolution of the processed target echo signal is increased and the proposed method has great advantage in the weak target echo extraction. Finally, the impact of filter order on algorithm processing results is discussed.

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程藻, 夏珉, 李微, 郭文平, 曾宪江, 杨克成. 基于可变遗忘因子RLS 算法的水下激光雷达回波提取[J]. 激光与光电子学进展, 2016, 53(1): 010101. Cheng Zao, Xia Min, Li Wei, Guo Wenping, Zeng Xianjiang, Yang Kecheng. A Target Echo Extraction Method in Underwater Lidar System Based on Variable Forgetting Factor RLS Algorithm[J]. Laser & Optoelectronics Progress, 2016, 53(1): 010101.

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