【摘要】 信噪条件会影响激光雷达低信噪比回波信号在时域上的相关性，导致信号识别结果准确性下降，对此，提出一种激光雷达低信噪比回波信号自适应识别方法。在低信噪比环境下，利用独立分量分析模型对低信噪比回波信号展开独立分量分析，分离出源回波信号和干扰信号，得到干扰抑制后的回波信号。采用短时傅里叶变换获取回波信号的时频谱图，通过时频谱图对改进SSD网络模型展开训练，以实现低信噪比回波信号自适应识别。仿真分析表明，所提方法在低信噪比回波信号自适应识别领域是可行性且有效性，能够有效提升激光雷达回波信号的可靠性。更多还原

【Abstract】 The signal-to-noise conditions can affect the temporal correlation of low signal-to-noise ratio LiDAR echo signals, leading to a decrease in the accuracy of signal recognition results.In this regard, a self-adaptive recognition method for low signal-to-noise ratio LiDAR echo signals is proposed.Firstly, under low signal-to-noise ratio environment, an independent component analysis model is used to perform independent component analysis on the low signal-to-noise ratio echo signal, separating the source echo signal and interference signal, and obtaining the echo signal after interference suppression.Then, using short-time Fourier transform to obtain the time-frequency spectrum of the echo signal, the improved SSD network model is trained through the time-frequency spectrum to achieve adaptive recognition of low signal-to-noise ratio echo signals.Simulation analysis shows that the proposed method is feasible and effective in the field of adaptive recognition of low signal-to-noise ratio echo signals, which can effectively improve the reliability of LiDAR echo signals.更多还原