Noise reduction in lidar signal based on discrete wavelet transform

Abstract Lidar is an efficient tool for remotely monitoring targets or objects, but the effective range is often limited by signal-to-noise ratio (SNR). The reason is that noises or interferences always badly affect the measured results. So, to detect the weak signals buried in noises is a fundamental and important problem in the Lidar systems. It has been found that digital filters are not suitable for processing Lidar signals in noises, while the wavelet transform is an efficient tool for signal analysis in time–frequency domain that is very sensitive to the transient signals. In this paper, we propose a new method of the Lidar signal acquisition based on discrete wavelet transform (DWT). This method can significantly improve the SNR so that the effective measured range of Lidar is increased. The performance for our method is investigated by detecting the simulating and real Lidar signals in white noise. To contrast, the results of Butterworth filter, which is a kind of finite impulse response (FIR) filter, are also demonstrated. Finally, the experimental results show that our approach outperforms the traditional methods.