Blind denoising for LiDAR signal based on high dimensional eigenvalue analysis

Abstract

In this paper, we address the problem of blind denoising for laser detection and ranging equipment (LiDAR) based on estimating noise level from LiDAR pulse echo. We first provide rigorous statistical analysis on the eigenvalue distributions of a sample covariance matrix. Then we propose an interval-bounded estimator for noise variance in high dimensional setting. To this end, an effective blind denoising filtering method for LiDAR is devised based on the adaptive estimation noise level. The estimation performance of our method has been guaranteed both theoretically and empirically. The analysis and experiment results have demonstrated that the proposed algorithm can reliably infer true noise levels, and outperforms the relevant existing methods.

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