This paper uses the measured atmospheric coherence length profile data of DCIM lidar to analyze the effect of different regularization parameter selection strategies on the inversion of atmospheric turbulence profile. The criterions of L-curve, generalized cross-validation(GCV), quasi-optimal are used respectively, The inversion results is evaluated by signal-tonoise ratio(SNR) and root mean square error(RMSE). The results show that the GCV criterion perform more stable for various measurements than L-curve and quasi-optimal criterion.
We develop differential column image motion (DCIM) lidar for monitoring atmosphere refractive structure constant Cn2 profile. It is important to use an appropriate regularization method for DCIM lidar since the ill-posedness of the integral equation between the Cn2 profile and the measured r0 profile. In this paper, three typical regularization methods are studied to retrieve the Cn2 profiles from r0 profiles.The experiments illustrate that the Tikhonov method and truncated SVD method perform good performance, while damped SVD shows poorer inversion accuracy.
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