A complex optical system used in polarization lidars often modifies the input polarization of the return signal so that it may significantly impact depolarization estimates and introduce errors to polarization lidar measurements. In most cases, retardation, depolarization, and misalignment of the system exist at the same time and interact with each other. Polarization effects of the system cannot be represented by a simple correction coefficient, so they cannot be removed using a traditional calibration method. Detailed analysis and correction technologies were provided to remove systematic biases in estimating depolarization values from a polarization lidar owing to multiple optical components. The Mueller matrices from an emitter to a receiver were calculated, and the expression for an aerosol depolarization parameter including system polarization effects was derived and obtained. In addition, the correction algorithm based on the Mueller matrix was introduced and provided. A polarization lidar was established, and the polarization characteristics of its optical components were measured with a laboratory ellipsometer; then, the Mueller matrix of the receiver was calculated and obtained. Lidar observations were performed, and our correction algorithm was applied to lidar field data. The results show that the correction method can significantly remove systematic polarization effects.

The use of Raman and high-spectral lidars enables measurements of a stratospheric aerosol extinction profile independent of backscatter, and a multi-wavelength (MW) lidar can obtain additional information that can aid in retrieving the microphysical characteristics of the sampled aerosol. The inversion method for retrieving aerosol particle size distributions and microphysical particle parameters from MW lidar data was studied. An inversion algorithm for retrieving aerosol particle size distributions based on the regularization method was established. Based on the inversion of regularization, the inversion method was optimized by choosing the base function closest to the aerosol distribution. The logarithmic normal distribution function was selected over the triangle function as the base function for the inversion. The averaging procedure was carried out for three main types of aerosol. The 1% averaging result near the minimum of the discrepancy gave the best estimate of the particle parameters. The accuracy and stabilization of the optimized algorithm for microphysical parameters were tested by scores of aerosol size distributions. The systematic effects and random errors impacting the inversion were also considered, and the algorithm was tested by the data, showing 10% systematic error and 15% random error. At the same time, the reliability of the proposed algorithm was also verified by using the aerosol particle size distribution data of the aircraft. The inversion results showed that the algorithm was reliable in retrieving the aerosol particle size distributions at vertical heights using lidar data.In the last 20 years, research has been performed on solving the underlying inverse integral equation system for obtaining the microphysical parameters of aerosol particles from their optical properties. The regularization algorithm [6], the principal component analysis (PCA) technique [13], and the linear estimation algorithm [14] have been used for determining the aerosol bulk properties. The regularization algorithm is used most commonly for inverting multi-wavelength measurements [6], allowing the retrieval of particle size, concentration, and to some extent the main features of the particle size distribution.Using the regularized inversion algorithm, the particle size distribution and microphysical parameters of aerosols are obtained without assuming the initial complex refractive index and aerosol distribution. The inversion results are unstable, and there will be good results under certain spectral types; however, in some cases, the inversion error is very large. In Veselovskii's modified regularized inversion algorithm [15,16], the effective radius, number, surface area, and volume concentration for three distributions were retrieved with an average accuracy of 55%, 70%, 40%, and 50%, respectively. D. analyzed the effects of systematic and random errors on particle microphysical properties from multi-wavelength lidar measurements using an inversion with regularization. Three ASDs were used for this analys...

Telescopes in polarization lidar often modify the input polarization of the return signal, such that the telescope may significantly impact the depolarization estimates of aerosol and introduce error to the polarization lidar measurements. The error cannot be corrected by a traditional calibration constant. We present a method to correct the polarization effect of the telescope. We analyze the polarization effect of a telescope on the basis of the Mueller formalism, and introduce an algorithm for correcting the depolarization parameter of aerosol. A Newton telescope and a Cassegrain telescope are often chosen as the receiver in lidar. Their polarization models are established, and the Mueller matrices are calculated. The components of these matrices are dependent on wavelength, incident angle of the incoming light, and surface properties. The polarization impact of the telescope in lidar can be calibrated by a parameter, and the effects of different telescopes are discussed. The polarization crosstalk induced by the Newton telescope is obvious. The depolarization parameters change greatly with coating and wavelength, and they are calculated and presented. Whereas the crosstalk of a Cassegrain telescope is much smaller, the error can reach the level of 10 −3 and can be negligible. The method presented in this paper could also be upgraded by taking into account all of the optical devices instead of only the telescope.

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Lidar is an active remote sensing instrument, and it has been widely used in the detection of atmospheric environmental parameters and meteorological parameters. In recent years, climate change has been widely concerned by the public, and the corresponding atmospheric detection technology has also been developed rapidly. Atmospheric Lidar has been developed rapidly in China, and has achieved good research achievements. The research progress and development status of Lidar for atmospheric detection in recent years are introduced and summarized in this invited paper. The advantages and disadvantages of all kinds of atmospheric detection Lidars and their applications in different detection objects are comprehensively introduced in this article. Finally, the bottlenecks of Lidar technology are summarized, and the development trend of Lidar is also prospected.

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