UAVC: A New Method for Correcting Lidar Overlap Factors Based on Unmanned Aerial Vehicle Vertical Detection

A method to calibrate the overlap factor of Lidar is proposed, named unmanned aerial vehicle correction (UAVC), which uses unmanned aerial vehicles (UAVs) to detect the vertical distribution of particle concentrations. The conversion relationship between the particulate matter concentration and the aerosol extinction coefficient is inverted by the high-altitude coincidence of the vertical detection profiles of the UAV and Lidar. Using this conversion relationship, the Lidar signal without the influence of the overlap factor can be inverted. Then, the overlap factor profile is obtained by comparing the signal with the original Lidar signal. A 355 nm Raman-Mie Lidar and UAV were used to measure overlap factors under different weather conditions. After comparison with the Raman method, it is found that the overlap factors calculated by the two methods are in good agreement. The changing trend of the extinction coefficient at each height is relatively consistent, after comparing the inversion result of the corrected Lidar signal with the ground data. The results show that after the continuously measured Lidar signal is corrected by the overlap factor measured by this method, low-altitude aerosol information can be effectively obtained.

The Overlap Factor Model of Spin-Polarised Coupled Lasers

A general model for the dynamics of arrays of coupled spin-polarised lasers is derived. The general model is able to deal with waveguides of any geometry with any number of supported normal modes. A unique feature of the model is that it allows for independent polarisation of the pumping in each laser. The particular geometry is shown to be introduced via ’overlap factors’, which are a generalisation of the optical confinement factor. These factors play an important role in determining the laser dynamics. The model is specialised to the case of a general double-guided structure, which is shown to reduce to both the spin flip model in a single cavity and the coupled mode model for a pair of guides in the appropriate limit. This is applied to the particular case of a circular-guide laser pair, which is analysed and simulated numerically. It is found that increasing the ellipticity of the pumping tends to reduce the region of instability in the plane of pumping strength versus guide separation.

Experimental Calibration of the Overlap Factor for the Pulsed Atmospheric Lidar by Employing a Collocated Scheimpflug Lidar

Lidar techniques have been widely employed for atmospheric remote sensing during past decades. However, an important drawback of the traditional atmospheric pulsed lidar technique is the large blind range, typically hundreds of meters, due to incomplete overlap between the transmitter and the receiver, etc. The large blind range prevents the successful retrieval of the near-ground aerosol profile, which is of great significance for both meteorological studies and environmental monitoring. In this work, we have demonstrated a new experimental approach to calibrate the overlap factor of the Mie-scattering pulsed lidar system by employing a collocated Scheimpflug lidar (SLidar) system. A calibration method of the overlap factor has been proposed and evaluated with lidar data measured in different ranges. The overlap factor, experimentally determined by the collocated SLidar system, has also been validated through horizontal comparison measurements. It has been found out that the median overlap factor evaluated by the proposed method agreed very well with the overlap factor obtained by the linear fitting approach with the assumption of homogeneous atmospheric conditions, and the discrepancy was generally less than 10%. Meanwhile, simultaneous measurements employing the SLidar system and the pulsed lidar system have been carried out to extend the measurement range of lidar techniques by gluing the lidar curves measured by the two systems. The profile of the aerosol extinction coefficient from the near surface at around 90 m up to 28 km can be well resolved in a slant measurement geometry during nighttime. This work has demonstrated a great potential of employing the SLidar technique for the calibration of the overlap factor and the extension of the measurement range for pulsed lidar techniques.

Lidar Overlap Function Determination Using the Raman Lidar Signals

The determination of vertical distribution of optical properties of clouds and aerosols using the lidar system is affected by the incomplete overlap between the field of view of transmitter i.e. laser beam & the receiver in the near‐field range. Thus, the study of vertical profiles of aerosol optical properties in the lower atmosphere is erroneous without the correction of lidar overlap function. Here we have analysed the effect of overlap using a simple technique proposed by Ansmann and Wandinger to determine overlap function. We have determined the overlap factor for 5 different days of June 2016 and then calculated the mean overlap profile and determined the relative deviation of each day with respect to mean overlap factor. Results reveal that the complete overlap was achieved beyond 300 meters.

Increasing the Overlap Factor in the Elastic Model of a Modified Gear

Coupled and approximate gears are considered in this article. Methods of localization of the contact patch and the elimination of edge impact are analyzed. Based on the solution of the Hertz problem, mathematical models of gearing in the MathCAD program are constructed, with the help of which the overlap ratio of the gearing is calculated taking into account contact deformations. Circular and parabolic modifications for cylindrical spur gears are proposed. The allowed values of the modification parameters are determined. Contact stresses are equal to the allowable stresses when calculating multi-cycle fatigue. The influence of contact deformation on the load capacity of non-conjugate gears is analyzed.

Fuzzy Weighted Least Squares Support Vector Regression with Data Reduction for Nonlinear System Modeling

This paper proposes a fuzzy weighted least squares support vector regression (FW-LSSVR) with data reduction for nonlinear system modeling based only on the measured data. The proposed method combines the advantages of data reduction with some ideas of fuzzy weighted mechanism. It not only possesses the capability of illuminating local characteristic of the modeled plant but also can deal with the problem of boundary effects resulted from local LSSVR method when the modeled data is at the boundary of whole data subset. Furthermore, in comparison of the SVR, the proposed method only utilizes fewer hyperparameters to construct model, and the overlap factor λ can be chosen in relatively smaller value than SVR to further reduce more computational time. First of all, distilling the original input space into several regions with fuzzy partition by applying Gustafson-Kessel clustering algorithm (GKCA) is a foundation for data reduction and the overlap factor is introduced to reduce the size of subsets. Following that, those subset regression models (SRMs) which can be simultaneously solved by LSSVR are integrated into an overall output of the estimated nonlinear system by fuzzy weighted. Finally, the proposed method is demonstrated by experimental analysis and compared with local LSSVR, weighted SVR, and global LSSVR methods by using the index of computational time and root-mean-square error (RMSE).