Polarization lidar: an extended three-signal calibration approach

Blind Signal Separation Using an Extended Infomax Algorithm

The Infomax algorithm is a popular method in blind source separation problem. In this article an extension of the Infomax algorithm is proposed that is able to separate mixed signals with any sub- or super-Gaussian distributions. This ability is the results of using two different nonlinear functions and new coefficients in the learning rule. In this paper we show how we can use the distribution...

Blind Signal Separation Using an Extended Infomax Algorithm

The Infomax algorithm is a popular method in blind source separation problem. In this article an extension of the Infomax algorithm is proposed that is able to separate mixed signals with any sub- or super-Gaussian distributions. This ability is the results of using two different nonlinear functions and new coefficients in the learning rule. In this paper we show how we can use the distribution...

Lidar Calibration Centre

This paper presents the newly established Lidar Calibration Centre, a distributed infrastructure in Europe, whose goal is to offer services for complete characterization and calibration of lidars and ceilometers. Mobile reference lidars, laboratories for testing and characterization of optics and electronics, facilities for inspection and debugging of instruments, as well as for training in goo...

Polarization in Lidar

Polarization Diversity Lidar (pdl) Development

As reviewed at the start of the ARM Program (Sassen 1991), polarization lidar techniques have unique cloudsensing capabilities, particularly with regard to the unambiguous discrimination of cloud phase and acx:urate determination of cloud boundaries. Various polarization techniques had not been systematically evaluated in the field, but such evaluations could now be facilitated by modern lidard...