Title :
Adaptive filter applications to LIDAR: return power and log power estimation
Author :
Lainiotis, Demetrios G. ; Papaparaskeva, Paraskevas ; Kothapalli, Giri ; Plataniotis, Kostas
Author_Institution :
Intelligent Syst. Technol., Melbourne Beach, FL, USA
fDate :
7/1/1996 12:00:00 AM
Abstract :
The problem of estimating the return power in a LIDAR system in the presence of multiplicative noise (speckle) is addressed. A significant class of the partitioning approach is applied and comparisons are made with the extended Kalman filter (EKF) in the case where model parameter uncertainty exists. Through extensive simulations, the partitioned filter is shown to be significantly superior to the EKF algorithm
Keywords :
adaptive signal processing; atmospheric techniques; geophysical signal processing; oceanographic techniques; optical information processing; optical radar; remote sensing by laser beam; adaptive filter applications; adaptive signal processing; atmosphere; laser beam remote sensing; lidar; log power estimation; measurement technique; meteorology; multiplicative noise; ocean; partitioned filter; partitioning approach; return power; sea; speckle; Adaptive filters; Additive noise; Equations; Gaussian noise; Laser radar; Noise measurement; Partitioning algorithms; Power measurement; Power system modeling; Speckle;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
