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Adaptive filter applications to LIDAR: return power and log power estimation

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4 Author(s)
Lainiotis, D.G. ; Intelligent Syst. Technol., Melbourne Beach, FL, USA ; Papaparaskeva, P. ; Kothapalli, G. ; Plataniotis, K.

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

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:34 ,  Issue: 4 )