Lidar Signal Processing for Under-Water Object Detection

2005 ◽  
pp. 556-561
Author(s):  
Vikramjit Mitra ◽  
Chiajiu Wang ◽  
Satarupa Banerjee
Keyword(s):  
Signal Processing ◽  
Object Detection ◽  
Lidar Signal ◽  
Water Object

scholarly journals Development and assessment of a Wake Vortex characterization algorithm based on a hybrid LIDAR signal processing

2016 ◽  
Author(s):  
Alexandre Hallermeyer ◽  
Agnès Dolfi-Bouteyre ◽  
Matthieu Valla ◽  
Laurent Le Brusquet ◽  
Gilles Fleury ◽  
...  
Keyword(s):  
Signal Processing ◽  
Wake Vortex ◽  
Lidar Signal

Road Border Recognition Using FIR Images and LIDAR Signal Processing

2007 ◽  
Author(s):  
Basel Fardi ◽  
Hendrik Weigel ◽  
Gerd Wanielik ◽  
Kiyokazu Takagi
Keyword(s):  
Signal Processing ◽  
Lidar Signal

scholarly journals Nonlinear filtering for LIDAR signal processing

1996 ◽  
Vol 2 (5) ◽  
pp. 367-392 ◽  
Author(s):  
D. G. Lainiotis ◽  
Paraskevas Papaparaskeva ◽  
Kostas Plataniotis
Keyword(s):  
Signal Processing ◽  
Nonlinear Filtering ◽  
Nonlinear Models ◽  
Practical Importance ◽  
Nonlinear Filter ◽  
Engineering Problem ◽  
Lidar Signal ◽  
Highly Nonlinear ◽  
Model Partitioning ◽  
And Performance

LIDAR (Laser Integrated Radar) is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF), which has been the standard nonlinear filter in past engineering applications.

scholarly journals Combined range ambiguity resolution and noise reduction in lidar signal processing

2018 ◽  
Vol 57 (07) ◽  
pp. 1 ◽  
Author(s):  
Gunnar Arisholm ◽  
Torbjørn Skauli ◽  
Stig Landrø
Keyword(s):  
Signal Processing ◽  
Noise Reduction ◽  
Ambiguity Resolution ◽  
Lidar Signal ◽  
Range Ambiguity

Noise extraction for Raman lidar signal processing

2003 ◽  
Author(s):  
Aime Lay-Ekuakille ◽  
Andrea Cataldo ◽  
Ferdinando De Tomasi ◽  
Maria R. Perrone ◽  
Amerigo Trotta
Keyword(s):  
Signal Processing ◽  
Lidar Signal ◽  
Raman Lidar
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