Continuous wavelet transform and iterative decrement algorithm for the Lidar full-waveform echo decomposition

Area of Science:

• Geospatial Science
• Signal Processing
• Remote Sensing Technology

Background:

• Full-waveform LiDAR data offers rich information but presents challenges in signal decomposition.
• Overlapping echoes in LiDAR signals complicate accurate data interpretation and analysis.

Purpose of the Study:

• To develop a robust algorithm for decomposing complex full-waveform LiDAR echoes into Gaussian components.
• To accurately detect and isolate individual echo components, even when heavily overlapped.

Main Methods:

• Proposed a continuous wavelet transform (CWT) coupled with an iterative decrement algorithm.
• Real-time CWT scale calculation based on transmitted laser pulse characteristics.
• Identified component positions using CWT maxima and detected boundary points for echo clipping.
• Employed iterative decrement and Levenberg-Marquardt algorithms for parameter estimation of obscured components.

Main Results:

• The proposed method successfully decomposed complex full-waveform LiDAR echoes.
• Accurate detection and separation of overlapping Gaussian components were achieved.
• Simulations and experiments validated the algorithm's effectiveness on challenging datasets.

Conclusions:

• The developed CWT and iterative decrement algorithm provides an effective solution for full-waveform LiDAR echo decomposition.
• This method enhances the analysis of complex LiDAR data, improving the accuracy of geospatial information extraction.