| Decomposition of waveform is a key link in airborne LiDAR bathymetry data processing, which can provide the basic information for deriving water depth, inverting seafloor sediment tyoe, and analyzing water turbidity. Traditional waveform fitting algorithms are less robust to noise, and cannot detect weak signals and superposed signals in an accurate way. To overcome these problems, a method was proposed in this paper. Firstly, the proposed algorithm is used to calculate the difference between the last part of the original waveform and the waveform after wavelet threshold denoising. Then, the Gaussian model is adopted to continuously extract Gaussian components which are optimized by the LM algorithm. Then this algorithm is tested by measured data obtained from the South China Sea, demonstrating that it can detect weak signals. The experiment results show that, whether in shallow or deep water, the fitting precision of the proposed algorithm outperforms the traditional algorithms. |
