Signal processing techniques for airborne laser bathymetry




Wong, Henry

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Airborne laser bathymetry, a relatively new state-of-the-art technology for the mapping of sea depth by using active airborne laser ranging systems, has proved successful for charting shallow waters worldwide including Canada, Australia, and the United States. In order to improve the reliability and efficiency of using airborne laser ranging systems, in particular, the Canadian LARSEN 500 airborne system, for the estimation of sea depth, one- and two-dimensional (1-D and 2-D) signal processing algorithms are developed. The processing involved is carried out in a two-phased approach. In phase I, 1-D signal processing is explored. Specifically, 1-D digital smoothing is applied to the laser waveforms for noise reduction. Results show that this process can remove noise while preserving the important characteristics of the laser signal. In order to analyze the laser reflections quantitatively, a mathematical model function that can be used to characterize the smoothed laser waveforms received by the LARSEN 500 under diverse circumstances is established. Two algorithms are also developed for the detection of the peak of the laser pulse reflected from the sea surface and bottom. The algorithms have been implemented and tested extensively with real-world LARSEN waveforms. Tests show that the algorithms can reject noise pulses and pulses arising from turbid layers in the sea and locate the correct pulse in the presence of varying degrees of noise. In order to separate the surface and bottom reflections independently of the degree of their overlap, a waveform-decomposition technique based on a robust optimization method is developed. An initialization scheme is also developed in conjunction with the decomposition technique which can reduce the amount of computation required in the decomposition quite significantly. Comparison resuits obtained from statistical analysis show that the proposed technique offers considerable potential in improving the depth estimates particularly when the resolution between the surface and bottom reflections is low. In addition, it can be used to automate the depth estimation process. In phase II, 2-D signal processing is used to improve the reconstruction of ocean topography from individual depth estimates. A type of 2-D interpolating filter is introduced to suppress impulsive noise present in the scattered measurements. It is found that as a result of the filtering, the representation of the sea floor, which can be in the form of 2-D contour maps or 3-D surface plots, becomes a more accurate representation of the ocean bottom. To improve the accuracy in the reconstruction, a sophisticated triangle based 2-D interpolation technique designed using the finite-element method is applied. To increase the reliability of the reconstruction, optimal triangulated irregular networks are constructed before carrying out the interpolation. In order to assess the accuracy of the decomposition results when the resolution between the laser reflections is very low, a procedure which incorporates the 2-D interpolation technique is developed. To further enhance the reconstructed profiles, an adaptive 2-D filtering procedure is introduced. This procedure is developed using 2-D power spectral analysis of the depth profiles. In areas where the signal characteristics of the bathymetric data vary rapidly, 2-D filtering based on minimum mean-squared error estimation is explored. It is shown that the derived filter is a 2-D space-variant filter and its application to bathymetric profiles collected by the LARSEN 500 system is also implemented. Results obtained show that these two filtering procedures are useful in reducing random noise inherent in the reconstructed profiles which is difficult to detect and eliminate in 1-D processing.



Signal processing, Digital techniques, Lasers