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Improved waveform decomposition with bound constraints for green waveforms of airborne LiDAR bathymetry

机译:利用空气流动激光雷达族浴的绿色波形的束缚分解改进了波形分解

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摘要

Waveform decomposition using the Levenberg-Marquardt algorithm is a powerful tool for detecting surface return, bottom return, and volume backscatter return in a superposed green waveform of airborne LiDAR bathymetry (ALB). However, traditional decomposition methods do not handle bound constraints and are easily trapped in local optimum. Thus, the decomposed components may be inconsistent with the measurement principle of ALB. This study proposes an improved waveform decomposition method by setting reasonable lower and upper bounds of waveform parameters to guarantee the fidelity of the decomposed components. First, a comprehensive mathematical model of a green waveform is proposed by considering the early return. Second, the lower and upper bounds of the waveform parameters are given on the basis of the measurement principle of ALB. Finally, improved waveform decomposition is achieved using the comprehensive model and a constrained nonlinear optimization. The proposed method is applied to a practical ALB measurement using Optech coastal zone mapping and imaging LiDAR. Compared with traditional decomposition methods, the improved waveform decomposition not only ensures good fitness but also guarantees the fidelity of the decomposed components. (C) 2020 Society of Photo-Optical Instrumentation Engineers (SPIE)
机译:使用Levenberg-Marquardt算法的波形分解是一种强大的检测表面返回,底部返回和体积反向散射在空气传播的LIDAR沐浴浴(ALB)的叠加绿色波形中返回的强大工具。然而,传统的分解方法不处理约束约束,并且很容易被捕获在局部最佳状态。因此,分解的组件可能与ALB的测量原理不一致。本研究提出了通过设置波形参数的合理下限和上限来提高波形分解方法,以保证分解组件的保真度。首先,通过考虑早期返回,提出了一种绿色波形的综合数学模型。其次,基于ALB的测量原理给出波形参数的下限和上限。最后,使用综合模型和约束的非线性优化实现了改进的波形分解。该方法应用于使用Optech沿海区域映射和成像激光雷达的实际ALB测量。与传统的分解方法相比,改进的波形分解不仅可以确保良好的健身,而且保证了分解组件的保真度。 (c)2020光学仪表工程师协会(SPIE)

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