Optimized-LM-algorithm-based laser radar waveform decomposition method

A LM algorithm and laser radar technology, applied in the field of laser remote sensing, can solve problems such as the existence of optimized space, and achieve the effects of improving efficiency, reducing the number of changes, and quickly converging performance

Active Publication Date: 2015-11-25
NANJING UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The traditional LM algorithm introduces a constant jitter term for

Method used

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  • Optimized-LM-algorithm-based laser radar waveform decomposition method
  • Optimized-LM-algorithm-based laser radar waveform decomposition method
  • Optimized-LM-algorithm-based laser radar waveform decomposition method

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Embodiment Construction

[0031] The technical implementation of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0032] Such as figure 1 As shown, the method of full waveform decomposition based on the optimized LM algorithm, the specific steps are as follows:

[0033] (1) Digitally collect the backscatter full waveform data through the laser radar system. The wavelength of the laser used in the embodiment is 1064 nm, the half-amplitude pulse width is 5 ns, and the sampling rate is 1 Gsps. figure 2 It is the full waveform of the noisy laser collected in the examples.

[0034] (2) Carry out signal enhancement on the observed waveform, including noise processing and smoothing processing. In the embodiment, wavelet denoising is selected for noise processing, and Gaussian smoothing is selected for smoothing. image 3 The blue solid line of represents the waveform obtained by signal enhancement in the embodiment.

[0035] (3) Set the threshold, ...

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Abstract

The invention discloses an optimized-levenberg-marquardt (LM)-algorithm-based laser radar waveform decomposition method. The method comprises the following steps that: (1), a laser radar system records observation waveform data of back scattering in a digital mode; (2), signal enhancement is carried out on the observation waveform data, wherein the signal enhancement contains noise processing and smoothing processing; (3), a threshold value is set, peak-inflection point detection is carried out on the enhanced signal, and initialization estimation values containing a number, an amplitude, a position, and a pulse width initialization parameter are determined; (4), a standard LM algorithm is corrected by using an improved training module and iteration is carried out on the initialization estimation values to obtain feature parameters, including amplitudes, positions, and pulse widths, of all components of the enhanced signal; and (5), goodness of fit is calculated by using fitting data and original observation data and precision of the goodness of fit is determined; and an efficiency of a fitting algorithm is determined by using the number of times of iteration.

Description

technical field [0001] The invention relates to the field of laser remote sensing, in particular to the improvement of the decomposition algorithm of full waveform data obtained by laser radar. Background technique [0002] Lidar detection and ranging system (Light Detection and Ranging, referred to as Lidar) as an active remote sensing technology is applied to the direct distance measurement of the surface, and then obtains the two-dimensional or three-dimensional image of the target. [0003] At present, full-waveform lidar has been widely commercialized, and its suppliers include RIEGL, Leica, Optech and other companies. The full waveform lidar can record the complete backscattering waveform of the target, and obtain the distance and intensity information of the target through efficient data processing. [0004] With the wide application and upgrading of large-spot laser radar, the amount of waveform data obtained by laser radar detection becomes larger and larger. The ...

Claims

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Application Information

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IPC IPC(8): G01S7/487
CPCG01S7/4802G01S7/487
Inventor 徐帆王元庆李芬芳
Owner NANJING UNIV
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