Full-waveform laser radar echo data gaussian decomposition method based on genetic algorithm

Abstract

The invention discloses a full-waveform laser radar echo data gaussian decomposition method based on a genetic algorithm. The method is mainly formed by five steps including echo denoising, initial wave crest extracting, initial parameter estimating, waveform fitting and precision judging; when the precision of initial fitting meets the requirements, second fitting is not carried out, when the precision of the initial fitting does not meet the requirements, iteration fitting is carried out, and in each iteration, the fitting precision is improved by a method of increasing a gaussian component until a stopping condition is met; a gaussian function is used for fitting echo data of a full-waveform laser radar; and a gaussian filter method is adopted to filter noise of the echo data of the full-wave form laser radar, the number of initial gaussian components is confirmed by extracting a peak value point, an initial parameter range is estimated, fitting and precision adjusting are carried out on the echo data of the full-waveform laser through the genetic algorithm, an echo gaussian decomposition software system based on the genetic algorithm is manufactured, and echo decomposition operation is simplified.

Description

technical field [0001] The invention discloses a Gaussian decomposition method of full-waveform laser radar echo data based on a genetic algorithm. The method is mainly composed of five steps: echo denoising, initial wave peak extraction, initial parameter estimation, waveform fitting and accuracy judgment . Background technique [0002] The traditional pulse ranging laser radar system calculates the target point distance by recording the time point of a transmission pulse and an echo pulse. If there is only one real target in the propagation path of the laser pulse, then one scattered echo is enough to complete the accuracy. However, in reality, there may be multiple targets with different elevations in the laser propagation path, and only recording the echo once cannot meet the measurement requirements. So there is a laser radar system that can record multiple echoes. A typical multiple-echo laser radar system records the first echo pulse and the last echo pulse (because ...

AI Technical Summary

Problems solved by technology

However, both the LM Gaussian decomposition method and the EM Gaussian decomposition method have their own shortcomings.

As a point-to-point optimization algorithm, the LM algorithm has very high requirements on the accuracy of the initial parameters. Inaccurate initial parameters can easily bring the entire operation into a local optimum. When the echo component is determined, the weak and small Latent components exist

In the EM Gaussian decomposition method, the number of Gaussian pulse components is obtained through algebraic calculation, which makes the EM algorithm, which has a large amount of calculation and calculation time, more complicated, and the EM Gaussian decomposition method is easy to fall into a local optimum, and the newly added echo The component may lead to the failure of the fitting, and the EM algorithm also has the problem of being unable to find the potential echo component, which will also lead to insufficient calculation accuracy or insufficient authenticity of the calculation results

[0004] The purpose of the patent of the present invention is to solve the above-mentioned Gaussian decomposition algorithm, which requires strict initial parameter extraction, is difficult, cannot find potential echo components and has low robustness of the algorithm. The method adopted is the Gaussian decomposition method based on genetic algorithm.

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