Self-adaptive empirical mode decomposition denoising method for satellite-borne full-waveform signals

Abstract

The invention provides an adaptive empirical mode decomposition denoising method for satellite-borne full-waveform signals. The adaptive empirical mode decomposition denoising method comprises the following steps: acquiring noisy full-waveform signals; carrying out EMD decomposition to acquire all IMF components; determining a Hurst index value of each IMF component; judging whether the componentis a high-frequency IMF component or not according to the index value; if the component is a high-frequency IMF component, performing soft threshold processing to obtain a denoised high-frequency IMFcomponent and reserving the denoised high-frequency IMF component, otherwise, directly reserving the denoised high-frequency IMF component; and superposing the denoised high-frequency IMF component and the denoised low-frequency IMF component, and reconstructing a denoised full-waveform signal. According to the self-adaptive empirical mode decomposition denoising method, rapid and large-scale judgment of high-frequency noise components is achieved by constructing an H value; meanwhile, soft threshold processing is carried out on the selected high-frequency IMF components, so that possible signal components are searched again in the components needing to be removed, effective signal loss caused by direct removal of the high-frequency components is avoided, and the signal-to-noise ratio is higher.

Description

technical field [0001] The invention belongs to the field of spaceborne laser altimeters, and in particular relates to an adaptive empirical mode decomposition and denoising method for spaceborne full waveform signals. Background technique [0002] In the full waveform signal processing obtained by the spaceborne laser altimeter, the full waveform decomposition is the key to improving the accuracy of ranging and accurately inverting the characteristic parameters of ground objects such as slope and roughness. [1] . Due to the background noise such as sunlight and the thermal noise of instruments and equipment that are filled in the waveform signal [2] It will interfere with the estimation of initial parameters in the process of full waveform decomposition and affect its ranging accuracy [3] , therefore, it is very necessary to study the full waveform denoising method of laser altimetry that can effectively remove noise while maintaining the waveform morphological characteri...

AI Technical Summary

Problems solved by technology

Existing EMD-Hurst index method found that there will be a loss of effective signal after the real GF-7 waveform test

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