Chirp-Z conversion-based surface water velocity detection method

Abstract

A Chirp-Z conversion-based surface water velocity detection method comprises the following steps of inputting a Doppler radar signal, wherein the Doppler radar signal comes from an echo wave of a continuous wave radar and is subjected to front-end filtering and digital sampling of a baseband signal after down conversion; performing signal pre-processing on the input Doppler radar signal; performing N-point rapid Fourier transformer on the pre-processed data, and roughly calculating a frequency point; taking a zone nearby the frequency point, performing Chirp-Z conversion spectrum zooming on the zone, and calculating water velocity; and inputting the water velocity obtained by calculation into a kalman filter to smooth velocity data, thereby obtaining the surface water velocity. According to the method, spectrum zooming is performed by Chirp-Z conversion, a picket fence effect brought by discrete Fourier transform is reduced, the frequency accuracy is improved, and the speed informationaccuracy is indirectly improved.

Description

technical field [0001] The invention relates to the technical field of water velocity measurement, in particular to a method for detecting surface water velocity based on Chirp-Z transformation. Background technique [0002] Hydrological monitoring activities are of great significance to the management and development of water resources. The hydrological characteristics of rivers include water level, velocity, discharge, flood season, ice age, sediment concentration, etc. Among them, the measurement of water flow velocity is an important part of water flow calculation and monitoring. Traditional contact measuring instruments are not only time-consuming to install, but also very difficult to maintain. Therefore, the demand for non-contact measuring methods is increasing, and its research and application are becoming more and more extensive. At present, non-contact measurement is usually carried out by ultrasonic, laser, radar and other methods. Among them, the radar curren...

AI Technical Summary

Problems solved by technology

[0005] (1) The noise in the echo will affect the discrete Fourier transform effect, and the velocity information is easily overwhelmed by the noise at low speed and low frequency;

[0006] (2) The defects of the discrete Fourier transform itself will reduce the accuracy of the speed calculation results;

[0007] (3) Certain disturbances in the environment are sufficient to cause anomalies in echo data, and traditional digital signal processing methods are difficult to deal with these abnormal disturbances

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