Self-adaptive variable-sampling rate audio frequency sampling method

Abstract

The invention provides a self-adaptive variable-sampling rate audio frequency sampling method. The method measures the zero crossing number according to sampling data and adjusts the sampling frequency based on the zero crossing number. The method concretely comprises the following steps (1) estimating the zero crossing time by the magnitudes of voltage of sampling points, and determining that whether symbols of a former sampling value and a later sampling value are identical or not, wherein if the symbols are the same, no zero crossing occurs between two sampling points of the two sampling values, and if the symbols are different, voltage between the two sampling points of the two sampling values crosses zero once, and voltage symbols of the two sampling points are changed once; (2) counting the number of change in a frame of sampling data to make out the zero crossing number, in particularly, the sign bit of the sampling data is used as a timing clock, the rising edge and a falling edge of the sign bit are used to count during a time period for transmitting a frame of sampling data, and an obtained count value is the zero crossing number of the frame of sampling data; and (3) according to the corresponding relation between the zero crossing number and the frequency, carrying out the sampling frequency selection by means of block sampling.

Description

technical field [0001] The invention belongs to the technical field of signal processing, in particular to an adaptive variable sampling rate audio sampling method. Background technique [0002] When the radio integrated tester tests the audio signal, in order to test the distortion and SNR of the audio signal, the sampling rate is more than 10 times the highest frequency, so as to collect the 5th harmonic of the highest audio. Excessively high sampling rate leads to less than one cycle of collected data when collecting low-frequency audio signals, which affects the accuracy of parameters such as audio frequency, audio level, audio distortion, and signal-to-noise ratio. The traditional solution is to discard the low-frequency audio signal or reduce the frequency of the highest audio signal. Although this method can solve the contradiction between the measurability of the 5th harmonic of the highest frequency audio signal and the full period of sampling data of the lowest fre...

AI Technical Summary

Problems solved by technology

The time domain adjustment is to estimate the frequency by measuring the zero-crossing point based on the sampling data, and then adjust the sampling frequency according to the estimated frequency. The zero-crossing point detection requires the input signal to be a strict sinusoidal waveform. Due to the influence of noise and detection methods in engineering, the error is large

Secondly, the Fourier transform method estimates the frequency; sufficient sampling data is required, which is not applicable at low frequencies

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