Undersampling frequency selection method for improving phase discrimination precision

Abstract

The invention provides an undersampling frequency selection method for improving phase discrimination precision. The undersampling frequency selection method comprises the following steps of setting a to-be-sampled signal parameter, setting an undersampling parameter, sampling according to the relative relationship between the undersampling sampling position and the to-be-sampled signal, and confirming the final undersampling frequency, so that the phase discrimination precision is improved. The set to-be-sampled signal parameters comprise set to-be-sampled signal frequency f. The setting of the undersampling parameters comprises setting an undersampling frequency fs. The undersampling frequency fs can meet the effectiveness of undersampling, n is a positive integer, and f is the frequency of the to-be-sampled signal. By means of the method, the technical problem that in the prior art, due to selection of the undersampling frequency, the phase discrimination precision is poor can be solved.

Description

technical field [0001] The present disclosure relates to the technical field of laser ranging, and in particular to a method for selecting an under-sampling frequency for improving phase detection accuracy. Background technique [0002] Phase laser ranging is the main measurement method for medium and long-range high-precision ranging. In the phase laser ranging system, the main factor that determines the distance measurement accuracy is the phase calculation accuracy, and the two important links for phase calculation are signal sampling and processing for the sampled signal. For signal sampling, in general, in order to avoid spectral aliasing of the sampled signal, the sampling rate must satisfy the Nyquist sampling theorem, but if the frequency of the signal to be sampled is too high, increasing the sampling rate will lead to a significant increase in the complexity of the sampling circuit. The under-sampling method can restore the waveform of the signal to be sampled and...

AI Technical Summary

Problems solved by technology

For the selection of undersampling sampling frequency, existing papers have analyzed that the sampling frequency cannot be set to f_s / n, where f_s is the frequency of the sampled signal, and n is a positive integer; and the larger the value of n, the lower the phase detection accuracy

[0004] However, under the above-mentioned constraints of the under-sampling frequency, there are still many under-sampling frequencies that meet the requirements. Therefore, based on this constraint, how to choose the under-sampling frequency to improve the accuracy of phase detection is a technical issue that needs to be solved urgently.

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