Method for mutual correlation phase difference measurement based on Hilbert transform

Abstract

The invention relates to a method for mutual correlation phase difference measurement based on the Hilbert transform and the field of signal processing, in particular to a method for phase difference measurement. The method is suitable for a plurality of signal segments with the same center frequency. The method comprises the following steps that firstly, three signal segments are randomly selected from the signal segments with the same center frequency, wherein the three signal segments comprise two signal segments containing the phase difference to be calculated and one reference signal segment; secondly, the Hilbert transform is conducted on the reference signal segment or 90-degree phase shift is conducted on the reference signal segment so that a second reference signal segment can be obtained; thirdly, mutual correlation is conducted on the two reference signal segments and the two signal segments with the phase difference to be calculated so that four kinds of mutual correlation relationships can be obtained; finally, a phase difference value of tested signals can obtained according to the four kinds of mutual correlation relationships. According to the method for phase difference measurement, the phase difference of the signals can be accurately measured under the condition that the center frequency of the signals is unknown, and the accuracy and the robustness are good.

Description

technical field [0001] The invention relates to the field of signal processing, in particular to a method for measuring cross-correlation phase difference based on Hilbert transform. Background technique [0002] Phase difference is a very important parameter in the analysis and research of sinusoidal steady-state circuits, and it is an important index for comparing the phase relationship between two sinusoidal signals of the same frequency. With the development of science and technology, the measurement of phase difference has extensive and important applications in the fields of electronic measurement, communication, instrumentation, equipment fault diagnosis, radar, automatic control, navigation and positioning, such as the detection of fluid velocity and flow, underwater Positioning of targets, measurement of power factor of power system, detection of mechanical and physical parameters of shallow seabed, flow measurement of Coriolis mass flowmeter, detection of phase-sen...

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Problems solved by technology

[0005] (2) Hilbert transform method (reference [2]: Manuel Varlet, MichaelJ.Richardson. Computation of continuous relative phase and modulation of frequency of human movement [J]. Journal of Biomechanics, 2011, 44 (2): 1200-1204. Reference [3]: Zhang Tao, Lin Chengyan, Zhang Xianguo, etc. High-resolution processing method of well logging curve based on Hilbert transform [J]. Journal of China University of Petroleum (Natural Science Edition), 2012, 36( 1): 68-72.): The Hilbert transform method can reflect the phase change of the whole process, so it has a good application prospect in the phase dynamic measurement, but the instantaneous phase measured by this method has a sudden change, which leads to the existence of phase measurement In addition, this method has high requirements on the storage capacity and real-time performance of the computer, which limits the wide application of the Hilbert transform dynamic phase measurement method.

[0006] (3) Correlation method (reference [4]: ​​Weng Lijing, Zhang Xiyun. Phase difference calculation method based on DSP and signal correlation analysis [J]. Information Technology Research, 2010, 36(6): 22-25. Reference [ 5]: Huang Youpeng, Cao Wanhua, Li Lin, Zhao Xiaolan. A Robust Correlation Algorithm for Infrared Sensors and Passive Radar Tracks [J]. Journal of Instrumentation, 2012, 33(11): 2629-2634. Reference [6]: Jing Li, Zhang Huijuan. Detection and location of copy tampering in image area based on phase correlation [J]. Computer Applications, 2013, 33(3): 660-662, 687.): Correlation method for interference such as DC offset and noise in the signal It has a strong suppression ability, and its error is mainly due to the fact that the measured signal and its own noise are not completely irrelevant, coupled with the strict requirement of full-cycle sampling, the accuracy of its phase difference measurement needs to be improved

[0007] (4) Discrete Burier transform method (Reference [7]: Guo Xiangyu, Fei Shumin. A method for detecting cloth defects based on phase transformation [J]. Industrial Control Computer, 2012, 25(6): 64-65 , 69. Reference [8]:

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