On precise phase difference measurement approach using border stability of detection resolution

Bai, Lina; Su, Xin; Zhou, Wei; Ou, Xiaojuan

doi:10.1063/1.4905623

Cited by 10 publications

(6 citation statements)

References 8 publications

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“…Monotonically-changing phase leads to detection of concentrated "coincidence cluster" around the strict phasecoincidence points, resulting in concentrated fuzzy areas. [17] In this case, the phase difference always enters the inside of the fuzzy area from the outside of it monotonically and continuously.…”

Section: Phase Change Regularities Between Any Frequency Signal and B...mentioning

confidence: 99%

Border effect-based precise measurement of any frequency signal

Bai¹,

Ye²,

Xuan³

et al. 2015

Chinese Phys. B

Self Cite

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Limited detection resolution leads to fuzzy areas during the measurement, and the discrimination of the border of a fuzzy area helps to use the resolution stability. In this way, measurement precision is greatly improved, hence this phenomenon is named the border effect. The resolution fuzzy area and its application should be studied to realize highresolution measurement. During the measurement of any frequency signal, the fuzzy areas of phase-coincidence detection are always discrete and irregular. In this paper the difficulty in capturing the border information of discrete fuzzy areas is overcome and extra-high resolution measurement is implemented. Measurement precision of any frequency-signal can easily reach better than 1 × 10 −11 /s in a wide range of frequencies, showing the great importance of the border effect. An in-depth study of this issue has great significance for frequency standard comparison, signal processing, telecommunication, and fundamental subjects.

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Section: Phase Change Regularities Between Any Frequency Signal and B...mentioning

confidence: 99%

Border effect-based precise measurement of any frequency signal

Bai¹,

Ye²,

Xuan³

et al. 2015

Chinese Phys. B

Self Cite

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“…Whether it is a centralized fuzzy zone, a discrete fuzzy zone, or a dynamic progressive multifuzzy zone, the quantitative fuzzy zone exists when it has the quantization. And its essence is that the edge of the fuzzy zone produced in the adjacent digital conversion is more stable than that in the whole fuzzy zone, and the edge position of the fuzzy zone reflects the stability [12,13] of the fuzzy zone. Therefore, the edge value could be obtained effectively based on the principle of the border effect.…”

Section: Amplitude Characteristicmentioning

confidence: 99%

“…Therefore, the measurement of the AC voltage can widely represent the applications of many digital quantization measurements at the present stage [42,43] and reveal that the quantization resolution of the system devices is fixed, the measurement accuracy is greatly improved when the multi-fuzzy zone border information is obtained using the quantization stability of the system. [12,13] Comparing the 6 1 2 digital multimeter GDM8261A (equal to 21bits) with 8 bit ADC direct measurement, the results are shown in Fig. 5.…”

Section: Frequency Characteristicsmentioning

confidence: 99%

“…For a 24 bit quantized digital system, the sampling rate is only a million samples per second (MSPS), while an 8 bit quantized digital system has a sampling rate up to a gigabit samples per second (GSPS). The concept, application, and development of the border effect [12,13] can make the low bit quantization system realize the measurement accuracy that is higher than the quantization resolution. Meanwhile, for the less quantization bits, the quantization system could reach a higher sampling rate.…”

Section: Introductionmentioning

confidence: 99%

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ADC border effect and suppression of quantization error in the digital dynamic measurement

Bai¹,

Liu²,

Zhou³

et al. 2017

Chinese Phys. B

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The digital measurement and processing is an important direction in the measurement and control field. The quantization error widely existing in the digital processing is always the decisive factor that restricts the development and applications of the digital technology. In this paper, we find that the stability of the digital quantization system is obviously better than the quantization resolution. The application of a border effect in the digital quantization can greatly improve the accuracy of digital processing. Its effective precision has nothing to do with the number of quantization bits, which is only related to the stability of the quantization system. The high precision measurement results obtained in the low level quantization system with high sampling rate have an important application value for the progress in the digital measurement and processing field.

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“…Phase difference measurement of sinusoidal signals [1,2,3,4,5,6,7,8,9] is one of the most important research topics in applications such as phase error calibration of the spaceborne single-pass interferometric synthetic aperture radar (InSAR) system [10,11,12,13], power system monitoring [14], radio frequency communication [15], and laser ranging [16]. For the spaceborne single-pass InSAR system, a possible interferometric phase error can arise from relative phase differences between the two receiver channels, because the two signal receivers are not identical mechanically or thermally, and the signal path length from receiving antenna to electronics is vastly different because of the 60 m baseline [12].…”

Section: Introductionmentioning

confidence: 99%

Phase Difference Measurement of Under-Sampled Sinusoidal Signals for InSAR System Phase Error Calibration

Yuan

Xing

et al. 2019

Sensors

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Phase difference measurement of sinusoidal signals can be used for phase error calibration of the spaceborne single-pass interferometric synthetic aperture radar (InSAR) system. However, there are currently very few papers devoted to the discussion of phase difference measurement of high-frequency internal calibration signals of the InSAR system, especially the discussion of sampling frequency selection and the corresponding measuring method when the high-frequency signals are sampled under the under-sampling condition. To solve this problem, a phase difference measurement method for high-frequency sinusoidal signals is proposed, and the corresponding sampling frequency selection criteria under the under-sampling condition is determined. First, according to the selection criteria, the appropriate under-sampling frequency was chosen to sample the two sinusoidal signals with the same frequency. Then, the sampled signals were filtered by limited recursive average filtering (LRAF) and coherently accumulated in the cycle of the baseband signal. Third, the filtered and accumulated signals were used to calculate the phase difference of the two sinusoidal signals using the discrete Fourier transform (DFT), digital correlation (DC), and Hilbert transform (HT)-based methods. Lastly, the measurement accuracy of the three methods were compared respectively by different simulation experiments. Theoretical analysis and experiments verified the effectiveness of the proposed method for the phase error calibration of the InSAR system.

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On precise phase difference measurement approach using border stability of detection resolution

Cited by 10 publications

References 8 publications

Border effect-based precise measurement of any frequency signal

Border effect-based precise measurement of any frequency signal

ADC border effect and suppression of quantization error in the digital dynamic measurement

Phase Difference Measurement of Under-Sampled Sinusoidal Signals for InSAR System Phase Error Calibration

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