High-Accuracy Amplitude and Phase Measurements for Low-Level RF Systems

Wang, Zheng; Mao, Luhong; Liu, Rong

doi:10.1109/tim.2011.2179334

Cited by 12 publications

(3 citation statements)

References 20 publications

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“…The relative deviation exists between the desired control setting and the practical output of control, i.e. the control error or accuracy [13], [14]. This control accuracy affects the AiP performance.…”

Section: Introductionmentioning

confidence: 99%

Design and Experimental Validation of Automated Millimeter-Wave phased Array Antenna-in-Package (AiP) Experimental Platform

Gao

Wang

Fan

et al. 2021

IEEE Trans. Instrum. Meas.

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Antenna-in-package (AiP) technology has been a main design scheme of millimeter-wave (mmWave) phased array antennas for 5G communications. The beamforming pattern of mmWave phased array AiP is steered by controlling the amplitude and phase excitations of AiP elements. It would be helpful to evaluate the control accuracy of complex excitations and to reliably calibrate mmWave AiP. However, these tasks are not trivial and time-consuming in practice, especially when the number of AiP elements is large. To address this problem, this paper presents an efficient and automated mmWave phased array experimental platform. To reduce measurement time, a control software is developed to automatically control the AiP and measurement instruments simultaneously. This experimental platform has flexible gain and phase control of AiP element excitations, and customized measurements in an automated and efficient way can be realized. The effectiveness of the experimental platform is demonstrated by several measurement campaigns, where control accuracy, array calibration, and beam steering for mmWave phased array AiP are extensively investigated.

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Section: Introductionmentioning

confidence: 99%

Design and Experimental Validation of Automated Millimeter-Wave phased Array Antenna-in-Package (AiP) Experimental Platform

Gao

Wang

Fan

et al. 2021

IEEE Trans. Instrum. Meas.

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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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“…Estimating the phase difference between two sinusoidal signals is a typical technique in a wide range of measurement applications such as: specification and calibration of electronic and sensor systems [1,2], interferometric applications [3], impedance spectroscopy [4], optical [5] or ultrasonic [6] time-of-flight ranging, near-field direction-of-arrival estimation [7], laser anemometry [8] or radio frequency control in synchrotrons [9,10]. Several techniques can be used to estimate the phase difference, such as quadrature phase detectors [11] and lock-in amplifiers [12], sine wave fits [13], cross-correlation [14] and methods based on the discrete Fourier transform [15].…”

Section: Introductionmentioning

confidence: 99%

SNR Degradation in Undersampled Phase Measurement Systems

Salido-Monzú

Meca

Martín-Gorostiza

et al. 2016

Sensors

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A wide range of measuring applications rely on phase estimation on sinusoidal signals. These systems, where the estimation is mainly implemented in the digital domain, can generally benefit from the use of undersampling to reduce the digitizer and subsequent digital processing requirements. This may be crucial when the application characteristics necessarily imply a simple and inexpensive sensor. However, practical limitations related to the phase stability of the band-pass filter prior digitization establish restrictions to the reduction of noise bandwidth. Due to this, the undersampling intensity is practically defined by noise aliasing, taking into account the amount of signal-to-noise ratio (SNR) reduction caused by it considering the application accuracy requirements. This work analyzes the relationship between undersampling frequency and SNR reduction, conditioned by the stability requirements of the filter that defines the noise bandwidth before digitization. The effect of undersampling is quantified in a practical situation where phase differences are measured by in-phase and quadrature (I/Q) demodulation for an infrared ranging application.

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High-Accuracy Amplitude and Phase Measurements for Low-Level RF Systems

Cited by 12 publications

References 20 publications

Design and Experimental Validation of Automated Millimeter-Wave phased Array Antenna-in-Package (AiP) Experimental Platform

Design and Experimental Validation of Automated Millimeter-Wave phased Array Antenna-in-Package (AiP) Experimental Platform

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

SNR Degradation in Undersampled Phase Measurement Systems

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