Impact Analysis and Calibration Methods of Excitation Errors for Phased Array Antennas

He, Guolong; Gao, Xin; Zhang, Rentian

doi:10.1109/access.2021.3073222

Cited by 18 publications

(17 citation statements)

References 126 publications

(184 reference statements)

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“…According to the principle of pattern multiplication, AF has nothing to do with the characteristics of the array element and only reflects the information contained in the array manifold. Nevertheless, AF is not related to array manifolds when θ ¼ 0 as indicated in (3). It is necessary to remove this observation point from the training dataset since it does not contain any useful information for evaluation.…”

Section: Eliminate Redundant Datamentioning

confidence: 99%

“…Therefore, there is an increasing interest in these ubiquitous errors described by the random excitation errors of array elements or sub‐arrays. In addition, a good knowledge of radiation characteristics at any spatial location in the presence of random excitation amplitude and phase errors is crucial for phased array calibration 3 …”

Section: Introductionmentioning

confidence: 99%

“…However, its actual radiation performance is different from an ideal one due to the existence of random errors. Random errors 3 are related to several factors such as manufacturing tolerance, component aging, and harsh environments, which may cause severe degradation of the radiation characteristics in terms of sidelobe level (SLL), realized gain, and main beam pointing direction 4–6 . This issue is more severe if the number of array elements is small, for example, no more than

16\times 16

.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Statistical analysis of phased arrays with random excitation errors using a unified neural network architecture

Zhao

2023

Int J Numerical Modelling

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Radiation patterns of a phased array tend to be affected by random excitation errors. In this paper, a unified neural network (UNN) architecture is presented to study the statistical characteristics of radiation patterns. Benefited from the inherent symmetry of the array manifolds and efficient data preprocessing, the UNN architectures are almost identical for planar arrays consisting of 4–10 000 elements except for a slight difference existed in the output layer. Therefore, this merit avoids repetitive selections of training hyperparameters and network architectures. This method can efficiently treat the problems with multiple observation points in order to obtain statistical radiation patterns, and an analytic or closed‐form solution is not required. Moreover, it can combine with the method of moments (MoM), which takes account of the element pattern and mutual coupling effects. The trained UNN models can predict the probability density function (PDF) of radiation characteristics at any spatial location. Numerical results show that the UNN and Monte Carlo (MC) results are comparable in accuracy.

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Section: Eliminate Redundant Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

16\times 16

.…”

Section: Introductionmentioning

confidence: 99%

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Statistical analysis of phased arrays with random excitation errors using a unified neural network architecture

Zhao

2023

Int J Numerical Modelling

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“…When the satellite is in orbit, the working state and environment are different from the ground test, especially the temperature field variation of the SAR antenna panel, leading to the antenna pattern difference. Phased array antenna calibration is applied to sample each antenna element in the array to identify the differences among the elements [7]. e calibration methods are divided into four categories: the near-filed scanning probe method, the peripheral fixed probe method, the mutual coupling method, and the built-in network method.…”

Section: Introductionmentioning

confidence: 99%

SAR Antenna Pattern Measurement by Internal Calibration Method for GF-3 Satellite

Sun

Xing

et al. 2022

International Journal of Antennas and Propagation

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GF-3 is the first C-band multipolarization synthetic aperture radar (SAR) satellite in China. The SAR system is equipped with an active phased array antenna to electronically generate various antenna beams. The accuracy of SAR antenna patterns is of main importance for precise SAR image processing. The traditional method for antenna pattern measurement is the near-field method but it is unable to satisfy the demand for fast measuring in-orbit. In order to measure the SAR antenna pattern quickly with high accuracy, we propose the internal calibration method. The internal calibration uses calibration signals which are routed along the nominal signal path in SAR systems, thus monitoring the gain and phase variations for each T/R channel is possible. This paper will focus on this method, including its principle, operation steps, and results, compared to the near-field method. The internal calibration method provides a valuable solution for SAR antenna pattern measurement.

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“…Rocca et al proposed a statistical method based on the interval analysis to analyze the influence of the amplitude and phase excitation with random errors on the radiation pattern of the phased array [8]. He et al introduced how to use the probability-based method and method based on the interval arithmetic to evaluate the effects of the phased array antenna with excitation errors [9].…”

Section: Introductionmentioning

confidence: 99%

Anti-Error Robust Pattern Synthesis Algorithm in Time-Modulated Array Antenna

et al. 2022

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Compared with the traditional antenna array, the time-modulated array can increase the flexibility of the array by adding time switches. However, due to the introduction of time switches, the timemodulated array antenna is more sensitive to random errors than the traditional array. Besides random errors caused by unavoidable factors such as array deformation and defects of processing and assembly in the traditional array, time-modulation parameter errors will be introduced by time switches. As errors in the traditional array can degrade the performance of the array, time-modulation parameter errors can lower the performance of the array pattern as well, which will lift the side-lobe and increase the dynamic range of the side-lobe. Aiming at the time-modulation parameter errors in the time-modulated array, an anti-error robust pattern synthesis algorithm (AERPS) based on the convex optimization (CVX) is proposed in this paper. In the algorithm, the optimization model for the pattern synthesis of the time-modulated array is established and analyzed. Then the model is divided into two sub-models of the center frequency and the first sideband, and the convex optimization solution is first performed on the center frequency model. After the center frequency model is solved, the convex optimization solution is used to solve the first-order sideband model to obtain the final results. The simulation results of the time-modulated array in this paper show that the algorithm can reduce the average value and the dynamic range of the normalized side-lobe level, thus verifying the effectiveness and the robustness of the algorithm.

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Impact Analysis and Calibration Methods of Excitation Errors for Phased Array Antennas

Cited by 18 publications

References 126 publications

Statistical analysis of phased arrays with random excitation errors using a unified neural network architecture

Statistical analysis of phased arrays with random excitation errors using a unified neural network architecture

SAR Antenna Pattern Measurement by Internal Calibration Method for GF-3 Satellite

Anti-Error Robust Pattern Synthesis Algorithm in Time-Modulated Array Antenna

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