Method for fast automatic calibration of phased array based on residual neural network
US12288936B1 · kind B1 · utility
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Inventors
Key dates
| Filing date | Dec 20, 2024 |
| Grant date | Apr 29, 2025 |
| Priority date | — |
| Expiry date | Dec 20, 2044 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02D30/70
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed is a method for fast automatic calibration of a phased array based on a residual neural network. A phase setting matrix is set and an amplitude and a phase of a array far-field complex signal are measured with a network analyzer to obtain an amplitude and phase vector of the array far-field complex signal. A real part, an imaginary part, and a magnitude of the far-field measured complex signal value are separated and normalized, and mapped to RGB three-channel image data. Datasets are automatically generated according to a preset amplitude-phase error range by a simulation software, the datasets are proportionally divided into a training set and a test set to be input into the residual neural network for training to obtain a calibration model. Measured data is input into the calibration model for automatic estimation of the amplitude-phase error of the phased array.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.