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Fast Antenna Array Calibration Using One External Receiver
In multiple array communication or radar systems, waveform diversity can be utilized for beampattern design. However, one of the critical issues for such systems is the presence of mutual coupling, which degrades the beampattern design’s quality. We address the calibration of the mutual coupling of...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675131/ https://www.ncbi.nlm.nih.gov/pubmed/38005414 http://dx.doi.org/10.3390/s23229026 |
Sumario: | In multiple array communication or radar systems, waveform diversity can be utilized for beampattern design. However, one of the critical issues for such systems is the presence of mutual coupling, which degrades the beampattern design’s quality. We address the calibration of the mutual coupling of transmit arrays by developing a new matrix-inversion-free algorithm that requires only a single antenna receiver. It has a very low computational complexity for accelerating the mutual coupling calibration compared to previous methods; therefore, it can be utilized for large array systems such as massive multiple-input–single-output (MISO) systems. The key idea here revolves around utilizing fast Fourier transform (FFT). This approach simplifies matrix calculations and reduces the number of multiplications required to compute the inverse of FFT. Moreover, the algorithm is applicable for high-power active radar calibration, since it incorporates a constant modulus training sequence. The application of the algorithm in MISO systems, including massive MISO, offers the potential for calibrating mutual coupling. It enables the precise measurement and compensation of mutual coupling effects, improving the signal quality and system performance in areas such as radars, mobile communications and more. We evaluated the proposed algorithm under various scenarios, compared it with the ground truth and showed that it achieves excellent performance with few computations. |
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