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COMPARATIVE STUDY ON SPARSE AND RECOVERY ALGORITHMS FOR ANTENNA MEASUREMENT BY COMPRESSED SENSING

By L. Zhang, T. Wang, Y. Liu, M. Kong, and X.-L. Wu

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Abstract:
Compressed sensing (CS) is utilized in antenna measurements. The antenna data are compressed using the CS method, and the performances of different sparse and recovery algorithms of CS are used to solve antenna measurements. Experiments are conducted on various types of antennas. The results show that efficiency can be greatly improved by reducing the number of measurement points. The best reconstruction performance is exhibited by the Discrete Wavelet Transform (DWT) algorithm combined with the Compressive Sampling Matching Pursuit (COSAMP) algorithm.

Citation:
L. Zhang, T. Wang, Y. Liu, M. Kong, and X.-L. Wu, "Comparative Study on Sparse and Recovery Algorithms for Antenna Measurement by Compressed Sensing," Progress In Electromagnetics Research M, Vol. 81, 149-158, 2019.
doi:10.2528/PIERM19041803

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