Description: Antenna Array Diagnosis problem is formulated in compressive sensing framework using a priori information about the failure-free antenna array radiation pattern. This framework uses the linear relationship relating the difference of the far-field radiation patterns between the reference array and the antenna under test. Three sparse based recovery approaches namely the minimization of the L1, the total variation (TV) norm, and the mixed L1/lL2 norm are discussed and analyzed by performing simulations in MATLAB. Simulations were performed using antenna array of 10 x 10 WR90 waveguide at 10GHz. Thus, the results obtained complies with our objective of having faster antenna array diagnosis with small number of measurement points.
This User's Guide inside the .zip file describes the functionality and basic usage of the software package.
All the work done is based on the following papers:
- Marco Donald Migliore, IEEE Transactions On Antennas And Propagation, Vol. 59, No. 6, June 2011
- O.M. Bucci, M.D. Migliore, G. Panariello, and P. Sgambato, IEEE Transactions On Antennas And Propagation, Vol. 53, No. 3, March 2005
Following solvers are used in the algorithms:
- YALL1 basic solver code: Y. Zhang, J. Yang, and W. Yin. YALL1: Your ALgorithms for L1 [Online]. Available: yall1.blogs.rice.edu, 2011
- CVX Research, Inc. (2012, Sep.). CVX: Matlab Software for Disciplined Convex Programming, Version 2.0 Beta [Online]. Available: http://cvxr.com/cvx
Muhammet Emin YANIK (2023). Fast Antenna Array Diagnosis from a Small Number of Far-Field Measurements (https://www.mathworks.com/matlabcentral/fileexchange/63323-fast-antenna-array-diagnosis-from-a-small-number-of-far-field-measurements), MATLAB Central File Exchange. Retrieved .
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