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Journal of Sensors
Volume 2016, Article ID 6139802, 8 pages
Research Article

Detection of Defective Sensors in Phased Array Using Compressed Sensing and Hybrid Genetic Algorithm

1School of Engineering & Applied Sciences, ISRA University, Islamabad 44000, Pakistan
2Electrical Department, Air University, Islamabad 44000, Pakistan
3Electronic Department, International Islamic University, Islamabad 44000, Pakistan

Received 3 February 2015; Revised 12 June 2015; Accepted 14 July 2015

Academic Editor: Manuel Pineda-Sanchez

Copyright © 2016 Shafqat Ullah Khan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A compressed sensing based array diagnosis technique has been presented. This technique starts from collecting the measurements of the far-field pattern. The system linking the difference between the field measured using the healthy reference array and the field radiated by the array under test is solved using a genetic algorithm (GA), parallel coordinate descent (PCD) algorithm, and then a hybridized GA with PCD algorithm. These algorithms are applied for fully and partially defective antenna arrays. The simulation results indicate that the proposed hybrid algorithm outperforms in terms of localization of element failure with a small number of measurements. In the proposed algorithm, the slow and early convergence of GA has been avoided by combining it with PCD algorithm. It has been shown that the hybrid GA-PCD algorithm provides an accurate diagnosis of fully and partially defective sensors as compared to GA or PCD alone. Different simulations have been provided to validate the performance of the designed algorithms in diversified scenarios.