Investigation of a Proposed ANN-Based Array Antenna Diagnosis Technique on a Planar Microstrip Array Antenna
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Investigation of a Proposed ANN-Based Array Antenna Diagnosis Technique on a Planar Microstrip Array AntennaAbstract
In this article, a realistic neural network based method is proposed for the array antenna fault diagnosis through the utilization of array far field characteristics. Defective elements are those elements that are not excited directly by the feed lines but radiations due to the induced currents on the surface of these elements still remain. Neural network performs a nonlinear mapping between some samples of the degraded patterns and the array elements which may have caused these degradations. The proposed method is investigated on a real fabricated micro-strip planar array via its far field degraded radiation pattern measurements. A multilayer perceptron neural network trained in the back propagation mode with some samples of the simulated degraded patterns is used in an innovative manner to map the measured radiation pattern to its corresponding faulty elements configuration. After the training procedure the proposed fault diagnosis system is very fast and has a satisfactory success rate both in theory and application that makes it suitable for real time applications.
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