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Evolutionary Computing Based Antenna Array Beamforming with Low Probabality of Intercept Property

In this work we have proposed a new approach for array antenna beamforming based on evolutionary computing, which offers low probability of intercept. These active array antennas are highly vulnerable to intercept receivers due to their high-gain. The detection performance of proposed approach remains unchanged as the amount of energy on the target is same as that of the high gain beam pattern, while the intercept range of the enemy receiver has been greatly reduced. In this paper, the set of complex weights for synthesis of high gain beam pattern using spoiled set of basis patterns is derived using genetic algorithm. The two major advantages of proposed algorithm are the improved performance and at the same time the low complexity specifically by avoiding the matrix inversions. Simulation results ensure that the beam synthesized by this technique is at par with the existing LPI beamforming techniques employing phased arrays.