Heat-seeking missiles continue to be serious threats to aircrafts. In recent years, open-loop DIRCM systems have proven to be efficient countermeasures against these missiles. However, closed-loop DIRCM systems seem to be more promising as they employ a jamming code based on the classification or identification of an incoming missile through retro-reflection from the seeker head. In these systems, the retro-reflected beam is influenced by the optical turbulence in both transmission and return paths. In this paper, the influence of optical turbulence on the identification performance of a closed-loop DIRCM system is investigated. A dataset is created by varying the seeker spin and carrier frequencies along with the optical turbulence levels and range. Deep neural network classifiers were trained on this dataset and evaluated in terms of their effectiveness in identifying missile seekers with the DIRCM system.
A normally-off InAlN/GaN high electron mobility transistor (HEMT) on Si substrate with a p-GaN gate is reported. Devices are fabricated on two different epitaxial structures, one containing a high resistive GaN buffer layer and one containing an AlGaN back-barrier, and the threshold voltage, drain current density, and buffer leakage current are compared. With the epitaxial structure containing a high resistive GaN layer, normally-off operation with a threshold voltage of +0.5 V is achieved. The threshold voltage is further increased to +2 V with the AlGaN back-barrier, and the buffer leakage current was improved by over an order of magnitude.
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