ASAS is designed for today’s electronic battlefield of low power, wide bandwidth, and non-periodic RF signals. It is an I/Q signal analysis tool for integration with any digital receiver. The fundamental technology of ASAS is a machine learning classifier which uses adaptive feature extraction algorithms and traditional signal processing functions. At the core is our feature fusion framework which outperforms individually extracted features in non-periodic signal classification.

RESEARCH: Cognitive radio testbed for Digital Beamforming of satellite communication, Wenhao Xiong; Jingyang Lu; Xin Tian; Genshe Chen; Khanh Pham; Erik Blasch; 2017 Cognitive Communications for Aerospace Applications Workshop (CCAA), pp. 1-5, 2017. Read More

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