As sensors become more software definable, the ability to add additional capabilities to them becomes desirable as SWaP is always a premium, especially on airborne platforms both manned and unmanned. The same can be said for apertures. The prevailing standard is that each sensor has its own aperture. In reality, that does not have to (and should not) be the case. In the high-band and low-band chassis designed for the Navys Triton platform as part of the Multi-INT system, Azure has architected a 16x12 fully non-blocking switch that connects to various aircraft apertures and downconverters and can route those to any tuner channel. For this effort, Azure plans to extend this approach to the C-RACAS (AN/ZPY-9) to provide high gain steerable beam outputs to the Multi-INT system to aid in both threat and friendly automatic radar identification in C-band. The added (and intended) benefit of this approach is that the C-RACAS aperture has significant performance benefits over the existing ISR SAA aperture on the Triton platform in that 5 to 6GHz frequency range. Our automated recognition capability along with the benefits of sharing aperture beams will be discussed in more detail in the technical approach.
Benefit: Azure Summit is ideally positioned to rapidly transition our automatic recognition and aperture sharing technology to the Navy and the rest of DoD. Azures Switchblade family of Intelligent Transceivers was developed for NAVAIR PMA-290 and is the basis of the Navys Common Chassis as well as High-band and Low-band chassis. It is currently being integrated into EP-3, P-8, Triton, and Virginia Class submarines, and is under consideration for other platforms. Azure will use Switchblade hardware to demonstrate the feasibility of the or our recognition algorithm as it would be implemented in the Multi-INT system as well as integration of the artificial intelligence spectrum monitoring capability. The ability to rapidly classify co-channel emitters in the cluttered C-band also has significant value in the Commercial communications market. As the ISM and other frequencies within C-band become more saturated with competing emitter waveforms, this capability will allow co-located systems to be spectrally aware of their surroundings and make decisions on how and where to transmit to protect themselves and to prevent interference with other communications and/or radar systems.
Keywords: SIGINT, SIGINT, Machine Learning, Radar, AESA, Automatic Recognition, Spectral Awareness, COMINT, Artificial Intelligence