Rapid Upgrades for Airborne Cognitive Sensing Systems
Deepwave’s platform delivers AI and high-performance computing for edge analysis. By integrating Deepwave’s software and hardware into the Containerized Algorithm Deployment System (CADS), aircraft gain low-latency situation awareness capabilities previously reserved for the most advanced airborne fleets.
CADS enables electronic warfare (EW) systems with modern, cognitive sensing to identify and prioritize complex threats at the tactical edge. An RTX and Deepwave partnership is behind CADS, and the main components include:
While AirStack software and AIR2302 Flight Series hardware are being deployed on fourth generation aircraft via integration with CADS, Deepwave’s RF AI edge solutions can scale to modern aircraft platforms.
Impact
Ensuring electromagnetic dominance in a crowded, contested spectrum is required for airborne fleet survivability. However, leveraging the latest cognitive sensing capabilities from commercial technologies is a constant challenge. Nimble adversaries continue to innovate, delivering advanced capabilities in areas such as jamming and cloaking. Even the newest aircraft are vulnerable.
CADS provides a path for modular, commercial product upgrades to deployed cognitive systems. This solution framework is specifically designed to reduce the complexity, time, cost, and technical debt associated with traditional fleet modernization. CADS can be deployed in days at a fraction of the cost of rip-and-replace upgrades, and it supports a simple upgrade path for future deployments.
How it Works
CADS addresses the complexity and cost challenges of enhancing airborne cognitive systems. The CADS framework achieves this technical feat by integrating modular edge AI and high-performance computing with the core cognitive system.
The software and hardware function as an independent coprocessor alongside legacy avionics. It pulls in wideband data and processes it at the edge to deliver immediate RF Intelligence. This sidecar design isolates heavy computing loads from critical flight controls. Operators receive real-time threat analysis without risking core system stability.
High-Performance Edge Software
Cognitive AI algorithms are the engines for extracting intelligence from complex, dynamic radio frequency (RF) data environments. However, these AI models require advanced computing resources that traditional systems lack. Deepwave’s AirStack Core software overcomes this limitation by enabling advanced AI models to run on high-performance edge computing platforms such as Deepwave’s AIR-T to augment existing cognitive sensing systems.
The AirStack Core operating system not only powers high-performance AI edge computing but also supports a wide range of AI model standards and machine learning operations (MLOps) tools and frameworks, such as PyTorch. This expands the utilization of existing AI investments and speeds model deployments to production environments.
AirStack Core is also designed to ensure AI integrity and security, which is a concern for all at-scale AI programs. The software provides FIPS-grade security and also supports secure MLOps workflows. A module to secure CADS AI model development is included with AirStack Core. This add-on, the Cognitive Application Virtual Environment (CAVE), is an open-standard digital twin that mirrors the AirStack Core software environment. CAVE allows developers to create, test, and refine AI algorithms on any computer, ensuring that the exact software environment can be deployed directly onto the AIR-T hardware without modification.
Edge Data Parsing Software
The CADS Data Parser software is the bridge that brings everything together. This container-based tool extracts data from an existing cognitive sensing system for additional analysis on the Deepwave AI edge platform. By translating from legacy, compressed, PCI bus traffic to modern JSON data streams, this parsing software is the key to enabling a modern computing stack on legacy platforms. It uses open standards frameworks to support high-performance edge and AI computing, ensuring MLOps interoperability and security.
Edge AI Hardware
Deepwave’s RF AI edge platform provides the advanced computing resources to power Cognitive AI algorithms. This edge platform augments existing cognitive systems through its modular hardware and software capabilities.
Deepwave’s AIR-T Flight Series is designed to power CADS. This RF AI edge platform serves as a modular, plug-in upgrade to bridge the gap between legacy hardware and modern AI systems. It supports installed sensing systems through its real-time execution of neural networks and cognitive algorithms, and its ability to simultaneously record wideband data.
Integration
The CADS framework reduces complexity, time, cost, and technical debt for modernizing cognitive sensing systems. Perhaps even more importantly, CADS provides a simple upgrade path for future deployments, enabling fleets to leverage the latest commercial cognitive capabilities.
Deepwave’s AirStack software delivers scalable, secure, high-performance AI edge computing through developer-friendly frameworks and toolchains. The AirStack software stack is simple to integrate and support, and scales across MLOps, command and control, and other technology platforms.
Deepwave’s AIR-T Flight Series hardware also plays its part to deliver AI and high-performance edge computing. While the AIR2302 is configured to support fourth generation aircraft interfaces, Deepwave’s Flight AIR-T platform is designed to scale across legacy and modern aircraft.
Take the Next Step
The CADS solution provides a rapid upgrade path for airborne cognitive sensing capabilities.
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AIR-T Flight Series