ESD eBook September/October 2026: Rethinking Mil/Aero System Design
Embedded engineers designing military and aerospace systems traditionally have built hardware devices and systems around the need for ruggedness and military-grade components to ensure operation in harsh environments while meeting size, weight, and power (SWaP) budgets. As mission-critical systems from electronic warfare equipment to military drones become more intelligent and complex, designers face challenges around the need for more compute capability, modular design, secure connectivity, and software-driven functionality.
In the ESD September/October 2026 eBook, we look at how embedded system design for aerospace and defense is changing to meet new autonomous and edge AI requirements. We also see how core components such as advanced RF devices, processors, field-programmable gate arrays (FPGAs), sensors, and modular solutions enable real-time control and mission-critical workloads while meeting safety and reliability requirements.
Building hardware to tolerate harsh environments with ruggedized packaging, military-grade components, and rigorous qualification testing is no longer sufficient, reports contributing writer Filippo Di Giovanni. Modern aerospace and defense platforms require higher levels of integration, heterogeneous compute architectures, AI accelerators, high-speed connections, software-driven functionality, and cybersecurity to enable new mission capabilities at the cost of greater design complexity, he said.
Among those new applications are unmanned aerial vehicles (UAVs). On-board autonomy is changing the way developers fit compute, sensors, and software in tight SWaP constraints.
Contributing writer Abhishek Jadhav finds that the embedded architecture of UAVs is evolving as more intelligence moves from the remote operator to the aircraft. He explains that when RF links are disrupted or GPS becomes unavailable, the UAV must perform navigation, perception, and other time-sensitive functions locally, which changes the computational requirement.
Jadhav also explores how modular computing provides an upgrade path for aerospace computing, addressing cost, lifecycles, processor obsolescence, rising compute demands, and certification challenges in avionic systems.
Traditional avionics programs primarily need modularity to manage long service lives, but advanced drones need it to keep up with faster changes in AI, software, and cybersecurity, Jadhav said. A computer-on-module gives aerospace developers a modular upgrade path by separating the dynamic computing layer from slower-changing application-specific electronics, eliminating the need for a complete board redesign, he added.
Contributing writer Saumitra Jagdale finds that modularity makes it quicker to update hardware, particularly in UAVs/drones, when trying to introduce edge inference capabilities. Components responsible for flight, navigation, combat, and logistics leave limited room for adding computational capabilities to meet SWaP-C (cost) requirements.
Contributing writer Giordana Francesca Brescia examines the factors impacting the selection between microcontrollers, FPGAs, and system-on-chips for critical aerospace and defense applications and explores chiplet-based FPGAs for greater flexibility and reliability.
Technology is also improving for RF systems. Contributing writer Stefano Lovati looks at advances in RF systems such as direct RF sampling, GaN semiconductors, and software-defined radio processing.
Contributing writer Sonu Daryanani explains why sensor fusion is important for drone navigation and detection. He reports that the combination of multiple sensors with real-time AI algorithms improves overall system robustness, reliability, and accuracy in challenging environments.
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Cover image: Adobe AI Generated
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