Emerging Technologies in FPGAs and Custom ASICs for Aerospace and Safe-Critical Applications

Dear Colleagues,

The design of embedded systems for Aerospace and Safety-Critical applications represents a critical field of application where extreme performance requirements are combined with very harsh operational environments. Unlike consumer electronics, where design cycles prioritize cost and rapid iteration, Aerospace systems—such as satellite payloads, radiation-hardened space computing— and Safety-Critical systems demand high reliability, real-time deterministic processing, and long-term survivability. At the heart of these modern systems lies a strategic choice between two primary hardware architectures: Field-Programmable Gate Arrays (FPGAs) and Custom Application-Specific Integrated Circuits (ASICs).

The shift toward Software-Defined Defense has made FPGA and ASIC research more vital than ever. As threats evolve, the ability to update a satellite's radar algorithms mid-flight via FPGA reconfiguration provides a "future-proof" advantage that fixed hardware cannot match. Conversely, the push for Edge AI in autonomous drones necessitates the extreme power efficiency that only custom ASICs can provide. Ultimately, advancements in this field do more than just improve hardware; they enable the next generation of global security and space exploration, ensuring that mission-critical systems remain functional when there is no possibility of manual repair.

This Special Issue focuses on the advancements, architectures, and applications based on FPGA/ASIC designs for next-generation embedded systems for aerospace and safety-critical applications. Specifically, we aim to address ionizing radiation (cosmic rays and solar particles), which can cause Single-Event Upsets (SEUs)—spontaneous bit-flips in memory—or permanent hardware damage like Single-Event Latch-up (SEL) and provide hardware-level security as well. We encourage submissions that explore embedded systems based on RISC-V as a key element to avoid the use of proprietary architectures and commercial giants, allowing the desired technology sovereignty. Additionally, we invite research that leverages Digital Signal Processing (DSP) and Machine Learning (ML) to enhance the performance, reliability, and adaptability of these embedded systems but considering the Size, Weight, and Power (SWaP) analysis and optimizing the implementation of these DSP/ML elements in terms of area and power consumption.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• Innovative Digital Signal Processing (DSP) and machine learning (ML) hardware and software solutions for embedded applications;
• Innovative techniques to handle ionizing radiation in embedded applications;
• Security and privacy algorithms and solutions in AI-driven embedded systems;
• Hardware–software co-design and methodologies to optimize the performance and energy consumption of embedded applications;
• Advanced RISC-V-based systems for aerospace applications;
• Soft and hard IP cores in embedded system design;
• Verification, analysis, and validation techniques of embedded systems;
• Deploying neural networks on RISC-V;
• Techniques of low-power design in embedded systems.

We look forward to receiving your contributions that will not only broaden the academic understanding of FPGA/ASIC/RISC-V designs and implementations for aerospace/defense applications but also inspire the industry to adopt and implement these advanced technologies to meet the application demands of the future.

Dr. Ainhoa Cortés
Dr. Andoni Irizar
Guest Editors

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