Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to labs and cloud servers—they’re now operating at the edge in space. From satellites to deep space probes, missions increasingly depend on onboard AI/ML to analyze data, detect anomalies, and make decisions without relying on ground stations.

This evolution is reshaping electronic warfare (EW) in orbit. AI-enabled EW systems are vital for jamming detection, spectrum awareness, and autonomous threat response. To support these capabilities, the aerospace and defense industry is adopting space-qualified processors like GPUs and NPUs, alongside cyber-resilient software.

Modular Open Systems Architectures (MOSA) are also key. Mercury Systems leverages standards like SpaceVPX for modular electronics, SOSA™ for sensor interoperability, and OpenVPX™ for rugged computing. These frameworks allow rapid integration of new AI/ML tools and future-proof systems for evolving mission needs.

Real-Time Intelligence at the Edge

Space platforms generate vast amounts of data—from Earth observation to threat detection. Transmitting this data to Earth is slow, costly, and vulnerable. Onboard AI/ML solves this by enabling satellites and spacecraft to process data locally, reducing latency, conserving bandwidth, and operating autonomously.

This is especially critical for:

  • LEO constellations performing dynamic tasking and threat monitoring.
  • GEO platforms managing complex sensor fusion and signal analysis.
  • Deep space missions requiring autonomous fault detection.
  • Defense payloads executing time-sensitive targeting and SIGINT.

Accelerating AI with Space-Ready Hardware

Modern AI models like convolutional neural networks and transformers demand high-performance computing in space, which requires:

  • Radiation-tolerant GPUs for high-throughput AI/ML.
  • Low-power NPUs for autonomous inference and EW decisions.
  • Heterogeneous architectures combining CPU, GPU, and FPGA resources.

These technologies enable image and signal classification, threat localization, sensor fusion, and autonomous navigation—even in communication-denied environments. Systems must be engineered for radiation resilience, thermal control, and fault tolerance to perform reliably in orbit.

Mercury’s AI Platforms in Space

Mercury’s SCFE6933 SpaceVPX board, built on AMD Versal™ AI Core adaptive SoCs, exemplifies how radiation-tolerant, MOSA/SOSA-aligned platforms can handle ML inference, beamforming, and SDR in space. These systems empower spacecraft to adapt quickly, respond intelligently, and operate independently across LEO, GEO, and deep space.

Real-World Impact

Mercury’s AI/ML and EW solutions are already supporting critical space missions. In LEO, ISR satellites use onboard image recognition for rapid object classification. Agentic AI systems enable high-level decision-making at the edge, reducing latency. GEO weather platforms analyze sensor data in real time to improve forecasting. Deep space probes rely on ML for autonomous fault recovery. Defense payloads use AI for targeting and threat classification.

All these systems are built to endure radiation and thermal extremes in the most unforgiving environments.

To explore how Mercury’s space-qualified AI and EW systems can elevate your mission, reach out to sales@mrcy.com.