Radar technology plays a crucial role in a variety of industries, including defense, aerospace, automotive, and industrial monitoring. While traditional radar processing has long relied on FPGA-based architectures due to their real-time determinism and low latency, modern radar workloads increasingly demand advanced AI, flexible signal interpretation, and rapid algorithm evolution—areas where GPUs excel.
WOLF Advanced Technology delivers high-performance radar processing solutions that harness the power of NVIDIA GPUs, either as standalone accelerators or in tightly integrated FPGA + GPU hybrid systems. These solutions enable developers to leverage the real-time signal control of FPGAs alongside the parallel processing and AI capabilities of GPUs—unlocking new levels of radar performance, adaptability, and mission readiness.
GPUs can act as a more flexible and user-friendly processing platform that complements or even replaces certain FPGA workloads, particularly in applications involving signal classification, image formation, AI inference, or post-processing. As radar systems evolve beyond basic signal detection toward more sophisticated signal processing and interpretation, GPUs enable faster development cycles and easier experimentation with new algorithms and processing types, using familiar high-level programming environments like CUDA, OpenCL, and TensorRT.
This information paper explores the advantages of WOLF’s GPU and FPGA+GPU radar solutions, highlights specific use cases across military and aerospace domains, and details how leveraging NVIDIA GPUs in VPX and XMC form factors supports both traditional radar pipelines and next-gen AI-enhanced radar systems.