Realtime Defense Imaging & Sensing

A project by Concurrent EDA LLC.

Product

In modern defense environments, imaging and sensing systems must operate at speeds that leave no room for delay. Missions depend on the ability to capture high‑bandwidth sensor data, process it immediately, and deliver reliable results in real time. Whether the task involves tracking a fast‑moving target, stabilizing a weapons platform, guiding a missile, or fusing data from multiple sensors, the system must convert raw data into decisions within microseconds.

The end application described here is a real‑time defense processing system designed for airborne ISR platforms, stabilized optics, targeting units, electronic warfare payloads, and other edge‑deployed systems. These platforms cannot rely on traditional CPU or GPU pipelines that depend on full‑frame buffering or large memory transfers. Even a few milliseconds of latency can reduce accuracy or compromise mission outcomes.

The product is therefore not a single device, but a mission‑critical capability. It is a streaming, FPGA‑accelerated processing chain that begins computation the moment data leaves the sensor. It enables defense customers to achieve deterministic performance, extremely low latency, and reliable operation in environments where conventional computing hardware cannot meet the timing requirements.

Implementation

The system is built around a continuous streaming architecture. Instead of waiting for full frames or performing multi‑stage transfers through DRAM or PCIe, the FPGA fabric processes the incoming data as it arrives. This eliminates the bottlenecks that normally occur in CPU or GPU systems and allows the processing chain to maintain microsecond‑level responsiveness.

At the front end, high‑speed image sensors, SWIR detectors, or RF receivers generate raw data streams at very high bandwidth. These streams feed directly into an FPGA or RFSoC module. Trenz SoMs provide the hardware foundation for this stage. They integrate FPGA logic, ARM processors, high‑speed transceivers, memory interfaces, and industrial‑grade power management in a compact, production‑ready form factor.

Inside the FPGA, the data is processed in a fully pipelined flow. Operations such as flat‑field correction, radiometric normalization, noise reduction, lens distortion correction, feature extraction, motion compensation, and region‑of‑interest selection occur without buffering. Because the data never leaves the streaming path, latency remains extremely low and fully deterministic.

Concurrent EDA provides the algorithm‑to‑FPGA expertise that makes this architecture practical. Their engineers take customer algorithms for tracking, stabilization, detection, or sensor fusion and convert them into optimized FPGA pipelines. These pipelines are deployed in smart cameras, frame grabbers, airborne processing units, or RFSoC‑based systems. The result is a hardware implementation that matches the customer’s mission requirements while maintaining predictable timing behavior.

On the ARM cores, a lightweight Linux environment handles configuration, communication, and system‑level control. The software layer remains simple because the FPGA performs the computationally intensive work. It manages ISP parameters, networking, health monitoring, and secure boot functions without adding latency to the processing chain.

The final system is compact, power‑efficient, and suitable for deployment in harsh or space‑constrained defense environments.

Impact

The combination of Trenz SoMs and Concurrent EDA’s FPGA design expertise provides clear benefits in cost, schedule, and operational capability.

Time‑to‑market improves because Trenz SoMs remove the need for custom high‑speed PCB design, power optimization, and signal‑integrity work. Concurrent EDA accelerates the algorithm integration phase by using proven FPGA development flows. Together, they reduce development cycles from years to months and allow customers to field new capabilities quickly.

Development and lifecycle costs are lower because off‑the‑shelf SoMs reduce hardware NRE and simplify long‑term maintenance. Supply chain risk is minimized through stable module availability. FPGA‑based processing also reduces system‑level cost by eliminating GPUs, industrial PCs, large heat sinks, and additional security hardware.

SWaP‑C performance improves because FPGA‑accelerated systems consume less power, generate less heat, and fit into smaller enclosures. This is essential for airborne, handheld, or soldier‑worn platforms where size and power budgets are limited.

Operational performance increases significantly. By processing data as it arrives, the system achieves microsecond‑level latency instead of millisecond‑level delays. This improves tracking accuracy, stabilizes control loops, enhances detection in low‑light or high‑speed scenarios, and ensures deterministic behavior under all conditions. For defense customers, this translates directly into better mission outcomes and higher reliability.

The partnership between Trenz and Concurrent EDA gives customers a fast, cost‑effective path to high‑performance real‑time processing. It combines robust, production‑ready hardware with deep expertise in FPGA‑based algorithm implementation, resulting in a solution that is both technically advanced and practical to deploy.

Contact:
Concurrent EDA LLC
5001 Baum Blvd, Suite 640
Pittsburgh, PA 15213
https://www.concurrenteda.com/

Trenz Electronic’s products are available worldwide through a network of authorized distributors. In North America, Trenz Embedded provides direct coordination and support. We look forward to hearing from you and exploring how we can support your design and development needs.