ISR Signal Processing Brings Performance to Sensors and Enables AI at the Edge

September 28, 2018

ISR Signal Processing Brings Performance to Sensors and Enables AI at the Edge

Published in Military Embedded Systems.

Authored by John McHale, Editorial Director for Military Embedded Systems
 Tammy Carter, Senior Product Manager – GPGPUs & Software – Curtiss-Wright Defense Solutions

Military intelligence, surveillance, and reconnaissance (ISR) applications continue to make demands on signal-processing designers for more performance, better thermal management, and reduced size, weight, and power (SWaP). These systems - as they move closer to the sensor on various platforms - are also starting to enable artificial intelligence (AI) solutions at the edge.

Speeding up “sensor to shooter” time is a bit of a blunt term, as ISR sensor data sent to a warfighter does not always end with shots being fired. However, speeding up the filtering of data at the sensor level does shorten the time that it takes for actionable intelligence actually gets to warfighters, enabling them to make better, faster, and more informed decisions. Some call this new reality “shortening the sensor chain.”

To enable such performance, sensor systems integrators rely on high-­performance embedded signal-processing solutions that leverage the latest commercial processors and FPGAs [field-programmable gate arrays].

“Our [defense] customers want wider signal bandwidths, improved dynamic range, higher channel density, and lower cost per channel,” says Rodger Hosking, Vice President and Founder, Pentek (Upper Saddle River, New Jersey). “There is no ultimate ‘good-enough target’ for any of these parameters because each step of improvement opens up new applications, extends the range of deployment environments, increases detection range, improves acquisition of small signals in the presence of large ones, and accommodates the newer wideband spread-spectrum and encryption techniques for signals that must be captured and generated.

“As technology moves on wider bandwidths, applications can be deployed in different ways and with different cost profiles,” Hosking continues. “For example, lower-cost form-factor profiles now have functionality that was unaffordable before. Applications such as small drones are driving this. The drone needs to be able to detect a faraway small signal while there are large signals right next to it. Capturing that small signal is akin to pulling something out of a noisy environment – a difficult task made easier by modern signal-processing techniques.”

Increased bandwidths also mean increased use of all types of commercial processing elements. “Higher bandwidths mean more data and a larger variety of data set sizes,” says Tammy Carter, Senior Product Manager for OpenHPEC products for Curtiss-Wright Defense Solutions (Ashburn, Virigina). “We are seeing more systems that mix DSPs [digital signal processors], GPGPUs [general-purpose graphics processing units], and FPGAs, with no single technology taking over the whole signal-processing chain. Four or five years ago, I would’ve said that GPUs, as far as signal processing, were totally dead, but there has been a resurgence as defense integrators embrace the increasing throughput and decreased SWaP that GPUs bring to a system when compared to CPU-only solutions. Other factors include the ease of reconfigurability when compared to FPGAs and latency gains that can be achieved by data transfer directly to the GPU without having to go through the CPU.”

Read the full article here.

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