Published in Military Embedded Systems
Military users of signal processors seemingly want it all: parts that can process more data but be less detectable to the enemy, transmit data more quickly but don’t heat up from the effort, and operate at extremely powerful levels but are lightweight and ideally palm-sized. These requirements present an obvious challenge for engineers designing these processors for intelligence, surveillance, and reconnaissance (ISR) applications. The various solutions to these ISR demands involve artificial intelligence, machine learning, classification algorithms, and sensor fusion.
The amount of data that needs to be processed in intelligence, surveillance, and reconnaissance (ISR) applications is nearly endless and frequently comes from varying sources. Identifying specific objects of interest within this barrage of data requires a very sophisticated level of processing; on top of the sheer amount of material coming in, much of the information is often very sensitive.
“The amount of data to be processed continues to increase,” says Shaun McQuaid, director of product management at Mercury Systems in Andover, Massachusetts. “What we’re dealing with is often called a ‘big data problem,’ which needs to be solved on the platform itself, and I think this is a trend we’re seeing more and more of. In order to deal with big data problems, you have to be able to leverage a data center solution, which is what we’re focused on here.”
In other words, the ability to take that glut of sensor data and make sense out of it requires a huge amount of processing on the platform, a process that enables users to sift through the signals on the receiving end and decide which countermeasures should follow. All of this requires acquisition and translation of real-time ISR imagery – or quickly and efficiently making sense of the data being recorded – a processing capability that calls for significant speed and power.
These considerable modern-day processing requirements have led to what industry professionals claim to be revolutionary design characteristics. Driving the thought behind ISR processors’ builds now are trends including machine learning-enabled information extraction; significantly reduced size, weight, and power (SWaP); and the ever-increasing demand for higher bandwidth.
“The ability to detect objects of interest, while filtering out noise and transmitters that you don’t want to see, requires a never-ending increase in the amount of processing capability needed,” says Denis Smetana, senior product manager, DSP products, at Curtiss-Wright in Ashburn, Virginia. “The trend has always been to continue to exploit and leverage new developments within computer architectures and capabilities.”