Harnessing the full power of sensor fusion
The Army is refining tools and techniques that synthesize intelligence for ground operations
Sensor fusion and dissemination is all about getting left of the boom. In other words, the goal of sensor fusion is to have actionable intelligence before the detonation of an improvised explosive device rather than to the right, or after, the device has exploded.
That challenge requires collecting raw data from dozens of sensor sources and reconciling data so multiple sensors that pick up intelligence about the same target don't indicate that the data is from multiple targets. In addition, the data needs to be structured properly and then shared in real time for uses such as targeting or transferred to a database for future uses such as convoy planning.
All those functions need to be invisible to users.
“It’s about disseminating the right information,” said Brig. Gen. Thomas Cole, the Army’s program executive officer for intelligence, electronic warfare, and sensors at Fort Monmouth, N.J. “It’s no different than when you’re driving down the road in your car and you want to know what’s going on in the road in front of you and you have some display in your car that tells you ‘traffic is congested.’ You don’t care whether that comes from a satellite or from an [unmanned aerial vehicle] or from a policeman standing in the road putting data into a handheld device. It can be from any source. And then, the more sources you have, the better picture you have on what is going on.
“The same is true of the soldier," Cole said. "The soldier doesn’t care where the data is coming from. They just want to know reliably and timely what’s going on in their immediate vicinity.”
The Army’s primary tool for sensor fusion and dissemination is the Distributed Common Ground System-Army, which is one of the eight project managers in the Program Executive Officer for Intelligence, Electronic Warfare and Sensors. DCGS-A is responsible for the collection, reconciliation, normalization and dissemination of sensor data. One of the primary challenges for the unit is dealing with the constant stream of new sensor capabilities and volume of data that they produce.
“Older UAVs have analog [electro-optical, infrared] sensors; newer sensors provide digital data of high-definition quality,” said Kam Lok, acting chief engineer at DCGS-A. “The native form of data today requires a significant increase in bandwidth to bring data from the sensor platform to the ground for processing. Storage capacity for digital information must also increase.”
A number of enhancements to DCGS are being developed to deal with those issues, both for the short and long term.
Deployment of DCGS-A Version 3 systems to brigade combat teams and battalions in Iraq and Afghanistan is 70 percent complete. By the time it is 100 percent complete in late fiscal 2010 or early fiscal 2011, the Army will be moving toward the next-generation DCGS, which it calls Mobile Basic. Scheduled for deployment in fiscal 2011 with user tests in mid-2011 and a production decision by late 2011, Mobile Basic will eventually reduce the number of vehicles carrying DCGS sensors from 27 to nine.
“The challenge is dealing with the legacy equipment and software and bringing that into Mobile Basic rather than creating everything from scratch,” said Lt. Col. Scott Hamann, product manager of DCGS-A Mobile Systems.
In the long term, the DCGS organization is looking at what it calls the Tactical Signals Intelligence Super Cloud. “We’re looking to make the DCGS global enterprise more similar to commercial counterparts like Google where they have huge server farms,” said Sam Fusaro, deputy project manager of DCGS-A. “Now the computing is done within the current systems themselves.”
An initial prototype is expected to be tested in late fiscal 2010, with large-scale testing and development not expected until after fiscal 2012.
The DCGS-A team wants to get to the point where it is not only reporting data, but also predicting actions based on the data.
“We do an excellent job of normalizing and deconflicting data and of giving that one common picture of everything going on at present,” Fusaro said. “Where we need to improve is in taking what’s going on in a current situation and, with confidence, predict what will happen based on what we’re witnessing — predictive analysis. We’re missing a technology piece...a better algorithm that simulates gray matter and how commanders think. We haven’t been able to model the cognitive process yet.”
Such predictive patterns would give soldiers sufficient agility to predict enemies' patterns, said Lt. Col. Thomas Gloor, product manager of DCGS-A Intelligence Fusion.
And that ability would help the Army get left of the boom.
Barry Rosenberg is editor-in-chief of Defense Systems. Follow him on Twitter: @BarryDefense.