What's new

U.S. Army awards Leidos $34 million for reconnaissance systems

Zarvan

ELITE MEMBER
Joined
Apr 28, 2011
Messages
54,470
Reaction score
87
Country
Pakistan
Location
Pakistan
Photo by Mark Harkin

Leidos Inc. secured $34.3 million for research, development, test and evaluation support to intelligence, surveillance and reconnaissance (ISR) weapon systems, according to a May. 25 announcement.

The contract modification reportedly provides for the manufacturing and delivery of a new multi-sensor reconnaissance system to equip DHC-8 fixed-wing aircraft.

Work will be performed in Reston, Virginia, with an estimated completion date of June 13, 2022, according to the U.S. Department of Defense contract announcements.


Fiscal 2021 research, development, test and evaluation, Army funds in the amount of $25,895,386 were obligated at the time of the award.

According to Army’s website, the reconnaissance system on the DHC-8 platform is designated the Airborne Reconnaissance Low-Enhanced or ARL-E. It is the Army’s newest manned multisensor, day and night, all-weather AISR system.

ARL-E consists of a modified DHC-8-Q315 fixed-wing aircraft equipped with a reconfigurable payload with enhanced COMINT and IMINT sensors including long-range Ground and Dismounted Moving Target Indicator/Synthetic Aperture Radar high-definition EO/IR FMV, and Hyperspectral Imagery. The sensors are controlled and operated using onboard Distributed Common Ground Station-Army (DCGS-A) multifunction workstations. Intelligence collected on the ARL-E can be analyzed and disseminated in real time; transmitted via Beyond Line of Sight satellite communication; or stored onboard for post-mission analysis.

If you wish to report grammatical or factual errors within our news articles, you can let us know by using the online feedback form.

If you would like to show your support for what we are doing, here's where to do it: patreon.com/defenceblog

Executive Editor

U.S. Army awards Leidos $34 million for reconnaissance systems (defence-blog.com)
 
.
Back
Top Bottom