The US Missile Defense Agency (MDA) plans a software upgrade for its ballistic missile early warning radars to improve object classification during the midcourse phase of missile flight.
The improvement will enable the Upgraded Early Warning Radars (UEWR) to more accurately identify and track hostile ballistic missiles targeting the continental US.
Five UEWRs have been operational since the 2000s, with three in the US and one each in Greenland and the UK.
The radar is primarily designed to detect and track intercontinental ballistic missiles (ICBMs) and submarine-launched ballistic missiles, as well as to conduct general space surveillance and satellite tracking.
With a detection range of approximately 3,000 miles (4,828 kilometers) and 240 to 360 degrees of coverage, the phased-array sensor provides critical early-warning and tracking data to support missile interceptor launches and update target tracks during flight.
The UEWR is a key part of the Ground-Based Midcourse Defense (GMD) system, which is designed to protect the US homeland from long-range ballistic missile attacks.
Limited Effectiveness
Comprising 44 interceptors deployed in Alaska and California, the GMD system is designed to counter a limited number of ICBMs during their midcourse phase, when the missiles are most vulnerable to interception.
However, the system has demonstrated limited effectiveness against sophisticated or large-scale missile attacks, particularly in distinguishing actual warheads from decoys and other countermeasures.
To enhance the system’s classification capability, the MDA has implemented a phased radar software upgrade known as the Advanced Object Classification (AOC) program.
Radar Upgrade
By leveraging advanced signal processing algorithms and machine learning techniques, AOC improves target discrimination and tracking accuracy during the midcourse phase of an enemy missile’s flight, which typically lasts approximately 20 minutes.
The first version, AOC 1.0, has been tested and fielded across select UEWR sites since the early 2020s.
The forthcoming AOC 1.1 upgrade aims to further enhance classification performance without modifying existing radar hardware or waveforms, incorporating more advanced algorithms for object identification and threat assessment.
“While testing and fielding AOC 1.0, the Government identified minor algorithm opportunities as well as Interface Control Document-driven updates that must be incorporated into AOC 1.1,” an MDA source sought notice stated.
“Additionally, the Government envisions AOC 1.1 will have a flat-file classification database that can be re-configured without re-compiling software changes.
This capability will enable AOC rapid reconfiguration to address emerging threats without requiring the Government to return to the developer for software updates, assessments, or other modifications.”
