The Missile Defense Agency (MDA) has the responsibility for developing a Ballistic Missile Defense System (BMDS) to defend the United States, its deployed forces, allies, and friends from a ballistic missile attack. TSC is working with the MDA to develop advanced innovative physics-based concepts for improving the BMDS discrimination performance.

Discrimination, distinguishing lethal objects from non-lethal ones, is the most central and challenging problem of ballistic missile defense. The primary objective of the entire missile defense shield is to neutralize the lethal warhead, but this task is complicated by the presence of a large entourage of other objects; the so-called threat complex. Some of these objects can be expected to have characteristics intended to confuse the BMDS decision authorities. TSC’s MDA work is focused on developing methods for producing good discrimination performance even in such stressing threat environments.

The BMDS addresses the missile threat in three phases of flight: boost, midcourse, and terminal, in three corresponding defense segments. Destroying the missile during the boost phase prior to any potential separation of midcourse decoys is clearly advantageous but challenging due to the short time frame of this flight phase. The midcourse phase provides much more time for discrimination.

TSC is currently working on discrimination concepts applicable to the boost and midcourse defense segments, developing them into mature computational algorithms, with the goal of deploying them on current and future missile defense sensors. TSC’s algorithm development is targeted to sensors operating with frequencies from UHF (~70 cm wavelength) through X-band (~3 cm wavelength).

TSC’s missile defense discrimination work is based on a combination of theory and observation. Our personnel have experience in analyzing ballistic missile flight test data collected by a wide range of radars. TSC maintains secure computer systems and special-purpose in-house developed software for this purpose. Flight test data analysis is valuable for suggesting new discrimination methods and for testing methods under development.

For more information please download the MDA Fact Sheet (PDF, 121KB).