Advanced Radar Data Fusion

In Phase II, TSC proposes to further develop and validate a novel approach to multisensor 3D radar imaging and simultaneous motion parameter estimation, which was successfully demonstrated in Phase I. 3D radar images produced by TSC’s algorithm offer a means of estimating the size of targets in three dimensions, a key discriminant for robust object discrimination. TSC’s Phase I approach will be refined and applied to government-provided threat based target models, scenarios and radar systems during Phase II. TSC’s technique simultaneously generates 3D volumetric radar images and estimates the precise target rotational state of targets in ballistic torque-free motion using one or more radars. TSC’s 3D radar imaging methods are an innovation over traditional radar discrimination features such as RCS statistics and apparent length, which are derived from time-dependent radar signatures and do not estimate genuine invariant properties of the target or its motion state. 3D radar images are referred to a body-fixed principal axis coordinate frame which is the same for all radars that view the target at any time during the exoatmospheric midcourse stage of flight, greatly simplifying the task of registering images for true data level fusion compared to conventional approaches.