A High Performance Framework for Radar Clutter Suppression, Target Tracking and Identification

Detection, tracking, and identification of dim targets are challenging for the following reasons. First, MDA radars encounter strong clutter due to chaff and decoys. The manmade clutter can be non-Gaussian, non-stationary, and unpredictable. Second, the distance between radar and a target can be hundreds of miles, which make the radar returns very weak. Third, some target motions may be maneuvering, making the Doppler frequencies non-stationary and rendering the conventional techniques ineffective. Fourth, ballistic missiles may carry a number of decoys that confuse the radar detection. We propose a high performance system that can address all the challenges mentioned above. Our system is comprehensive and includes clutter suppression, target detection, target tracking, and target identification. State-of-the-art algorithms will be integrated into our system. In Phase I, we implemented the proposed framework and performed extensive simulations to validate its performance. Our simulations showed that we can detect dim maneuvering targets even when the raw data have a signal-to-clutter-ratio (SCR) of less than -70 dB, which is a significant result. In Phase II, we will develop a real-time system containing clutter suppression, target detection, target tracking, and target identification. Real-time demonstrations will be performed in a MDA base at the end of Phase II.