Multistatic signature feature estimation for improved target discrimination

In order to successfully identify a lethal object in a ballistic missile launch complex it is important to have a good description (or image) of the interrogated area. Radar’s ability to interrogate and accurately characterize complex target environments is of great importance for missile defense. Large targets and high resolution surveillance radar systems provide multiple raw detection data depending on a target’s orientation to the radar. We are proposing a novel radar signal processing algorithm that estimates the reflectivity of complex target systems containing multiple objects while intelligently using multiple existing radar assets. The proposed approach has several advantages as compared with the traditional discrimination imaging techniques. First, it requires only a single coherent pulse interval (CPI) to be processed at the receiver(s) although multiple CPIs may be used for better accuracy. Second, it is well suited to utilize signals from multiple sensors. Third, since the approach is based on processing signals that are passed through a traditional matched filter bank it is relatively easy to implement on existing systems. And fourth, resultant processing can be performed numerically without human image interpretation.