Multi-Sensor Tracking and Fusion for Space Radar Application

A constellation of Space Radar (SR) sensors provides the capability to track surface moving targets to a high degree of accuracy. The incorporation of target characterization information from High Range Resolution (HRR) and Inverse Synthetic Aperture Radar (ISAR) modes into tracking and fusion (TAF) algorithms provides enhanced information to the intelligence analyst and decision maker. This study will examine the ability of multiple sensors to provide accurate position and identity of moving targets. Extremely accurate states are required to support imaging algorithms used to discriminate military targets from civilian targets. Accurate imaging of targets of interest requires sub-meter range accuracy as well as precise knowledge of the target heading which is related to the velocity vector accuracy. The tracking algorithms must provide range accuracy on the order of meters depending on the target spacing and scenario; the imaging pre-processing algorithms can reduce this error to levels approaching fractions of a resolution cell. Stringent requirements on heading accuracy may be obviated by the use of prominent point tracking in the case of ISAR images. The Radiance tracking and fusion (TAF) Tool has been used to investigate a number of different types of multi-platform radar sensor architectures.