Detection advantages of spatial oversampling in imaging sensors

Cyan Systems has recently developed an approach to focal plane assembly (FPA) architecture which represent a significant advancement in information extraction from the data as it is being collected. This approach utilizes sub-pixels which achieve a high degree of oversampling of the sensors Point Spread Function (PSF), well beyond the Nyquist limit for a critically sampled sensor. The data contained in an oversampled image has the obvious advantage of readily discriminating between focal plane and object generated artifacts as the first step in false alarm rejection. This effect is particularly useful at identification of radiation events. However there are further advantages that can be exploited through nearest neighbor subpixel correlation, and pooling that achieves significant noise reduction and therefore improved sensitivity. In Cyan’s architecture these processes are accomplished for the first time at the input to the preamp in the ROIC. This approach not only allows improved fidelity in imaging, but further reduces false alarm rates, improves detection ranges, and demonstrates an improved ability to track closely spaced objects. The small pixels that enable this approach also ensure improved radiation hardness reducing the capture cross section. The architecture has been modeled and simulations run which illustrate the dramatic improvements possible.