IR pixel size optimization from a tracking perspective

This paper considers the optimal resolution cell (pixel) size in detection and tracking IR targets. Using refined resolution can help localizing the position of the targets precisely. However, along with a smaller resolution cell the signal power in each resolution cell becomes lower, because a point target is recorded as a blur according to the point spread function (PSF). Meanwhile, since the noise power is proportional to the area of the pixel, the noise is also lower. On the other hand, using coarse resolution (which is the result of opting for a high signal power in the resolution cell) renders less accurate target position estimates together with higher noise power. That is, as the pixel size changes there is a trade-off in terms of detection performance versus estimation accuracy. We submit that the only defensible way to rationalize this is from system level concerns: what is best for tracking? We will first look at the initial state estimation of a constant velocity target. Relationships between the Cramer-Rao lower bound for the initial state estimation and the resolution cell size will be established. Then, from a general target tracking perspective, the pixel-size effects on the probability of detection and the target location centroiding accuracy will be analyzed.