Tracking Very Low SNR Targets with the Quanta Tracking Algorithm

The Quanta Tracking (QT) algorithm is a fairly new algorithm that is showing very promising results tracking unresolved, dim targets in highly cluttered environments. Traditional detection and tracking approaches use thresholding and signal processing to declare measurements that are then fed into the tracker. The QT algorithm does this all organically in an optimal manner, called, “track-before-detect”. The algorithm requires no thresholding of the data such that all of the data is utilized. The question that always arises is what is the lowest Signal-to-Noise-Ratio (SNR)target that can be tracked by this algorithm? Initial results showed that dim targets down to -15 dB could be tracked reasonably well. Furthermore, it was found that the QT algorithm's performance against ever dimmer targets decreased gracefully without falling off of “a cliff.” In this paper, we explore a slightly different aspect of low SNR tracking of targets on a focal plane array (FPA). That is, we vary the parameters of the first SNR equation in a different manner that we believe is more controlled.