Extraction and optimal use of measurements from an imaging sensor for precision target tracking

Abstract

This paper deals with the extraction of measurements for precision tracking of the centroid of a target from a forward looking infrared imaging sensor. The size of the target's image is assumed to be small, i.e., around 10 pixels. The statistical characterization of the centroid of a frame as a noisy linear measurement of the centroid of the target is obtained. Similarly, the statistical properties of the image correlation of two frames, which measures the target offset, are derived. Explicit expressions that map the video noise statistics into measurement noise statistics are obtained. The offset measurement noise is shown to be autocorrelated. Following this, state variable models for tracking the target centroid with these measurements are presented. Finally, simulations and quantitative conclusions about achievable subpixel tracking accuracy are given. It is shown that the filter that models the autocorrelated measurement noise provides the best performance.