A Multi-Dimensional Hough Transform-Based Track-Before-Detect Technique for Detecting Weak Targets in Strong Clutter Backgrounds

The Hough transform (HT) algorithm detects straight-line features in two-dimensional data. This correspondence extends the HT to N -dimensional data to efficiently combine multiple first-threshold crossings from moving targets. The data dimensions can be the target position, its range and range-rate, and/or the first-threshold crossing times. This multi-dimensional HT (MHT) technique can be applied to enhance the detection of targets in random clutter backgrounds through the application of track-before-detect (TBD) processing.