Pattern-Theoretic Foundations of Automatic Target Recognition in Clutter

Pattern - Theoretic Foundations of Automatic Target Recognition

This effort advanced the art of applying Grenander's pattern theory to automatic target recognition (ATR) problems. We extended jump-diffusion ATR algorithms to accommodate unknown infrared camera calibration effects and include more stable diffusion procedures for pose refinement, and developed flexible shape models to accommodate clutter. We also developed performance bounds on estimation and...

Pattern-theoretic automatic target recognition for infrared and laser radar data

Clutter Removal in Sonar Image Target Tracking Using PHD Filter

In this paper we have presented a new procedure for sonar image target tracking using PHD filter besides K-means algorithm in high density clutter environment. We have presented K-means as data clustering technique in this paper to estimate the location of targets. Sonar images target tracking is a very good sample of high clutter environment. As can be seen, PHD filter because of its special f...

Robust detection of SAR/IR targets via invariance

One of the most challenging problems in automatic target recognition is reliable detection of targets in high clutter backgrounds. When the clutter statistics are unknown or highly variable, the false alarm rate of classical detection algorithms , e.g. the matched lter, cannot be controlled and target detections become unreliable. The reason for this is lack of robustness of the test statistics...

Radar Target Identification Using an Eigen-Image Approach

In support of the ARPA-sponsored Critical Mobile Target (CMT) program, MIT Lincoln Laboratory has developed a complete, end-to-end, 2-D SAR automatic target recognition (ATR) system. This baseline ATR system performs three basic functions: First, a CFAR (constant false alarm rate) detector locates candidate targets in a SAR image on the basis of radar amplitude. Next, a target-size matched filt...