Model-based multisensor automatic target identification for FLIR fused with MMW

Mark K. Hamilton; Teresa A. Kipp

doi:10.1117/12.213094

5 July 1995 Model-based multisensor automatic target identification for FLIR fused with MMW

Mark K. Hamilton, Teresa A. Kipp

Proceedings Volume 2485, Automatic Object Recognition V; (1995) https://doi.org/10.1117/12.213094
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

This paper describes the US Army's efforts under the ATR relational template matching program to develop a multi-sensor forward-looking IR (FLIR) and millimter wave (MMW) radar automatic target recognition (ATR) algorithm. The general problem consists of identifying ground targets at low depression angles of less than 6 degrees and ranges of 500 to 6000 m. However, the algorithm is directly applicable to other target sets, including air targets, and ground targets at high depression angles. Our phase I goal was to provide a proof- of-principle demonstration of this new model-based methodology. We did this on simulated FLIR imagery for a three target class problem. A comprehensive test and evaluation was performed at the Night Vision and Electronic Sensors Directorate. Our goal in phase II was to demonstrate this new algorithm approach on realistic field-collected second-generation FLIR imagery with a larger target set consisting of ten ground vehicles. With phase III, our goal was to demonstrate multisensor fusion on FLIR (first generation) fused with laser radar. This was demonstrated on a four-ground-target-class problem. The limitations to first-generation FLIR data and four targets was due purely to restrictions of the field-collected data. Our goal in phase IV is to demonstrate this methodology for FLIR fused with MMW radar data. Phase IV will be a three-year effort, with the first year concentrating on using the MMW radar data for detection, reduction in false alarms, and the provision of accurate range (i.e., scale) to the FLIR algorithm. The goal of the second and third years will be to fuse the MMW data into not only the detection phase of the algorithm but also the recognition and identification portions of the algorithm. This paper presents the general model-based methodology used for the FLIR and the neural network methodology used to provide the FLIR with the MMW detections and scale. Results are provided for the FLIR-only algorithm for short range and moderate range scenarios given an accurate estimate of target range.

Citation Download Citation

Mark K. Hamilton and Teresa A. Kipp "Model-based multisensor automatic target identification for FLIR fused with MMW", Proc. SPIE 2485, Automatic Object Recognition V, (5 July 1995); https://doi.org/10.1117/12.213094

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