Title :
MUltiSensor Target Recognition System (MUSTRS)
Author :
Forman, Arthur V., Jr. ; Brown, David B. ; Hughen, James H. ; Pressley, Rebecca R. ; Sanders, Albert R. ; Sullivan, Daniel J.
Author_Institution :
Electron. & Missiles, Martin Marietta Technol. Inc., Orlando, FL, USA
Abstract :
The paper describes the Advanced Research Projects Agency (ARPA) MUltiSensor Target Recognition System (MUSTRS). A smart sensor manager controls forward-looking infrared (FLIR) and millimeter wave (MMW) radar sensors to obtain multiple looks at targets on the ground. Targets in IR images are recognized using a variation on minimum average correlation energy (MACE) filtering and/or a model-based algorithm called key features. Radar data are processed using quadratic distance composite filtering techniques. Evidence is combined using a Bayesian method. The system has been designed to correctly classify time critical mobile targets with very low false alarm rates
Keywords :
Bayes methods; correlation methods; filtering theory; image recognition; infrared imaging; military systems; radar imaging; radar signal processing; radar target recognition; sensor fusion; Bayesian method; IR images; MACE; MUSTRS; MUltiSensor Target Recognition System; false alarm rates; filtering; forward-looking infrared data; key features; millimeter wave radar sensors; minimum average correlation energy; model-based algorithm; multiple look; quadratic distance composite filtering; smart sensor manager; Bayesian methods; Filtering; Filtering algorithms; Hardware; Image recognition; Infrared sensors; Intelligent sensors; Millimeter wave radar; Millimeter wave technology; Missiles; Radar imaging; Synthetic aperture radar; Target recognition;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342514
