Adaptive target recognition

被引:7
作者
Bhanu, B [1 ]
Lin, YQ [1 ]
Jones, G [1 ]
Peng, J [1 ]
机构
[1] Univ Calif Riverside, Ctr Res Intelligent Syst, Riverside, CA 92521 USA
关键词
target recognition; reinforcement learning; parameter learning;
D O I
10.1007/s001380050113
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Target recognition is a multilevel process requiring a sequence of algorithms at low, intermediate and high levels. Generally, such systems are open loop with no feedback between levels and assuring their performance at the given probability of correct identification (PCI) and probability of false alarm (Pf) is a key challenge in computer vision and pattern recognition research. In this paper, a robust closed-loop system for recognition of SAR images based on reinforcement learning is presented. The parameters in model-based SAR target recognition are learned. The method meets performance specifications by using PCI and Pf as feedback for the learning system. It has been experimentally validated by learning the parameters of the recognition system for SAR imagery, successfully recognizing articulated targets, targets of different configuration and targets at different depression angles.
引用
收藏
页码:289 / 299
页数:11
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