凝视
抖动
计算机科学
探测器
性能指标
公制(单位)
光学
计算机视觉
人工智能
物理
工程类
电信
噪声整形
运营管理
经济
管理
作者
Ronald G. Driggers,Carl E. Halford,Michael J. Theisen,David M. Gaudiosi,S. Craig Olson,Gene Tener
出处
期刊:Optical Engineering
[SPIE - International Society for Optical Engineering]
日期:2018-05-04
卷期号:57 (05): 1-1
被引量:15
标识
DOI:10.1117/1.oe.57.5.053101
摘要
Operationally significant infrared search and track (IRST) systems have been primarily second-generation thermal imager technology with scanned time-delay-integration (TDI) detector operation. The benefit of the scanned technology provides for large aperture, gimbal-scanned sensors with extremely wide field of regard, but with low revisit rates. Dramatic progress in large format staring arrays has provided the possibility of higher performance systems with lower complexity. These large format infrared staring arrays may be able to provide systems with higher performance (due to detector count) with less complexity (fewer gimbal scan limitations). In fact, lower performance IRST systems may satisfy operational requirements without scanning or stare-step operation in a "strap-down" architecture. The first step in a full capability staring system IRST design requires a thorough knowledge of staring array IRST performance. This knowledge includes a basic understanding of signal to noise (SNR) in both undersampled and well-sampled systems, with and without a matched filter. For undersampled systems, unresolved targets result in low SNR in both the average case and worst-case scenarios. We assess (using SNR as our primary metric) how the staring IRST system benefits from typical staring operations, such as dither and stare step. We provide a comparison of staring IRST system performance in the midwave infrared (MWIR) and longwave infrared (LWIR) with three modes of operation: basic staring (no sensor movement), dither, and stare step. In addition, we introduce a metric that allows comparison of different types of IRST systems. We use this metric to compare the performance of MWIR and LWIR as well as staring, dither, and stare-step systems. In the future, we will compare scanned systems to staring IRST systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI