Staring Array Infrared Search And Track Performance With Dither And Stare Step

Keywords

imaging systems; infrared; infrared search and track

Abstract

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.

Publication Date

5-1-2018

Publication Title

Optical Engineering

Volume

57

Issue

5

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1117/1.OE.57.5.053101

Socpus ID

85046703421 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85046703421

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