Paper
18 May 2006 Nonimaging detection of target shape and size
Author Affiliations +
Abstract
Estimation of a remote object's physical characteristics, such as size, shape and optical cross-section (OCS) can provide valuable strategic and tactical information. Imaging systems, such as those employing adaptive optics, can provide excellent images of space objects through a corrupting atmosphere. However, such systems are extremely expensive when thought of from the viewpoint of queuing sensors. A queuing sensor may interrogate a target of interest on a regular basis and if substantial changes in target characteristics are discovered, the sensor can alert an imaging system to investigate. The techniques discussed in this paper use only the total received time-series signal from a laser illumination experiment. The authors have specialized in the analysis of such signals and have shown that estimates of laser pointing disruptions, known as jitter and boresight, may be made using χ2 tests. Moreover, these estimates, as well as others, may be performed in real time, far more useful than post-processing. Nukove is currently supported by an AFOSR Phase II STTR to develop a prototype software tool to provide realtime estimates and the technique has been demonstrated successfully in a laboratory environment. This paper studies the potential for a well-controlled system to determine approximate target size and shape using statistical χ2 techniques similar to the pointing techniques. Moreover, such estimates may be made in realtime. Since the data is taken from a full aperture and not a focal plane, effects such as speckle and scintillation, which corrupt imaging systems, have been shown to have little impact when the receiving aperture is on the order of one meter or larger.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Susan Chandler and Gordon Lukesh "Nonimaging detection of target shape and size", Proc. SPIE 6234, Automatic Target Recognition XVI, 62340B (18 May 2006); https://doi.org/10.1117/12.663335
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KEYWORDS
Speckle

Scintillation

Data modeling

Imaging systems

Target detection

Monte Carlo methods

Optical simulations

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