Paper
1 September 1991 Computer analysis of signal-to-noise ratio and detection probability for scanning IRCCD arrays
Gianni Uda, Alessandro Tofani
Author Affiliations +
Abstract
The loss of the energy falling on a IR CCD array due to the effect of finite image size of point targets and of its motion on the focal plane was computed through a Monte Carlo simulation. The aberration-free point spread function (PSF) of the system was supposed to move in the focal plane with spatial steps having an amplitude of the order of the linear scan velocity times the IR CCD integration time. The starting position of the motion was varied randomly near to a reference detector element and each position was assumed to have the same probability of occurrence. By considering the energy integrated by the single detectors it is possible to compute the effective signal-to-noise ratio and the overall detection probability of the system. A new figure of merit, called the spreading factor (SF), can be defined by considering the maximum ratio of the energy integrated by the single detectors to the total energy subtended by the PSF and by taking the average of these maxima over all the random displacements. With the parameters considered in this simulation, the SF turns out to be in the range between 0.2 and 0.5, with a considerable reduction of the corresponding detection range.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gianni Uda and Alessandro Tofani "Computer analysis of signal-to-noise ratio and detection probability for scanning IRCCD arrays", Proc. SPIE 1488, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing II, (1 September 1991); https://doi.org/10.1117/12.45807
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Sensors

Point spread functions

Signal to noise ratio

Infrared sensors

Computing systems

Systems modeling

Infrared imaging

Back to Top