Paper
5 June 2013 Mean time for target acquisition in collaborative search with multiple imaging sensors
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Abstract
In this paper the mean time to acquire a stationary target by n stationary imaging sensors is computed using probability theory by making use of the well established result that the detection time for a single imaging sensor is a random variable from an exponential probability density function. Each imaging sensor is characterized by a separate P∞ value which describes the probability an observer using that sensor will eventually acquire the target and a separate t value which describes the mean time to acquire the target using that sensor. There is no restriction on the wavelength band used by the imaging sensor. There are no empirical constants in the model presented here and the results are in agreement with and generalize previously published equations. The newly developed equations have been verified by numerical simulations and also yield the expected mean detection time for all limiting values of the input parameters. The code used in the numerical simulations is exhibited. For any given scenario, the separate τ observer-sensor-target parameters P∞ and t can be estimated using the NV-IPM model or measured in perception experiments. Thus the input parameters needed by the model are generally available. Comparing results presented here with results from war game simulations such as OneSAF may improve the quality of both products.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Melvin Friedman "Mean time for target acquisition in collaborative search with multiple imaging sensors", Proc. SPIE 8706, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIV, 87060E (5 June 2013); https://doi.org/10.1117/12.2018349
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Target detection

Optical sensors

Target acquisition

Computer simulations

Probability theory

Binary data

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