Abstract
A criterion and an algorithm of detecting dynamic objects (DOs) in a complex background formed by an intense cumulus and high-altitude cumulus are proposed. The object image has a small size (point image) and low contrast. The principle of DO detection is fractal-correlation: it is based on the use of sampling as a relationship of likelihood functions of similar alternative conditions: either “only complex background within the sight of an optoelectron device (OED)” or “DO on the complex background within the sight of an OED.” The DO detection algorithm is designed as a binary accumulator according to the most powerful local criterion. The critical limit of decision making is defined by the Neumann — Pearson lemma for the acceptable possibility of false detection of a DO. Simulation proves the algorithm to be highly effective.
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References
A. A. Khramichev, M. P. Koval’chuk, and V. B. Vasil’ev, “Technology for Determining the Spatial Frequency Characteristics of a Sky Background,” Vestn. MGTU “Antenny i Ustroistva Radio- i Opticheskogo Diapazonov,” Ser. Priborostroenie, 246–252 (2009).
G. J. Hahn and S. S. Shapiro, Statistical Models in Engineering Problems (John Wiley & Sons, Inc., 1967).
V. M. Shchigolev, Mathematical Processing of Observations (FML, Moscow, 1962) [in Russian].
A. A. Potapov, “Fractals, Fractional Operators, and Scaling Are the Basis for the New Methods of Data Processing and Fractal Synthesis of Radio Systems, Antennas, and Impedances,” in Proc. of the 20th Intern. Crimean Conf. “Microwave & Telecommunication Technology,” Ukraine, 39–46 (2010).
S. M. Borzov and O. I. Potaturkin, “Detection of Small-Size Dynamic Objects by a Moving Observation System,” Avtometriya 48 (1), 23–29 (2012) [Optoelectron., Instrum. Data Process. 48 (1), 18–23 (2012)].
V. S. Kirichuk and V. P. Kosykh, “Construction of a Multichannel Filter for Detecting Point Targets in the Image Formed by a Matrix Photodetector,” Avtometriya 48 (5), 82–92 (2012) [Optoelectron., Instrum. Data Process. 48 (5), 497–505 (2012)].
D. R. Cox and D. V. Hinkley, Theoretical Statistics (Chapman & Hall, 1974).
H. Cramer, Mathematical Methods of Statistics (Princeton University Press, 1946).
Yu. G. Sosulin, Theoretical Fundamentals of Radio Location and Radio Navigation (Radio i Svyaz’, Moscow, 1992) [in Russian].
R. M. Kronover, Fractals and Chaos in Dynamic Systems (Postmarket, Moscow, 2000) [in Russian].
S. Z. Kuz’min, Basics of Digital Processing of Radar Data (Sov. Radio, Moscow, 1974) [in Russian].
A. E. Basharinov and B. S. Fleyshman, Methods of Statistical Sequential Analysis and Their Applications (Sov. Radio, 1962) [in Russian].
G. M. Mosyagin, V. B. Nemtinov, and E. N. Lebedev, Theory of Optoelectronic Devices (Mashinostroenie, 1990) [in Russian].
L. E. Franks, Signal Theory (Prentice Hall, 1969).
B. A. Alpatov, P. V. Babayan, O. E. Balashov, and A. I. Stepashin, Systems of Automatic Detection and Tracking of Objects. Image Processing and Management (Radiotekhnika, Moscow, 2008) [in Russian].
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Original Russian Text © A.N. Katulev, A.A. Khramichev, O.V. Guzenko, 2015, published in Avtometriya, 2015, Vol. 51, No. 2, pp. 38–48.
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Katulev, A.N., Khramichev, A.A. & Guzenko, O.V. Criterion and algorithm for detecting dynamic objects in a complex background by a low-contrast point image. Optoelectron.Instrument.Proc. 51, 134–143 (2015). https://doi.org/10.3103/S8756699015020053
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DOI: https://doi.org/10.3103/S8756699015020053