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Improvement of the performance evaluation algorithm of discernment of the thermal images with a high level of radiation intensity

Keywords:

V.N. Sanin - Dr.Sc. (Phys.-Math.), Professor, Department “Physics and chemistry”, Military-Air Academy named after Professor N.E. Zhukovsky and Yu. A. Gagarin (Voronezh) Е-mail: svn616039@gmail.com A.V. Ivantsov - Dr.Sc. (Military), Associate Professor, Military-Air Academy named after Professor N.E. Zhukovsky and Yu. A. Gagarin (Voronezh) Е-mail: kagan13@yandex.ru N.N. Shamshin - Graduated in a Military Academy, Military-Air Academy named after Professor N.E. Zhukovsky and Yu. A. Gagarin (Voronezh) Е-mail: shamshin2012@ yandex.ru


Currently known methodological apparatus that allows you to select images from a set of quantum characteristics of the received optical radiation incident on the sensing elements of the receiver of optical radiation (PSI) working in bliznetsova region of the IR range. The information accumulated on the sensitive elements of the matrix of charge coupled devices (CCD) POI represents the absorbed radiation photons emitted from the surface and having different quantization levels, as reflected from the object heat flows differ by the value of their initial energy. In the case when received signals represent the additive mixture of the useful radiation and interference (noise) component , characteristic of the weak contrast of the object to the surrounding background (for example, when you register the object, are not subject to any mechanical heating of its parts, in cloudy, rainy or snowy weather and also in the wee hours), it can be argued that their value has slabitelny the discrete nature of the radiation. In the result, the data values of transient characteristics can be accurately enough approximated by a Poisson distribution. However, it is often necessary to recognize the true target among false objects in the accepted mixture of useful and interference signal with a set of giveaways, characteristic of intense thermal radiation (for example, a bright target is ob-served against a dark sky or a region of heat in the engine compartment contrasts sharply with a moderate background) of the object. In this case, the parameters of the received images in aperture will be a matter of photons that are converted to the output parameters of the adopted implementation in the form of a continuous current of parcels, or voltage. As a result, it is necessary to determine an algorithm that takes into account the continuous Gaussian nature of the distributions of signals and noise. Effectiveness of the decision on the presence of target in the visible area taking into account the distribution of signals and noises, which is a stationary Gaussian process in each cell total implementations POI. According to the results of the article studies have shown that: 1 Improvement of the evaluation algorithm was performed on the basis of statistical independence of joint probability densities of the adopted implementations based on the criterion of Bayes and ideal observer, which has been reduced to the following procedure: check images multi-element matrix photodetector unit (FPU); measuring the distribution of radiation intensity on the surface of the distinguishable object; - function evaluation of joint density distribution of values taken from cells receiving matrix; - according to the obtained values, the determination of the probability of detection of a signal in each element and compare the obtained values with the threshold. The resulting analytical relation from which it follows that the improved optimal algorithm would be: 1. The procedure of registration of brightness in the adopted implementations of thermal images taken with the sen-sitive elements of the photodetector; 2. in accordance with specified conditions based on the received signal-to-noise, the determination of the weight multiplier; 3. the operation of summation adopted implementation with weighting coefficients, with subsequent comparison of the obtained values with the specified optimum threshold detection.
References:

 

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June 24, 2020
May 29, 2020

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