Formation of reference images and decision function in radiometric correlationextremal navigation systems
DOI:
https://doi.org/10.15587/1729-4061.2018.139723Keywords:
correlationextreme system, reference image, geometric invariants, selective images, decision functionAbstract
Methods for formation of reference images (RI) and unimodal decision function (DF) have been developed to ensure efficient functioning of radiometric correlationextreme navigation systems (CENS) of flying machines (FM). The methods were developed for the conditions of CENS position finding on the surfaces of sighting (SS) with a highly developed infrastructure at insignificant altitudes of flight of the flying machine which leads to formation of current images (CI) with a nonstationary structure. Nonstationarity of CI arises when geometric conditions of sighting the threedimensional objects change. The method of RI formation is based on the use of a set of threedimensional stationary objects with the highest radiobrightness temperature, their contouring and determination of mean radiobrightness temperature.
A method for forming a unimodal DF of radiometric CENS which takes into account threedimensional form of SS objects, spatial position and orientation of the FM was developed. The method is based on CI preprocessing which consists in its layering with respect to the mean radiobrightness temperature of background and determination of a set of objects with the highest radiobrightness temperature. The set of objects defined by their contouring is used as a geometric invariant with an informative attribute in the form of average radiobrightness temperature.
It was established by simulating the process of formation of DF that pronounced unimodal DFs are formed at signaltonoise ratio (q=5...10) at the output of the radiometric channel. At the same time, the possibility of correct localization of the binding object in TI is close to unity and reduction of influence of perspective and scale distortions of images on accuracy of CENS location is ensured.
The simulation results have confirmed effectiveness of the proposed methods of formation of RI and DF for location of radiometric CENS on the sighting surfaces with complex threedimensional objects leading to formation of a nonstationary CI.
References
- Blohinov, A. (2011). Metod kompleksirovaniya dannyh raznorakursnoy s'emki dlya obnaruzheniya slozhnyh ob'ektov v usloviyah sil'noy zashumlennosti. Shtuchnyi intelekt, 3, 220–227.
- German, E. (2013). Klassifikaciya i issledovanie mer informativnosti izobrazheniy podstilayushchey poverhnosti v korrelyacionno-ekstremal'nyh navigacionnyh sistemah. Vestnik RGRTU, 2 (44), 35–40.
- Sotnikov, A., Tarshyn, V., Yeromina, N., Petrov, S., Antonenko, N. (2017). A method for localizing a reference object in a current image with several bright objects. Eastern-European Journal of Enterprise Technologies, 3 (9 (87)), 68–74. doi: https://doi.org/10.15587/1729-4061.2017.101920
- Fursov, V. A., Bibikov, S. A., Yakimov, P. Y. (2013). Localization of objects contours with different scales in images using Hough transform. Computer Optics, 37(4), 496–502. doi: https://doi.org/10.18287/0134-2452-2013-37-4-496-502
- Potapov, A. A. (2013). Fractal paradigm and fractal-scaling methods in fundamentally new dynamic fractal signal detectors. 2013 International Kharkov Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves. doi: https://doi.org/10.1109/msmw.2013.6622151
- Tsvetkov, O. V., Tananykina, L. V. (2015). A preproсessing method for correlation-extremal systems. Computer Optics, 39 (5), 738–743. doi: https://doi.org/10.18287/0134-2452-2015-39-5-738-743
- Vasil'eva, I. (2017). Vydelenie vneshnih konturov ob'ektov raspoznavaniya na mnogokanal'nyh izobrazheniyah. Radioelektronni i kompiuterni systemy, 2 (82), 17–23.
- Abramov, N., Fralenko, V. P. (2012). Opredelenie rasstoyaniy na osnove sistemy tekhnicheskogo zreniya i metoda invariantnyh momentov. Informacionnye tekhnologii i vychislitel'nye sistemy, 4, 32–39.
- Gnilitskii, V. V., Insarov, V. V., Chernyavskii, A. S. (2010). Decision making algorithms in the problem of object selection in images of ground scenes. Journal of Computer and Systems Sciences International, 49 (6), 972–980. doi: https://doi.org/10.1134/s1064230710060158
- Bogush, R., Maltsev, S. (2007). Minimax Criterion of Similarity for Video Information Processing. 2007 Siberian Conference on Control and Communications. doi: https://doi.org/10.1109/sibcon.2007.371310
- Kharchenko, V., Mukhina, M. (2014). Correlation-extreme visual navigation of unmanned aircraft systems based on speed-up robust features // Aviation, 18 (2), 80–85. doi: https://doi.org/10.3846/16487788.2014.926645
- Mukhina, M. P., Seden, I. V. (2014). Analysis of modern correlation extreme navigation systems. Electronics and Control Systems, 1 (39). doi: https://doi.org/10.18372/1990-5548.39.7343
- Muñoz, X., Freixenet, J., Cufı́, X., Martı́, J. (2003). Strategies for image segmentation combining region and boundary information. Pattern Recognition Letters, 24 (1-3), 375–392. doi: https://doi.org/10.1016/s0167-8655(02)00262-3
- Hruska, R., Mitchell, J., Anderson, M., Glenn, N. F. (2012). Radiometric and Geometric Analysis of Hyperspectral Imagery Acquired from an Unmanned Aerial Vehicle. Remote Sensing, 4 (9), 2736–2752. doi: https://doi.org/10.3390/rs4092736
- Acevo-Herrera, R., Aguasca, A., Bosch-Lluis, X., Camps, A., Martínez-Fernández, J., Sánchez-Martín, N., Pérez-Gutiérrez, C. (2010). Design and First Results of an UAV-Borne L-Band Radiometer for Multiple Monitoring Purposes. Remote Sensing, 2 (7), 1662–1679. doi: https://doi.org/10.3390/rs2071662
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