Локальная оценка параметров траектории и обнаружение двужущихся целей на фоне релеевской помехи
Анотація
Рассмотрена проблема и предложен алгоритм обнаружения и локальной оценки параметров траектории движущихся целей на основе анализа данных в форме двумерного изображения. Исходя из принятых моделей цели и детектора, фоновая помеха имеет распределение Рэлея, а сигнал — распределение Райса. Рассмотрены два метода оценки параметров траектории: метод наименьших квадратов и метод преобразования Хафа. Предложена процедура обнаружения цели, основанная на интегрировании отраженной мощности вдоль вероятной траектории. Проведено статистическое моделирование, по результатам которого построены характеристики обнаружения для предложенного алгоритма.
Посилання
Li X. R., Bar-Shalom Y. Multiple-model estimation with variable structure. IEEE Trans. Autom. Control, 1996, vol. 41, no 4, pp. 478-492.
Ristic B., Arulampalam S., Gordon N. Beyond the Kalman Filter: Particle Filters for Tracking Applications, Artech House, 2004.
Viterbi A. J. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Trans. Inf. Theory, 1967, vol. 13, no 2, pp. 260-269.
Jang B., Rabiner L. An introduction to hidden Markov models. IEEE ASSP Mag, 1986, vol. 3, no 1, pp. 4-16.
Pohlig S. C. An algorithm for detection of moving optical targets. IEEE Trans. Aerosp. Electron. Syst, 1989, vol. 25, no 1, pp. 56–63.
Bruno M. G. S., Moura J. M. F. Multiframe detector/ tracker: Optimal performance. IEEE Trans. Aerosp. Electron. Syst, 2001, vol. 37, no 3, pp. 925-945.
Tonissen S. M., Bar-Shalom Y. Maximum likelihood track-before-detect with fluctuating target amplitude. IEEE Trans. Aerosp. Electron. Syst, 1998, vol. 34, no 3, pp. 796-809.
Salmond D. J., Birch H. A particle filter for trackbefore- detect. Proc. of the American Control Conf, USA, VA, Arlington, 2001, pp. 3755-3760.
Driessen H., Boers, Y. Efficient particle filter for jump Markov nonlinear systems. Radar, Sonar and Navigation, IEE Proceedings, 2005, vol. 152, no 5, pp. 323-326.
Rutten M. G., Gordon N. J., Maskell S. Recursive trackbefore- detect with target amplitude fluctuations. IEE Proc. Radar, Sonar and Navigation, 2005, vol. 152, no 5, pp. 345-352.
Rutten M. G., Gordon N. J., Maskell S. Efficient particle-based track-before-detect in Rayleigh noise. Proc. of the 7th Int. Conf. on Information Fusion, Sweden, Stockholm, 2004, pp. 693-700.
Streit R. L., Graham M. L., Walsh M. J. Multitarget tracking of distributed targets using histogram-PMHT. Digital Signal Processing, 2002, vol. 12, no 2-3, pp. 394-404.
Blanding W. R., Willett P. K., Bar-Shalom Y. Off-line and real-time methods for ML-PDA track validation. IEEE Trans. Signal Process, 2007, vol. 55, no 5, pp. 1994–2006.
Kirubarajan T., Bar-Shalom Y. Low observable target motion analysis using amplitude information. IEEE Trans. Aerosp. Electron. Syst, 1996, vol. 32, no 4, pp. 1367-1384.
Stone L. D., Barlow C. A., Corwin T. Bayesian Multiple Target Tracking, Norwood, MA: Artech House, 1999.
Colegrove S. B., Davis A. W., Ayliffe J. K. Track initiation and nearest neighbours incorporated into probabilistic data association. Journal of Electrical and Electronics Engineers, Australia, 1986, vol. 6, no 3, pp. 191-198.
Davey S. J., Gray D. A. Integrated track maintenance for the pmht via the hysteresis model. IEEE Trans. Aerosp. Electron. Syst, 2007, vol. 43, no 1, pp. 93–111.
Davey S. J., Rutten M. G., Cheung B. A comparison of detection performance for several Track-Before-Detect algorithms. Proc of the 11th Int. Conf. on Information Fusion, Germany, Cologne, 2008, pp. 1-8.
Leite E., Alves G., Seixas J. et al. Radar meteor detection: concept, data acquisition and online triggering. In Book: Wave Propagation. Ed. by Dr. Andrey Petrin, InTech, 2011, pp. 537-549. http://www.intechopen.com/books/wave-propagation/radar-meteor-detection-concept-dataacquisition-and-online-triggering.
Yilmaz A., Shafique K., Shah M. Target tracking in airborne forward looking infrared imagery. Proc. Image Vision Comput, 2003, vol. 21, no 7, pp. 623-635.
Savanevich V. E., Kozhuhov A. M., Briuhovetskii A. B. et al. [Asteroid detection method based on signal accumulation along trajectories with unknown parameters] Systemy obrobky informatsii: Zb. nauk. prats. HUPS, Kharkiv, 2011, no 92(2), pp. 137-144 (Ukr)]
Prokopenko I., Vovk V., Omelchuk I., Chirka Y. Tracking and detection of rapid moving targets. Proc. of the 14th International Radar Symposium (IRS), Germany, Dresden, 2013, vol. 2, pp. 768-773.
Chernov N., Lesort C. Least squares fitting of circles and lines, 2003. http://arxiv.org/abs/cs/0301001v1
Duda R. O., Hart P. E. Use of the Hough transformation to detect lines and curves in pictures. Comm. ACM, 1972, vol. 15, pp. 11-15.
Kuzmin S. Z. Osnovy teorii tsifrovoy obrabotki radiolokatsionnoy informatsii. [Fundamentals of the theory of digital radar data processing]. Moscow, Sovetskoie radio, 1974 (Rus)
Hart P. E. How the Hough transform was invented [DSP History]. IEEE Signal Processing Mag, 2009, vol. 26, no 6, pp. 18-22.
Ballard D. H. Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition, 1981, vol. 13, no 2, pp. 111-122.
Vassileva B. Target detection and track formation algorithm for radar management and tracking benchmark with ECM. Reports of the Bulgarian Academy of Sciences, 2001, vol. 54, no 5, pp. 35-38.
Fardi B., Wanielik G. Hough transformation based approach for road border detection in infrared images. Intelligent Vehicles Symp., 2004 IEEE, Italy, Parma, 2004, pp. 549-554.
Авторське право (c) 2014 Прокопенко И. Г., Вовк В. Ю., Омельчук И. П., Чирка Ю. Д., Прокопенко К. И.
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