Ship detection by different data selection templates and multilayer perceptrons from incoherent maritime radar data

IET Radar, Sonar and Navigation

Volumn 5, Issue 2, 2011, Pages 144-154

  Vicen Bueno, R ^a   Carrasco Alvarez R ^a   Jarabo Amores, M P ^a   Nieto Borge, J C ^a   Rosa Zurera, M ^a  

^a UNIVERSITY OF ALCALÁ   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

CA-CFAR; COMMONLY USED; COMPUTATIONAL COSTS; DATA SELECTION; DETECTION PERFORMANCE; FALSE ALARMS; FEED-FORWARD ARTIFICIAL NEURAL NETWORKS; HIGH ROBUSTNESS; MARITIME RADAR; MULTI-LAYER PERCEPTRONS; RADAR IMAGE; SEA CLUTTERS; SHIP DETECTION;

CYBERNETICS; DATA REDUCTION; FEEDFORWARD NEURAL NETWORKS; KNOWLEDGE BASED SYSTEMS; MULTILAYER NEURAL NETWORKS; MULTILAYERS; PATTERN RECOGNITION SYSTEMS; RADAR; SHIPS; SIGNAL DETECTION;

DETECTORS;

EID: 78650233221     PISSN: 17518784     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-rsn.2010.0001     Document Type: Article

References (22)

1. Skolnik, M.: 'Introduction to radar systems', 3rd(McGraw-Hill, New York 2001)
2. Harati-Mokhtari, A., Wall, A., Brooks, P., and Wang, J.: 'Automatic identification system (AIS): Data reliability and human error implications', J. Navig., 2007, 60, p. 373-3890373-4633
3. Gandhi, P., and Kassam, S.: 'Analysis of CFAR processors in nonhomogeneous background', IEEE Trans. Aerosp. Electron. Syst., 1988, 24, (4), p. 427-44510.1109/7.7185 0018-9251
4. Barkat, M., and Soltani, F.: 'Cell-averaging CFAR detection in compound clutter with spatially correlated texture and speckle', IEE Proc. Radar, Sonar Navig., 1999, 146, (6), p. 279-28410.1049/ip-rsn:19990650 1350-2395
5. Watts, S.: 'The performance of cell-averaging CFAR systems in sea clutter', IEEE Int. Radar Conf., 2000, p. 398-403
6. Farrouki, A., and Barkat, M.: 'Automatic censoring CFAR detector based on ordered data variability for nonhomogeneous environments', IEE Proc. Radar, Sonar and Navigation, 2005, 152, (1), p. 43-51
7. Erfanian, S., and Tabataba, V.: 'Introducing switching ordered statistic CFAR type I in different radar environments', EURASIP J. Adv. Signal Process., 2009, 2009, p. 11
8. Messali, Z., and Soltani, F.: 'Performance of distributed CFAR processors in Pearson distributed clutter', EURASIP J. Adv. Signal Process., 2007, 2007, p. 7
9. Haykin, S.: 'Neural networks. A comprehensive foundation', 2nd(Prentice-Hall, London 1999)
10. Ruck, D., Rogers, S., Kabrisky, M., Oxley, M., and Suter, B.: 'The multilayer perceptron as an approximation to a Bayes optimal discriminant function', IEEE Trans. Neural Netw., 1990, 1, (4), p. 296-2981045-9227
11. Jarabo-Amores, M.-P., Rosa-Zurera, M., Gil-Pita, R., and Lopez-Ferreras, F.: 'Study of two error functions to approximate the Neyman-Pearson detector using supervised learning machines', IEEE Trans. Signal Process., 2009, 57, (11), p. 4175-41811053-587X
12. Vicen-Bueno, R., Carrasco-Álvarez, R., Rosa-Zurera, M., and Nieto-Borge, J.C.: 'Sea clutter reduction and target enhancement by neural networks in a marine radar system', Sensors, 2009, 9, (3), p. 1913-19360746-9462
13. Vicen-Bueno, R., Carrasco-Álvarez, R., Rosa-Zurera, M., and Nieto-Borge, J.C.: 'Sea clutter power reduction in radar measurement systems by feedforward multilayer perceptrons with medium input data integration rate', Proc. IEEE Int. Instrument and Measure Technology Conf. (12MTC 2009), 2009, p. 1069-1074
14. López-Risueno, G., Grajal, J., Haykin, S., and Díaz-Oliver, R.: 'Convolutional neural networks for radar detection', Proc. Int. Conf. on Artificial Neural Networks, ICANN'02, 2002, p. 1150-1155
15. Leung, H., Hennessey, G., and Drosopoulos, A.: 'Signal detection using the radial basis function coupled map lattice', IEEE Trans. Neural Netw., 2000, 11, p. 1133-11511045-9227
16. Khairnar, D., Merchant, S., and Desai, U.: 'Radial basis function neural network for pulse radar detection', IET Radar Son. Nav., 2007, 1, (1), p. 8-17
17. Jun, Y., Xiaoyan, M., Qianhong, L., Bin, L., and Bin, D.: 'A modified RBF neural network and its application in radar', Proc. Fourth Int. Symp. on Neural Networks, ISNN'07, 2007, p. 981-987
18. Ziemer, F., Brockmann, C., Vaughan, R., Seemann, J., and Senet, C.: 'Radar survey of near shore bathymetry within the OROMA project', EARSeL eProc., 2004, 3, p. 282-288
19. Reichert, K., Hessner, K., Dannenberg, J., Trankmann, I., and Lund, B.: 'X-band radar as a tool to determine spectral and single wave properties', Eigth Int. Workshop on Wave Hindcasting and Forecasting, 2005
20. World Meteorological Organization official Web site: http://www.wmo.int/pages/index_en.html
21. Bishop, C.: 'Neural networks for pattern recognition', (Oxford University Press Inc., New York 1995)
22. Coates, R., Janacek, G., and Lever, K.: 'Monte Carlo simulation and random number generation', IEEE J. Sel. Areas in Com., 1988, 6, (1), p. 58-66