Sea clutter reduction and target enhancement by neural networks in a marine radar system

Sensors

Volumn 9, Issue 3, 2009, Pages 1913-1936

  Vicen Bueno, Raúl ^a   Carrasco Álvarez, Rubén ^a   Rosa Zurera, Manuel ^a   Nieto Borge, José Carlos ^a  

^a UNIVERSITY OF ALCALÁ   (Spain)

Author keywords

Clutter reduction; Neural networks; Non linear signal processing; Radar; Remote sensing; SCR improvement; Target enhancement

Indexed keywords

CLUTTER REDUCTION; COMPUTATIONAL COSTS; NEURAL NETWORKS (NNS); NON-LINEAR SIGNAL PROCESSING; PROCESSING SPEED; RADAR SIGNAL PROCESSING; SIGNAL-TO-CLUTTER RATIOS; VISUAL ANALYSIS;

CLUTTER (INFORMATION THEORY); MARINE RADAR; NEURAL NETWORKS; RADAR; RADAR CLUTTER; RADAR SYSTEMS; RADAR TARGET RECOGNITION; REMOTE SENSING;

SIGNAL PROCESSING;

EID: 63849306478     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s90301913     Document Type: Article

References (23)

1. Harati-Mokhtari, A.; Wall, A.; Brooks, P.; J., W. Automatic identification system (AIS): Data reliability and human error implications. J. Navig. 2007, 60, 373-389.
2. Ellis, G.; Dix, A. A Taxonomy of Clutter Reduction for Information Visualisation. IEEE T. Vis. Comput. Gr. 2007, 13, 1216-1223.
3. Ellis, G.; Dix, A. Enabling Automatic Clutter Reduction in Parallel Coordinate Plots. IEEE T. Vis. Comput. Gr. 2006, 12, 717-724.
4. Merwe, A.; Gupta, I. AA Novel Signal Processing Technique for Clutter Reduction in GPR Measurements of Small, Shallow Land Mines. IEEE T. Geosci. Remote 2000, 38, 2627-2637.
5. Karlsen, B.; Larsen, J.; Sorensen, H.; Jakobsen, K. Comparison of PCA and ICA based clutter reduction in GPR systems for anti-personal landmine detection. In Statistical Signal Processing. Proc. 11th IEEE Signal Processing Workshop on, 2001, pp. 146-149.
6. Karlsen, B.; Sorensen, H.; Larsen, J.; Jakobsen, K. Independent component analysis for clutter reduction in ground penetrating radar data. Proc. SPIE 2002, 4742, 378-389.
7. Brunzell, H. Clutter reduction and object detection in surface penetrating radar. In Radar 97, 1999, pp. 688-691.
8. Carevic, D. Clutter reduction and target detection in ground-penetrating radar data using wavelets. Proc. SPIE 1999, 3710, 973-984.
9. Carevic, D. Clutter Reduction and Detection of Minelike Objects in Ground Penetrating Radar Data Using Wavelets. Subsurface Sensing Technologies and Applications 2000, 1, 101-118.
10. Nieto-Borge, J.; Hessner, K.; Jarabo-Amores, P.; Mata-Moya, D. Signal-to-noise ratio analysis to estimate ocean wave heights from X-band marine radar image time series. IET Radar Son. Nav. 2008,2,35-41.
11. Hennessey, G.; Leung, H.; Drosopoulos, A.; Yip, P. Sea-clutter modeling using a radial-basis-function neural network. IEEE J. Oceanic Eng. 2001, 26, 358-372.
12. Leung, H.; Hennessey, G.; Drosopoulos, A. Signal detection using the radial basis function coupled map lattice. IEEE T. Neural Networ. 2000, 11, 1133-1151.
13. Rico-Ramirez, M.; Cluckie, I. Classification of Ground Clutter and Anomalous Propagation Using Dual-Polarization Weather Radar. IEEE T. Geosci. Remote 2008, 46, 1892-1904.
14. Ziemer, F.; Brockmann, C.; Vaughan, R.; Seemann, J.; Senet, C. Radar survey of near shore bathymetry within the oroma project. EARSeL eProceedings 2004, 3, 282-288.
15. Reichert, K.; Hessner, K.; Dannenberg, J.; Trankmann, I.; Lund, B. X-band radar as a tool to determine spectral and single wave properties. In 8th Int. Workshop on Wave Hindcasting and Forecasting, 2005.
16. Bishop, C. Neural networks for pattern recognition. Oxford University Press Inc.: New York, 1995.
17. Haykin, S. Neural Networks. A Comprehensive Foundation (Second Edition). Prentice-Hall: London, 1999.
18. Nguyen, D.; Widrow, B. Improving the Learning Speed of 2-layer Neural Networks by Choosing Initial Values of the Adaptive Weights. In Neural Networks, 1990 IJCNN Int. Joint Conf. on, 1990, pp. 21-26.
19. Bowditch, N. H.O. pub No. 9: American Practical Navigator. Revised Edition 1938 (Not Copy-righted). United States Hydrographic Office, 1938.
20. Faltinsen, O. Sea Loads on Ships and Offshore Structures. Cambridge University Press: Cambridge, 1999.
21. World Meteorological Organization official Web site: http://www.wmo.int/pages/index_en.html.
22. Holland, J.; Holyoak, K.; Nisbett, R.; Thagard, P. Induction: Processes of Inference, Learning, and Discovery. The MIT Press: Cambridge, 1986.
23. Baum, E.; Haussler, D. What Size Net Gives Valid Generalization? Neural Comput. 1989, 1, 151-160.