Detection in gamma-distributed nonhomogeneous backgrounds

IEEE Transactions on Aerospace and Electronic Systems

Volumn 46, Issue 3, 2010, Pages 1127-1139

  Magraner, Éric ^a   Bertaux, Nicolas ^a   Réfrégier, Philippe ^a  

^a AIX MARSEILLE UNIVERSITÉ   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTANT FALSE ALARM RATE DETECTIONS; DETECTION PROBABILITIES; DETECTION TECHNIQUE; DOPPLER; FALSE ALARMS; GAMMA-DISTRIBUTED; NON-HOMOGENEOUS; TARGET DETECTION;

ERRORS;

TRACKING RADAR;

EID: 77955607999     PISSN: 00189251     EISSN: None     Source Type: Journal    
DOI: 10.1109/TAES.2010.5545178     Document Type: Article

References (35)

1. Campbell, L. L. Air-to-air RADAR modes for the CP-140 maritime patrol aircraft. Ph.D. dissertation, Dept. of Systems and Computer Engineering, Ottawa-Carleton Institute for Electrical Engineering, Carleton University, Faculty of Engineering, Ottawa, Canada, 1996.
2. Stimson, G. W. Introduction to Airborne RADAR (2nd ed.). Rayleigh, NC: Scitech Publishing, 1998.
3. Gini, F., Farina, A., and Greco, M. Selected list of references on radar signal processing. IEEE Transactions on Aerospace and Electronic Systems, 37, 1 (Jan. 2001), 329-359.
4. Le Chevalier, F. Principles of RADAR and SONAR Signal Processing. Norwood, MA: Artech House, 2002.
5. Rohling, H. Some RADAR topics: Waveform design, range CFAR and target recognition. In NATO, Advanced Study Institute: Advances in sensing with security applications (Il Ciocco, Italy), Technical University Hamburg, Harburg, Germany, July 15-30, 2005.
6. Shnidman, D. A. Radar detection in clutter. IEEE Transactions on Aerospace and Electronic Systems, 41, 3 (July 2005), 1056-1067.
7. Khalighi, M. and Bastani, M. Adaptive CFAR processor for nonhomogeneous environments. IEEE Transactions on Aerospace and Electronic Systems, 36, 3 (July 2000), 889-897.
8. Chen, B. and Varshney, P. Adaptive CFAR detection for clutter-edge heterogeneity using Bayesian inference. IEEE Transactions on Aerospace and Electronic Systems, 39, 4 (Oct. 2003), 1470.
9. Farrouki, A. and Barkat, M. Automatic censoring CFAR detector based on ordered data variability for nonhomogeneous environments. IEE Proceedings on Radar, Sonar, and Navigation, 152, 1 (Feb. 2005), 43-51.
10. Finn, H. M. and Johnson, P. S. Adaptive detection mode with threshold control as a function of spatially sampled clutter estimation. RCA Review, 29, 3 (1968), 414-464.
11. Alberola-López, C., Casar-Corredera, J. R., and de Miguel-Vela, G. Object CFAR detection in gamma-distributed textured-background images. IEE Proceedings on Vision, Signal and Image Processing, 146, 3 (June 1999), 130-136.
12. Gandhi, P. P. and Kassam, S. A. Optimality of the cell averaging CFAR detector. IEEE Transactions on Information Theory, 40, 4 (July 1994).
13. Swerling, P. Probability of detection for fluctuating targets. IEEE Transactions on lnformation Theory, IT-6, 2 (Apr. 1960), 269-308.
14. Swerling, P. Detection of RADAR echoes in noise revisited. IEEE Transactions on Information Theory, IT-12, 3 (July 1966), 348-361.
15. Swerling, P. RADAR probability of detection for some additional fluctuating target cases. IEEE Transactions on Aerospace and Electronic Systems, 33, 2 (Apr. 1997), 698-709.
16. Gandhi, P. P. and Kassam, S. A. Analysis of CFAR processors in nonhomogeneous background. IEEE Transactions on Aerospace and Electronic Systems, 24, 4 (July 1988).
17. Nitzberg, R.Analysis of the arithmetic mean CFAR normalizer for fluctuating targets. IEEE Transactions on Aerospace and Electronic Systems, AES-1 (1978), 44-47.
18. McConnell, I. and Oliver, C. A comparison of segmentation methods with standard CFAR for point target detection. SAR Image Analysis, Modelling and Techniques. In Proceedings of SPIE, vol.3497, 1998, 76-87.
19. McConnell, I. and Oliver, C. Segmentation-based target detection in SAR. SAR Image Analysis, Modelling and Techniques II. Proceedings of SPIE, vol.3869, 1999, 45-54.
20. Ndili, U., Nowak, R., Baraniuk, R., Choi, H., and Figueiredo, M. Coding-theoretic approach to segmentation and a robust CFAR detector for LADAR images. In Algorithms for Synthetic Aperture Radar Imagery VIII. Proceedings of the SPIE 15th Annual International Symposium on Aerospace/Defense Sensing, Simulation, and Controls, vol.4382, Apr. 2001.
21. Rohling, H. RADAR CFAR thresholding in clutter and multiple target situations. IEEE Transactions on Aerospace and Electronic Systems, AES-19, 4 (1983), 608-621.
22. Trees, H. L. V. Detection, Estimation, and Modulation Theory-Part I. Detection, Estimation, and Linear Modulation Theory. New York: Wiley-Interscience, 2001.
23. Abramowitz, M. Handbook of Mathematical Functions. New York: Dover, 1965.
24. Bronshtein, I. and Semendyayev, K. Handbook of Mathematics. New York: Springer, 1997.
25. Isar, A., Moga, S., and Isar, D. A new method for denoising sonar images. In Proceedings of the International Symposium on Signals, Circuits and Systems, vol.2, July 2005, 469-472.
26. Gradshteyn, I. S. and Ryzhik, I. M. Table of Integrals Series and Products (6th ed.). Burlington, MA: Academic Press, 2000.
27. Press, W., Teukoisky, S., and Flannery, B. Numerical Recipes in C (2nd ed.). New York: Cambridge, 1973.
28. Paranjape, R. B., Rabie, T. F., and Rangayyan, R. M. Image restoration by adaptive-neighborhood noise subtraction. Applied Optics, 33, 14 (May 1994), 2861-2869.
29. Rangayyan, R. M., Ciuc, M., and Faghih, F. Adaptive-neighborhood filtering of images corrupted by signal-dependent noise. Applied Optics, 37, 20 (July 1998), 4477-4487.
30. Vasile, G., Trouve, E., Lee, J. S., and Buzuloiu, V. Intensity-driven adaptive-neighborhood technique for polarimetric and interferometric SAR parameters estimation. IEEE Transactions on Geoscience and Remote Sensors, 44, 6 (June 2006), 1609-1621.
31. Papoulis, A. Probability, Random Variables, and Stochastic Processes (3rd ed.). New York: McGraw-Hill, 1991.
32. Boccara, N. Functional Analysis. Boston, MA: Academic Press, 1990.
33. Weiss, M. Analysis of some modified cell-averaging CFAR processors in multiple-target situations. IEEE Transactions on Aerospace and Electronic Systems, AES-18 (Jan. 1982), 102-114.
34. Acito, N., Corsini, G., Diani, M., and Pennucci, G. Experimental performance analysis of clutter removal techniques in IR images. IEEE International Conference on Image Processing, vol.3, Sept. 2005.
35. Moschopoulos, P. G. The distribution of the sum of independent gamma random variables. Annals of the Institute of Statistical Mathematics (Part A), 37 (1985), 541-544.