Adaptive Detection of Signals with Linear Feature Mappings and Representations

IEEE Transactions on Signal Processing

Volumn 43, Issue 12, 1995, Pages 2953-2963

  Yu, Xiaoli ^a   Reed, Irving S ^b  

^a SCIENCE APPLICATIONS INTERNATIONAL CORPORATION   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; MATRIX ALGEBRA; RADAR CLUTTER; RADAR IMAGING; STATISTICAL METHODS; SYNTHETIC APERTURE RADAR; WAVEFORM ANALYSIS;

CLUTTER COVARIANCE MATRIX; CONSTANT FALSE ALARM RATE; LINEAR FEATURE MAPPINGS; MAXIMUM LIKELIHOOD ESTIMATION;

SIGNAL DETECTION;

EID: 0029514717     PISSN: 1053587X     EISSN: 19410476     Source Type: Journal    
DOI: 10.1109/78.476439     Document Type: Article

References (20)

1. I. S. Reed, “I.R. detection of resolved signals represented by linear combinations of elementary signals,” Adaptive Sensors, Inc., Final Tech. Rep. DARPA subcontract 92-01 for Technical Research Assoc., Inc., Jan. 1993.
2. L. B. Stotts, “Moving-target detection techniques for optical-image-sequence,” Ph.D. dissertation, Univ. of Calif., San Diego, 1988.
3. B. Friedlander and B. Porat, “Performance analysis of transient detectors based on a class of linear data transforms,” IEEE Trans. Inform. Theory, vol. 38, Mar. 1993.
4. L. L. Scharf and B, Fridlander, “Matchéd subspace detectors,” IEEE Trans. Signal Processing, vol. 42, Aug. 1994.
5. M. Frisch and H. Messer, “The use of the wavelet transform in the detection of an unknown transient signal,” IEEE Trans. Inform. Theory, vol. 38, Mar. 1993.
6. E. E. Anderson, “Adaptive detection of multidimensional signals, Ph.D. dissertation, Univ. of Southern Calif., Aug. 1993.
7. F. C. Robey, D. R. Furmann, R. Nitzberg, and E. J. Kelly, “A CFAR adaptive matched filter detector,” IEEE Trans. Aerospace Electron. Syst., Jan. 1992.
8. W. S. Chen and I. S. Reed, “A new CFAR detection test for radar,” Digital Signal Processing. San Diego, CA: Academic, vol. 4, Oct. 1991.
9. R. J. Muirhead, Aspects of Multivariate Statistical Theory. New York: Wiley, 1982.
10. X. Yu, I. S. Reed, and A. Stocker, “Performance comparison of adaptive multi-band optical target detection,” IEEE Trans. Signal Processing, Aug. 1993.
11. I. S. Reed and X. Yu, “Adaptive multi-band CFAR detection of an optical pattern with unknown spectral distribution,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 38, Oct 1990.
12. X. Yu, I. S. Reed, W. Kraske, and A. D. Stocker, “A robust adaptive multi-spectral object detection by using wavelet transform,” in Proc. IEEE ICASSP, San Francisco, CA, 1992.
13. K. Fulkunaga, Introduction to Statistical Pattern Recognition. New Yrok: Academic, 1990.
14. A. K. Jain, Fundamentals of Digital Image Processing. Englewood Cliffs, NJ: Prentice-Hall, 1989.
15. I. S. Reed and L. S. Lan, “A fast approximate Karhunen-Loeve transform (AKLT) for data compression,” J. Visual Commun. Image Rep., vol. 5, no. 4, pp. 304-316, Dec. 1994.
16. I. Daubechies, “Orthonormal bases of compactly supported wavelets,” Commun. Pure Appl. Math., vol. 41, pp. 909-996, Nov. 1988.
17. D. Gabor, “Theory of communications,” J. Inst. Elect. Eng., vol. 93, no. III, pp. 429-457, Nov. 1946.
18. L. L. Scharf, Statistical Signal Processing. Reading, MA: Addison Wesley, 1991.
19. X. Yu, L. Hoff, I. Reed, D. Buck, and A. M. Chen, “A comparative study of feature mappings and selections for ATR: Experiments on actual SAR data,” in SPIE Conf. Aerospace Sensing, Orlando, FL, Apr. 1994.
20. X. Yu, L. Hoff, I. S. Reed, A. M. Chen, and D. Buck, “A linear feature mapping framework for adapti ve detection and recognition of targets in complex SAR data,” in Proc. IEEE 28th Conf. Signals Syst. Comput., Monterey, CA, Oct. 1994.