CFAR Target Detector in Synthetic Aperture Radar
https://doi.org/10.32603/1993-8985-2024-27-3-52-67
Abstract
Introduction. Constant false alarm rate (CFAR) detectors have found application in synthetic aperture radar (SAR) systems. The operating principle of a classic cell averaging detector (CA-CFAR detector) is based on comparing the decision statistics in the test resolution element with an adaptive threshold, which is calculated from signals in the reference cells. The decision statistic is an estimate of the signal power. Therefore, target signal detection is based on the brightness contrast of the test and reference resolution cells. Such a detector is optimal provided that the noise background is homogeneous. In cases where the background homogeneity is violated, the quality of detection deteriorates. There are several known methods for improving the quality of detection (GO-CFAR, SO-CFAR, OS-CFAR, etc.). However, the precise principle of detection by brightness contrast in such CFAR detectors remains unchanged.
Aim. To synthesize a CFAR detector that uses not only the brightness contrast between the test and reference resolution cells, but also the spectral differences of the signals.
Materials and methods. The proposed CFAR detector uses estimates of the algebraic moments of the power spectral density of signals in range cells, based on which three decision statistics are calculated containing information about the power, the position of the energy center, and the width of the signal spectrum. The decision about the presence of a target in the test cell is carried out according to the 2/3 rule (2 threshold overshoots out of 3 comparisons).
Results. A comparison of the proposed detector with the SO-CFAR detector, performed by computer simulation, showed that, under a signal-to-clutter ratio of -6 dB and a false alarm probability of 10-4, the detection probability of the proposed detector was 0.933 versus 0.708 for the SO-CFAR detector.
Conclusion. The article proposes a three-parameter CFAR detector for a synthetic aperture radar system, in which the decision on the presence of a target in the test cell is made via estimation of the first three algebraic moments of the signal spectrum. The synthesized detection algorithm can also be used when detecting moving targets in SAR.
About the Author
A. A. Monakov
Institute of Radio Technique and Telecommunication Technologies, Saint Petersburg State University of Aerospace Instrumentation
Russian Federation
Russian Federation
Andrey A. Monakov - Dr Sci. (Eng.) (2000), Professor (2005) of the Department of Radio Engineering Systems of Saint Petersburg State University of Aerospace Instrumentation, Honored Mechanical Engineer of the Russian Federation (2005), Honored Worker of Higher Professional Education of the Russian Federation (2006).
67 A, Bolshaya Morskaya St., St Petersburg 190000
References
1. Gandhi P. P., Kassam S. A. Analysis of CFAR Processors in Non-Homogeneous Background. IEEE Transactions on Aerospace and Electronic Systems. 1988, vol. 24, no. 4, pp. 427-445. doi: 10.1109/7.7185
2. Finn H. M., Johnson R. S. Adaptive Detection Mode with Threshold Control as a Function of Spatially Sampled Clutter Level Estimates. RCA Review. 1968, vol. 29, pp. 414-468.
3. Moore J. D., Lawrence N. B. Comparison of Two CFAR Methods Used with Square Law Detection of Swerling I Targets. Proc. of the IEEE Intern. Radar Conf., Arlington, VA, April 1980, pp. 403-409.
4. Weiss M. Analysis of Some Modified Cell-Averaging CFAR Processors in Multiple-Target Situations. Transactions on Aerospace and Electronic Systems. 1982, vol. 18, no. 1, pp. 102-113. doi: 10.1109/taes.1982.309210
5. Hansen V. G. Constant False Alarm Rate Processing in Search Radars. Proc. of the IEEE Intern. Radar Conf., London, UK, 1973, pp. 325-332.
6. Trunk G. V. Range Resolution of Targets Using Automatic Detectors. IEEE Transactions on Aerospace and Electronic Systems. 1978, vol. 14, no. 5, pp. 750-755. doi: 10.1109/TAES.1978.308625
7. Rohling H. Radar CFAR Thresholding in Clutter and Multiple Target Situations. IEEE Transactions on Aerospace and Electronic Systems. 1983, vol. 19, no. 4, pp. 608-621. doi: 10.1109/taes.1983.309350
8. Hansen V. G., Sawyers. J. H. Detectability Loss Due to Greatest of Selection in a Cell-Averaging CFAR. IEEE Transactions on Aerospace and Electronic Systems. 1980, vol. 16, no. 1, pp. 115-118. doi: 10.1109/taes.1980.308885
9. El-Darymli K., McGuire P., Power D., Moloney C. R. Target Detection in Synthetic Aperture Radar Imagery: a State-of-the-Art Survey. J. of Applied Remote Sensing. 2013, vol. 7, pp. 1-35. doi: 10.1117/1.jrs.7.071598
10. El-Darymli K., McGuire P., Power D., Moloney C. R. Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review. IEEE Access. 2016, vol. 4, pp. 6014-6058. doi: 10.1109/ACCESS.2016.2611492
11. Ai J., Yang X., Dong Z., Zhou F., Jia L. A New Two Parameter CFAR Ship Detector in Log-Normal Clutter. IEEE Radar Conf. Seattle, WA, USA, 08-12 May 2017. IEEE, 2017, pp. 195-199. doi: 10.1109/RADAR.2017.7944196
12. Goldstein G. B. False-Alarm Regulation in Log-Normal and Weibull Clutter. IEEE Transactions on Aerospace and Electronic Systems. 1973, vol. AES-9, no. 1, pp. 84-92. doi: 10.1109/TAES.1973.309705
13. Kuttikkad S., Chellappa R. Non-Gaussian CFAR Techniques for Target Detection in High Resolution SAR Images. Proc. of the IEEE Intern. Conf. on Image Processing, Austin, Texas, USA, 13-16 Nov. 1994. IEEE, 1994, pp. 910-914. doi: 10.1109/icip.1994.413444
14. Smith M. E., Varshney P. K. Intelligent CFAR Processor Based on Data Variability. IEEE Transactions on Aerospace and Electronic Systems. 2000, vol. 36, no. 3, pp. 837-847. doi: 10.1109/7.869503
15. Ji K., Xing X., Zou H., Sun J. A Novel Variable Index and Excision CFAR Based Ship Detection Method on SAR Imagery. J. of Sensors. 2015, vol. 2015, art. ID 437083. doi: 10.1155/2015/437083
16. Wang L., Wang D., Hao C. Intelligent CFAR Detector Based on Support Vector Machine. IEEE Access. 2017, vol. 5, pp. 26965-26972. doi: 0.1109/ACCESS.2017.2774262
17. Pham Q. H., Brosnan T. M., Smith J. M. Multistage Algorithm for Detection of Targets in SAR Image Data. Proc. of the SPIE. 1997, vol. 3070, pp. 66-75. doi: 10.1117/12.281583
18. Subotic N. S., Thelen B. J., Gorman J. D., Reiley M. F. Multiresolution Detection of Coherent Radar Targets. IEEE Transactions on Image Processing. 1997, vol. 6, no. 1, pp. 21-35. doi: 10.1109/83.552094
19. Kaplan L. M., Murenzi R., Namuduri K. R. Extended Fractal Feature for First-Stage SAR Target Detection. Proc. of the SPIE. 1999, vol. 3721, pp. 35-46. doi: 10.1117/12.357684
20. Kaplan L. M. Improved SAR Target Detection via Extended Fractal Features. IEEE Transactions on Aerospace and Electronic Systems. 2001, vol. 37, no. 2, pp. 436-451. doi: 10.1109/7.937460
21. Hatem G. M., Sadah J. W., Saeed T. R. Comparative Study of Various CFAR Algorithms for Non-Homogenous Environments. IOP Conf. Ser.: Materials Science and Engineering, Kerbala, Iraq, 26-27 March 2018, vol. 433, art. no. 012080. doi: 10.1088/1757-899x/433/1/012080
22. Novak L. M., Burl M. C., Irving W. W. Optimal Polarimetric Processing for Enhanced Target Detection. IEEE Transactions on Aerospace and Electronic Systems. 1993, vol. 29, no. 1, pp. 234-244. doi: 10.1109/7.249129
23. Monakov A. A. Observation of Extended Targets in Radar Systems with Antenna Arrays. Radioengineering. 1999, vol. 63, no. 3, pp. 3-9. (In Russ.)
24. Monakov A. A. Radar Observation of Extended Targets with Antenna Arrays. IEEE Transactions on Aerospace and Electronic Systems. 2000, vol. 36, no. 1, pp. 297-302. doi: 10.1109/7.826333
25. Monakov A. A. Estimation of the Algebraic Spectrum Moments of Random Processes in Problems of the Extended Radar Target Theory. J. of Achievements of Modern Radioelectronics. 2006, vol. 60, no. 10, pp. 36-50. (In Russ.)
26. Monakov A. A., Monakov Yu. A. Observation of Atmospheric Turbulence in Airborne Weather Radars: Estimation of Turbulence Parameters. J. of Achievements of Modern Radioelectronics. 2012, vol. 66, no. 5, pp.14-28. (In Russ.)
27. Marple Jr. S. L. Digital Spectral Analysis with Applications. New Jersey, Prentice-Hall, 1987, 492 p.
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For citations:
Monakov A.A. CFAR Target Detector in Synthetic Aperture Radar. Journal of the Russian Universities. Radioelectronics. 2024;27(3):52-67. (In Russ.) https://doi.org/10.32603/1993-8985-2024-27-3-52-67
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