Vol. 85
Latest Volume
All Volumes
PIERC 150 [2024] PIERC 149 [2024] PIERC 148 [2024] PIERC 147 [2024] PIERC 146 [2024] PIERC 145 [2024] PIERC 144 [2024] PIERC 143 [2024] PIERC 142 [2024] PIERC 141 [2024] PIERC 140 [2024] PIERC 139 [2024] PIERC 138 [2023] PIERC 137 [2023] PIERC 136 [2023] PIERC 135 [2023] PIERC 134 [2023] PIERC 133 [2023] PIERC 132 [2023] PIERC 131 [2023] PIERC 130 [2023] PIERC 129 [2023] PIERC 128 [2023] PIERC 127 [2022] PIERC 126 [2022] PIERC 125 [2022] PIERC 124 [2022] PIERC 123 [2022] PIERC 122 [2022] PIERC 121 [2022] PIERC 120 [2022] PIERC 119 [2022] PIERC 118 [2022] PIERC 117 [2021] PIERC 116 [2021] PIERC 115 [2021] PIERC 114 [2021] PIERC 113 [2021] PIERC 112 [2021] PIERC 111 [2021] PIERC 110 [2021] PIERC 109 [2021] PIERC 108 [2021] PIERC 107 [2021] PIERC 106 [2020] PIERC 105 [2020] PIERC 104 [2020] PIERC 103 [2020] PIERC 102 [2020] PIERC 101 [2020] PIERC 100 [2020] PIERC 99 [2020] PIERC 98 [2020] PIERC 97 [2019] PIERC 96 [2019] PIERC 95 [2019] PIERC 94 [2019] PIERC 93 [2019] PIERC 92 [2019] PIERC 91 [2019] PIERC 90 [2019] PIERC 89 [2019] PIERC 88 [2018] PIERC 87 [2018] PIERC 86 [2018] PIERC 85 [2018] PIERC 84 [2018] PIERC 83 [2018] PIERC 82 [2018] PIERC 81 [2018] PIERC 80 [2018] PIERC 79 [2017] PIERC 78 [2017] PIERC 77 [2017] PIERC 76 [2017] PIERC 75 [2017] PIERC 74 [2017] PIERC 73 [2017] PIERC 72 [2017] PIERC 71 [2017] PIERC 70 [2016] PIERC 69 [2016] PIERC 68 [2016] PIERC 67 [2016] PIERC 66 [2016] PIERC 65 [2016] PIERC 64 [2016] PIERC 63 [2016] PIERC 62 [2016] PIERC 61 [2016] PIERC 60 [2015] PIERC 59 [2015] PIERC 58 [2015] PIERC 57 [2015] PIERC 56 [2015] PIERC 55 [2014] PIERC 54 [2014] PIERC 53 [2014] PIERC 52 [2014] PIERC 51 [2014] PIERC 50 [2014] PIERC 49 [2014] PIERC 48 [2014] PIERC 47 [2014] PIERC 46 [2014] PIERC 45 [2013] PIERC 44 [2013] PIERC 43 [2013] PIERC 42 [2013] PIERC 41 [2013] PIERC 40 [2013] PIERC 39 [2013] PIERC 38 [2013] PIERC 37 [2013] PIERC 36 [2013] PIERC 35 [2013] PIERC 34 [2013] PIERC 33 [2012] PIERC 32 [2012] PIERC 31 [2012] PIERC 30 [2012] PIERC 29 [2012] PIERC 28 [2012] PIERC 27 [2012] PIERC 26 [2012] PIERC 25 [2012] PIERC 24 [2011] PIERC 23 [2011] PIERC 22 [2011] PIERC 21 [2011] PIERC 20 [2011] PIERC 19 [2011] PIERC 18 [2011] PIERC 17 [2010] PIERC 16 [2010] PIERC 15 [2010] PIERC 14 [2010] PIERC 13 [2010] PIERC 12 [2010] PIERC 11 [2009] PIERC 10 [2009] PIERC 9 [2009] PIERC 8 [2009] PIERC 7 [2009] PIERC 6 [2009] PIERC 5 [2008] PIERC 4 [2008] PIERC 3 [2008] PIERC 2 [2008] PIERC 1 [2008]
2018-06-22
An Investigation of the Generalised Range-Based Detector in Pareto Distributed Clutter
By
Progress In Electromagnetics Research C, Vol. 85, 1-8, 2018
Abstract
The purpose of this paper is to examine whether a generalised range-based sliding window detector provides any improved detection performance relative to a single order statistic based counterpart. This is for non-coherent target detection in an X-band maritime surveillance radar environment, and as such the intensity clutter is modelled by a Pareto distribution. It will be demonstrated mathematically that a single order statistic detector is in fact sucient. Some numerical examples are also provided to clarify the theoretical results.
Citation
Graham V. Weinberg, and Charlie Tran, "An Investigation of the Generalised Range-Based Detector in Pareto Distributed Clutter," Progress In Electromagnetics Research C, Vol. 85, 1-8, 2018.
doi:10.2528/PIERC18042601
References

1. Finn, H. M. and R. S. Johnson, "Adaptive detection model with threshold control as a function of spatially sampled clutter-level estimates," RCA Review, Vol. 29, 414-464, 1968.

2. Nitzberg, R., "Low-loss almost constant false-alarm rate processors," IEEE Transactions on Aerospace and Electronic Systems, Vol. 15, 719-723, 1979.
doi:10.1109/TAES.1979.308861

3. Gregers Hanson, V. and J. H. Sawyers, "Detectability loss due to greatest of selection in a cell-averaging CFAR," IEEE Transactions on Aerospace and Electronic Systems, Vol. 16, 115-118, 1980.
doi:10.1109/TAES.1980.308885

4. Weiss, M., "Analysis of some modified cell-averaging CFAR processers in multiple-target situations," IEEE Transactions on Aerospace and Electronic Systems, Vol. 18, 102-114, 1982.
doi:10.1109/TAES.1982.309210

5. Gandhi, P. P. and S. A. Kassam, "Analysis of CFAR processors in nonhomogeneous background," IEEE Transactions on Aerospace and Electronic Systems, Vol. 24, 427-445, 1988.
doi:10.1109/7.7185

6. Minkler, G. and J. Minkler, CFAR: The Principles of Automatic Radar Detection in Clutter, Magellan, Baltimore, 1990.

7. Qin, X., S. Zhou, H. Zou, and G. Gao, "A CFAR detection algorithm for generalized Gamma distributed background in high-resolution SAR images," IEEE Geoscience and Remote Sensing Letters, Vol. 10, 806-810, 2013.
doi:10.1109/LGRS.2012.2224317

8. Zhang, R., W. Sheng, and X. Ma, "Improved switching CFAR detector for non-homogeneous environments," Signal Processing, Vol. 93, 35-48, 2013.
doi:10.1016/j.sigpro.2012.06.015

9. Weinberg, G. V., "Management of interference in Pareto CFAR processes using adaptive test cell analysis," Signal Processing, Vol. 104, 264-273, 2014.
doi:10.1016/j.sigpro.2014.04.025

10. Zaimbashi, A., "An adaptive cell averaging-based CFAR detector for interfering targets and clutter-edge situations," Digital Signal Processing, Vol. 31, 59-68, 2014.
doi:10.1016/j.dsp.2014.04.005

11. Baadeche, M. and F. Soltani, "Performance analysis of ordered CFAR detectors for MIMO radars," Digital Signal Processing, Vol. 44, 47-57, 2015.
doi:10.1016/j.dsp.2015.05.010

12. Dai, H., L. Du, Y. Wang, and Z. Wang, "A modified CFAR algorithm based on object proposals for ship target detection in SAR images," IEEE Geoscience and Remote Sensing Letters, Vol. 13, 1925-1929, 2016.
doi:10.1109/LGRS.2016.2618604

13. Kong, L., B. Wang, G. Cui, and X. Yang, "Performance prediction of OS-CFAR for generalized Swerling-Chi fluctuating targets," IEEE Transactions on Aerospace and Electronic Systems, Vol. 52, 492-500, 2016.
doi:10.1109/TAES.2015.140967

14. Tao, D., A. P. Doulgeris, and C. Brekke, "A segmentation-based CFAR detection algorithm using truncated statistics," IEEE Transactions on Geoscience and Remote Sensing, Vol. 54, 2887-2898, 2016.
doi:10.1109/TGRS.2015.2506822

15. Yu, W., Y. Wang, H. Liu, and J. He, "Superpixel-based CFAR target detection for high-resolution SAR images," IEEE Geoscience and Remote Sensing Letters, Vol. 13, 730-734, 2016.
doi:10.1109/LGRS.2016.2540809

16. Bakry, E. M., "Heterogeneous performance analysis of the new model of CFAR detectors for partially-correlated χ2-targets," Journal of Systems Engineering and Electronics, Vol. 29, 1-17, 2018.

17. Zhao, W., J. Li, X. Yang, Q. Peng, and J. Wang, "Innovative CFAR detector with effective parameter estimation method for generalised Gamma distribution and iterative sliding window strategy," IET Image Processing, Vol. 12, 60-69, 2018.
doi:10.1049/iet-ipr.2017.0225

18. Ai, J., X. Yang, J. Song, Z. Dong, L. Jia, and F. Zhou, "An adaptively truncated clutter-statistics-based two-parameter CFAR detector in SAR imagery," IEEE Journal of Oceanic Engineering, Vol. 43, 267-279, 2018.
doi:10.1109/JOE.2017.2768198

19. Lu, S., W. Yi, W. Liu, G. Cui, L. Kong, and X. Yang, "Data-dependent clustering-CFAR detector in heterogeneous environment," IEEE Transactions on Aerospace and Electronic Systems, Vol. 54, 476-485, 2018.
doi:10.1109/TAES.2017.2740065

20. Balleri, A., A. Nehorai, and J. Wang, "Maximum likelihood estimation for compound-gaussian clutter with inverse-Gamma texture," IEEE Transactions on Aerospace and Electronic Systems, Vol. 43, 775-779, 2007.
doi:10.1109/TAES.2007.4285370

21. Farshchian, M. and F. L. Posner, "The Pareto distribution for low grazing angle and high resolution X-band sea clutter," X-band sea clutter, 789-793, 2010.

22. Weinberg, G. V., "Assessing Pareto fit to high resolution high grazing angle sea clutter," IET Electronics Letters, Vol. 47, 516-517, 2011.
doi:10.1049/el.2011.0518

23. Weinberg, G. V., "Constant false alarm rate detectors for Pareto clutter models," IET Radar, Sonar and Navigation, Vol. 7, 153-163, 2013.
doi:10.1049/iet-rsn.2011.0374

24. Weinberg, G. V., Radar Detection Theory of Sliding Window Processes, CRC Press, Florida, 2017.
doi:10.1201/9781315154015

25. Weinberg, G. V., "Trimmed geometric mean order statistic CFAR detector for Pareto distributed clutter Signal," Image and Video Processing, 2018 (in press).

26. Levanon, N. and M. Shor, "Order statistics CFAR for Weibull background," IEE Proceedings F --- Radar and Signal Processing, Vol. 137, 157-162, 1990.
doi:10.1049/ip-f-2.1990.0023

27. Weinberg, G. V., "Examination of classical detection schemes for targets in Pareto distributed clutter: Do classical CFAR detectors exist, as in the Gaussian case?," Multidimensional Systems and Signal Processing, Vol. 26, 599-617, 2015.
doi:10.1007/s11045-013-0275-y

28. Weinberg, G. V. and A. Alexopoulos, "Analysis of a dual order statistic constant false alarm rate detector," IEEE Transactions on Aerospace and Electronic Systems, Vol. 52, 2567-2574, 2016.
doi:10.1109/TAES.2016.150508

29. Weinberg, G. V., "Assessing detector performance, with application to Pareto coherent multilook radar detection," IET Radar, Sonar and Navigation, Vol. 7, 401-412, 2013.
doi:10.1049/iet-rsn.2012.0127