对数正态纹理海杂波背景非相干CFAR检测方法

doi:10.19665/j.issn1001-2400.2022.05.001

摘要/Abstract

摘要：

在相参体系的雷达系统中,相比于相干积累检测方法,非相干积累检测方法具有快速检测的能力,能够满足雷达信号实时处理的需求,在实际应用中具有重大意义。然而,非相干积累检测方法对累积脉冲数、参考单元数、海杂波幅度分布模型的形状参数以及海杂波散斑协方差矩阵均是非恒虚警率的。为了实现对数正态纹理复合高斯海杂波背景下运动目标的快速检测,提出了一种累积前白化和非相干累积级联的检测方法,证明该方法对海杂波幅度分布的尺度参数以及散斑协方差矩阵均是恒虚警率的。此外,分析了功率累积和幅度累积方法对检测性能的影响。通过匹配于海杂波形状参数、累积脉冲数以及参考单元数的检测门限,可以确保所提出检测方法的恒虚警率特性,继而实现对海雷达在大场景下对目标的快速恒虚警率检测。实验结果表明,在检测性能上幅度累积优于功率累积,而且累积前白化总体上提高了运动目标的信杂比,同时对于位于主杂波区之外的高速运动目标也能带来明显的性能改善。

关键词: 对数正态纹理复合高斯海杂波, 非相干积累检测, 恒虚警率, 海杂波, 白化

Abstract:

In a coherent radar system,compared with the coherent integration detectors,non-coherent integration detectors with fast implementation can meet the demand of real-time processing,and are of great significance in practical applications.However,these detectors do not have a constant false alarm rate (CFAR) with respect to the integrated pulse number,the number of reference cells,the shape parameter of the sea clutter model,and the speckle covariance matrix of the sea clutter.In order to realize fast CFAR detection of moving targets in sea clutter amplitude distribution with a log-normal texture,this paper proposes a detection method of speckle whitening followed by non-coherent integration,which is CFAR with respect to the scale parameter and speckle covariance matrix of the sea clutter.Moreover,it is also analyzed how the power integration and amplitude integration are to affect detection performance.By using the decision thresholds matching to the clutter shape parameter,the integrated pulse number,and the number of reference cells,the CFAR characteristic of the proposed detection method can be ensured,and then the proposed detector can implement a large-scene fast detection of maritime radars.Experiments show that the amplitude integration behaves better than the power integration and the speckle whitening before the integration wholly improves the signal-to-clutter ratios of moving targets,and that it can also bring a significant performance improvement for the high-speed moving target.

Key words: compound Gaussian clutter with log-normal texture, non-coherent integration detectors, constant false alarm rate, sea clutter, speckle whitening

中图分类号:

TN959.72

段亭宇, 水鹏朗, 封天. 对数正态纹理海杂波背景非相干CFAR检测方法[J]. 西安电子科技大学学报, 2022, 49(5): 1-8.

DUAN Tingyu, SHUI Penglang, FENG Tian. Non-coherent integration constant false alarm rate detectors against the log-normal textured sea clutter[J]. Journal of Xidian University, 2022, 49(5): 1-8.

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参考文献 16

[1]	RICHARDS M S. Fundamentals of Radar Signal Processing[M]. New York: McGraw-Hill Education, 2014:449-554.
[2]	GRECO M, GINI F, RANGASWARMY M. Statistical Analysis of Measured Polarimetric Clutter Data at Different Range Resolutions[J]. IEE Proceedings-Radar,Sonar & Navigation, 2006, 153(6):473-481.
[3]	MEZACHE A, SOLTANI F, SAHED M, et al. Model for Non-Rayleigh Clutter Amplitudes Using Compound Inverse Gaussian Distribution:An Experimental Analysis[J]. Steel Rolling, 2012, 51(1):142-153.
[4]	ROHLING H. Radar CFAR Thresholding in Clutter and Multiple Target Situations[J]. IEEE Transactions on Aerospace and Electronic Systems, 1983, 19(4):2024-2037.
[5]	时艳玲, 水鹏朗. ANMF和CM-CFAR在K分布海杂波下的性能分析[J]. 西北大学学报, 2012, 42(3):359-364.
	SHI Yanling, SHUI Penglang. Performance Analysis of ANMF and CM-CFAR Detectors Against K-Distributed Sea Clutter[J]. Journal of Northwest University, 2012, 42(3):359-364.
[6]	GRECO M, BORDONI F. X-Band Sea-Clutter Nonstationarity:Influence of Long Waves[J]. IEEE Journal of Oceanic Engineering, 2004, 29(2):269-283. doi: 10.1109/JOE.2004.828548
[7]	CARRETERO-MOYA J, GISMERO-MENOYO J, et al. Statistical Analysis of a High-Resolution Sea-Clutter Database[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(4):2024-2037. doi: 10.1109/TGRS.2009.2033193
[8]	CHALABI I, MEZACHE A. Estimators of Compound Gaussian Clutter with Log-Normal Texture[J]. Remote Sensing Letters, 2019, 10(7):706-716.
[9]	张坤, 水鹏朗, 王光辉. 相参雷达K分布海杂波背景下非相干积累恒虚警检测方法[J]. 电子与信息学报, 2020, 42(7):1627-1635.
	ZHANG Kun, SHUI Penglang,WANG Guanghui.Non-Coherent Integration Constant False Alarm Rate Detectors Against K-Distributed Sea Clutter for Coherent Radar Systems[J]. Journal of Electronics and Information Technology, 2020, 42(7):1627-1635.
[10]	张坤, 水鹏朗. 广义Pareto分布海杂波背景下非相干检测器恒虚警性能分析[J]. 电子与信息学报, 2021, 43(3):523-530.
	ZHANG Kun, SHUI Penglang.CFAR Analysis of Non-Coherent Detectors in Generalized Pareto Distributed Sea Clutter[J]. Journal of Electronics and Information Technology, 2021, 43(3):523-530.
[11]	XUE J, XU S W, SHUI P L. CFAR Analysis ofNon-Coherent Detectors in Compound-Gaussian Clutter with Inverse Gaussian Texture[C]// 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP). Piscataway: IEEE, 2019:440-444.
[12]	刘明, 水鹏朗. 基于功率中值和归一化采样协方差矩阵的自适应匹配滤波检测器[J]. 电子与信息学报, 2015, 37(6):1395-1401.
	LIU Ming, SHUI Penglang. Adaptive Matched Filter Detector Based on Power Median and Normalized Sample Covariance Matrix[J]. Journal of Electronics and Information Technology, 2015, 37(6):1395-1401.
[13]	GINI F. Performance Analysis of Two Structured Covariance Matrix Estimators in Compound-Gaussian Clutter[J]. Signal Processing, 2000, 80:365-371. doi: 10.1016/S0165-1684(99)00135-8
[14]	李东宸, 水鹏朗, 许述文. 块白化杂波抑制的海面漂浮小目标检测方法[J]. 西安电子科技大学学报, 2016, 43(6):21-26.
	LI Dongchen, SHUI Penglang, XU Shuwen. Floating Small Target Detection in The Sea clutter via Block-Whitened Clutter Suppression[J]. Journal of Xidian University, 2016, 43(6):21-26.
[15]	The Defence,Peace,Safety,and Security Unit of the Council for Scientific and Industrial Research. The Fynmeet Radar Database(2021)[DB/OL].[2021-01-01]. http://www.csir.co.za/small_boat_detection .
[16]	牟效乾, 陈小龙, 关键, 等. 基于INet的雷达图像杂波抑制和目标检测方法[J]. 雷达学报, 2020, 9(4):640-653.
	MOU Xiaoqian, CHEN Xiaolong, GUAN Jian, et al. Clutter Suppression and Marine Target Detection for Radar Images Based on INet[J]. Journal of Radars, 2020, 9(4):640-653.