基于相干度优化的极化顺轨干涉SAR慢小目标CFAR检测

张鹏; 张嘉峰; 刘涛

doi:10.13700/j.bh.1001-5965.2018.0322

基于相干度优化的极化顺轨干涉SAR慢小目标CFAR检测

doi: 10.13700/j.bh.1001-5965.2018.0322

张鹏¹,
张嘉峰²,
刘涛^1, ,

1.
海军工程大学电子工程学院, 武汉 430033
2.
海军作战支援舰第二支队, 舟山 316000

基金项目:

国家自然科学基金 61771483

详细信息

作者简介:
张鹏, 男, 硕士研究生。主要研究方向:极化SAR图像模型辨识、极化干涉SAR慢动目标检测

张嘉峰, 男, 硕士, 助理工程师。主要研究方向:极化SAR图像统计建模与目标CFAR检测

刘涛, 男, 博士, 教授。主要研究方向:瞬态极化统计理论、雷达极化抗干扰、极化SAR GMTI、极化分解

通讯作者:
刘涛, E-mail:liutao1018@sina.com

中图分类号: TN955;TN957.51;TN959.73
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出版历程
- 收稿日期: 2018-06-03
- 录用日期: 2018-08-24
- 网络出版日期: 2019-03-20

Slow and small target CFAR detection of polarimetric along-track interferometric SAR using coherence optimization

1.
School of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China
2.
The Second Detachment of Naval Combat Support Ship, Zhoushan 316000, China

Funds:

National Natural Science Foundation of China 61771483

More Information

Corresponding author: LIU Tao, E-mail:liutao1018@sina.com

摘要

摘要:
为改善干涉合成孔径雷达（SAR）系统对慢动小目标的检测性能，研究了全极化顺轨干涉SAR（AT-POLINSAR）实现慢动目标恒虚警（CFAR）检测的方法。首先，通过对单基线AT-POLINSAR的系统设计，明确了其在现有技术条件下的可实现性，并对其信号形式与极化干涉回波进行了建模分析。然后，针对AT-POLINSAR 6维极化干涉矢量提出了以背景杂波平均相干度为优化准则的极化降维新方法，构建了一种统计分布类型与单极化干涉数据相同的次优极化标量干涉回波，从而使目前单极化顺轨干涉SAR（AT-INSAR）慢动目标CFAR检测方法可直接扩展至全极化情形。最后，通过检测实验对次优极化与单极化的慢动目标检测性能进行了对比分析。结果表明，次优极化方法能充分利用全极化信息提高INSAR对慢小目标的检测概率。
- 极化干涉 /
- 合成孔径雷达 /
- 地面运动目标检测(GMTI) /
- 雷达极化 /
- 顺轨干涉
Abstract:
To improve the slow and small target detection performance of current interferometric SAR (INSAR), a new method is explored to implement constant false alarm rate (CFAR) detection for full polarimetric along-track INSAR (AT-POLINSAR). First, by designing a single-baseline AT-POLINSAR, we point out its feasibility under current technology conditions and analyze its signal form as well as polarimetric interferometric echo. Second, a new dimension reduction method for AT-POLINSAR 6D polarimetric interferometric vector is proposed using the background clutter average coherence as optimization criterion, from which the scalar echo in suboptimal polarization that has the same distribution type with single polarization can be obtained, and then the traditional single polarimetric INSAR slow target detector can be extended to be full polarimetric. Finally, Monte Carlo experiments and AT-POLINSAR scene detection experiments are carried out to compare the slow target detection performance of suboptimal polarimetric detectors and single polarimetric ones. The results indicate that suboptimal polarization can make full use of full polarimetric information to improve the INSAR detection probability of slow and small target.
- polarimetric interferometry /
- synthetic aperture radar /
- ground moving target indication (GMTI) /
- radar polarimetry /
- along-track interferometry

HTML全文

图 1 单基线AT-POLINSAR成像几何示意图

Figure 1. Geometry schematic diagram of single-baseline AT-POLINSAR acquisition

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图 2 次优极化统计分布

Figure 2. Statistical distribution of suboptimal polarization

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图 3 干涉图二维散布特性

Figure 3. scatter characteristics of interferograms

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图 4 采用SICP进行运动目标检测流程图

Figure 4. Flowchart of moving target detection using SICP

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图 5 ROC曲线仿真结果

Figure 5. Simulated curves of ROC

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图 6 场景图像仿真流程和仿真结果

Figure 6. Generated flow and result of simulated scene image

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图 7 AT-POLINSAR信号级仿真图像和不同检测算法的检测结果

Figure 7. Signal level simulation image AT-POLINSAR and its detection results by different algorithms

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图 8 目标径向速度估计相对误差

Figure 8. Relative estimation error of target radial velocity

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图 9 估计点数对SICP性能的影响

Figure 9. Performance of SICP vs. estimation point number

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表 1 分布式杂波、目标仿真关键参数

Table 1. Key parameters of distributed clutter and target simulation

项目		σ_xy/σ_hh	TCR	SNR	ρ_xy-hh	ρ_xy-hv
杂波	hh	1		1	1	0.2
	hv	0.25		0.5	0.2	1
	vv	2		2	0.7	0.2
目标1 (0.8 m/s)	hh	1	0.9	4	1	0.5
	hv	0.25	0.9	1	0.5	1
	vv	4	0.9	8	0.7	0.5
目标2 (1.6 m/s)	hh	1	1.1	4	1	0.5
	hv	0.25	1.1	1	0.5	1
	vv	4	1.1	8	0.7	0.5

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表 2 AT-POLINSAR场景图像仿真参数

参数	数值
雷达工作距离/m	4 000.0
载机飞行速度/(m·s^-1)	276.0
波长/m	0.1
脉冲重复频率/Hz	662.0
基线长度/m	3.34
合成孔径时间/s	0.869 6
重复观测时间/s	0.012 1
发射脉冲宽度/μs	1.0
发射信号带宽/MHz	216.0
发射信号中心频率/GHz	3.0
过采样率	1.2
斜视角/(°)	0
分辨率(方位/m×距离/m)	1.0×1.0
分辨率加权因子	1.2
目标1坐标(距离向/m，方位向/m)	(25, 0)
目标2坐标(距离向/m，方位向/m)	(75, 0)
目标3坐标(距离向/m，方位向/m)	(125, 0)
目标4坐标(距离向/m，方位向/m)	(175, 0)
目标1径向速度/(m·s^-1)	0
目标2径向速度/(m·s^-1)	0.9
目标3径向速度/(m·s^-1)	-1.2
目标4径向速度/(m·s^-1)	0
注：成像算法为距离多普勒；杂波类型为复Wishart。

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