Swerling I 型起伏目标斜对称自适应检测算法

doi:10.12305/j.issn.1001-506X.2026.08.07

系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (8): 2581-2592.doi: 10.12305/j.issn.1001-506X.2026.08.07

• 传感器与信号处理 • 上一篇

Swerling I 型起伏目标斜对称自适应检测算法

郑园园¹^,²(), 郭洪志¹(), 何子述¹(), 吴昊琦¹, 王志航¹, 程子扬¹

1. 电子科技大学信息与通信工程学院，四川成都 611731
2. 中国电子科技集团公司第十四研究所，江苏南京 210039

收稿日期:2025-05-19 修回日期:2025-08-04 接受日期:2025-08-13 出版日期:2025-11-27 发布日期:2025-11-27
通讯作者: 何子述 E-mail:zyy65682@sina.com;hongz_guo@126.com;zshe@uestc.edu.cn
作者简介:郑园园（1982—），男，研究员，博士，主要研究方向为雷达目标检测、天波雷达信号处理
郭洪志（2000—），男，博士研究生，主要研究方向为复杂背景雷达自适应检测
吴昊琦（1999—），男，博士研究生，主要研究方向为非零均值背景雷达目标检测
王志航（1993—），男，助理研究员，博士，主要研究方向为雷达自适应检测
程子扬（1991—），男，研究员，博士研究生导师，博士，主要研究方向为分布式雷达信号处理、雷达波形设计
基金资助:
国家自然科学基金（62031007，62301124，62371093，62231006）资助课题

Persymmetric adaptive detection algorithm for Swerling I fluctuating targets

Yuanyuan ZHENG¹^,²(), Hongzhi GUO¹(), Zishu HE¹(), Haoqi WU¹, Zhihang WANG¹, Ziyang CHENG¹

1. School of Information and Communication Engineering，University of Electronic Science and Technology of China，Chengdu 611731，China
2. The 14th Research Institute，China Electronics Technology Group Corporation，Nanjing 210039，China

Received:2025-05-19 Revised:2025-08-04 Accepted:2025-08-13 Online:2025-11-27 Published:2025-11-27
Contact: Zishu HE E-mail:zyy65682@sina.com;hongz_guo@126.com;zshe@uestc.edu.cn

摘要/Abstract

摘要：

针对高斯背景中的Swerling I型起伏目标检测问题，在二元假设中将目标复幅度建模为复高斯分布的随机变量，并将目标信号能量嵌入到雷达回波的协方差矩阵中。利用协方差矩阵的斜对称结构降低检测器对于训练样本的需求。基于一步广义似然比检测（generalized likelihood ratio test，GLRT）、两步GLRT、Rao、Wald和梯度准则设计5种斜对称检测器。推导目标功率估计的克拉美罗界，证明提出检测器的恒虚警率特性，并分析提出检测器的计算复杂度。仿真结果显示，所提检测器的检测性能优于现有检测器，且在目标信号失配场景下，基于两步GLRT准则的自适应检测器具有最好的检测稳健性；而基于Rao准则设计的自适应检测器则具有更好的失配信号抑制能力。仿真结果证明所提算法的有效性。

关键词: 自适应检测, 起伏目标, 斜对称, 恒虚警率特性

Abstract:

Focusing on the Swerling I fluctuating targets detection problem in the Gaussian environment, in the binary hypothesis test, the complex amplitude of the target is modeled as a random variable with a complex Gaussian distribution, and the target signal energy is embedded into the covariance matrix of radar echo. The persymmetric structure of the covariance matrix is utilized to reduce the demand of detector for training samples. Five persymmetric detectors are designed by using the one-step generalized likelihood ratio test （GLRT）, two-step GLRT, Rao, Wald, and gradient criteria, respectively. The Cramer Rao bound for target power estimation is derived, and proof of the constant false alarm rate feature of the derived detectors is provided, as the computational complexity of the proposed detectors is analyzed. Simulations illustrate that the proposed detectors attain better detection performance compared to existing detectors. In the scenario of target signal mismatch, the adaptive detector based on the two-step GLRT criterion is the most robust one, and the adaptive detector designed based on the Rao criteria has better ability to reject the mismatch signals. Simulation results demonstrate the effectireness of the proposed algorithm.

Key words: adaptive detection, fluctuating target, persymmetry, constant false alarm rate （CFAR） property

中图分类号:

TN 957.51

郑园园, 郭洪志, 何子述, 吴昊琦, 王志航, 程子扬. Swerling I 型起伏目标斜对称自适应检测算法[J]. 系统工程与电子技术, 2026, 48(8): 2581-2592.

Yuanyuan ZHENG, Hongzhi GUO, Zishu HE, Haoqi WU, Zhihang WANG, Ziyang CHENG. Persymmetric adaptive detection algorithm for Swerling I fluctuating targets[J]. Systems Engineering and Electronics, 2026, 48(8): 2581-2592.

图/表 5

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检测器	检测统计量	计算复杂度
PGLRT-1S	式（46）	$ \mathcal{O}({g_1}{N_\varepsilon }{N^2}) $
PGLRT-2S	式（56）	$ \mathcal{O}({g_2}{N^2}) $
PRAO	式（80）	$ \mathcal{O}({g_1}{N^2}) $
PWALD	式（83）	$ \mathcal{O}({g_1}{N_\varepsilon }{N^2}) $
PGDT	式（86）	$ \mathcal{O}({g_1}{N_\varepsilon }{N^2}) $

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Swerling I 型起伏目标斜对称自适应检测算法

Persymmetric adaptive detection algorithm for Swerling I fluctuating targets

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