随机PRI信号联合数据矩特征的干扰抑制算法

doi:10.12305/j.issn.1001-506X.2026.04.10

系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (4): 1195-1208.doi: 10.12305/j.issn.1001-506X.2026.04.10

• 传感器与信号处理 • 上一篇

随机PRI信号联合数据矩特征的干扰抑制算法

罗军(), 陈辉(), 张昭建, 王晓戈, 刘维建, 李槟槟

空军预警学院，湖北武汉 430019

收稿日期:2024-12-09 修回日期:2025-02-20 接受日期:2026-03-06 出版日期:2025-07-03 发布日期:2025-07-03
通讯作者: 陈辉 E-mail:junluo_2001@163.com;574667385@qq.com
作者简介:罗　军（2001—），男，硕士研究生，主要研究方向为雷达抗干扰
张昭建（1988—），男，副教授，博士，主要研究方向空时自适应处理、雷达抗干扰
王晓戈（1996—），男，博士研究生，主要研究方向为雷达抗干扰
刘维建（1982—），男，副教授，博士，主要研究方向为自适应检测、雷达抗干扰
李槟槟（1990—），男，副教授，博士，主要研究方向为阵列信号处理、雷达抗干扰

Jamming suppression algorithm by integrating random PRI signals with statistical moment features

Jun LUO(), Hui CHEN(), Zhaojian ZHANG, Xiaoge WANG, Weijian LIU, Binbin LI

Air Force Early Warning Academy，Wuhan 430019，China

Received:2024-12-09 Revised:2025-02-20 Accepted:2026-03-06 Online:2025-07-03 Published:2025-07-03
Contact: Hui CHEN E-mail:junluo_2001@163.com;574667385@qq.com

摘要/Abstract

摘要：

密集假目标干扰具有欺骗性和压制性的双重特点，因而严重干扰雷达对真实目标的检测与识别。针对这一问题，提出一种随机脉冲重复间隔信号联合数据矩特征的干扰抑制算法。首先，利用灰度熵算法对脉压后的数据矩阵进行二值化处理。其次，利用统计学中的一阶矩作为鉴别指标，沿快时间维对大部分干扰进行抑制。然后，利用统计学中的Z-score法沿慢时间维对剩余干扰旁瓣进行剔除。最后，进行慢时间相参积累实现对目标的检测。在二值化处理效果不佳时，利用数据滑窗预处理的方式抑制干扰，保证干扰抑制效果。仿真结果表明，当干信比为59 dB时，所提算法仍能有效抑制干扰检测目标，验证了所提算法的有效性。

关键词: 密集假目标干扰, 随机脉冲重复间隔信号, 灰度熵, 矩特征, 数据预处理

Abstract:

Dense false target jamming is characterized by its deceptive and suppressive nature, significantly interfering with the detection and recognition of real targets. To address this issue, this paper proposes a jamming suppression algorithm that combines random pulse repetition interval signals with statistical moment features. Firstly, the gray-level entropy algorithm is utilized to binarize the data matrix after pulse compression. Secondly, the first-order moment in mathematical statistics is employed as a discriminant index to suppress most of the jamming along the fast-time dimension. Then, the Z-score method in mathematical statistics is applied to eliminate jamming sidelobes along the slow-time dimension. Finally, slow-time coherent integration is directly performed to achieve target detection. When the binarization effect is ineffective, data sliding window preprocessing is applied to enhance jamming suppression. Simulation results demonstrate that when the jamming-to-signal ratio is 59 dB, the proposed algorithm can still effectively suppress jamming and detect the target, validating the effectiveness of the proposed algorithm.

Key words: dense false target jamming, random pulse repetition interval (PRI) signals, gray-level entropy, moment features, data preprocessing

中图分类号:

TN 974

罗军, 陈辉, 张昭建, 王晓戈, 刘维建, 李槟槟. 随机PRI信号联合数据矩特征的干扰抑制算法[J]. 系统工程与电子技术, 2026, 48(4): 1195-1208.

Jun LUO, Hui CHEN, Zhaojian ZHANG, Xiaoge WANG, Weijian LIU, Binbin LI. Jamming suppression algorithm by integrating random PRI signals with statistical moment features[J]. Systems Engineering and Electronics, 2026, 48(4): 1195-1208.

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参数	数值	参数	数值
雷达载频/MHz	2000	目标脉压后信噪比/dB	5
发射带宽/MHz	10	干信比/dB	45
发射脉冲宽度/μs	50	干扰移频量/MHz	2
基准发射PRI/μs	500	干扰数目	50
离散均匀分布区间	[0,5]	干扰机转发时延/μs	0.2
扰动因子	1	假目标转发间隔/μs	1
脉冲数	64	假目标调制多普勒频率/Hz	750
目标距离/km	30	采样频率/MHz	20
目标径向速度/m/s	75	目标多普勒频率/Hz	750

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随机PRI信号联合数据矩特征的干扰抑制算法

Jamming suppression algorithm by integrating random PRI signals with statistical moment features

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