帮助 关于我们

返回检索结果

基于多级箱与深度森林的雷达信号分选算法
The Radar Signal Deinterleaving Algorithm Based on Multi-Level Bin and Deep Forest

查看参考文献21篇

张春杰 1,2   刘俞辰 1,2 *   司伟建 1,2  
文摘 针对复杂电磁环境下大范围抖动、滑变等特殊类型雷达信号难以分选,脉冲重复周期(Pulse Repetition Interval,PRI)估计精度低,脉冲序列搜索效果不佳等问题,提出一种基于PRI多级箱与深度森林的雷达信号单参数分选算法.该算法利用PRI多级箱结构进行PRI变换,提升针对特殊类型雷达的分选正确率.在多级箱中的脉冲对个数与PRI变换结果中,提取雷达信号PRI边界特征,将不同电磁环境下特殊类型雷达信号PRI边界特征混合,通过平滑滤波器增强特征,训练深度森林预测完整雷达信号PRI范围,从而校正中心PRI估计值.最后依据PRI中心值与变化范围,搜索提取脉冲序列,完成分选.仿真实验表明,所提算法可在复杂电磁环境下,对大范围抖动、单线性滑变、双线性滑变、锯齿波滑变以及正弦滑变等特殊类型雷达信号进行有效分选,PRI范围预测效果在原始深度森林基础上提升14%,PRI估计误差降低75%.
其他语种文摘 To address the difficulty of deinterleaving special radars with large pulse repetition interval(PRI) range and the low accuracy of PRI estimation in complex electromagnetic environment, a radar signal deinterleaving algorithm based on PRI multi-level bin and deep forest is proposed. The algorithm utilizes the PRI multi-level bin structure for PRI transformation to improve the detection rate for special radars. The PRI boundary features of radar signals are derived from the number of pulse pairs in the multi-level bin and the PRI transform results. The PRI boundary features of special radars in different environments is mixed and the features by smoothing filters are enhanced. The deep forest is trained to predict the complete PRI range and thus to correct the central PRI estimate. Finally, based on the central value of PRI and the PRI range, the pulses are searched and extracted. Simulation experiments show that the proposed algorithm can effectively deinterleaving jittered, unilinear, bilinear, sawtooth and sinusoidal radars with large PRI range. The PRI range prediction performance is improved by 14% and the PRI estimation error is reduced by 75%.
来源 电子学报 ,2022,50(6):1351-1358 【核心库】
DOI 10.12263/DZXB.20210934
关键词 电子侦察 ; 特殊类型雷达信号 ; 多级箱 ; 深度森林 ; PRI估计 ; PRI范围
地址

1. 哈尔滨工程大学信息与通信工程学院, 黑龙江, 哈尔滨, 150001  

2. 哈尔滨工程大学, 先进船舶通信与信息技术工业和信息化部重点实验室, 黑龙江, 哈尔滨, 150001

语种 中文
文献类型 研究性论文
ISSN 0372-2112
学科 电子技术、通信技术
基金 国家自然科学基金 ;  黑龙江省自然科学基金
文献收藏号 CSCD:7240125

参考文献 共 21 共2页

1.  Chen C X. A new method for sorting unknown radar emitter signal. Chinese Journal of Electronics,2014,23(3):499-502 CSCD被引 13    
2.  Nan H. Pulse interference method against PRI sorting. The Journal of Engineering,2019,2019(19):5732-5735 CSCD被引 5    
3.  Rogers J A V. ESM processor system for high pulse density radar environments. IEE Proceedings F Communications, Radar and Signal Processing,1985,132(7):621-625 CSCD被引 4    
4.  Ahmed M G S. Sorting radar signal from symmetry clustering perspective. Journal of Systems Engineering and Electronics,2017,28(4):690-696 CSCD被引 9    
5.  Jiang W. Improved de-interleaving algorithm of radar pulses based on dual fuzzy vigilance ART. Journal of Systems Engineering and Electronics,2020,31(2):303-311 CSCD被引 5    
6.  Liu Y C. Improved method for deinterleaving radar signals and estimating PRI values. IET Radar, Sonar & Navigation,2018,12(5):506-514 CSCD被引 9    
7.  Zhang C J. Synthetic algorithm for deinterleaving radar signals in a complex environment. IET Radar, Sonar & Navigation,2020,14(12):1918-1928 CSCD被引 4    
8.  姜宏志. 基于时差多参的单脉冲信号实时配对分选. 电子学报,2021,49(3):566-572 CSCD被引 6    
9.  Mardia H K. New techniques for the deinterleaving of repetitive sequences. IEE Proceedings F Radar and Signal Processing,1989,136(4):149-154 CSCD被引 45    
10.  Milojevicd J. Improved algorithm for the deinterleaving of radar pulses. IEE Proceedings F Radar and Signal Processing,1992,139(1):98-104 CSCD被引 38    
11.  Xiao W H. An improved SDIF radar pulse signal main sorting algorithm. Advanced Materials Research,2013,710:637-641 CSCD被引 3    
12.  Bagheri M. A new approach to pulse deinterleaving based on adaptive thresholding. Turkish Journal of Electrical Engineering & Computer Sciences,2017,25(5):3827-3838 CSCD被引 2    
13.  Nishiguchi K. Improved algorithm for estimating pulse repetition intervals. IEEE Transactions on Aerospace and Electronic Systems,2000,36(2):407-421 CSCD被引 52    
14.  Mao Y. An improved algorithm of PRI transform. 2009 WRI Global Congress on Intelligent Systems,2009:145-149 CSCD被引 1    
15.  Jiang H Z. Coherent Integration Algorithm for Frequency-Agile and PRF-Jittering Signals in Passive Localization. Chinese Journal of Electronics,2021,30(4):781-792 CSCD被引 2    
16.  陈涛. 基于PRI变换的雷达脉冲序列搜索方法. 系统工程与电子技术,2017,39(6):1261-1267 CSCD被引 7    
17.  秦鑫. 基于扩张残差网络的雷达辐射源信号识别. 电子学报,2020,48(3):456-462 CSCD被引 28    
18.  潘剑飞. 基于Attention深度随机森林的社区演化事件预测. 电子学报,2019,47(10):2050-2060 CSCD被引 3    
19.  Zhou Z H. Deep forest: Towards an alternative to deep neural networks. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence Main track,2017:3553-3559 CSCD被引 1    
20.  张亮. LFM雷达对抗移频干扰方法研究. 电子学报,2021,49(3):510-517 CSCD被引 3    
引证文献 3

1 陈涛 基于点云分割网络的雷达信号分选方法 电子与信息学报,2024,46(4):1391-1398
CSCD被引 0 次

2 张春杰 一种针对驻留转换雷达的信号分选算法 系统工程与电子技术,2024,46(6):1925-1934
CSCD被引 0 次

显示所有3篇文献

论文科学数据集
PlumX Metrics
相关文献

 作者相关
 关键词相关
 参考文献相关

版权所有 ©2008 中国科学院文献情报中心 制作维护:中国科学院文献情报中心
地址:北京中关村北四环西路33号 邮政编码:100190 联系电话:(010)82627496 E-mail:cscd@mail.las.ac.cn 京ICP备05002861号-4 | 京公网安备11010802043238号