Online Detection Method of Multi-Function Radar Work Mode Changepoints Non-ideal Observations

BAO Jia-di; LI Yun-jie; ZHU Meng-tao; ZHANG Wei

doi:10.12263/DZXB.20210830

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Online Detection Method of Multi-Function Radar Work Mode Changepoints Non-ideal Observations

Intelligent game of electromagnetic spectrum | 更新时间：2025-12-08

- Online Detection Method of Multi-Function Radar Work Mode Changepoints Non-ideal Observations
- ACTA ELECTRONICA SINICA Vol. 50, Issue 6, Pages: 1291-1300(2022)
- 作者机构：
  
  1.北京理工大学信息与电子学院，北京 100081
  2.中国电子科技集团公司第二十九研究所，四川成都 610097
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20210830
  CLC： TN971.+1;
- Received：02 July 2021，
  
  Revised：2021-12-31，
  
  Published：25 June 2022
- 稿件说明：
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鲍加迪,李云杰,朱梦韬等.非理想观测下的多功能雷达工作状态在线切换点检测方法[J].电子学报,2022,50(06):1291-1300.

BAO Jia-di,LI Yun-jie,ZHU Meng-tao,et al.Online Detection Method of Multi-Function Radar Work Mode Changepoints Non-ideal Observations[J].ACTA ELECTRONICA SINICA,2022,50(06):1291-1300.
鲍加迪,李云杰,朱梦韬等.非理想观测下的多功能雷达工作状态在线切换点检测方法[J].电子学报,2022,50(06):1291-1300. DOI： 10.12263/DZXB.20210830.

BAO Jia-di,LI Yun-jie,ZHU Meng-tao,et al.Online Detection Method of Multi-Function Radar Work Mode Changepoints Non-ideal Observations[J].ACTA ELECTRONICA SINICA,2022,50(06):1291-1300. DOI： 10.12263/DZXB.20210830.

摘要

先进多功能雷达可以实现灵活的波束调度和复杂的工作状态调制，进而在雷达时间线上同时执行多个不同的任务，给电子侦察设备带来了巨大挑战.准确快速地对多功能雷达工作状态切换点进行在线检测对识别多功能雷达行为意图具有重要意义.本文在对多功能雷达层次化模型中工作状态所在“符号-脉冲”层进行调制类型级和参数级扩展表征基础上，提出了一种非理想观测下的多功能雷达工作状态在线切换点检测算法.该方法针对真实信号环境中存在的测量误差、虚假脉冲和缺失脉冲等情况进行适应性设计，通过离群点剔除处理和广义切换点检测算法处理，不仅可以实现调制参数粒度的雷达工作状态在线切换点检测，还可以给出雷达工作状态调制参数在切换点前后的准确估计.仿真实验验证了本文提出方法相较传统切换点检测方法的有效性和优越性.

Abstract

Multi-function radars(MFRs) have great flexibilities in beam scheduling and complex modulation of radar work modes. It can perform multiple system tasks simultaneously in the radar timeline

which brings great challenges to electronic reconnaissance devices. Online detection of multiple MFR work mode changepoints accurately and rapidly is of great importance for identifying the behavioral intentions of a multi-function radar. This paper proposes an online detection method of MFR work mode changepoints. The proposed method takes the measurement noise

spurious pulses and lost pulses in real electromagnetic environment into consideration and can realize online changepoints detection of radar working mode under the observations contaminated by these non-ideal situations. Also

this method can estimate the modulation parameters of the work modes before and after the changepoints. Experimental results validate the effectiveness and superiority of the proposed method compared with the traditional changepoint detection methods.

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Keywords

references

LI Y J , ZHU M T , MA Y H , et al . Work modes recognition and boundary identification of MFR pulse sequences with a hierarchical seq2seq LSTM [J]. IET Radar , Sonar & Navigation, 2020 , 14 ( 9 ): 1343 - 1353 .

FANG Y , BI D P , PAN J F , et al . Multi-function radar behavior state detection algorithm based on Bayesian criterion [C]// 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference(IAEAC) . Chengdu : IEEE , 2019 : 213 - 217 .

TARTAKOVSKY A , NIKIFOROV I , BASSEVILLE M . Sequential Analysis: Hypothesis Testing and Changepoint Detection [M]. New York : Chapman & Hall/CRC , 2014 .

POOR H V , HADJILIADIS O . Quickest Detection [M]. Cambridge : Cambridge University Press , 2008 .

VEERAVALLI V V , BANERJEE T . Quickest change detection [M]// Academic Press Library in Signal Processing . Amsterdam : Elsevier , 2014 : 209 - 255 .

CHEN Y C , BANERJEE T , DOMINGUEZ-GARCIA A D , et al . Quickest line outage detection and identification [J]. IEEE Transactions on Power Systems , 2016 , 31 ( 1 ): 749 - 758 .

RAGHAVAN V , VEERAVALLI V V . Quickest change detection of a Markov process across a sensor array [J]. IEEE Transactions on Information Theory , 2010 , 56 ( 4 ): 1961 - 1981 .

PEEL L , CLAUSET A . Detecting change points in the large-scale structure of evolving networks [C]// Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence . New York : ACM , 2015 : 2914 - 2920 .

AMORESE D . Applying a change-point detection method on frequency-magnitude distributions [J]. Bulletin of the Seismological Society of America , 2007 , 97 ( 5 ): 1742 - 1749 .

LEE K C , KRIEGMAN D . Online learning of probabilistic appearance manifolds for video-based recognition and tracking [C]// 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition . San Diego : IEEE , 2005 : 852 - 859 .

LAI L F , FAN Y J , POOR H V . Quickest detection in cognitive radio: A sequential change detection framework [C]// 2008 IEEE Global Telecommunications Conference . New Orleans : IEEE , 2008 : 1 - 5 .

马爽 , 柳征 , 姜文利 . 基于幅度变化点检测的多功能雷达脉冲列解析方法 [J]. 电子学报 , 2013 , 41 ( 7 ): 1436 - 1441 .

MA S , LIU Z , JIANG W L . A method for multifunction radar pulse train analysis based on amplitude change point detection [J]. Acta Electronica Sinica , 2013 , 41 ( 7 ): 1436 - 1441 . (in Chinese)

VISNEVSKI N A . Syntactic Modeling of Multi-Function Radars [D]. Hamilton : McMaster University , 2005 .

VISNEVSKI N , KRISHNAMURTHY V , WANG A , et al . Syntactic modeling and signal processing of multifunction radars: A stochastic context-free grammar approach [J]. Proceedings of the IEEE , 2007 , 95 ( 5 ): 1000 - 1025 .

WANG A , KRISHNAMURTHY V . Signal interpretation of multifunction radars: Modeling and statistical signal processing with stochastic context free grammar [J]. IEEE Transactions on Signal Processing , 2008 , 56 ( 3 ): 1106 - 1119 .

OU J , CHEN Y G , ZHAO F , et al . Method for operating mode identification of multi-function radars based on predictive state representations [J]. IET Radar , Sonar & Navigation, 2017 , 11 ( 3 ): 426 - 433 .

刘海军 , 樊昀 , 李悦 , 等 . 多功能雷达建模中的雷达字提取技术研究 [J]. 国防科技大学学报 , 2010 , 32 ( 2 ): 91 - 96 .

LIU H J , FAN Y , LI Y , et al . Research on extracting of radar words in modeling of multi-function radar [J]. Journal of National University of Defense Technology , 2010 , 32 ( 2 ): 91 - 96 . (in Chinese)

王勇军 . 一种改进的事件驱动的MFR雷达字提取方法 [J]. 现代雷达 , 2019 , 41 ( 3 ): 17 - 20,26 .

WANG Y J . Novel approach of radar word extraction for MFRs based on event-driven method [J]. Modern Radar , 2019 , 41 ( 3 ): 17 - 20,26 . (in Chinese)

代鹂鹏 , 王布宏 , 蔡斌 , 等 . 基于SCFG建模的多功能雷达状态估计算法 [J]. 空军工程大学学报(自然科学版) , 2014 , 15 ( 3 ): 24 - 28 .

DAI L P , WANG B H , CAI B , et al . A method for states estimation of multi-function radar based on stochastic context free grammar [J]. Journal of Air Force Engineering University(Natural Science Edition) , 2014 , 15 ( 3 ): 24 - 28 . (in Chinese)

OU J , CHEN Y G , ZHAO F , et al . Novel approach for the recognition and prediction of multi-function radar behaviours based on predictive state representations [J]. Sensors(Basel, Switzerland) , 2017 , 17 ( 3 ): 632 .

APFELD S , CHARLISH A , Modelling ASCHEID G. , learning and prediction of complex radar emitter behaviour [C]// 2019 18th IEEE International Conference on Machine Learning and Applications . Boca Raton : IEEE , 2019 : 305 - 310 .

ZHU M T , ZHANG Z W , LI C , et al . JMRPE-Net: Joint modulation recognition and parameter estimation of cognitive radar signals with a deep multitask network [J]. IET Radar , Sonar & Navigation, 2021 , 15 ( 11 ): 1508 - 1524 .

ZHU M T , WANG S F , LI Y J . Model based representation and deinterleaving of mixed radar pulse sequences with neural machine translation network [J]. IEEE Transactions on Aerospace and Electronic Systems , 2021 : DOI:10.1109/TAES.2021.3122411.

NIKIFOROV I V . Two strategies in the problem of change detection and isolation [J]. IEEE Transactions on Information Theory , 1997 , 43 ( 2 ): 770 - 776 .

Nielsen S F . An introduction to analysis of financial data with R [J]. Journal of Applied Statistics , 2014 , 41 ( 12 ): 2777 - 2778 .

LORDEN G . Procedures for reacting to a change in distribution [J]. The Annals of Mathematical Statistics , 1971 , 42 ( 6 ): 1897 - 1908 .

TAKEUCHI J , YAMANISHI K . A unifying framework for detecting outliers and change points from time series [J]. IEEE Transactions on Knowledge and Data Engineering , 2006 , 18 ( 4 ): 482 - 492 .

ZHU M T , LI Y J , WANG S F . Model-based time series clustering and interpulse modulation parameter estimation of multifunction radar pulse sequences [J]. IEEE Transactions on Aerospace and Electronic Systems , 2021 , 57 ( 6 ): 3673 - 3690 .

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