Journal of Convergence for Information Technology (융합정보논문지)

Convergence Society for SMB (중소기업융합학회)
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Feature Extraction of Radar Signals Using Streaming Process

스트리밍 처리에 의한 레이더 신호 특성 추출

  • Kim, Gwan-Tae (Division of Technology-Research, VICTEK) ;
  • Ju, Young-Kwan (Department of Computer Science, Chungbuk National University) ;
  • Jeon, Joongnam (Department of Computer Science, Chungbuk National University)
  • 김관태 ((주)빅텍 기술연구소) ;
  • 주영관 (충북대학교 소프트웨어학과) ;
  • 전중남 (충북대학교 소프트웨어학과)
  • Received : 2020.11.10
  • Accepted : 2020.12.20
  • Published : 2020.12.28
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Abstract

Radar signal identification of electronic warfare is a technology that recognizes the pulse repetition interval (PRI) from a set of pulse description words (PDWs) generated by the signal receiver. Conventionally batch processing is widely used in which a number of PDWs are collected as a unit and identifies PRI from the batch. In this paper, we propose a feature extraction algorithm based on the streaming process. This technique does not wait to form a batch. Whenever a PDW(Pulse Description Word) is generated from the signal receiver, the streaming process tries to form a cluster of PDWs, and makes the DTOA (Difference of Time of Arrival) histogram, finds out the frame PRI based on the concentration ratio, and decides the number of stagger stages. Experiments proved that the proposed algorithm derives stable recognition results as the cluster size increases.

전자전의 레이더 신호식별은 신호수신기가 생성한 PDW(Pule Description Word)를 분석해서 펄스반복 간격(PRI, Pulse Repetition Interval)을 인식하는 기술이다. 일반적으로 여러 개의 PDW를 수집해 한 번에 처리하는 배치처리 방식으로 PRI를 식별한다. 본 논문에서는 스트리밍 프로세스에 기초한 신호 특성 추출 알고리즘을 제안한다. 이 기술은 신호수신기에서 PDW를 생성할 때마다 PDW 군집이 형성되는지 조사하고, 레이더 펄스의 도착시간 차이(difference of TOA(Time of Arrival)) 히스토그램을 만들고, 집중도를 기반으로 프레임 PRI를 구하고, 스태거 단계 수를 결정한다. 실험에 의하여 군집의 크기가 증가함에 따라 안정된 인식 결과를 도출한다는 것을 입증했다.

Keywords

References

  1. D. R. Wilkinson & A.W. Watson, (1985). Use of metric techniques in ESM data processing, IEE proceedings on F Communications radar and signal processing. 132(4), 229-232. DOI : 10.1049/ip-f-1.1985.0055
  2. H. K. Mardia, (1998). Adaptive Multi-Dimensional Clustering for ESM. In IEE Colloquium on signal processing for ESM systems (pp. 5-1). IET.
  3. D. W. Lee, J. W. Han & W. D. Lee, (2008). Adaptive radar pulses clustering based on density cluster window, In ITC-CSCC: International Technical Conference on Circuits Systems, Computers and Communications (pp. 1377-1380).
  4. J. W. Han, K. H. Song, D. W. Lee & S. C. Lye, (2007). A novel clustering algorithm of radar pulses based on the adaptive cluster window, International Symposium on Computer and Information Sciences.
  5. H. K. Mardia, (1989). New technique for the deinterleaving of repetitive sequence, In IEE Proceedings F (Radar and Signal Processing) (Vol. 136, No. 4, pp. 149-154). IET Digital Library. DOI : 10.1049/ip-f-2.1989.0025.
  6. Y. W. Kim & H. W. Yang, (2002). An Algorithm for Estimating Pulse Repetition Intervals of Stagger PRI Pulse Train Using 2D-TDOA Histogram, Journal of Institute of Control, Robotics and Systems, 8(8), 673-681. DOI : 10.5302/J.ICROS.2002.8.8.673
  7. Y. J. Ryu, K. H. Song & W. W. Kim, (2007). Recognition of PRI modulation types of radar signals using the autocorrelation, IEICE transactions on communications, 90(5), 1290-1294. DOI : 10.1093/ietcom/e90-b.5.1290
  8. J. S. Lim, K. H. Hong, G. S. Jun, S. C. Moon, C. J. Lee & S. H. Suh, (2008). Analysis of PRI Pattern with the Second Deviation of LASER Pulse Train, The Journal of the Korea Contents Association, 8(4), 63-70. DOI : 10.5392/JKCA.2008.8.4.063
  9. J. S. Lim, K. H. Hong, D. Y. Lee, D. H. Shin & Y. H. Kim, (2009). A De-interleaving Method of Frequency Agility Radar Signals in Comparison with PRI's of radars. Journal of the Korea Academia-Industrial cooperation Society, 10(8), 1832-1838. DOI : 10.5762/KAIS.2009.10.8.1832
  10. J. S. Lim, K. H. Hong, D. Y. Lee, D. H. Shin & Y. H. Kim, (2009). An Identify of Two Step Stagger Signals Using the Second Deviation of Pulse Train, Journal of the Korea Academia-Industrial cooperation Society, 10(7), 1536-1541. DOI : 10.5762/KAIS.2009.10.7.1536
  11. Y. K. Ju & J. N. Jeon, (2020). Extraction of Pulse Repetition Interval for Radar Signals Using Kernel Function based DTOA Histogram, The Institute of Electronics and Information Engineers, 57(2), 81-87. DOI : 10.5573/ieie.2020.57.2.81
  12. J. T. Lee, Y. K. Ju, G. T. Kim & J. N. Jeon, (2014). A Clustering Technique of Radar Signals using 4-Dimensional Features. Journal of the Institute of Electronics and Information Engineers, 51(10), 137-144. DOI : 10.5573/ieie.2014.51.10.137
  13. S. H. Park, Y. K. Ju, G. T. Kim & J. N. Jeon, (2016). A Detection Algorithm for Pulse Repetition Interval Sequence of Radar Signals based on Finite State Machine, The Institute of Electronics and Information Engineers, 53(7) 85-91, DOI : 10.5573/ieie.2016.53.7.085
  14. G. T. Kim, Y. K. Ju & J. N. Jeon, (2018). A Detection Algorithm for Modulation Types of Radar Signals Using Autocorrelation Comparison Ranges, Journal of Convergence for Information Technology, 8(5), 137-143,. DOI : 10.22156/CS4SMB.2018.8.5.137