Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
권호 표지
DOI QR코드

DOI QR Code

Source Enumeration Method using Eigenvalue Gap Ratio and Performance Comparison in Rayleigh Fading

Eigenvalue Gap의 Ratio를 이용한 신호 개수 추정 방법 및 Rayleigh Fading 환경에서의 신호 개수 추정 성능 비교

  • Kim, Taeyoung (Electronic Warfare Research Center, Gwangju Institute of Science and Technology) ;
  • Lee, Yunseong (Electronic Warfare Research Center, Gwangju Institute of Science and Technology) ;
  • Park, Chanhong (Electronic Warfare Research Center, Gwangju Institute of Science and Technology) ;
  • Choi, Yeongyoon (School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology) ;
  • Kim, Kiseon (School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology) ;
  • Lee, Dongkeun (Radar & EW Technology Center, Agency for Defense Development) ;
  • Lee, Myung-Sik (Electronic Warfare R&D center, LIG Nex1 Co., Ltd.) ;
  • Kang, Hyunjin (Electronic Warfare R&D center, LIG Nex1 Co., Ltd.)
  • 김태영 (광주과학기술원 전자전특화연구센터) ;
  • 이윤성 (광주과학기술원 전자전특화연구센터) ;
  • 박찬홍 (광주과학기술원 전자전특화연구센터) ;
  • 최영윤 (광주과학기술원 전기전자컴퓨터공학부) ;
  • 김기선 (광주과학기술원 전기전자컴퓨터공학부) ;
  • 이동근 (국방과학연구소 레이다/전자전기술센터) ;
  • 이명식 (LIG넥스원(주) 전자전연구소) ;
  • 강현진 (LIG넥스원(주) 전자전연구소)
  • Received : 2021.03.08
  • Accepted : 2021.08.10
  • Published : 2021.10.05
Download PDF
⟨ Previous Next ⟩

Abstract

In electronic warfare, source enumeration and direction-of-arrival estimation are important. The source enumeration method based on eigenvalues of covariance matrix from received is one of the most used methods. However, there are some drawbacks such as accuracy less than 100 % at high SNR, poor performance at low SNR and reduction of maximum number of estimating sources. We suggested new method based on eigenvalues gaps, which is named AREG(Accumulated Ratio of Eigenvalues Gaps). Meanwhile, FGML(Fast Gridless Maximum Likelihood) which reconstructs the covariance matrix was suggested by Wu et al., and it improves performance of the existing source enumeration methods without modification of algorithms. In this paper, first, we combine AREG with FGML to improve the performance. Second, we compare the performance of source enumeration and direction-of-arrival estimation methods in Rayleigh fading. Third, we suggest new method named REG(Ratio of Eigenvalues Gaps) to reduce performance degradation in Rayleigh Fading environment of AREG.

Keywords

Acknowledgement

본 연구는 국방과학연구소(과제명: 무인기용 U/VHF 대역 통신 ES장비)의 지원을 받아 수행한 연구 결과입니다. 보안상 장비제원은 실제원과 다를 수 있음을 고지합니다.

References

  1. D. Adamy, "EW Against a New Generationof Threats: EW 104," GIST Press, Korea, pp. 9-39, 2020.
  2. H. Chin, S. Kim, J. Choi and J. Lee, "A Study on the Accuracy Enhancement Using the Direction Finding Process Improvement of Ground-Based Electronic Warfare System," Journal of the Korea Academia-Industrial Cooperation Society, Vol. 18, No. 6, pp. 627-635, 2017. https://doi.org/10.5762/KAIS.2017.18.6.627
  3. L. Huang, S. Wu and X. Li, "Reduced-Rank MDL Method for Source Enumeration in High-Resolution Array Processing," IEEE Transactions on Signal Processing, Vol. 55, No. 12, pp. 5658-5667, 2007. https://doi.org/10.1109/TSP.2007.899344
  4. P. Chen, T. Wu and J. Yang "A Comparative Study of Model Selection Criteria for the Number of Signals," IET Radar, Sonar & Navigation, Vol. 2, Issue. 3, pp. 180-188, 2008. https://doi.org/10.1049/iet-rsn:20070102
  5. K. Han and A. Nehorai, "Improved Source Number Detection and Direction Estimation with Nested Arrays and ULAs using Jackknifing," IEEE Transactions on Signal Processing, Vol. 61, No. 23, pp. 6118-6128, 2013. https://doi.org/10.1109/TSP.2013.2283462
  6. M. Morency, S. Vorobyov and G. Leus, "Joint Detection and Localization of an Unknown Number of Sources using the Algebraic Structure of the Noise Subspace," IEEE Transactions on Signal Processing, Vol. 66, No. 17, pp. 4685-4700, 2018. https://doi.org/10.1109/tsp.2018.2847692
  7. Q. Pan, C. Mei, N. Tian, B. Ling and E. Wang, "Source Enumeration based on a Uniform Circular Array in a Determined Case," IEEE Transactions on Vehicular Technoglogy, Vol. 68, No. 1, pp. 700-712, 2019. https://doi.org/10.1109/TVT.2018.2884522
  8. M. Wax and T. Kailath, "Detection of Signals by Information Theoretic Criteria," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 33, No. 2, pp. 387-392, 1998. https://doi.org/10.1109/TASSP.1985.1164557
  9. Z. He, A. Cichocki, S. Xie and K. Choi, "Detecting the Number of Clusters in n-Way Probabilistic Clustering," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 11, pp. 2006-2021, 2010. https://doi.org/10.1109/TPAMI.2010.15
  10. R. Schmidt, "Multiple Emitter Location and Signal Parameter Estimation," IEEE Transactions on Antennas and Propagation, Vol. 34, No. 3, pp. 276-280, 1986. https://doi.org/10.1109/TAP.1986.1143830
  11. R. Roy and T. Kailath, "ESPRIT-Estimation of Signal Parameters via Rotational Invariance Techniques," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 37, No. 7, pp. 984-995, 1989. https://doi.org/10.1109/29.32276
  12. Z. Chen, G. Gokeda and Y. Yu, "Introduction to Direction-of-Arrival Estimation," Artech House, U.S.A., pp. 31-92, 2010.
  13. X. Wu, W. Zhu and J. Yan, "A Fast Gridless Covariance Matrix Reconstruction Method for Oneand Two-Dimensional Direction-of-Arrival Estimation," IEEE Sensors Journal, Vol. 17, No. 15, pp. 4916-4927, 2017. https://doi.org/10.1109/JSEN.2017.2709329
  14. Y. Lee, C. Park, T. Kim, Y. Choi, K. Kim, D. Kim, M.-S.Lee and D. Lee, "Source Enumeration Approaches using Eigenvalue Gaps and Machine Learning based Threshold for Direction-of-Arrival Estimation," Applied Science, Vol. 11, No. 4, p. 1942, Feb. 2021. https://doi.org/10.3390/app11041942
  15. S. Beheshti and S. Sedghizadeh, "Number of Source Signal Estimation by the Mean Squared Eigenvalue Error," IEEE Transactions on Signal Processing, Vol. 66, No. 21, pp. 5694-5704, 2018. https://doi.org/10.1109/tsp.2018.2870357
  16. E. Fishler and H. Poor, "Estimation of the Number of Sources in Unbalanced Arrays via Information Theoretic Criteria," IEEE Transactions on Signal Processing, Vol. 53, No. 9, pp. 3543-3553, 2005. https://doi.org/10.1109/TSP.2005.853099
  17. K. Xu, W. Pedrycz, Z. Li and W. Nie, "High-Accuracy Signal Subspace Separation Algorithm based on Gaussian Kernel Soft Partition," IEEE Transactions on Industrial Electronics, Vol. 66, No. 1, pp. 491-499, 2019. https://doi.org/10.1109/tie.2018.2823666
  18. H. Trees, "Optimum Array Processing - Detection, Estimation, and Modulation Theory," John Wiley & Sons, Inc., U.S.A., pp. 827-841, 2002.
  19. A. Badawy, T. Salman, T. Elfouly, T. Khattab, A. Mohamed and M. Guizani, "Estimating the Number of Sources in White Gaussian Noise: Simple Eigenvalues based Approaches," IET SIgnal Processing, Vol. 11, Issue. 6, pp. 669-673, 2017.
  20. F. Yan, J. Wang, S. Liu, B. Cao and M. Jin, "Computationally Efficient Direction of Arrival Estimation with Unknown Number of Signals," Digital Signal Processing, Vol. 78, pp. 175-184, 2018. https://doi.org/10.1016/j.dsp.2018.03.012
  21. A. Liavas and P. Regalia, "On the Behavior of Information Theoretic Criteria for Model Order Selection," IEEE Transactions on Signal Processing, Vol. 49, No. 8, pp. 1689-1695, 2001. https://doi.org/10.1109/78.934138
  22. S. Schell and W. Gardner, "High-Resolution Direction Finding," Handbook of Statistics, Vol. 10, pp. 755-817, 1993.
  23. T. Shan, M. Wax and T. Kailath, "On Spatial Smoothing for Direction-of-Arrival Estimation of Coherent Signals," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 33, No. 4, pp. 806-811, 1985. https://doi.org/10.1109/TASSP.1985.1164649
  24. A. Barabell, "Improving the Resolution Performance of Eigenstructure-based Direction-Finding Algorithms," ICASSP '83. IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 8, pp. 336-339, 1983.
  25. P. Pal and P. Vaidyanathan, "Nested Arrays: A Novel Approach to Array Processing with Enhanced Degrees of Freedom," IEEE Transactions on Signal Processing, Vol. 58, No. 8, pp. 4167-4181, 2010. https://doi.org/10.1109/TSP.2010.2049264
  26. P. Chevalier, A. Ferroeol and L Albera, "High-Resolution Direction Finding from Higher Oder Statistics - The 2q-MUSIC," IEEE Transactions on Signal Processing, Vol. 54, No. 8, pp. 2986-2997, 2006. https://doi.org/10.1109/TSP.2006.877661
  27. Z. Zhu and A. Nandi, "Automatic Modulation Classification - Principles, Algorithms and Applications," John Wiley & Sons, Inc., U.K., pp. 144-150, 2015.
  28. J. Jeong, K. Sakaguchi, J. Takada and K. Araki, "Performance of MUSIC and ESPRIT for Joint Estimation of DOA and Angular Spread in Slow Fading Environment," IEICE Transactions on Communications, Vol. E85-B, No. 5, pp. 972-977, 2002.
  29. J. Proakis and M. Salehi, "Digital Communications," McGraw-Hill, U.S.A., pp. 830-843, 2007.
  30. O. Hu, F. Zheng and M. Faulkner, "Detecting the Number of Signals using Antenna Array: A Single Threshold Solution," ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications(IEEE Cat. No.99EX359), pp. 905-908, 1999.
  31. M. Grant, S. Boyd, and Y. Ye, "CVX: Matlab Software for Disciplined Vonvex Programming," 2008.