Vol. 67
Latest Volume
All Volumes
PIERM 126 [2024] PIERM 125 [2024] PIERM 124 [2024] PIERM 123 [2024] PIERM 122 [2023] PIERM 121 [2023] PIERM 120 [2023] PIERM 119 [2023] PIERM 118 [2023] PIERM 117 [2023] PIERM 116 [2023] PIERM 115 [2023] PIERM 114 [2022] PIERM 113 [2022] PIERM 112 [2022] PIERM 111 [2022] PIERM 110 [2022] PIERM 109 [2022] PIERM 108 [2022] PIERM 107 [2022] PIERM 106 [2021] PIERM 105 [2021] PIERM 104 [2021] PIERM 103 [2021] PIERM 102 [2021] PIERM 101 [2021] PIERM 100 [2021] PIERM 99 [2021] PIERM 98 [2020] PIERM 97 [2020] PIERM 96 [2020] PIERM 95 [2020] PIERM 94 [2020] PIERM 93 [2020] PIERM 92 [2020] PIERM 91 [2020] PIERM 90 [2020] PIERM 89 [2020] PIERM 88 [2020] PIERM 87 [2019] PIERM 86 [2019] PIERM 85 [2019] PIERM 84 [2019] PIERM 83 [2019] PIERM 82 [2019] PIERM 81 [2019] PIERM 80 [2019] PIERM 79 [2019] PIERM 78 [2019] PIERM 77 [2019] PIERM 76 [2018] PIERM 75 [2018] PIERM 74 [2018] PIERM 73 [2018] PIERM 72 [2018] PIERM 71 [2018] PIERM 70 [2018] PIERM 69 [2018] PIERM 68 [2018] PIERM 67 [2018] PIERM 66 [2018] PIERM 65 [2018] PIERM 64 [2018] PIERM 63 [2018] PIERM 62 [2017] PIERM 61 [2017] PIERM 60 [2017] PIERM 59 [2017] PIERM 58 [2017] PIERM 57 [2017] PIERM 56 [2017] PIERM 55 [2017] PIERM 54 [2017] PIERM 53 [2017] PIERM 52 [2016] PIERM 51 [2016] PIERM 50 [2016] PIERM 49 [2016] PIERM 48 [2016] PIERM 47 [2016] PIERM 46 [2016] PIERM 45 [2016] PIERM 44 [2015] PIERM 43 [2015] PIERM 42 [2015] PIERM 41 [2015] PIERM 40 [2014] PIERM 39 [2014] PIERM 38 [2014] PIERM 37 [2014] PIERM 36 [2014] PIERM 35 [2014] PIERM 34 [2014] PIERM 33 [2013] PIERM 32 [2013] PIERM 31 [2013] PIERM 30 [2013] PIERM 29 [2013] PIERM 28 [2013] PIERM 27 [2012] PIERM 26 [2012] PIERM 25 [2012] PIERM 24 [2012] PIERM 23 [2012] PIERM 22 [2012] PIERM 21 [2011] PIERM 20 [2011] PIERM 19 [2011] PIERM 18 [2011] PIERM 17 [2011] PIERM 16 [2011] PIERM 14 [2010] PIERM 13 [2010] PIERM 12 [2010] PIERM 11 [2010] PIERM 10 [2009] PIERM 9 [2009] PIERM 8 [2009] PIERM 7 [2009] PIERM 6 [2009] PIERM 5 [2008] PIERM 4 [2008] PIERM 3 [2008] PIERM 2 [2008] PIERM 1 [2008]
2018-04-06
Accurate Parameter Estimation of Over -the-Horizon Radar Signals Using RANSAC and MUSIC Algorithms
By
Progress In Electromagnetics Research M, Vol. 67, 85-93, 2018
Abstract
Processing over-the-horizon radar (OTHR) signals is challenging due to appearance of several very close components in the time-frequency plane, strong noise and clutter, multipath propagation, and aliasing. We propose a two-stage procedure for estimating multipath signal components from the received mixture. In the first stage, the instantaneous frequency is estimated from the time-frequency representation of the received signal. The random samples consensus algorithm is applied to the instantaneous frequency estimate to improve the robustness of the procedure against various effects in the underlying signals. In the second stage, the MUSIC algorithm is applied to the dechirped and downsampled signal. The effectiveness of the proposed approach is verified using real-life signals.
Citation
Igor Djurovic, and Yimin D. Zhang, "Accurate Parameter Estimation of Over -the-Horizon Radar Signals Using RANSAC and MUSIC Algorithms," Progress In Electromagnetics Research M, Vol. 67, 85-93, 2018.
doi:10.2528/PIERM18022004
References

1. Fabrizio, G. A., High Frequency Over-the-Horizon Radar: Fundamental Principles, Signal Processing, and Practical Applications, Mc-Graw Hill Education, 2013.

2. Lan, H., Y. Liang, Q. Pan, F. Yang, and C. Guan, "An EM algorithm for multipath state estimation in OTHR target tracking," IEEE Transactions on Signal Processing, Vol. 62, No. 11, 2814-2826, 2014.
doi:10.1109/TSP.2014.2318134

3. Romeo, K., Y. B.-Shalom, and P. Willett, "Detecting low SNR tracks with OTHR using a refraction model," IEEE Transactions on Aerospace and Electronic Systems, Vol. 53, No. 6, 3070-3078, Dec. 2017.
doi:10.1109/TAES.2017.2726918

4. Thayaparan, T., R. Riddolls, and K. Shimotakahara, "Frequency monitoring system for over-the-horizon radar (OTHR) in Canada," Proc. of IRS, May 2016, DOI: 10.1109/IRS.2016.7497370.

5. Headrick, J. and M. Skolnik, "Over-the-horizon radar in the HF band," Proceedings of the IEEE, Vol. 62, 664-673, Jun. 1974.
doi:10.1109/PROC.1974.9506

6. Zhang, Y., M. Amin, and G. Frazer, "High-resolution time-frequency distributions for manoeuvring target detection in over-the-horizon radars," IEE Proceedings Radar, Sonar and Navigation, Vol. 150, 299-304, Aug. 2003.
doi:10.1049/ip-rsn:20030672

7. Wang, G., X.-G. Xia, B. Root, V. Chen, Y. Zhang, and M. Amin, "Manoeuvring target detection in over-the-horizon radar using adaptive clutter rejection and adaptive chirplet transform," IEE Proceedings Radar, Sonar and Navigation, Vol. 150, 292-298, Aug. 2003.
doi:10.1049/ip-rsn:20030700

8. Ioana, C., Y. Zhang, M. Amin, F. Ahmad, G. Frazer, and B. Himed, "Time-frequency characterization of micro-multipath signals in over-the-horizon radar," Proc. of Radar Conf., May 2012.

9. Djurović, I., S. Djukanović, M. G. Amin, Y. D. Zhang, and B. Himed, "High-resolution time-frequency representations based on the local polynomial Fourier transform for over-the-horizon radars," Proc. of SPIE, Vol. 8361, May 2012, doi: 10.1117/12.919954.

10. Stanković, L. J., I. Djurović, S. Stanković, M. Simeunović, and M. Daković, "Instantaneous frequency in time-frequency analysis: Enhanced concepts and performance of estimation algorithms," Digital Signal Processing, Vol. 35, 1-13, Dec. 2014.
doi:10.1016/j.dsp.2014.09.008

11. Djurović, I., "A WD-RANSAC instantaneous frequency estimator," IEEE Signal Processing Letters, Vol. 23, No. 5, 757-761, May 2016.
doi:10.1109/LSP.2016.2551732

12. Djurović, I., "QML-RANSAC: PPS and FM signals estimation in heavy noise environments," Signal Processing, Vol. 130, 142-151, Jan. 2017.
doi:10.1016/j.sigpro.2016.06.022

13. Sheng, H., Y. Gao, B. Zhu, K. Wang, and X. Liu, "Feature extraction of SAR scattering centers using M-RANSAC and STFRFT-based algorithm," EURASIP Journal on Advances in Signal Processing, Vol. 2016, No. 1, 46, 2016.
doi:10.1186/s13634-016-0345-z

14. Djurović, I. and L. J. Stanković, "An algorithm for the Wigner distribution based instantaneous frequency estimation in a high noise environment," Signal Processing, Vol. 84, 631-643, Mar. 2004.
doi:10.1016/j.sigpro.2003.12.006

15. Conru, C., I. Djurovic, C. Ioana, A. Quinquis, and L. J. Stanković, "Time-frequency detection using Gabor filter bank and Viterbi based grouping algorithm," Proc. of IEEE ICASSP, 2005.

16. Stanković, L. J., I. Djurović, A. Ohsumi, and H. Ijima, "Instantaneous frequency estimation by using Wigner distribution and Viterbi algorithm," Proc. of IEEE ICASSP, 2003.

17. Djurović, I., "Viterbi algorithm for chirp-rate and instantaneous frequency estimation," Signal Processing, Vol. 91, No. 5, 1308-1314, May 2011.
doi:10.1016/j.sigpro.2010.10.007

18. Djurović, I. and L. J. Stanković, "STFT-based estimator of polynomial phase signals," Signal Processing, Vol. 92, No. 11, 2769-2774, Nov. 2012.
doi:10.1016/j.sigpro.2012.05.015

19. Djurović, I. and L. J. Stanković, "Quasi maximum likelihood estimator of polynomial phase signals," IET Signal Processing, Vol. 13, No. 4, 347-359, Jun. 2014.
doi:10.1049/iet-spr.2013.0104