Известия высших учебных заведений России. Радиоэлектроника

Расширенный поиск

Probability of Pulse Overlap as a Quantitative Indicator of Signal Environment Complexity

Полный текст:


Introduction. Simultaneous operation of numerous sources of radio emission form complex signal environment. Different devices with the common name “wideband analyzers” (WBA) are widely used to analyze and to control such environment. There is currently a need for developing the quantitative characteristics of a complex signal environment, which will make it possible to predict the stability of the WBA operation.

Aim. The development of the indicator of the signal environment complexity, which will make possible the quantitative assessment of such environment.

Materials and methods. To provide the desired indicator, simulation and mathematical tools for random events description are used. All calculations are performed using MatLab.

Results. The principles of disturbances in the WBA receiver and algorithmic errors in the processing of overlapped signals are described. To quantify the “complexity” of the signal environment it is proposed to use the probability that pulses from several sources overlap in time. This allows one to compare signal environments with each other. The new analytical expression for estimating the pulse overlap probability is proposed. Functions of the pulse overlap probability from the complex signal environment parameters were obtained.

Conclusion. According to the comparative analysis of the calculations using proposed analytical expression and simulation, the new expression allows one to achieve the calculation speed up to 6 orders of magnitude higher with an error below 7% compared to the simulation. The high performance of the calculations using the proposed expression allows one to simulate the complex signal environment in dynamics more efficiently.

Об авторах

А. S. Podstrigaev
Saint Petersburg Electrotechnical University
Alexey S. Podstrigaev, Cand. Sci. (Eng.) in Radar and Radio Navigation (2016), Associate Professor of the Department of Radio-Electronic Means, Head of Research Laboratory at JSC "Research Institute "Vector", 5 Professor Popov St., St Petersburg 197376, Russia

А. V. Smolyakov
Saint Petersburg Electrotechnical University
Andrey V. Smolyakov, Bachelor in Radio Engineering (2020), Design Engineer at JSC "Research Institute "Vector", 5 Professor Popov St., St Petersburg 197376, Russia

I. V. Maslov
EvoCo Inc.
Igor V. Maslov, PhD in Computer Science (2008, City University of New York), co-founder at the start-up R&D company, member of the Association for Computing Machinery, member of IEEE, 1-24-16 Sasazuka, Shibuya-ku, Tokyo, Japan

Список литературы

1. Soltanmohammadi E., Ghavami K., Naraghi-Pour M. A Survey of Traffic Issues in Machine-to-Machine Communications Over LTE. IEEE Internet of Things Journal, 2016, vol. 3, no. 6, pp. 865–884. doi: 10.1109/JIOT.2016.2533541

2. Wang B., Xu Q., Chen C., Zhang F., Liu K. J. R. The Promise of Radio Analytics: A Future Paradigm of Wireless Positioning, Tracking, and Sensing. IEEE Signal Processing Magazine, 2018, vol. 35, no. 3, pp. 59–80. doi: 10.1109/MSP.2018.2806300

3. Jaber M., Imran M. A., Tafazolli R., Tukmanov A. 5G Backhaul Challenges and Emerging Research Directions: A Survey. IEEE Access, 2016, vol. 4, pp. 1743–1766. doi: 10.1109/ACCESS.2016.2556011

4. Wiley R. G. ELINT: The Interception and Analysis of Radar Signals. Norwood: Artech House Publishers, 2006. 470 p.

5. Albaker B. M., Rahim N. A. Signal Acquisition and Parameter Estimation of Radio Frequency Pulse Radar Using Novel Method. IETE Journal of Research, 2009, vol. 55, no. 3, pp.128–134. doi: 10.4103/0377-2063.54903

6. Marki F., Marki C. Mixer Basics Primer: A Tutorial for RF & Microwave Mixers. Available at: (accessed 26.05.2020)

7. Sharma S., Bhatia V., Deka K., Gupta A. Sparsity-Based Monobit UWB Receiver Under Impulse Noise Environments. IEEE Wireless Communications Letters, 2019, vol. 8, no. 3, pp. 849–852. doi: 10.1109/LWC.2019.2896998

8. Yin H., Wang Z., Ke L., Wang J. Monobit digital receivers: design, performance, and application to impulse radio. IEEE Transactions on Communications, 2010, vol. 58, no. 6, pp. 1695–1704. doi: 10.1109/TCOMM.2010.06.080446

9. Wang Z., Yin H., Zhang W., Wei G. Monobit Digital Receivers for QPSK: Design, Performance and Impact of IQ Imbalances. IEEE Transactions on Communications, 2013, vol. 61, no. 8, pp. 3292–3303. doi: 10.1109/TCOMM.2013.061913.120304

10. Sanchez M. A., Garrido M., Lopez-Vallejo M., Grajal J. Implementing FFT-based digital channel-ized receivers on FPGA platforms. IEEE Transactions on Aerospace and Electronic Systems, 2008, vol. 44, no. 4, pp. 1567–1585. doi: 10.1109/TAES.2008.4667732

11. Moon T., Choi H. W., Tzou N., Chatterjee A. Wideband Sparse Signal Acquisition With Dual-rate Time-Interleaved Undersampling Hardware and Multicoset Signal Reconstruction Algorithms. IEEE Transactions on Signal Processing, 2015, vol. 63, no. 24, pp. 6486–6497. doi: 10.1109/TSP.2015.2469648

12. Fu N., Huang G., Zheng L., Wang X. Sub-Nyquist Sampling of Multiple Sinusoids. IEEE Signal Processing Letters, 2018, vol. 25, no. 4, pp. 581–585. doi: 10.1109/LSP.2018.2813321

13. Maroosi A., Bizaki H. K. Digital Frequency Determination of Real Waveforms Based on Multiple Sensors With Low Sampling Rates. IEEE Sensors Journal, 2012, vol. 12, no. 5, pp. 1483–1495. doi: 10.1109/JSEN.2011.2173482

14. Nguyen T. D.; Reeves S. J., Denney T. S. Optimal pulse shape for estimating positions of superim-posed pulses. Proceedings of the 1998 IEEE International Conf. on Acoustics, Speech and Signal Processing. Seattle, WA, USA, 1998, pp. 2413–2416. doi: 10.1109/ICASSP.1998.681637

15. Podstrigaev A. S., Smolyakov A. V., Davydov V. V., Myazin N. S., Slobodyan M. G. Features of the Development of Transceivers for Information and Communication Systems Considering the Distribution of Radar Operating Frequencies in the Frequency Range. Lecture Notes in Computer Science, 2018, pp. 509–515. doi: 10.1007/978-3-030-01168-0_45

16. Arenas J. P., Al-Oudatallah, J., Abboud F., Khoury M., Ibrahim H. Overlapping Signal Separation Method Using Superresolution Technique Based on Experimental Echo Shape. Advances in Acoustics and Vibration, 2017, vol. 2017, 9 p. doi: 10.1155/2017/7132038

17. Sarabia E. G., Llata J. R., Robla S., Torre-Ferrero C., Oria J. P. Accurate Estimation of Airborne Ultrasonic Time-of-Flight for Overlapping Echoes. Sensors, 2013, vol. 13, pp. 15465–15488. doi: 10.3390/s131115465

18. Petrochilos N., van der Veen A. J. Algorithms to separate overlapping secondary surveillance radar replies. 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing. Montreal, 2004, pp. 49–52. doi: 10.1109/ICASSP.2004.1326191

19. Liu Y., Zhang Q. Improved method for deinterleaving radar signals and estimating PRI values. IET Radar, Sonar & Navigation, 2018, vol. 12, no. 5, pp. 506–514. doi: 10.1049/iet-rsn.2017.0516

20. Ge Z., Sun X., Ren W., Chen W., Xu G. Improved Algorithm of Radar Pulse Repetition Interval De-interleaving Based on Pulse Correlation. IEEE Access, 2019, vol. 7, pp. 30126–30134. doi: 10.1109/ACCESS.2019.2901013

21. Skolnik M. I. Radar handbook. New York: McGraw-Hill, 2008. 1328 p.

22. Self A. G., Smith B. G. Intercept time and its prediction. IEE Proceedings F - Communications, Radar and Signal Processing, 1985, vol. 132, no. 4, pp. 215–220. doi: 10.1049/ip-f-1.1985.0052

23. Kelly S. W., Noone G. P., Perkins J. E. Synchronization effects on probability of pulse train interception. IEEE Transactions on Aerospace and Electronic Systems, 1996, vol. 32, no. 1, pp. 213–220. doi: 10.1109/7.481263

24. Apfeld S., Charlish A., Koch W. An Adaptive Receiver Search Strategy for Electronic Support. 2016 Sensor Signal Processing for Defence. Edinburgh, 2016, pp. 1–5. doi: 10.1109/SSPD.2016.7590587

25. Clarkson I. V. L. Optimisation of Periodic Search Strategies for Electronic Support. IEEE Transactions on Aerospace and Electronic Systems, 2011, vol. 47, no. 3, pp. 1770–1784. doi: 10.1109/TAES.2011.5937264

26. Sauter M. From GSM to LTE-Advanced Pro and 5G: An Introduction to Mobile Networks and Mobile Broadband. Hoboken: Wiley, 2017, 544 p.

27. Mobile, radiodetermination, amateur and related satellite services. ITU Recommendations. Available at: (accessed 26.05.2020)


Для цитирования:

Podstrigaev А.S., Smolyakov А.V., Maslov I.V. Probability of Pulse Overlap as a Quantitative Indicator of Signal Environment Complexity. Известия высших учебных заведений России. Радиоэлектроника. 2020;23(5):37-45.

For citation:

Podstrigaev A.S., Smolyakov A.V., Maslov I.V. Probability of Pulse Overlap as a Quantitative Indicator of Signal Environment Complexity. Journal of the Russian Universities. Radioelectronics. 2020;23(5):37-45.

Просмотров: 482

Creative Commons License
Контент доступен под лицензией Creative Commons Attribution 4.0 License.

ISSN 1993-8985 (Print)
ISSN 2658-4794 (Online)