ANALYSIS OF RESCUE RADAR NOISE IMMUNITY UNDER BROADBAND INTERFERENCE

DOI: https://doi.org/10.15407/rpra29.03.173

O. V. Sytnik, S. O. Masalov

Abstract


Subject and Purpose. The subject of the research is the statistical characteristics of the signal, noise, and interference and their distribution functions. The emphasis is on exploring the properties of these elements and assessing their impact on algorithms designed to detect and identify the manifestations of human breathing and heartbeat during rescue operations. The work seeks comprehensive descriptions of broadband structural noise to develop optimum digital signal processing algorithms and ensure quicker and more reliable detection and identification of information signals during rescue missions.

Method and Methodology. The analysis is grounded on the mathematical modeling method. The distribution function of correlation function peaks for a pseudo-noise signal is synthesized considering the first moments. The estimates derived from this distribution are used to assess the influence of broadband structural noise on the performance of algorithms for detecting and identifying radar signals.

Results. In the most important band, where signal spectral components bear information on human breathing and heartbeat, estimates of the first four moments of a random process have been made to contribute to an appropriate model of fluctuating broadband structural noise. Analytical expressions of the function of structural interference distribution have been derived. A specific case focused on the interference represented by a phase-shift keyed signal with randomly alternating ones and zeros has been examined. Estimates of probabilities of false alarms and target misses have been calculated across various signal-to-noise ratios. Furthermore, a procedure to determine an optimal signal-detection threshold has been proposed.

Conclusions. Analytical expressions of the distribution density of broadband structural interference have been derived. Quantitative estimates have been calculated to assess the impact this interference exerts on algorithms designed for detecting and recognizing radar information signals for rescuers. An adaptive procedure adjusting a target detection threshold as interference varies during the radar operation has been proposed.

Keywords: Pseudo-Noise Modulation, Noise, Algorithm, Pulse Modulation, Mersenne code, Broadband Structural Interference, Rescue Radar, Opaque Obstacle

Manuscript submitted  19.12.2023

Radio phys. radio astron. 2024, 29(3): 173-179

REFERENCES

1. Sytnik, O.V., 2021. Problems and Solutions of Alive Human Detection Behind the Opaque Obstacles. Telecommunications and Radio Engineering, 80(9), pp. 1—13. DOI:  10.1615/TelecomRadEng.2021041902

2. Chen, K.M., Huang, Y., Zhang, J., and Norman, A., 2000. Microwave life-detection systems for searching human subjects under earthquake rubble or behind barrier. IEEE Trans. Biomed. Eng., 47(1), pp. 105—114.

3. Sytnik, O.V., 2007. Identification of Slow-Moving Targets Outside Optically Opaque Obstacles. Telecommunications and Radio Engineering, 66(18), pp. 1677—1683. DOI:https://doi.org/10.1615/TelecomRadEng.v66.i18.60

4. Sytnik, O.V., 2015. Adaptive Radar Techniques for Human Breathing Detection. J. Mechatron., 3(4), pp. 1–6. DOI:

5. Sytnik, O.V., Kartashov, V.M., 2019. Methods and Algorithms for Technical Vision in Radar Introscopy. Optoelectronics in Machine Vision-Based Theories and Applications — Advances in Computational Intelligence and Robotics, pp. 373—391. DOI: 10.4018/978- 1-5225-5751-7.ch013

6. Nguyen, T.V., Liqiong, T., Veysel, D., Syed, F.H., Nguyen, D.M., & Subhas, M., 2019. Review-Microwave Radar Sensing Systems for Search and Rescue Purposes. Sensors, 19(13), pp. 28—79.

7. Sytnik, O.V., 2018. Methods and Algorithms of Signal Processing for Rescuer’s Radar. Riga, Latvia, Palmarium Academic Publ.

8. Bugaev, A.S., Chapursky, V.V., Ivashov, S.I., Razevig, V.V., Sheyko, A.P. & Vasilyev, I.A., 2004. Through wall sensing of human breathing and heart beating by monochromatic radar. In: Proc. of the Tenth Int. Conf. on Ground Penetrating Radar, GPR 2004. Vol. 1, pp. 291—294. Delft, The Netherlands, 21—24 June 2004, Delft University of Technology.

9. Aristov, V., Gaigals, G., Supols, G., Lobanovs, Ed., Riekstins, V., and Zujs, V., 2021.Ultra-Wideband Pulse Radar with Discrete Stroboscopic Receiver for Detection of Small Targets Behind Dielectric Obstacles, Transp. Telecommun., 22(2), pp. 196—206.

10. Chernov, V.M., Pershina, M.V., 1997. "Error-free" calculation of the convolution using generalized Mersenne and Fermat transforms over algebraic fields. In: Sommer, G., Daniilidis, K., Pauli, J. (eds). Computer Analysis of Images and Patterns. CAIP 1997. Lecture Notes in Computer Science, vol. 1296. Springer, Berlin, Heidelberg. DOI: 10.1007/3-540-63460-6_171

11. Taylor, J.D. ed., 2012. Ultrawideband Radar. Applications and Design. Boca Raton, London, New York: CRC Press.

12. Sytnik, O.V., 2014. Quasi-Optimal Receiver with Non-Coherent Discriminators for Rescuer Radar. J. Commun. Eng. Networks,
2(2), pp. 55—62.

13. Saikawa, T., Tanaka, K., Tanaka, K., 2020. Formal Verification and Code-Generation of Mersenne-Twister Algorithm. In: Proc. of the Int. Symp. on Information Theory and Its Applications (ISITA), Kapolei, HI, USA, 2020.

14. Zhang, J., Du, Y., & Yan, He, 2020. Code Design for Moving Target-Detecting Radar in Nonhomogeneous Signal-Dependent Clutter. Math. Probl. Eng., 2020, id 7609547, 13 p.

15. Levanon, N., & Mozeson, E., 2004. Radar Signal. Hoboken, NJ: John Willey & Sons, Inc.

16. Van Trees, H.L., 2001. Detection, Estimation, and Modulation Theory: Detection, Estimation, and Linear Modulation Theory. John Wiley & Sons. DOI:10.1002/0471221082

17. Allan, D.W., Shoaf, J.H. & Halford, D., 1974. Statistics of Time and Frequency Data Analysis. NBS Monograph140, Washinghton D.C., pp. 151—204.

18. Hall, P. 1992. The Bootstrap and Edgeworth Expansion. Springer Series in Statistics, Springer & Verlag.

19. Garren, S.T., 1998. Maximum likelihood estimation of the correlation coefficient in a bivariate normal model, with missing data. Stat. Probab. Lett., 38(3), pp. 281—288.


Keywords


Pseudo-Noise Modulation; Noise; Algorithm; Pulse Modulation; Mersenne code; Broadband Structural Interference; Rescue Radar; Opaque Obstacle

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