Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-25T04:38:12.608Z Has data issue: false hasContentIssue false

Hypothesis Test-based Detection of Wi-Fi Interference on NavIC/IRNSS S-band Signal

Published online by Cambridge University Press:  19 March 2019

Priyanka L. Lineswala
Affiliation:
(Electronics Engineering Department, SVNIT, Surat, India)
Darshna D. Jagiwala*
Affiliation:
(Electronics Engineering Department, SVNIT, Surat, India)
Shweta N. Shah
Affiliation:
(Electronics Engineering Department, SVNIT, Surat, India)
*

Abstract

The Navigation with Indian Constellation (NavIC)/Indian Regional Navigation Satellite System (IRNSS) is an emerging satellite navigation system that provides an independent navigation system for positioning and timing services in India and up to 1,500 km from its borderline. The dual frequency NavIC system uses the L5 frequency and S-band for navigation. These navigation signals are extremely weak and susceptible to interference when they are received on Earth's surface. Moreover, the performance of these bands may be degraded by other band or out-of-band communication systems, which can become the major threat to the performance of a NavIC receiver. The main focus of this paper is to detect real-time interference of Wi-Fi signals in the S-band of the NavIC receiver. The results are prepared with respect to the Power Spectral Density (PSD), execution of acquisition stage and the detection of Wi-Fi interference with two sample hypothesis testing methods including the Kolmogorov-Smirnov (KS)-test, the t-test and the Variance (var)-test. A performance analysis of the p-value is used to measure the evidence of interference existence for hypothesis testing, decision hypothesis and probability of detection are evaluated for each hypothesis method. The results show the severity of the Wi-Fi signal as a potential source of interference for future NavIC applications.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Baghel, S.K., Ingale, M.A. and Goyal, G. (2011). Coexistence possibilities of LTE with ISM technologies and GNSS. IEEE National Conference on Communication, Bangalore, India, 15.10.1109/NCC.2011.5734742Google Scholar
Balaei, A., and Dempster, A. (2009). A statistical inference technique for GPS interference detection. IEEE Transactions on Aerospace and Electronic Systems, 45(4), 14991511.10.1109/TAES.2009.5310313Google Scholar
Desai, M.V., Jagiwala, D.D. and Shah, S.N. (2016). Impact of dilution of precision for position computation in Indian regional navigation satellite system. International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 980–986.Google Scholar
Dovis, F. (2015). GNSS Interference Threats and Counter Measures. Artech House, 2238.Google Scholar
Fadaei, N. (2016). Detection, Characterization and Mitigation of GNSS Jamming Interference using Pre-Correlation Methods, PhD Dissertation, University of Calgary, 48.Google Scholar
ISRO ICD. (2017). Indian Regional Navigation Satellite System, Signal In Space ICD, For Standard Positioning Service, Version 1.1.Google Scholar
Landry, R.J. and Renaud, A. (1997). Analysis of Potential Interference Sources and Assessment of Present Solutions for GPS/GNSS Receivers. 4th Saint Petersburg International Conference on Integrated Navigation Systems, 113.Google Scholar
Lehmann, E.L. and Romano, J.P. (2006). Testing statistical hypotheses. Springer Science & Business Media, 584590.Google Scholar
Marti, L. and Van Graas, F. (2004). Bias Detection and Its Confidence Assessment in Global Positioning System Signals. In Aerospace Conference, IEEE Proceedings, Big Sky, MT, USA, 14181431.10.1109/AERO.2004.1367935Google Scholar
Mateu, I., Boulanger, C., Issler, J.L., Ries, L., Avila-Rodriguez, J.A., Wallner, S., Kraus, T., Eissfeller, B., Mulassano, P., Caporale, M. and Germaine, S. (2009). Exploration of Possible GNSS Signals in S-band. Proceedings of the 22nd International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS), Savannah, United States, 15731587.Google Scholar
Peck, R., Olsen, C. and Devore, J.L. (2015). Introduction to statistics and data analysis. Cengage Learning, 577683.Google Scholar
Santra, A., Mahato, S., Mandal, S., Dan, S., Verma, P., Banerjee, P. and Bose, A. (2018). Augmentation of GNSS utility by IRNSS/NavIC constellation over the Indian region. Advances in Space Research, DOI: 10.1016/j.asr.2018.04.020.Google Scholar
Sawilowsky, S.S. (2002). Fermat, Einstein, and Behrens-Fisher: the probable difference between two means. Journal of Modern Applied Statistical Methods, 1, pp. 461472.10.22237/jmasm/1036109940Google Scholar
Soualle, F., Bey, T., Floch, J.-J., Hurd, D., Notter, M., Mathew, C., Mattos, P. and Mongredien, C. (2011). Assessment on the use of S-Band for Combined Navigation and Communication. Proceedings of the 24th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2011), Portland, Oregon, 12191223.Google Scholar
Tani, A. and Fantacci, R. (2008). Performance Evaluation of a Precorrelation Interference Detection Algorithm for the GNSS based on Nonparametrical Spectral Estimation. IEEE Systems Journal, 2(1), 2026.10.1109/JSYST.2007.914772Google Scholar
Zaminpardaz, S., Teunissen, P.J. and Nadarajah, N. (2017). IRNSS/NavIC Single-Point Positioning: A Service Area Precision Analysis. Journal of Marine Geodesy, 40(2), 259274.10.1080/01490419.2016.1269034Google Scholar