This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.
Sayanti Dutta,
Rintu Kumar Gayen,
Raisa Chatterjee,
Tamesh Halder,
Rintu Kumar Gayen,
- Student, Department of Electronics and Communication Engineering Institute of Engineering & Management,, kolkata, India
- Student, Department of Electronics and Communication Engineering Institute of Engineering & Management,, kolkata, India
- Student, Department of Electrical Engineering, Jadavpur University,, kolkata, India
- Professor, Department of Mining Engineering Indian Institute of Technology,, Kolkata, India
- Student, Department of Electronics and Communication Engineering Institute of Engineering & Management,, Kolkata, India
Abstract
This paper provides insights into Time Multiplexed Binary Offset Carrier (TMBOC), a modulation technique employed in satellite navigation systems, specifically designed for GPS L1C. TMBOC improves signal correlation properties by time-multiplexing Binary Offset Carrier (BOC) (1, 1) and (6, 1). The text discusses various TMBOC models, including spectral representations and power distributions. Performance analysis reveals the potential of TMBOC signals in achieving superior tracking accuracy and interference resistance compared to other modulation techniques. Spectrum allocation considerations for TMBOC in the GPS L1 band are addressed. The information underscores the significance of TMBOC in enhancing the robustness and precision of satellite navigation systems, contributing to the continual evolution of signal modulation strategies in this technological domain. The literature on PolInSAR and PolSAR assesses the various techniques for estimating the forest height, biomass, and complex coherence. The study involves complex Wishart distribution-based methods and target decomposition-based methods. These techniques have the potency to demonstrate and retrieve the vegetation parameters and perform various land cover-based classifications. The images taken by radar have to be linked with GPS co-ordinates and ground control points for making digital surface model (DSM). This work is done at base stations while the GPS signals and images are received at master control units (MCU). Hence the thorough study and simulation of current state of arts in navigation paves the way of geographic-information systems (GIS) with remote sensing. The article bridge the GPS of current era modulation technique TMBOC and radar image Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR).
Keywords: Time Multiplexed Binary Offset Carrier (TMBOC), Spectral Representations, GPS L1 Band, Signal Correlation, Signal Modulation, Spectrum Allocation, PolSAR, Pol-InSAR, Vegetation height determination, RVoG.
[This article belongs to International Journal of Satellite Remote Sensing ]
Sayanti Dutta, Rintu Kumar Gayen, Raisa Chatterjee, Tamesh Halder, Rintu Kumar Gayen. Time Multiplexed Binary Offset Carrier (TMBOC) Transmitter with Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR). International Journal of Satellite Remote Sensing. 2026; 04(01):-.
Sayanti Dutta, Rintu Kumar Gayen, Raisa Chatterjee, Tamesh Halder, Rintu Kumar Gayen. Time Multiplexed Binary Offset Carrier (TMBOC) Transmitter with Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR). International Journal of Satellite Remote Sensing. 2026; 04(01):-. Available from: https://journals.stmjournals.com/ijsrs/article=2026/view=244169
References
[1] Rabus B, Eineder M, Roth A, Bamler R. The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar. ISPRS journal of photogrammetry and remote sensing. 2003 Feb 1;57(4):241-62.
[2] Rossi C, Gonzalez FR, Fritz T, Yague-Martinez N, Eineder M. TanDEM-X calibrated raw DEM generation. ISPRS Journal of Photogrammetry and Remote Sensing. 2012 Sep 1;73:12-20.
[3] Treuhaft RN, Moghaddam M, van Zyl JJ. Vegetation characteristics and underlying topography from interferometric radar. Radio science. 1996 Nov;31(6):1449-85.
[4] Treuhaft RN, Siqueira PR. Vertical structure of vegetated land surfaces from interferometric and polarimetric radar. Radio science. 2000 Jan;35(1):141-77.
[5] Bamler R, Hartl P. Synthetic aperture radar interferometry. Inverse problems. 1998 Aug 1;14(4):R1-54.
[6] Li M. Z., H. J. Guo, W. Y. Fan, and Z. Zhen, “Remote sensing analysis of forest site quality in 6 Daxing’an mountain based on GWR,” Scientia Silvae Sinicae, June 2017, vol. 53, pp. 56-66. M. Young, The Technical Writer’s Handbook. Mill Valley, CA: University Science, 1989.
[7] Reza M, Amir MM, Imran M, Pandey G, Camponeschi F, Maresca S, Scotti F, Serafino G, Malacarne A, Porzi C, Ghelfi P. Multi-static multi-band synthetic aperture radar (SAR) constellation based on integrated photonic circuits. Electronics. 2022 Dec 12;11(24):4151.
[8] Cloude SR, Papathanassiou KP. Polarimetric SAR interferometry. IEEE Transactions on geoscience and remote sensing. 1998 Sep 30;36(5):1551-65.
[9] Brandfass M, Hofmann C, Mura JC, Papathanassiou KP. Polarimetric SAR interferometry as applied to fully polarimetric rain forest data. InIGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No. 01CH37217) 2001 Jul 9 (Vol. 6, pp. 2575-2577). IEEE.
[10] Yamada H, Sato K, Yamaguchi Y, Boerner WM. Interferometric phase and coherence of forest estimated by ESPRIT-based polarimetric SAR interferometry. InIEEE International Geoscience and Remote Sensing Symposium 2002 Jun 24 (Vol. 2, pp. 829-831). IEEE.
| Volume | 04 |
| Issue | 01 |
| Received | 17/03/2026 |
| Accepted | 18/03/2026 |
| Published | 16/05/2026 |
| Publication Time | 60 Days |
Login
PlumX Metrics