Topic Editors

Prof. Dr. Zhongliang Deng
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Dr. Jichong Han
School of Geography and Planning, Chengdu University of Technology, Chengdu, China

Communication–Navigation–Sensing for Space-Air-Ground-Sea Integrated System

Abstract submission deadline
31 December 2026
Manuscript submission deadline
31 March 2027
Viewed by
506

Topic Information

Dear Colleagues,

Space–Air–Ground-Sea Integrated Systems (SAGSIN) represent a major step forward in global connectivity and environmental monitoring. By combining satellites, aerial platforms (e.g., UAVs/HAPS), terrestrial and ocean networks, SAGSIN enable seamless service continuity across oceans, remote regions, and disaster areas. Today, communication, navigation, and remote sensing are often designed and operated independently, leading to fragmented architectures, congested spectrum usage, and costly multi-function hardware. Looking toward 6G and beyond, satellite communications will be a core pillar of future networks, delivering ubiquitous coverage, resilient backhaul, and rapid on-demand capacity via flexible payloads, multi-beam operation, and dynamic resource coordination. In this context, integrating Communication, Navigation, and Sensing (CNS) is essential to improve spectrum efficiency, simplify hardware, and enable intelligent network management while supporting high-precision Earth observation and robust global services across space, air, and ground.

This Topic aims to collect research on the design, theory, and application of CNS integration within SAGSIN. Also, we aspire to delve into the challenges brought forth by network heterogeneity and the diversification of business requirements in future terrestrial and satellite communication networks. We welcome contributions that explore how to combine these functions to improve both data transmission and remote sensing capabilities.

We invite authors to submit original research and reviews that bridge the gap between telecommunications and remote sensing. The goal is to highlight solutions for autonomous systems, disaster response, maritime surveillance, and environmental monitoring, ensuring that future networks can sense and navigate as effectively as they communicate.

Prof. Dr. Zhongliang Deng
Dr. Jichong Han
Topic Editors

Keywords

  • communication–navigation–sensing
  • satellite navigation
  • multi-platform sensing
  • sensor fusion
  • integrated observation system
  • network optimization
  • earth observation
  • remote sensing
  • wireless communication
  • 5G/6G communication

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Electronics
electronics
2.6 6.1 2012 16.4 Days CHF 2400 Submit
Forests
forests
2.5 4.6 2010 16.8 Days CHF 2600 Submit
Future Internet
futureinternet
3.6 8.3 2009 16.1 Days CHF 1800 Submit
Geomatics
geomatics
2.8 5.1 2021 22.6 Days CHF 1200 Submit
Remote Sensing
remotesensing
4.1 8.6 2009 24.3 Days CHF 2700 Submit
Sensors
sensors
3.5 8.2 2001 17.8 Days CHF 2600 Submit

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Published Papers (1 paper)

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27 pages, 7984 KB  
Article
Indoor UAV Localization via Multi-Anchor One-Shot Calibration and Factor Graph Fusion
by Jianmin Zhao, Zhongliang Deng, Wenju Su, Boyang Lou and Yanxu Liu
Remote Sens. 2026, 18(9), 1407; https://doi.org/10.3390/rs18091407 - 2 May 2026
Viewed by 110
Abstract
Indoor localization for unmanned aerial vehicles (UAVs) remains challenging in GNSS-denied environments due to the difficulty of position calibration of multiple ultra-wideband (UWB) anchors and the asynchronous fusion of heterogeneous sensors. This paper proposes a multi-sensor fusion localization framework that integrates multi-anchor one-shot [...] Read more.
Indoor localization for unmanned aerial vehicles (UAVs) remains challenging in GNSS-denied environments due to the difficulty of position calibration of multiple ultra-wideband (UWB) anchors and the asynchronous fusion of heterogeneous sensors. This paper proposes a multi-sensor fusion localization framework that integrates multi-anchor one-shot calibration with factor graph optimization (FGO). First, Landmark Multidimensional Scaling (LMDS) is used to reconstruct the relative geometry of the anchors and the onboard tag from ranging measurements. Then, rigid Procrustes alignment is performed using a small number of anchors with known coordinates in the East–North–Up (ENU) frame to recover the transformation to the ENU frame, thereby enabling efficient position calibration of multiple UWB anchors and UAV pose initialization. Subsequently, a tightly coupled factor graph is constructed by incorporating inertial measurement unit (IMU) pre-integration, UWB ranging, laser rangefinder height measurements, and visual–inertial odometry (VIO) pose constraints. The resulting nonlinear optimization problem is solved using incremental smoothing, which improves robustness against non-line-of-sight (NLOS) errors and long-term drift. Experimental results on anchor calibration, public datasets, and real-world indoor UAV flights demonstrate that the proposed method improves the accuracy and robustness of indoor UAV localization. In particular, on the real-world rectangle trajectory, FGO-TC reduces the RMSE by approximately 38.8% compared with FGO-LC. Full article
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