Resource
2026 EN
Yejia Zeng · Zukun Lu · Xiaoyu Zhao
+4 more
Unmanned aerial vehicles (UAVs) have become indispensable in both civilian and military applications. However, their reliance on Global Navigation Satellite System (GNSS)-based navigation exposes them to escalating threats from sophisticated jamming and spoofing attacks. These threats severely compromise operational safety and mission integrity, necessitating the development of effective countermeasures. This survey provides a comprehensive overview of GNSS interference threats specific to UAV navigation, with a focus on the analysis of jamming and spoofing attacks, and summarizes state-of-the-art techniques for interference detection and mitigation. We first review the principles of satellite navigation for UAVs and identify the inherent vulnerability of GNSS signals to interference. Then, we systematically examine existing countermeasures, including signal processing-based, array antenna-based, and artificial intelligence-based approaches, highlighting their effectiveness against jamming and spoofing. Despite these advances, significant challenges remain in ensuring robust UAV navigation in adversarial electromagnetic environments, particularly those arising from resource constraints, limited algorithmic flexibility, and the lack of UAV-specific countermeasures. To address these issues, we propose a hierarchical framework that integrates robust signal reception, intelligent algorithm optimization, and system-level collaboration. This framework provides practical strategies for enhancing the resilience of next-generation UAV navigation systems to complex interference.
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2026 EN
Xun Tang · Qing Li · Junkun Peng
+5 more
The demand for low-latency video streaming has grown rapidly with the emergence of mission-critical and highly interactive applications such as extended reality (XR), remote surgery, cloud gaming, teleoperation, and autonomous systems. Despite continuing advances in networking and computing technologies, achieving consistently low end-to-end delay while maintaining service quality remains a fundamental challenge. Existing surveys often focus on individual components of the streaming pipeline, whereas a unified and up-to-date view of low-latency Internet video streaming is still lacking. This survey addresses this gap by providing a structured review of low-latency Internet video streaming from the perspectives of applications, core challenges , and future trends . We first summarize representative application domains and clarify how their latency requirements motivate different technical bottlenecks. We then organize the literature around three recurring challenges: Large Data, Network Bandwidth , and Prediction , covering representative solutions in video compression and delivery, transport and congestion control, adaptive streaming, and QoS/QoE prediction and evaluation. In addition, we review how recent AI techniques are reshaping the low-latency streaming pipeline, including learning-based optimization, generative/foundation-model-enabled streaming, and intelligent network control. By synthesizing representative techniques, distilling lessons learned, and highlighting open challenges and research directions, this survey provides a unified and forward-looking reference for researchers and practitioners working on next-generation low-latency video streaming systems.
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2026 EN
Md Sharif Hossen · Cole Dickerson · Ozgur Ozdemir
+33 more
In this work, we present an unmanned aerial vehicle (UAV) wireless dataset collected as part of the AERPAW Autonomous Aerial Data Mule (AADM) challenge, organized by the NSF Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) project. The AADM challenge was the second competition in which an autonomous UAV acted as a data mule, where the UAV downloaded data from multiple base stations (BSs) in a dynamic wireless environment. Participating teams designed flight control and decision-making algorithms for selecting which BSs to communicate with and how to plan flight trajectories to maximize data download within a mission completion time. The competition was conducted in two stages: Stage 1 involved development and experimentation using a digital twin (DT) environment, and in Stage 2, the final test run was conducted on the outdoor testbed. The total score for each team was compiled from both stages. The resulting dataset includes link quality and data download measurements, both in DT and physical environments. Along with the USRP measurements used in the contest, the dataset also includes UAV telemetry, Keysight RF sensor position estimates, link quality measurements from LoRa receivers, and Fortem radar measurements. It supports reproducible research on autonomous UAV networking, multi-cell association and scheduling, air-to-ground propagation modeling, DT-to-real-world transfer learning, and integrated sensing and communication, which serves as a benchmark for future autonomous wireless experimentation.
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2026 EN
Victor Ikenna Kanu · Ihunanya Udodiri Ajakwe · Simeon Okechukwu Ajakwe
+1 more
Biochemical threats remain a serious concern in mission-critical environments, particularly those characterized by intermittent connectivity and infrastructure degradation. Traditional centralized detection systems are ill-suited for such conditions, as they depend on stable communication channels and are inherently vulnerable to cyber–physical disruptions. This work introduces a decentralized solution integrating artificial intelligence (AI) and blockchain (BC) for autonomous biochemical threat detection within tactical mobile ad hoc networks (MANETs). The framework uses a random forest (RF) classifier trained on acetylcholinesterase (AChE) sensor data to identify sarin exposure with 100% accuracy and sub-25-ms inference latency. Threat verification is secured using a lightweight proof of authority and association ( $\mathtt {PoA^{2 BC, which provides tamper-resistant logging and distributed consensus. The architecture supports offline operations and maintains functionality under conditions of 20% packet loss and node disruption. Simulations conducted in degraded network environments confirmed the system’s robustness and scalability, establishing it as a resilient and efficient platform for secure biochemical threat detection in dynamic, resource-constrained mission-critical settings.
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2026 EN
Yueshan Lin · Wei Feng · Yunfei Chen
+3 more
This paper investigates latency-constrained resource synergization for mission-oriented non-terrestrial networks (NTNs) in post-disaster emergency scenarios. When terrestrial infrastructures are damaged, unmanned aerial vehicles (UAVs) equipped with edge information hubs (EIHs) are deployed to provide temporary coverage and synergize communication and computing resources for rapid situation awareness. We formulate a joint resource configuration and location optimization problem to minimize overall resource costs while guaranteeing stringent latency requirements. Through analytical derivations, we obtain closed-form optimal solutions that reveal the fundamental tradeoff between communication and computing resources, and develop a successive convex approximation method for EIH location optimization. Simulation results demonstrate that the proposed scheme achieves approximately 20% cost reduction compared with benchmark approaches, validating its optimality and effectiveness for mission-critical emergency response applications in the sixth-generation (6G) era.
Resource
2026 EN
Abhiram Sharma · Rudra Raj · P B Krishna
+4 more
Advanced NEHA is a three-tier symmetric cipher developed to meet the high-security and performance demands of mission-critical IoT environments, including military applications. It generates dynamic session keys using device-specific identifiers, then performs lightweight character substitution and circular bit rotation across fixed 512-bit blocks. A CRC32 checksum is appended to detect accidental transmission errors. The algorithm’s efficiency is evaluated using a unified, multi-criteria framework that standardizes five key metrics: encryption/decryption throughput, latency, memory footprint, computational complexity, and security strength. These metrics are normalized on a 0–10 scale and visualized through radar charts. A polygonal area derived from the chart quantifies overall efficiency. Compared to DES, 3DES, AES, RSA, and the original NEHA, Advanced NEHA achieves sub-millisecond encryption (0.4 ms) and decryption (0.2 ms) with low memory usage (4 KB and 2 KB respectively). Its aggregate efficiency score of 131.4 ranks second only to RSA, demonstrating strong practical performance. A controlled decryption challenge involving 237 cybersecurity professionals yielded a success rate below 1%, indicating strong resistance to brute-force and known-plaintext attacks. While the algorithm is lightweight and highly efficient, further analysis is needed to assess its scalability, entropy strength at large scales, and resistance under side-channel attack scenarios. These aspects are recommended for future exploration. Overall, Advanced NEHA offers a secure, fast, and resource-efficient solution for encrypted communication in environments where both speed and robustness are paramount.
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2026 EN
Xiaoyang Guo · Panpan Wang · Hanzhong Wu
+2 more
Future space-based gravitational wave observatories, such as LISA and TianQin, require inter-satellite laser links that simultaneously support ultra-precise ranging, low-noise scientific phase measurements, and high-integrity data communication. Traditional pseudo-random noise (PRN) phase modulation on continuous-wave (CW) lasers is limited by phase disruption, bandwidth constraints, and poor spectral utilization. In this paper, we propose a unified inter-satellite ranging and communication architecture based on electro-optically generated optical frequency combs (OFCs). The system employs wavelength-division multiplexing (WDM) to assign distinct comb lines for PRN-based coarse ranging, high-throughput communication, and unmodulated dual-comb interferometry. A hierarchical ranging mechanism combines PRN time-of-flight estimation with dual-comb phase extraction, achieving sub-millimeter accuracy over million-kilometer baselines. System-level simulations based on LISA mission parameters demonstrate nanometric ranging resolution, data rates exceeding 1 Gbps, and minimal phase distortion in the scientific channel. The proposed architecture is compatible with existing EOM-based hardware and scalable to photonic integration, offering a promising solution for precision metrology and data transfer in next-generation space missions.
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2026 EN
Huadong Guo · Changyong Dou · Dong Liang
+13 more
The implementation of the United Nations (UN) 2030 Agenda for Sustainable Development (2030 Agenda), with its 17 sustainable development goals (SDGs), faces challenges such as insufficient data, limited research methodologies, and uneven progress across regions. Earth observation (EO), particularly scientific satellites, offers unique advantages in supporting global sustainable development by providing objective, dynamic, and large-scale datasets for SDG evaluations and policymaking, as well as by facilitating the study of Earth’s environmental systems and their interactions with human activity. Sustainable Development Science Satellite 1 (SDGSAT-1), the world’s first scientific satellite dedicated to supporting the 2030 Agenda, was designed and developed by the International Research Center of Big Data for Sustainable Development Goals (CBAS). Its three advanced EO sensors, i.e., Thermal Infrared Spectrometer (TIS), Glimmer Imager (GLI), and Multispectral Imager (MSI), furnish high-quality data, enabling continuous monitoring of human activity and environmental changes to bolster SDG-related research and global sustainability initiatives. As of November 2025, SDGSAT-1 has collected over 480 000 global terrain coverage images since its launch in November 2021. All its datasets have been shared free of charge with the Global Scientific Community through the SDGSAT-1 Open Science Program initiated in September 2022. The datasets have enabled researchers from more than 110 countries, 10 UN agencies, and various international organizations to publish over 180 scientific articles, 17 UN reports, and numerous public data products. These have demonstrated applications in urban development, disaster response, environmental monitoring, agriculture, and marine conservation. This article reviews the technical innovations and mission specifications of the SDGSAT-1 satellite, demonstrates its contribution in leveraging space technology for SDG monitoring and evaluation, and discusses the future evolution of development of EO systems, specifically the planned Sustainable Development Satellite Constellation, for supporting the global achievement of SDGs.
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2026 EN
Giovanni Macelloni · Kenneth C. Jezek · Marco Brogioni
+17 more
This article reviews existing and planned contributions of spaceborne microwave radiometry from P to S band to new measurements of key geophysical variables with a particular focus on the polar regions. It summarizes the current state of spaceborne microwave radiometry to measure ice sheet thermal states, sea ice thickness (SIT), salinity, and sea surface salinity (SSS). Then, this article discusses the potential of wideband radiometry, with continuous sampling in the range of 0.4–2 GHz, as a breakthrough for enhancing the estimation of geophysical variables such as SSS and the geothermal heat flux beneath the polar ice sheets, which are currently monitored primarily using L-band radiometry satellites. Furthermore, this article describes opportunities for new unique observations that cannot be achieved with the current constellation of satellite sensors. In addition, this article demonstrates the advantages of using low-frequency radiometry in sensing soil moisture and biomass from space due to the great sensing depth. This article concludes with a discussion of mission concepts highlighting the CryoRad mission, which has been selected as one of the four candidates for European Space Agency Earth Explorer 12 competition and is now conducting Phase 0 feasibility studies, envisions a 0.4–2-GHz dedicated spaceborne radiometer operated with circular polarization.
Resource
2026 EN
Klaus Scipal · Clement Albinet · Michele Caccia
+24 more
The European Space Agency’s (ESA) BIOMASS mission is a pioneering Earth observation satellite mission launched on April 29, 2025. Utilizing a P-band synthetic aperture radar (SAR), the objective of BIOMASS is to deliver estimates of above-ground forest biomass, forest height (FH), and forest disturbance (FD), with unprecedented accuracy. The mission’s primary scientific goal is to quantify the distribution and changes in forest biomass, thereby reducing uncertainties in carbon flux estimates and informing climate models. The satellite’s advanced instrumentation and innovative approach allow it to penetrate dense forest canopies, capturing data even in challenging environments. The mission will operate in two distinct phases: the tomographic phase and the interferometric phase, which will support polarimetric interferometric SAR (Pol-InSAR) and tomographic SAR (TomoSAR) processing. Additionally, BIOMASS will provide valuable observational data for ice sheets, deserts, the ionosphere, below canopy topography, and other domains.