惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

J
Java Code Geeks
Stack Overflow Blog
Stack Overflow Blog
P
Proofpoint News Feed
L
LangChain Blog
C
Check Point Blog
F
Fortinet All Blogs
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Blog — PlanetScale
Blog — PlanetScale
腾讯CDC
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Jina AI
Jina AI
Recent Announcements
Recent Announcements
雷峰网
雷峰网
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
N
Netflix TechBlog - Medium
博客园 - 【当耐特】
Hugging Face - Blog
Hugging Face - Blog
Microsoft Azure Blog
Microsoft Azure Blog
U
Unit 42
The Cloudflare Blog
月光博客
月光博客
有赞技术团队
有赞技术团队
G
Google Developers Blog
Vercel News
Vercel News

eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
Single-Satellite-Based Geolocation of Broadcast GNSS Spoo...
Zachary L. Clements, Patrick B. Ellis, Iain Goodridge, Matthew J · 2025-03-22 · via eess.SP updates on arXiv.org

This paper presents an analysis and experimental demonstration of single-satellite single-pass geolocation of a terrestrial broadcast Global Navigation Satellite System (GNSS) spoofer from Low Earth Orbit (LEO). The proliferation of LEO-based GNSS receivers offers the prospect of unprecedented spectrum awareness, enabling persistent GNSS interference detection and geolocation. Accurate LEO-based single-receiver emitter geolocation is possible when a range-rate time history can be extracted for the emitter. This paper presents a technique crafted specifically for indiscriminate broadcast-type GNSS spoofing signals. Furthermore, it explores how unmodeled oscillator instability and worst-case spoofer-introduced signal variations degrade the geolocation estimate. The proposed geolocation technique is validated by a controlled experiment, in partnership with Spire Global, in which a LEO-based receiver captures broadcast GNSS spoofing signals transmitted from a known ground station on a non-GNSS frequency band.