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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
Photonics-assisted microwave pulse detection and frequenc...
Pengcheng Zuo, Dong Ma, Qingbo Liu, Lizhong Jiang, Yang Chen · 2021-09-26 · via eess.SP updates on arXiv.org

A photonics-assisted microwave pulse detection and frequency measurement scheme is proposed. The unknown microwave pulse is converted to the optical domain and then injected into a fiber loop for pulse replication, which makes it easier to identify the microwave pulse with large pulse repetition interval (PRI), whereas stimulated Brillouin scattering-based frequency-to-time mapping (FTTM) is utilized to measure the carrier frequency of the microwave pulse. A sweep optical carrier is generated and modulated by the unknown microwave pulse and a continuous-wave single-frequency reference, generating two different frequency sweep optical signals, which are combined and used as the probe wave to detect a fixed Brillouin gain spectrum. When the optical signal is detected in a photodetector, FTTM is realized and the frequency of the microwave pulse can be determined. An experiment is performed. For a fiber loop containing a 210-m fiber, pulse replication and FTTM of the pulses with a PRI of 20 μs and pulse width of 1.20, 1.00, 0.85, and 0.65 μs are realized. Under a certain sweep frequency chirp rate of 0.978 THz/s, the measurement errors are below {\pm}12 and {\pm}5 MHz by using one pair of pulses and multiple pairs of pulses, respectively. The influence of the sweep frequency chirp rate and pulse width on the measurement error has also been studied. To a certain extent, the faster the frequency sweep, the greater the frequency measurement error. For a specific sweep frequency chirp rate, the measurement error is almost unaffected by the pulse width to be measured.