Tracking the Turn: Mamba-Powered Human Orientation Detection using UWB
2026-06-26T08:51:49Z•b0bced2075d75d8dd9ccce091f959d4f732f332705280015d3c8865fecdf33c2
CFO-estimation','sample-efficiency'Doppler-robustnessKalman-filterLPWANLiDARM-ASPMMIMOMamba-modelUWBVBSZak-OTFSbeam-managementbeamformingbearing-fault-diagnosischannel-estimationcollision-resistancedeep-learning-featuresenvironment-aware-communicationshuman-orientation-detectionlocalization-privacypilot-designpredictive-maintenancereinforcement-learningvirtual-base-stationwearable-tracking
What happened
This document is an arXiv EESS-Signal Processing feed containing multiple new papers covering UWB-based human orientation detection, bearing-fault feature learning, MIMO Zak-OTFS modulation and channel estimation, geometry-driven environment-aware beam management using LiDAR (virtual base stations), respiratory-based stress/affect recognition, collision-resistant M-ASPM for LPWANs, distributed massive MIMO with 1-bit radio-over-fiber fronthaul, WFRFT-based sub‑Rayleigh MIMO radar angle estimation, and deep‑learning inverse design of Doherty power amplifiers. Across these works there are common
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- b0bced2075d75d8dd9ccce091f959d4f732f332705280015d3c8865fecdf33c2
- Enrichment time
- 2026-06-26T08:51:49Z
- AI-assisted enrichment
- Yes
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