Complexity Reduction in Machine Learning-Based Wireless Positioning: Minimum Description Features
Author:
Affiliation:
1. Purdue University,Electrical and Computer Engineering,West Lafayette,IN,USA
2. the University of Kansas,Electrical Engineering and Computer Science,Lawrence,KS,USA
Funder
National Science Foundation (NSF)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622841.pdf?arnumber=10622841
Reference20 articles.
1. IEEE standard for low-rate wireless networks-amendment 1: Enhanced ultra wideband (UWB) physical layers (PHYs) and associated ranging techniques;IEEE Std 802.15.4z-2020 (Amendment to IEEE Std 802.15.4–2020),2020
2. Position Estimation via Ultra-Wide-Band Signals
3. Precise Indoor Positioning Using UWB: A Review of Methods, Algorithms and Implementations
4. A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques
5. Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review
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