Search Results for author: Jianyuan Yu

Found 8 papers, 0 papers with code

Multi-Modal Recurrent Fusion for Indoor Localization

no code implementations19 Feb 2022 Jianyuan Yu, Pu, Wang, Toshiaki Koike-Akino, Philip V. Orlik

This paper considers indoor localization using multi-modal wireless signals including Wi-Fi, inertial measurement unit (IMU), and ultra-wideband (UWB).

Indoor Localization regression

Multi-Band Wi-Fi Sensing with Matched Feature Granularity

no code implementations28 Dec 2021 Jianyuan Yu, Pu, Wang, Toshiaki Koike-Akino, Ye Wang, Philip V. Orlik, R. Michael Buehrer

The granularity matching is realized by pairing two feature maps from the CSI and beam SNR at different granularity levels and linearly combining all paired feature maps into a fused feature map with learnable weights.

Indoor Localization

Predicting Bit Error Rate from Meta Information using Random Forests

no code implementations10 Jul 2020 Jianyuan Yu, Yue Xu, Hussein Metwaly Saad, R. Michael Buehrer

With the increasing power of machine learning-based reasoning, the use of meta-information (e. g., digital signal modulation parameters, channel conditions, etc.)

Direction of Arrival Estimation for a Vector Sensor Using Deep Neural Networks

no code implementations12 Apr 2020 Jianyuan Yu, William W. Howard, Daniel Tait, R. Michael Buehrer

A vector sensor, a type of sensor array with six collocated antennas to measure all electromagnetic field components of incident waves, has been shown to be advantageous in estimating the angle of arrival and polarization of the incident sources.

Direction of Arrival Estimation

Interference Classification Using Deep Neural Networks

no code implementations3 Feb 2020 Jianyuan Yu, Mohammad Alhassoun, R. Michael Buehrer

The recent success in implementing supervised learning to classify modulation types suggests that other problems akin to modulation classification would eventually benefit from that implementation.

Classification General Classification

Multiple Angles of Arrival Estimation using Neural Networks

no code implementations3 Feb 2020 Jianyuan Yu

MUltiple SIgnal Classification (MUSIC) and Estimation of signal parameters via rotational via rotational invariance (ESPRIT) has been widely used in super resolution direction of arrival estimation (DoA) in both Uniform Linear Arrays (ULA) or Uniform Circular Arrays (UCA).

Direction of Arrival Estimation Super-Resolution

Cannot find the paper you are looking for? You can Submit a new open access paper.