Finding Direction of arrival (DOA) of small UAVs using Sparse Denoising Autoencoders and Deep Neural Networks.
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Updated
Oct 23, 2018 - Python
Finding Direction of arrival (DOA) of small UAVs using Sparse Denoising Autoencoders and Deep Neural Networks.
Project for finding beacon location using Angle of Arrival (AoA) signal. The Direction of Arrival estimation is based on the MUltiple SIgnal Classification (MUSIC) algorithm here.
SELD-TCN: Sound Event Detection & Localization via Temporal Convolutional Network | Python w/ Tensorflow
GNU Radio package implementing MUSIC and root MUSIC angle of arrival algorithms with blocks necessary to provide phase synchronization of USRP devices
This repo is a compilation of code and resources for multiple SDR Platforms as part of a phased array beamforming project.
Parametric analysis of MUSIC algorithm for Angle of Arrival estimation in Python
A DNN based Normalized Time-frequency Weighted Criterion for Robust Wideband DoA Estimation
The project is related to BeamForming and Direction of Arrival (DoA) algorithms and its scope is the analysis and understanding of such techniques.
Sequential adaptive elastic net (SAEN) approach, complex-valued LARS solver for weighted Lasso/elastic-net problems, and sparsity (or model) order detection with an application to single-snapshot source localization.
MATLAB code for the coarray tensor completion-based 2-D DOA estimation algorithm
DOA etimation algorithms implemented in Python for ULA, UCA and broadband/wideband DOA estimation
Speech processing ROS-package. Performs speech recognition and estimates the direction of arrival based on a real-time voice activity detection mechanism.
[WIP]Direction based Multi-Channel Speech Separation
Robot (or Device) Localization Using Particle Filter over DOA of Wireless Signals
Sound Angle Estimation by Fusion of Gaussian Mixture Model and Multiple Signal classification
A machine learning algorithm that estimates the directions of arrival and relative levels of an arbitrary number of sound sources using recorded data from a 16-channel spherical microphone array.
A tool to visualize DCASE format SELD labels and predictions
This project was part of the "Special Antennas-Antenna Synthesis" course in the Department of Electrical & Computer Engineering at AUTH. It consists of antenna analysis & beam-forming and DoA algorithms.
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