Multi-agent deep reinforcement learning with demonstration cloning for target localization
In target localization applications, readings from multiple sensing agents are processed to
identify a target location. The localization systems using stationary sensors use data fusion …
identify a target location. The localization systems using stationary sensors use data fusion …
UAV Swarm Cooperative Target Search: A Multi-Agent Reinforcement Learning Approach
The development of machine learning and artificial intelligence algorithms, as well as the
progress of unmanned aerial vehicle swarm technology, has significantly enhanced the …
progress of unmanned aerial vehicle swarm technology, has significantly enhanced the …
Joint data collection and sensor positioning in multi-uav-assisted wireless sensor network
Due to the high mobility and easy deployment, unmanned aerial vehicles (UAVs) have
attracted much attention in the field of wireless communication and positioning. To meet the …
attracted much attention in the field of wireless communication and positioning. To meet the …
TDOA/AOA Hybrid Localization Based on Improved Dandelion Optimization Algorithm for Mobile Location Estimation Under NLOS Simulation Environment
H Chen, L Cao, Y Yue - Wireless Personal Communications, 2023 - Springer
To improve the tracking accuracy of moving targets in Non-Line-of-Sight (NLOS)
environments and reduce positioning errors, a hybrid TDOA/AOA positioning method is …
environments and reduce positioning errors, a hybrid TDOA/AOA positioning method is …
On the Ground and in the Sky: A Tutorial on Radio Localization in Ground-Air-Space Networks
The inherent limitations in scaling up ground infrastructure for future wireless networks,
combined with decreasing operational costs of aerial and space networks, are driving …
combined with decreasing operational costs of aerial and space networks, are driving …
Channel Modeling and Characteristics Analysis under Different 3D Dynamic Trajectories for UAV-Assisted Emergency Communications
J Zhang, Y Liu, J Huang, H Chang, Z Zhang, J Li - Sensors, 2023 - mdpi.com
This study involved channel modeling and characteristics analysis of unmanned aerial
vehicles (UAVs) according to different operating trajectories. Based on the idea of …
vehicles (UAVs) according to different operating trajectories. Based on the idea of …
Blockchain-Assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning
Multi-Agent Deep Reinforcement Learning (MDRL) is a promising research area in which
agents learn complex behaviors in cooperative or competitive environments. However …
agents learn complex behaviors in cooperative or competitive environments. However …
Improvement of RSS-based measurement based on adaptive Kalman filter considering the anisotropy on antenna in dynamic environment
J Tian, M Yang, X Li, S Zou… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The classic propagation model of received signal strength (RSS) measurement is
significantly affected by the environment. This article divides the error sources of RSS …
significantly affected by the environment. This article divides the error sources of RSS …
Sky's the Limit: Navigating 6G with ASTAR-RIS for UAVs Optimal Path Planning
The surge in the number of various types of connected devices with the upcoming 6G
networks may surpass the capabilities of traditional wireless infrastructure. Specifically …
networks may surpass the capabilities of traditional wireless infrastructure. Specifically …
Indoor Vehicle Positioning for MIMO-OFDM WIFI Systems via Rearranged Sparse Bayesian Learning
J Du, J Cao, L Jin, S Li, J Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this paper, we propose a novel vehicle positioning method for commodity multiple-input
multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) WIFI systems in …
multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) WIFI systems in …