Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization

Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization

This paper presents a reinforcement learning approach for automatic adaptation of the process noise covariance (Q). The Q value plays a crucial role in estimating future state values within a Kalman filter tracking system. Proximal Policy Optimization (PPO), a state-of-the-art policy optimization al...

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Bibliographic Details
Main Author: Alhadhrami, Esra Ebrahim (author)
Other Authors: Seghrouchni, Amal El Fallah (author), Barbaresco, Frederic (author), Abu Zitar, Raed (author)
Published: 2023
Subjects:
Q measurement
Measurement uncertainty
Reinforcement learning
Radar
Radar tracking
Libraries
Feedforward neural networks
Online Access:https://depot.sorbonne.ae/handle/20.500.12458/1425
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https://depot.sorbonne.ae/handle/20.500.12458/1425

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