An Expectation-Maximization-Based Estimation Algorithm for AOA Target Tracking With Non-Gaussian Measurement Noises-Reference-Cited by-同舟云学术

An Expectation-Maximization-Based Estimation Algorithm for AOA Target Tracking With Non-Gaussian Measurement Noises

Published:2023-01 Issue:1 Volume:72 Page:498-511
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Xu Sheng¹^ORCID,Rice Mark²,Rice Feng³^ORCID,Wu Xinyu¹^ORCID

Affiliation:

1. Guangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

2. Institute for Telecommunications Research, University of South Australia, Mawson Lakes, SA, Australia

3. QinetiQ Australia, Mawson Lakes, SA, Australia

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Key Technology Research and Development Program of Shandong

Shenzhen Science and Technology Program

Shenzhen Institute of Artificial Intelligence and Robotics for Society

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/10017140/09866886.pdf?arnumber=9866886

Reference54 articles.

1. Target Tracking in Glint Noise Environment using Nonlinear Non-Gaussian Kalman Filter

2. A Novel Underwater Acoustic Signal Denoising Algorithm for Gaussian/Non-Gaussian Impulsive Noise

3. Maneuvering target tracking using q-learning based Kalman filter

4. Fault Detection using hybrid of KF-ELM for Wireless Sensor Networks

5. Learning-based Adaptive Estimation for AOA Target Tracking with Non-Gaussian White Noise