Bearing‐only underwater uncooperative target tracking for non‐Gaussian environment using fast particle filter-Reference-Cited by-同舟云学术

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Bearing‐only underwater uncooperative target tracking for non‐Gaussian environment using fast particle filter

Published:2021-11-30 Issue: Volume: Page:
ISSN:1751-8784
Container-title:IET Radar, Sonar & Navigation
language:en
Short-container-title:IET Radar, Sonar & Navigation

Author:

Hou Xianghao¹²^ORCID,Yang Long¹²^ORCID,Yang Yixin¹²,Zhou Jianbo¹²,Qiao Gang³

Affiliation:

1. School of Marine Science and Technology Northwestern Polytechnical University Xi'an Shaanxi China

2. Shaanxi Key Laboratory of Underwater Information Technology Xi'an Shaanxi China

3. College of Underwater Acoustic Engineering Harbin Engineering University Harbin Heilongjiang China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/rsn2.12198

Reference29 articles.

1. Underwater Target Tracking in Uncertain Multipath Ocean Environments

2. At‐sea evaluation of an underwater vehicle behavior for passive target tracking;Wolek A.;IEEE J. Ocean. Eng,2018

3. Automatic detection and tracking of contacts based in clusterization applied in passive sonar;Silva F.O.;J. Acoust. Soc. Am,2019

4. A Cramér‐Rao lower bound derivation for passive sonar track‐before‐detect algorithms;Northardt T.;IEEE Trans. Inf. Theory,2020

5. Particle filtering based track-before-detect method for passive array sonar systems

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1. Robust cardinalized probability hypothesis density filter based underwater multi-target direction-of-arrival tracking with uncertain measurement noise;Applied Acoustics;2024-01

2. Modified particle filter based on feature extraction coupling for track-before-detect algorithm;2023 International Conference on Cyber-Physical Social Intelligence (ICCSI);2023-10-20

3. Variational Bayesian cardinalized probability hypothesis density filter for robust underwater multi-target direction-of-arrival tracking with uncertain measurement noise;Frontiers in Physics;2023-02-28

4. Tracking an Underwater Object with Unknown Sensor Noise Covariance Using Orthogonal Polynomial Filters;Sensors;2022-06-30

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