Underwater Target Tracking Based on the Feature-Aided GM-PHD Method-Reference-Cited by-同舟云学术

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Underwater Target Tracking Based on the Feature-Aided GM-PHD Method

Published:2024 Issue: Volume:73 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Tian Yiwei¹^ORCID,Liu Meiqin²^ORCID,Zhang Senlin¹^ORCID,Zheng Ronghao¹^ORCID,Dong Shanling¹^ORCID,Liu Zhunga³^ORCID

Affiliation:

1. College of Electrical Engineering and the National Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China

2. National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi’an Jiaotong University, Xi’an, China

3. School of Automation, Northwestern Polytechnical University, Xi’an, China

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Joint Fund of Ministry of Education for Pre-research of Equipment

Fundamental Research Funds for Xi’an Jiaotong University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10330606.pdf?arnumber=10330606

Reference43 articles.

1. An Overview of Next-Generation Underwater Target Detection and Tracking: An Integrated Underwater Architecture

2. Energy-Efficient Distributed Adaptive Multisensor Scheduling for Target Tracking in Wireless Sensor Networks

3. Non-Cooperative Target Tracking, Fusion and Control

4. Vector-Sensor Array DOA Estimation Based on Spatial Time-Frequency Distribution

5. A Passive DOA Estimation Algorithm of Underwater Multipath Signals via Spatial Time-Frequency Distributions

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