Data Collection for Target Localization in Ocean Monitoring Radar-Communication Networks

Author:

Liu Yuan1ORCID,Zhao Shengjie234,Han Fengxia2ORCID,Chai Mengqiu2ORCID,Jiang Hao56ORCID,Zhang Hongming7ORCID

Affiliation:

1. College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China

2. School of Software Engineering, Tongji University, Shanghai 201804, China

3. Key Laboratory of Embedded System and Service Computing, School of Software Engineering, Tongji University, Shanghai 201804, China

4. Engineering Research Center of Key Software Technologies for Smart City Perception and Planning, Ministry of Education, Shanghai 200003, China

5. College of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing 210044, China

6. National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

7. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract

With the ongoing changes in global climate, ocean data play a crucial role in understanding the complex variations in the earth system. These variations pose significant challenges to human efforts in addressing the changes. As a data hub for the satellite geodetic technique, unmanned aerial vehicles (UAVs) instill new vitality into ocean data collection due to their flexibility and mobility. At the same time, the dual-functional radar-communication (DFRC) system is considered a promising technology to empower ubiquitous communication and high-accuracy localization. In this paper, we explore a new fusion of UAV and DFRC to assist data acquisition in the ocean surveillance scenario. The floating buoys transmit uplink data transmission to the UAV with non-orthogonal multiple access (NOMA) and attempt to localize the target cooperatively. With the mobility of the UAV and power control at the buoys, the system throughput and the target localization performance can be improved simultaneously. To balance the communication and sensing performance, a two-objective optimization problem is formulated by jointly optimizing the UAV’s location and buoy’s transmit power to maximize the system throughput and minimize the attainable localization mean-square error. We propose a joint communication and radar-sensing many-objective optimization (CRMOP) algorithm to meliorate the communication and radar-sensing performance simultaneously. Simulation results demonstrate that compared with the baseline, the proposed algorithm achieves superior performance in balancing the system throughput and target localization.

Funder

National Key Research and Development Project

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Reference59 articles.

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