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Hauptverfasser: Kim, Jeongbin, Jo, Jaehong, Jeon, Seunghyeon, Shin, Wonjae, Jeon, Yo-Seb, Poor, H. Vincent
Format: Preprint
Veröffentlicht: 2026
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Online-Zugang:https://arxiv.org/abs/2603.07622
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author Kim, Jeongbin
Jo, Jaehong
Jeon, Seunghyeon
Shin, Wonjae
Jeon, Yo-Seb
Poor, H. Vincent
author_facet Kim, Jeongbin
Jo, Jaehong
Jeon, Seunghyeon
Shin, Wonjae
Jeon, Yo-Seb
Poor, H. Vincent
contents This paper investigates a downlink multi-satellite integrated sensing and communication (ISAC) network, in which multiple satellites simultaneously transmit ISAC signals to provide communication services to ground user equipments and enable cooperative sensing of airborne targets through multiple gateways. To support this dual functionality, we introduce communication and sensing beamforming designs based on uniform planar arrays with optimized power allocation. Building on these designs, we propose two cooperative sensing frameworks, namely centralized and distributed. In the centralized framework, each gateway forwards its sensing observations to a central unit (CU), where the positions of multiple targets are jointly estimated from the aggregated data using a sparse signal recovery formulation. To mitigate the signaling overhead inherent in centralized processing, a distributed framework is further proposed, in which each gateway independently estimates target positions and transmits only the local estimates to the CU. To associate estimates from different gateways, a data association problem based on the squared Euclidean distance is formulated and efficiently solved using the Hungarian algorithm. The final target positions are then obtained by minimizing the distance estimation error. Simulation results demonstrate that the proposed centralized and distributed frameworks significantly outperform existing sensing schemes while satisfying communication performance requirements. We also evaluate the sensing-communication trade-off from the viewpoints of sensing accuracy and communication power consumption under the proposed frameworks.
format Preprint
id arxiv_https___arxiv_org_abs_2603_07622
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Cooperative Multi-Satellite ISAC Networks: Centralized vs. Distributed Sensing
Kim, Jeongbin
Jo, Jaehong
Jeon, Seunghyeon
Shin, Wonjae
Jeon, Yo-Seb
Poor, H. Vincent
Signal Processing
This paper investigates a downlink multi-satellite integrated sensing and communication (ISAC) network, in which multiple satellites simultaneously transmit ISAC signals to provide communication services to ground user equipments and enable cooperative sensing of airborne targets through multiple gateways. To support this dual functionality, we introduce communication and sensing beamforming designs based on uniform planar arrays with optimized power allocation. Building on these designs, we propose two cooperative sensing frameworks, namely centralized and distributed. In the centralized framework, each gateway forwards its sensing observations to a central unit (CU), where the positions of multiple targets are jointly estimated from the aggregated data using a sparse signal recovery formulation. To mitigate the signaling overhead inherent in centralized processing, a distributed framework is further proposed, in which each gateway independently estimates target positions and transmits only the local estimates to the CU. To associate estimates from different gateways, a data association problem based on the squared Euclidean distance is formulated and efficiently solved using the Hungarian algorithm. The final target positions are then obtained by minimizing the distance estimation error. Simulation results demonstrate that the proposed centralized and distributed frameworks significantly outperform existing sensing schemes while satisfying communication performance requirements. We also evaluate the sensing-communication trade-off from the viewpoints of sensing accuracy and communication power consumption under the proposed frameworks.
title Cooperative Multi-Satellite ISAC Networks: Centralized vs. Distributed Sensing
topic Signal Processing
url https://arxiv.org/abs/2603.07622