

FOLLOWUS
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China
School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China
Department of Electrical and Computer Engineering, The University of Hong Kong, Hong Kong 999077, China
✉ Xiaoming CHEN, chen_xiaoming@zju.edu.cn
Received:01 April 2026,
Revised:2026-06-16,
Online First:23 July 2026,
Published:01 August 2026
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Qi WANG, Xiaoming CHEN, Qiao QI, et al. Continuous aperture array-assisted integrated communication and navigation in low Earth orbit satellite constellations[J]. ENGINEERING Information Technology & Electronic Engineering, 2026, 27(8): 1-16.
Qi WANG, Xiaoming CHEN, Qiao QI, et al. Continuous aperture array-assisted integrated communication and navigation in low Earth orbit satellite constellations[J]. ENGINEERING Information Technology & Electronic Engineering, 2026, 27(8): 1-16. DOI: 10.1631/ENG.ITEE.2026.0090.
This paper proposes a novel continuous aperture array (CAPA)-assisted integrated communication and navigation (ICAN) framework for low Earth orbit (LEO) satellite constellations. Within this framework
an electromagnetic-based collaborative transmission model is developed
in which multiple satellites equipped with CAPAs simultaneously radiate downlink data streams and navigation reference signals over a shared spectrum. Building upon this
the achievable communication rate and the navigation Cramér–Rao bound (CRB) are derived
which explicitly characterize the intrinsic coupling between the dual-function beamformers and system performance. To improve the positioning accuracy with a communication quality of service guarantee
a joint beamforming optimization problem is formulated to minimize the average CRB subject to transmit power budgets and minimum rate constraints. To tackle the inherent infinite dimensionality of the CAPA beamformer design
an ICAN channel subspace is introduced to equivalently transform the formulation into a tractable finite-dimensional problem
which is then efficiently solved via an iterative convex optimization algorithm. Finally
numerical results demonstrate that the proposed CAPA-assisted beamforming design algorithm significantly outperforms conventional discrete phased array architectures and other benchmark schemes
yielding notable improvements in ICAN performance.
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