Year: 2026
Type: article
Abstract: ABSTRACT This paper investigates the joint beamforming design for ISAC‐enabled UAV systems, aiming to optimise the trade‐off between communication sum rate (SR) and sensing Cramér–Rao lower bound (CRLB) under stringent size, weight and power (SWaP) constraints. Departing from traditional relaxation methods, we first address the nonconvexity and variable coupling by constructing a tractable quadratic surrogate objective, which transforms the intractable original objective into an unconstrained optimisation framework strictly defined on the complex sphere manifold (CSM). We then propose a Riemannian trust‐region algorithm on the complex sphere manifold (RTR‐CSM). The problem is reformulated as a tractable quadratic surrogate, with a finite‐difference approximated Hessian used to construct the trust‐region subproblem, which is solved via truncated conjugate gradient to avoid expensive exact second‐order derivations and matrix inversions. Simulations show that RTR‐CSM achieves near‐optimal performance and converges significantly faster than state‐of‐the‐art benchmarks in terms of iteration count (e.g., reducing total runtime by 5.2×, 3.9×, and 2.9× compared with SCA, FP‐SGDA, and IRO‐CSM, respectively), making it highly suitable for resource‐constrained UAV‐enabled ISAC beamforming.
Source: IET Radar Sonar & Navigation
DOI: 10.1049/rsn2.70234
Authors: Zhiyuan You, Na Lv
Institution: Air Force Engineering University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,620
OpenAlex ID: W7208826713