Multi-Objective Beamforming for Low-Altitude Integrated Communication Sensing and Navigation Systems

Abstract

This letter proposes a genetic algorithm-based beamforming design for integrated communication sensing and navigation (ICSN) in low-altitude scenarios. In the developed ICSN system model, communication performance is measured by the sum rate, sensing capability is evaluated through the Cramér–Rao bound (CRB) of angle estimation, and navigation accuracy is quantified by the positioning error bound (PEB). To efficiently solve the multi-objective optimization problem, a genetic algorithm is employed to obtain the Pareto-optimal solution set. Numerical results validate the proposed scheme in multi-target low-altitude scenarios and illustrate beam patterns under various performance trade-offs.