低空空地协同感知中共形阵列稳健波束形成算法OA

To address the application requirements of air-ground cooperative sensing and positioning in airborne communication networks under low-altitude economy scenarios,a conformal array robust adaptive beamforming algorithm based on subspace projection is proposed.In low-altitude complex electromagnetic environments,conventional beamforming methods based on Interference-plus-Noise Covariance Matrix(INCM)reconstruction suffer from high computational complexity and sensitivity to array errors,leading to degraded positioning accuracy in air-ground cooperative target localization.The proposed algorithm corrects the signal Steering Vector(SV)through an error neighborhood table to accommodate array errors of conformal antennas on airborne platforms;then estimates the noise power by exploiting the non-orthogonality between signals,then constructs a projection subspace using the corrected SV to eliminate the desired signal component and obtains the interference power estimation through matrix transformation to reconstruct the INCM.This method avoids large-scale integration and solving convex optimization problem,significantly reducing computational complexity and making it suitable for real-time processing requirements in low-altitude dynamic networking scenarios.Simulation results demonstrate that under conditions of limited snapshots and complex array errors,the algorithm can accurately steer the main lobe toward the desired signal and form nulls in interference directions,with output Signal-to-Interference-plus-Noise Ratio(SINR)performance stably approaching the ideal value,effectively enhancing the sensing and positioning accuracy as well as anti-interference capability of low-altitude air-ground cooperative networks.