Coherent Signal DOA Estimation and 3D Point Cloud Imaging Based on a Straight-Curved Hybrid L-Shaped Conformal Array

High-speed airborne platforms impose stringent aerodynamic constraints that restrict traditional planar antenna designs. Concurrently, multi-component echoes from extended targets and complex propagation environments induce strong signal coherence, severely degrading spatial angle estimation. To address these dual challenges, this paper proposes a straight-curved hybrid L-shaped asymmetric conformal array hardware topology tailored for cylindrical radomes. Building upon this, a millimeter-wave radar 3D point cloud imaging framework is developed for coherent targets. An orthogonal virtual manifold transformation is first devised to effectively compensate for the non-linear phase distortion induced by the conformal topology. Subsequently, a cascaded Forward-Backward Spatial Smoothing (FBSS) and Root-MUSIC framework is used for efficient signal decoherence. To resolve angle mismatches, a global cost function based on the cross-covariance Frobenius norm is formulated, which pairs independent angles and significantly suppresses spatial ghost targets. Systematic evaluations using 3D computer vision metrics demonstrate that the proposed method achieves accurate geometric restoration of aircraft targets with coherent signals. In the representative simulation, the method obtains a median point-wise localization error of 0.3986 m, a Chamfer Distance (CD) of 0.9695 m², an Earth Mover's Distance (EMD) of 1.9504 m, and a spatial angular resolution of 1.0° under the stated test conditions. Under the stated simulation assumptions, boundary analyses indicate stable reconstruction around a post-pulse-compression SNR of -8.0 dB and a conformal curvature of 12.50 m^-1 (r=0.08 m), providing simulation-based design references for conformal radar 3D imaging.