To address the challenges posed by environmental factors such as temperature， humidity， air turbulence， station transfer， and line-of-sight obstructions in pose measurement systems like laser-based， iGPS， and visual imagery methods， a novel measurement field employing draw-wire displacement sensors was developed for detecting the relative pose of large aircraft components. The relative positions and orientations of these components were calculated using a back propagation BP neural network-Newton iteration method. By strategically arranging six sets of draw-wire displacement sensors along the docking surfaces of the aircraft components， a theoretical model for pose determination was established. The pose was subsequently resolved through the neural network-Newton algorithm. Numerical simulations demonstrate that the maximum position error is 4.9×10⁻⁷ mm， and the maximum attitude angle error is 1.97×10⁻⁹°. Comparative analyses between error simulations and experimental results confirmed the feasibility and precision of this approach. The findings indicate that the proposed method remains robust against external environmental disturbances and enables highly accurate detection of the relative pose of large components.