How to accurately and rapidly obtain target point coordinate information within large-scale, topographically complex power line networks is a common concern for power construction, inspection, and surveying operations. This paper proposes four coordinate unification techniques based on the irregularity of radio wave propagation: calibrated coordinate transformation, hand-eye calibration, feature matching, and world coordinate systems. Simultaneously, it employs compressed sensing theory to solve the direction of arrival (DOA) estimation for wireless positioning coordinates, incorporating a distance metric function to enhance estimation accuracy. The DOA estimation problem is transformed into a sparse signal reconstruction problem, utilizing an iterative shrinkage (parallel coordinate descent) algorithm to perform scalar shrinkage on the provisional coordinate direction solution. This establishes a parallel coordinate descent-based wireless positioning direction estimation method. After achieving coordinate unification and direction estimation for target points, particle filtering technology and w-KNN matching algorithms are integrated. RTK technology is employed to obtain the three-dimensional coordinates of target points, forming a power line coordinate domain model. In simulation experiments, the proposed wireless positioning direction estimation algorithm maintains relative error within [0.00, 1.00]%, demonstrating both computational accuracy and robustness.
