An adaptive voxel-wise iterative satellite interference localization method based on a double-layer UCA antenna

Aiming to balance localization accuracy, computational complexity, and robustness under low-SNR conditions in three-dimensional interference source localization, this paper proposes an efficient method combining frequency-domain covariance matrix reconstruction (FDCMR) and adaptive voxel iteration. First, the proposed method employs FDCMR-based direction-of-arrival (DOA) estimation for multi-station coarse localization and uses the intersection of direction cones to substantially compress the global search region. An adaptive voxel iteration with exponentially decreasing resolution is then performed within the compressed region for position refinement. Complexity analysis shows that the proposed method replaces exhaustive direct position determination (DPD) evaluation over the global search region with a bounded number of evaluations in a local adaptive voxel region, thereby substantially reducing the spatial-search complexity. Under the considered 2000 m × 2000 m × 2000 m search region with a 5 m spatial resolution, the number of DPD objective-function evaluations is reduced by approximately five orders of magnitude compared with conventional global DPD, while a localization accuracy of about 5 m is maintained at an SNR of 20 dB. At an SNR of -15 dB, the localization error is reduced by approximately 70% compared with the fixed-grid DPD method. These results demonstrate that the proposed method provides an effective balance between localization accuracy, computational efficiency, and low-SNR robustness.