An Efficient Method for Amplitude–Phase Error Calibration in Direct Localization for Distributed Multi-Station Systems

Direct localization methods offer significant advantages in modern high-frequency (HF) radar systems for maritime target localization. However, the presence of amplitude–phase errors poses severe challenges to their accuracy and reliability. Traditional active calibration methods for direct localization often face high costs and operational complexities, while self-calibration techniques are limited to addressing only single or, at most, two types of error models. To address these issues, the Multi-Station Azimuth-based Position Error Calibration Algorithm (MAPEC) is proposed in this paper, which is an active calibration algorithm to solve mixed amplitude–phase errors in direct positioning. The proposed algorithm converts the estimated amplitude–phase errors on each angle of stations into the corresponding position on the localization search grid and adjusts the steering vectors based on the converted errors. By integrating MAPEC with direct localization algorithms, the method enables precise and robust localization under complex amplitude–phase error conditions involving multiple error sources. Simulation results demonstrate that this approach significantly improves localization accuracy across various error conditions, validating its applicability to direct localization applications.