Frequency-Aided Extended Kalman Filter for Non-Contact Spatial Position Measurement of Overhead Power Lines Using Magnetic Sensors

Accurate spatial position measurement of overhead power lines is essential for ensuring the reliability of power systems, especially in smart grid scenarios that require real-time monitoring. However, existing methods face significant challenges: contact-based techniques, such as tension or differential GPS (DGPS) sensors, are costly and cumbersome, while image-based methods are vulnerable to weather conditions. Magnetic sensors, offering a non-contact measurement approach, present a promising alternative. However, current technology often suffers from non-linearity and high uncertainty in ac environments, limiting their accuracy. This article introduces a frequency-aided extended Kalman filter (FA-EKF) algorithm that integrates frequency information into the prediction model, thereby enhancing stability and efficiency in ac signal measurements. The proposed algorithm significantly reduces convergence time and measurement uncertainty. Experimental validation in laboratory-scale models demonstrates the method’s effectiveness, with a relative error of less than 2%. Further simulations show that the method achieves 97.5% relative accuracy at a 2.5-m distance in 1-D measurements and maintains over 90% relative accuracy in 2-D measurements within a 1.5-m radius around the target line in realistic scenarios. This article also explores the impact of factors such as sensor spacing, angular deviation, and interference from other current sources.