Abstract: This study aims to accurately perceive the position and posture information of hydraulic supports in a disturbed environment. To address this, a precise perception method for the position and posture of hydraulic supports based on multi-sensor fusion was proposed. Firstly, nine-axis attitude sensors were deployed on four components of the hydraulic support, including top beam, shield beam, rear linkage, and base, to measure roll, pitch, and yaw angles using gyroscopes, accelerometers, and magnetometers. Then, the position and posture data was filtered using the Unscented Kalman Filter (UKF) algorithm and Improved Gradient Descent (IGD) algorithm (IGD-UKF algorithm), reducing interference from disturbance factors. Finally, an adaptive weighted fusion algorithm was employed to merge the filtered yaw and roll angle data of the top beam and base of hydraulic supports, eliminating data deviations caused by external vibrations, noise, and other factors. Perception experiments were conducted on the position and posture of top beam, shield beam, rear linkage, and base under various working conditions. The disturbances included the lowering and raising of top beam and base, as well as left-leaning, right-leaning, left-deviating and right-deviating of hydraulic supports. The study found that the data curves processed by the IGD-UKF algorithm exhibited smoother fluctuations, significantly suppressing oscillations and reducing amplitude. The yaw angle error of hydraulic supports ranged from 0.001 8° to 0.025 1°, with an average absolute error of 0.004 8°. The roll angle error ranged from 0.001 4° to 0.028 1°, with an average absolute error of 0.004 7°. The results indicate that the precise perception of the position and posture of hydraulic supports in a disturbed environment is achieved.