Research on the Hovering Depth Estimation of AUV Based on Multi-Sensor Fusion

DOI: https://doi.org/10.62517/jes.202502201

Author(s)

Jiwei Zhao, Jiacheng Xin*, Dong Wang, Xiaoyu Zhao, Kai Chen

Affiliation(s)

Tianjin Hanhai Lanfan Marine Technology Co., Ltd., Tianjin, China *Corresponding Author

Abstract

Confronting the challenge faced by micro autonomous underwater vehicles (AUVs) during their hovering and depth-holding maneuvers-where they are vulnerable to the disruptive forces of ocean waves, causing the pressure readings from sensors to deviate from the true water depth pressures and consequently yielding inaccurate depth measurements-this paper unveils an innovative solution. It introduces a sophisticated method that harnesses the power of Kalman filtering for data fusion, a technique designed to elevate the precision of AUV depth measurement information to unprecedented levels. By seamlessly integrating data streams from dual pressure sensors with the acceleration values garnered from the inertial measurement unit (IMU), this method endeavors to capture the nuanced fluctuations in the AUV's actual depth with remarkable accuracy. It is as if the AUV is equipped with a heightened sense of awareness, allowing it to navigate the depths with a newfound precision and confidence. Through a series of rigorous simulation experiments, the efficacy of this algorithm is resoundingly verified. It demonstrates an exceptional capability to diminish the measurement errors associated with depth information, achieving a level of accuracy that is both impressive and invaluable. As such, this method holds immense promise for practical engineering applications.

Keywords

Micro and Small AUV; Pressure Sensor; Kalman Filter; Information Fusion

References

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