Sensor Misalignment-Tolerant AUV Navigation With Passive DoA and Doppler Measurements

We present a sensor misalignment-tolerant autonomous underwater vehicle (AUV) navigation method that leverages measurements from an acoustic array and dead reckoning (DR). Recent studies have demonstrated the potential use of passive acoustic direction of arrival (DoA) measurements for AUV navigation without requiring ranging measurements. However, position estimation accuracy degrades at shallow elevation angles, and the issue of sensor misalignment between the acoustic array and the attitude sensor has not been comprehensively investigated. To address this, we propose the incorporation of Doppler speed measurements, which significantly enhance navigation accuracy, as demonstrated through theoretical analysis and experiments. Since sensor misalignment deteriorates navigation accuracy, we also present a novel approach for simultaneous AUV navigation, beacon localization, and real-time sensor self-alignment, eliminating the need for external high-precision sensors. An unscented Kalman filter (UKF) that enables the necessary calculations to be completed at an affordable computational load is developed. A nonlinear least squares (NLS)-based technique is employed to find an initial solution for beacon localization and sensor alignment as early as possible using a short-term window of measurements. Experimental results validate the effectiveness of our proposed method, demonstrating substantial improvements in performance.