We present a sensor misalignment-tolerant AUV navigation method that leverages measurements from an acoustic array and dead reckoned information. Recent studies have demonstrated the potential use of passive acoustic Direction of Arrival (DoA) measurements for AUV navigation without requiring ranging measurements. However, the sensor misalignment between the acoustic array and the attitude sensor was not accounted for. Such misalignment may deteriorate the navigation accuracy. This paper proposes a novel approach that allows simultaneous AUV navigation, beacon localization, and sensor alignment. 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 demonstrate the performance of the proposed method.

翻译：本文提出一种传感器失准容忍的AUV导航方法，该方法利用声学阵列的测量数据与航位推算信息。近期研究表明，无需测距即可利用被动声学到达角（DoA）测量实现AUV导航。然而，现有方法未考虑声学阵列与姿态传感器之间的失准问题，这种失准可能降低导航精度。本文提出一种新方法，可同时实现AUV导航、信标定位与传感器校准。我们开发了一种无迹卡尔曼滤波（UKF），能够在可接受的计算负荷下完成必要计算；同时采用基于非线性最小二乘（NLS）的技术，利用短时测量窗口尽早获取信标定位与传感器校准的初始解。实验结果验证了所提方法的有效性。