A virtual velocity-based integrated navigation method for strapdown inertial navigation system and Doppler velocity log coupled with unknown current

Abstract

The integration of the strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) has become a basic navigation solution for Autonomous Underwater Vehicles (AUVs). However, DVL cannot obtain the velocity relative to the ground when the distance between the AUV and seabed is over the operating range, which occurs often when AUVs are sailing in the middle layer of the ocean. When the DVL velocity relative to the current is used for an integrated filter, the unknown current velocity is coupled with the measured velocity error, which decreases the positioning accuracy. To address this problem, the effect of unknown coupled current velocity is analyzed from the perspective of filter observability, and an integrated SINS/DVL/virtual velocity navigation method is proposed. The virtual velocity based on the velocity variation extracted from the inertial measurement unit and DVL is constructed and used as an aided measurement for the Kalman filter. With the help of virtual velocity, the current velocity can be easily decoupled from measured SINS velocity error. The results of simulation and experiments demonstrated that the proposed method can effectively improve both the convergence speed and accuracy of velocity error compared with the classical method with SINS/DVL integration and, thus, significantly improve the positioning accuracy.

Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current Velocity

“…There are four reasons for this: First, the two VMFs and the common KF met estimate the misalignment angles. Even if the ocean current velocity is coupled SINS velocity error, the misalignment angles' observability is not affected acco ( 21), (31), and (38). Second, the velocity error and position error affect the misa angle estimation, which is determined by the misalignment angle differential Thirdly, the upward misalignment angle is more vulnerable to velocity and po rors than the eastward and northward misalignment angles.…”

“…In [30], the authors assumed that ocean current velocity over a short period is relatively stable, chose the difference between the two adjacent sample points as the external measurement information, and the final simulation results show that the effect of unknown ocean current velocity can be alleviated. Wang et al constructed a virtual velocity by velocity variations of SINS and DVL and the SINS velocity of compensation and used it as a different measurement for the Kalman filter [31]. Inspired by these ideas, the main work of this study is to propose a novel method for estimating the constant ocean current velocity based on a virtual metrology filter (VMF) without using any external auxiliary information.…”

A water track laser Doppler velocimeter for use in underwater navigation

“…And the current within a period on the scale of minutes is commonly assumed as invariant. Under this assumption, several integrated navigation algorithms have been proposed such as the layer water area division-based water current aided localization mechanism [32], the staggered grid division water current estimation method [33], the SINS/DVL/virtual velocity integrated navigation scheme [34], the current-aided marginalized particle filter [30] and the augmented observable quantities filter [35]. Although the navigation performance of the water track velocity sensor is poorer than bottom track velocity sensor, the present current estimation algorithms ensure the feasibility of the water track velocity sensor in underwater environment.…”