Single-beacon range-constrained tightly coupled SINS/DVL navigation method for dam inspection underwater vehicles

• Developed a DVL virtual beam reconstruction model to mitigate velocity measurement errors caused by partial beam degradation or non-normal incidence. • Proposed a single-beacon range-constrained tightly coupled SINS/DVL navigation method with closed-loop correction under sparse ranging observations. • The proposed method reduces dependence on additional heading, velocity, or historical position information, thereby simplifying the positioning process. • The effectiveness and robustness of the proposed method are validated through real-world field experiments conducted at hydropower stations. To mitigate navigation accuracy degradation in underwater vehicles operating in dam inspection environments characterized by distinct structural boundaries, this paper proposes a tightly coupled Strapdown Inertial Navigation System (SINS)/Doppler Velocity Log (DVL) method augmented with single-beacon range constraints. The degradation arises from compounded error sources, including DVL velocity measurement failures, abnormal acoustic reflections from inclined dam surfaces, and insufficient exploitation of single-beacon ranging information. A virtual beam reconstruction model for the DVL is developed, and a beam rotation matrix is derived to decouple water-layer flow velocity from vehicle velocity. This approach reduces velocity measurement bias under non-normal incidence conditions. In addition, a bidirectional coupling architecture is constructed to integrate inertial navigation with single-beacon range constraints. A closed-loop correction algorithm based on dynamic range constraints is further designed to suppress error accumulation through real-time position feedback. Simulation and field experiments demonstrate that the proposed method reduces the error accumulation rate of conventional tightly coupled SINS/DVL navigation and improves navigation accuracy and system robustness in representative dam inspection scenarios.