Model and Algorithm Improvement for Unmanned Undersea Vehicle Navigation Based on Single Beacon

In the single beacon-based unmanned undersea vehicle(UUV) navigation algorithm, a small number of beacons, simple deployment and calibration at sea, and low maintenance costs are required. If combined with the inertial navigation system, this algorithm is expected to fulfill the needs for wide-area and low-cost underwater navigation. To solve the problems regarding its slow convergence speed and non-global observability, a single beacon underwater navigation algorithm, which increased target radial velocity observations, is proposed. The global observability of the system after the introduction of the target radial velocity observation is thereafter analyzed, and a new method to estimate the initial value and track the navigation is derived. Afterward, by combining this method with the extended Kalman filter algorithm, a 4-state 3-observation(4SV-3OB) single beacon navigation model is established. Finally, numerical simulations indicate that the convergence time of the 4SV-3OB is approximately 75% lower than that of the traditional single beacon navigation model. Simulation results show that adding the target radial velocity as a system observation can effectively simplify the process of initial value estimation and tracking in the single beacon navigation algorithm and can significantly reduce the convergence time of the navigation algorithm.