Accurate underwater navigation systems are required for closed-loop guidance and control of unmanned underwater vehicles (UUV). This paper proposes a sensor-based hybrid translational observer concept for underwater navigation using the hybrid dynamical systems framework, accounting for noisy, asynchronous and sporadic sensor measurements. Sensor measurements from an acoustic positioning system, a Doppler Velocity Log (DVL), an Inertial Measurement Unit (IMU) and a pressure gauge are used in the proposed observer. A method for filtering high-frequency noise is proposed, where the estimated states are obtained by taking a weighted discounted average of a finite number of previous measurements predicted forwards to the current time. The attitude of the vehicle is assumed known, and the acceleration measurements are assumed to be continuously available. Measurements of position, depth and linear velocity are assumed to be asynchronous and sporadically available, that is, they do not arrive at the same time, and their sampling rates are not constant. Uniform global asymptotic stability (UGAS) is established using Lyapunov theory for hybrid systems. Results from simulations are presented in order to demonstrate the performance of the proposed method.

中文翻译：

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用于水下导航零星测量传感器融合的混合观测器概念

无人水下航行器（UUV）的闭环制导和控制需要精确的水下导航系统。本文提出了一种基于传感器的混合平移观测器概念，用于使用混合动力系统框架的水下导航，考虑到嘈杂、异步和零星的传感器测量。来自声学定位系统、多普勒速度测井 (DVL)、惯性测量单元 (IMU) 和压力计的传感器测量值用于建议的观测器。提出了一种过滤高频噪声的方法，其中估计状态是通过对预测到当前时间的有限数量的先前测量值的加权折现平均值获得的。假设车辆的姿态已知，并且假定加速度测量值是连续可用的。位置、深度和线速度的测量被假定为异步且偶尔可用，即它们不会同时到达，并且它们的采样率不是恒定的。使用李雅普诺夫理论为混合系统建立了均匀全局渐近稳定性 (UGAS)。提供了模拟结果以证明所提出方法的性能。