Hybrid observer concept for sensor fusion of sporadic measurements for underwater navigation

Abstract

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.