Francisco Curado Teixeira

Geophysical Navigation of Autonomous Underwater Vehicles Using Geomagnetic Information

Abstract This paper addresses the general problem of Autonomous Underwater Vehicle navigation by exploiting the availability of terrain and geophysics-related data. Geophysical navigation algorithms are derived to estimate the position and velocity of an AUV in the presence of unknown ocean currents and sensor biases. The current implementation merges acoustic and magnetic measurements with dead-reckoning data. One of the main contributions of the paper is the utilization of maps of invariant gradients that can be calculated from prior maps of the geomagnetic field. The results obtained through computer simulations with real data show the effectiveness of the GN approach proposed.

AUV Terrain-Aided Doppler Navigation using Complementary Filtering

Abstract This paper addresses the challenging problem of achieving truly autonomous long-range navigation of underwater vehicles relying on affordable navigation sensors. Terrain-aided navigation (TAN) is a methodology that holds potential to solve this problem by dispensing with the need to use high-grade, inertial navigation sensors and the deployment and calibration of acoustic beacons. To implement TAN without incurring the additional cost of expensive dedicated sensors, we propose the utilization of a Doppler velocity logger (DVL) which is an equipment of widespread utilization in oceanography and also a standard instrument in underwater navigation. We avail ourselves of a less exploited characteristic of DVL sensors that consists in the ability to acquire, simultaneously with the velocity data, a set of accurate range measurements relatively to a reflective interface. The combination of these sensing capacities enables Doppler units to be used not only in dead-recknoning navigation but also in terrain-based localization of underwater vehicles. The main contribution of the paper is the design of a complementary filter (CF) for fusion of TAN estimates with DVL measurements. The CF approach is motivated by the need to reduce the short-term variability of position estimates that is typically observed in conventional TAN. The solution proposed is analysed in comparison with a well-known Rao-Blackwellized particle filter set-up which is shown to implement a data fusion filter designed in a stochastic estimation framework. The results obtained in Monte Carlo simulations performed with real bathymetric data evidence the superior performance of the complementary filter approach in terms of position estimation accuracy and long term output signal stability.

Complementary terrain/single beacon-based AUV navigation

Abstract This paper describes work done towards the development of advanced geophysical-based navigation systems for autonomous underwater vehicles (AUVs). The specific problem that we tackle is that of combining terrain-aided navigation (TAN) with single-beacon navigation (SBN) techniques. The resulting complementary TAN/SBN system has the potential to overcome some of the problems that arise with TAN navigation only, when an AUV undergoes motions that lead it temporarily across areas where the terrain below is not sufficiently “rich” in terms of topographic features. The key contribution of this paper is a formal analysis of the benefits of using complementary filtering, in opposition to TAN navigation only. To this effect, we exploit key tools of estimation theory, and in particular the Cramer-Rao lower bound inequality to obtain a lower bound on the minimum covariance of the estimation error that can be obtained with any unbiased estimator. For a real terrain profile we compute and compare the Cramer-Rao lower bounds for TAN only and TA/SB-based navigation. The increase in the expected performance that can be achieved with the second solution is clearly visible. The efficacy of the new solution proposed is illustrated with the help of computer simulations.

Magnetic navigation and tracking of underwater vehicles

Abstract This paper proposes novel methods with the potential to improve the performance of navigation and tracking systems in underwater environments. The work relies on well-established methods of potential field inversion and introduces a new analytic formulation designed to stabilize the solution of the inverse problem in real-time applications. The navigation method proposed exploits the terrain information associated with geomagnetic field anomalies, without the need of a priori maps. The procedure can also be applied to track a moving vehicle based on its associated disturbance of the environmental magnetic field. We envision the integration of theses methods in terrain-aided navigation systems, simultaneous localization and mapping algorithms, and tracking applications.

Geophysical navigation of autonomous underwater vehicles

Abstract The paper addresses the problem of Geophysical Navigation (GN) of Autonomous Underwater Vehicles (AUVs). The objective is to use bathymetric and geomagnetic information to estimate the position and velocity of an AUV in the presence of unknown ocean currents. The navigation estimator derived mechanizes a sequential Bayesian estimation strategy consisting of a novel particle filter algorithm that we name Smooth Kernel Particle Filter. The estimator relies essentially on the AUV kinematics. It integrates measurements derived from the terrain with dead-reckoning based on Doppler and attitude sensors. Central to the strategy derived is the concept of maps of invariant gradients of the geomagnetic field as an efficient form of representing geomagnetic terrain information. The results obtained through computer simulations show the effectiveness of the GN approach proposed.

Nonlinear adaptive depth tracking and attitude control of an underwater towed vehicle

Abstract This paper addresses the problem of simultaneous depth tracking and precise attitude control of an underwater towed vehicle integrated in a two-stage towing arrangement. A nonlinear Lyapunov-based output feedback controller is designed to operate in the presence of plant parameter uncertainty and proven to regulate pitch, yaw, and depth tracking errors to zero. When subjected to bounded external disturbances, the tracking errors converge to a neighborhood of the origin that can be made arbitrarily small. In the implementation proposed, a nonlinear observer is used to estimate the linear velocities used by the controller. The results obtained with computer simulations including sea wave driven disturbances and sensor noise, show that the controlled system exhibits good performance about different operating conditions and holds considerable potential for oceanographic missions that require simultaneous depth and attitude control.

Magnetic signal processing methods with application to geophysical navigation of marine robotic vehicles

The present paper describes the development of geophysical navigation (GN) methods for small, affordable underwater robotic vehicles. The proposed GN methods includes a classical, bathymetric-based terrain-aided navigation (TAN) approach, a magnetic-based geophysical navigation solution (MAGNAV), and an integration of both methods (TAN-MAGNAV). Due to insufficient topographic features in the adopted test site, the classical TAN approach performed poorly in terms of positioning accuracy. To mitigate this, the complementarity of magnetic and topographic terrain information was exploited, initially using only magnetic data to estimate the vehicle position and later by fusing magnetic and altitude data. The results obtained illustrate the high potential of using magnetic data for geophysical navigation of autonomous underwater vehicles. The navigation methods described are validated in simulated trials using real magnetic, topographic, and navigation data acquired with an autonomous marine vehicle in real trials. The equipment employed in the proposed solution consists of standard navigation sensors, a sonar altimeter, and an affordable total field magnetometer.

AUV terrain-aided navigation using a Doppler velocity logger

Abstract This paper addresses the design and implementation of terrain-aided navigation (TAN) methods for small autonomous underwater vehicles (AUVs) that rely on standard navigation sensors and dispense with the need for dedicated sensors for terrain data acquisition. The research described focuses on the problem of TAN implementation in underwater scenarios characterized by smooth sea-bottom topography and very shallow water, where the terrain information available for navigation is scarce. The navigation algorithms and the data fusion methods whose tests are documented in the paper build upon and expand prior theoretical work published by the authors; the TAN solutions adopted exploit the terrain information and the navigation data acquired with an inexpensive Doppler velocity logger (DVL) and a standard motion reference unit, respectively. The position estimation methods analyzed include a bi-dimensional particle filter (PF) and a four-dimensional Rao-Blackwellized PF that was designed to estimate the unknown Doppler velocity measurement biases responsible for the unbound localization errors typically observed in dead-recknoning navigation. The positioning accuracy achieved with these filters is compared with the output of a novel method, also proposed in the paper, that mechanizes a complementary-like filter designed to fuse the output of a TAN estimator with the velocity measurements provided by a DVL. Experimental results obtained during field tests with an autonomous marine vehicle are reported and analyzed.

Novel Approaches to Geophysical Navigation of Autonomous Underwater Vehicles

This paper introduces a method for the navigation of autonomous underwater vehicles (AUVs) and tracking of submersible targets that relies on analytic inversion of magnetic field anomalies. The magnetic sensor arrangement proposed configures a gradiometer array whose nodes may correspond to a set of collaborative AUVs deployed in a formation of adaptable geometry. The solution presented envisions applications to scientific, industrial, and military activities.