A toolbox of aiding techniques for the HUGIN AUV integrated inertial navigation system

Jalving, B.; Gade, Kenneth; Hagen, Ove Kent; Vestgård, K.

doi:10.1109/oceans.2003.178505

Cited by 82 publications

(61 citation statements)

References 4 publications

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“…When the onboard naviga tion system is highly accurate, a loosely coupled integration scheme works well in which (i) the filtered output of an INS is used as input to the TRN filter, and (ii) a central Kalman Filter is used to fuse the resulting INS and TRN filter estimates. This integration method is typical of what has been utilized in other fielded underwater TRN systems [17], [18].…”

Section: Trn/ahrs Integrationmentioning

confidence: 99%

Closed-loop terrain relative navigation for AUVs with non-inertial grade navigation sensors

Meduna

Rock

McEwen

2010

2010 IEEE/OES Autonomous Underwater Vehicles

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Terrain Relative Navigation (TRN) has the potential to enable drift-free, low-cost navigation for a wide range of underwater vehicles. Current underwater TRN systems have demonstrated meter-level navigation accuracy by utilizing high accuracy inertial navigation systems in combination with both low and high quality sonar sensors and bathymetry maps. No studies, however, have considered the application of underwater TRN to vehicles with non-inertial-grade navigation systems, an extension which would greatly increase its applicability. The use of low-grade motion sensors in TRN is problematic due to the presence of large errors which can cause highly inaccurate alignment of successive sonar pings. To address this, a TRN filter is developed in which information present in the terrain correlations is used to help identify and mitigate large motion sensor errors. The resulting filter consists of a tight coupling between TRN and the onboard navigation, yielding a significantly improved navigation solution. The development of this TRN system is detailed for an AUV with an Attitude, Heading and Reference System (AHRS)-based dead reckoning navigation, which has an observed accuracy of 5 -25% distance traveled.Field trials in Monterey Bay, CA demonstrate the ability of the TRN filter to acheive 5 -10m navigational precision. Field trials are also presented demonstrating successful real-time, closed-loop TRN on the AUV. For these trials, the combined TRN/AHRS system enabled the vehicle to fly to a known beacon location with ability comparable to an acoustic homing system. The presented results demonstrate that TRN technology can successfully be applied to non-inertial-grade vehicle platforms, greatly improving the navigation capabilities of such systems.

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Section: Trn/ahrs Integrationmentioning

confidence: 99%

Closed-loop terrain relative navigation for AUVs with non-inertial grade navigation sensors

Meduna

Rock

McEwen

2010

2010 IEEE/OES Autonomous Underwater Vehicles

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“…The unit beam vector is denoted by bBsbe and the Bsbe Nbottom range measurement is denoted by r . The transformed measurement in MN is then given by PBNb,ttom RMNB ( PBB b +RBB b, BbNb ) (1) Since mostly acoustic sensors are used for measuring bathymetry, some comments must be made on the simplified approach above. First assume that the sound velocity co is…”

Section: Generic Sensor and Map Processingmentioning

confidence: 99%

“…This navigation system [1] can utilize a variety of aiding sensors, selected from a toolbox of aiding techniques, fitting the operational requirements. In many operations submerged position updates may be required.…”

Section: Introductionmentioning

confidence: 99%

TerrLab ¿ a generic simulation and post-processing tool for terrain referenced navigation

Hagen

2006

Oceans 2006

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One of the challenges in underwater navigation for autonomous vehicles is to get position updates for the navigation system. For deep water applications or operations requiring a high degree of covertness, surfacing for GPS is not a solution. The conventional submerged position update techniques, like DGPS-USBL or LBL, requires external physical infrastructure in the operation area of the vehicle. Terrain referenced navigation is a promising technique for submerged position updates. It requires only a bathymetric map of the operation area and the use of a bathymetric sensor during the operation. Different algorithms for terrain referenced navigation have already successfully been tested for underwater applications. These algorithms include variants of the original TERCOM, different Kalman filter based techniques and non-linear Bayesian estimators like the point mass filter and particle filters. To asses the performance of the different algorithms and their robustness on both real and simulated data, FFI has developed a tool called TerrLab. The tool was originally used to qualify algorithms for the real-time terrain navigation system for the HUGIN AUVs. It is now also used to test different sensor and DTM error models for the algorithms.

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“…The use of these robotic platforms requires low-cost, compact, high performance robust navigation systems, that can accurately estimate the vehicle's position and attitude. These facts raised, in the last years, the robotics scientific community awareness towards the development of accurate navigation systems [2,3] tioning in open ocean with excellent short-term accuracy. However, unbounded positioning errors induced by the uncompensated rate gyro and accelerometer errors degrade the INS accuracy over time.…”

Section: Introductionmentioning

confidence: 99%

USBL/INS Tightly-Coupled Integration Technique for Underwater Vehicles

Morgado¹,

Oliveira²,

Silvestre³

et al. 2006

2006 9th International Conference on Information Fusion

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This paper presents a new Ultra-Short Baseline (USBL) tightly-coupled integration technique to enhance error estimation in low-cost strapdown Inertial Navigation Systems (INSs) with application to underwater vehicles. In the proposed strategy the acoustic array spatial information is directly exploited resorting to the Extended Kalman Filter implemented in a direct feedback structure. The determination and stochastic characterization of the round trip travel time are obtained resorting to pulse detection matched filters of acoustic signals modulated using spread-spectrum Code Division Multiple Access (CDMA). The performance of the overall navigation system is assessed in simulation and compared with a conventional loosely-coupled solution that consists of solving separately the triangulation and sensor fusion problems. From the simulation results it can be concluded that the proposed technique enhances the position, orientation, and sensors biases estimates accuracy.

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A toolbox of aiding techniques for the HUGIN AUV integrated inertial navigation system

Cited by 82 publications

References 4 publications

Closed-loop terrain relative navigation for AUVs with non-inertial grade navigation sensors

Closed-loop terrain relative navigation for AUVs with non-inertial grade navigation sensors

TerrLab ¿ a generic simulation and post-processing tool for terrain referenced navigation

USBL/INS Tightly-Coupled Integration Technique for Underwater Vehicles

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