A Triangle Matching Algorithm for Gravity-aided Navigation for Underwater Vehicles

Yang, Zifeng; Zhu, Zhuangsheng; Zhao, Weigao

doi:10.1017/s0373463313000660

Cited by 15 publications

(8 citation statements)

References 20 publications

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“…Autonomous Underwater Vehicles (AUV) are important tools for marine resource exploitation and marine scientific research (Zhu et al, 2014; Paull et al, 2014; Yang et al, 2014). Due to AUVs' limited energy, communication range/bandwidth, and sensing range, many applications have outgrown a single AUV's capability.…”

Section: Introductionmentioning

confidence: 99%

Multi-AUV Underwater Cooperative Search Algorithm based on Biological Inspired Neurodynamics Model and Velocity Synthesis

Cao

Zhu

2015

J. Navigation

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Ocean currents impose a negative effect on Autonomous Underwater Vehicle (AUV) underwater target searches, which lengthens the search paths and consumes more energy and team effort. To solve this problem, an integrated algorithm is proposed to realise multi-AUV cooperative search in dynamic underwater environments with ocean currents. The proposed integrated algorithm combines the Biological Inspired Neurodynamics Model (BINM) and Velocity Synthesis (VS) method. Firstly, the BINM guides a team of AUVs to achieve target search in underwater environments; BINM search requires no specimen learning information and is thus easier to apply to practice, but the search path is longer because of the influence of ocean current. Next the VS algorithm offsets the effect of ocean current, and it is applied to optimise the search path for each AUV. Lastly, to demonstrate the effectiveness of the proposed integrated approach, simulation results are given in this paper. It is proved that this integrated algorithm can plan shorter search paths and thus the energy consumption is lower compared with BINM.

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Section: Introductionmentioning

confidence: 99%

Multi-AUV Underwater Cooperative Search Algorithm based on Biological Inspired Neurodynamics Model and Velocity Synthesis

Cao

Zhu

2015

J. Navigation

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“…The establishment of the state equation and observation equation of CSITAN + WRIT has the same principle as that of the traditional SITAN algorithm except that it is a multipoint‐based Recursive Optimal Estimation . 1The Establishment of State Equation …”

Section: Principle Of the Traditional Sitan Algorithm And Csitan + Writmentioning

confidence: 99%

“…By using cartographic‐based digital terrain elevation data, it can achieve a median accuracy of less than 100 m under the conditions of gently rolling, forested terrain. proposed a HELI/SITAN algorithm that utilizes a set of single‐state Kalman filters to obtain favorable accuracy of positions even under large initial errors and position median radial error of real‐time implementation less than 50 m. proposed a Triangle Matching Algorithm, which contains the initial matching stage and the tracking matching stage that can work under a wide range of initial errors, from 0.05 deg to 0.002 deg. realized the TAN system by particle filter and Gaussian mixture filter in a Bayesian framework that obeyed the principle of achieving the optimal properties with limited resource.…”

Section: Introductionmentioning

confidence: 99%

A Robust Solution of Integrated SITAN with TERCOM Algorithm: Weight-Reducing Iteration Technique for Underwater Vehicles' Gravity-Aided Inertial Navigation System

et al. 2017

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The robustness of the Sandia Inertial Terrain‐Aided Navigation (SITAN) algorithm has a pivotal influence on underwater vehicles' Gravity‐Aided Inertial Navigation Systems (GAINS). An abrupt glitch of the accuracy of the GAINS will evolve into a disaster when vehicles pass through areas of smooth gravity. In order to resolve vulnerability issues of initial error and linearization error, we propose the Correlation SITAN algorithm with Weight‐Reducing Iteration Technique (CSITAN + WRIT), in which the correlation process equals Terrain Contour Matching (TERCOM). The CSITAN algorithm is a Multipoint‐based Extended Kalman Filtering (MEKF) method, which can work in real time. First, we need to derive the state equation and observation equation of the Multipoint‐based SITAN algorithm based on the principle of the traditional SITAN algorithm. Then the accuracy of the state prediction can be improved, and the linearization error can be reduced by the correlation method based on TERCOM. Finally, the WRIT is utilized to reduce the possible influence of gross errors existing in the results of the MEKF and to extract a value with higher precision. The experimental results show that CSITAN + WRIT can achieve better accuracy and higher success rate of matching and can improve the possibilities of the occurrence of large matching errors than traditional SITAN methods in areas with smooth gravity. Copyright © 2017 Institute of Navigation

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“…where Δ is the th gravity anomaly extracted from the gravity database; A is a 3-by-3 matrix to be estimated; and are the latitude and longitude corresponding to the th gravity anomaly. There are 9 elements to be estimated in A, and 9 equations corresponding to the 9 gravity anomalies as in (6), so this proper-determined set of equations can be solved to get A readily. Let…”

Section: Measurement Equationmentioning

confidence: 99%

“…So it is of strategic significance to aid INS using GMN. In fact, GMN aided INS has been widely studied recently; see, for example, [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter

Liu

Chang²

2015

Mathematical Problems in Engineering

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This paper is concerned with the topic of gravity matching aided inertial navigation technology using Kalman filter. The dynamic state space model for Kalman filter is constructed as follows: the error equation of the inertial navigation system is employed as the process equation while the local gravity model based on 9-point surface interpolation is employed as the observation equation. The unscented Kalman filter is employed to address the nonlinearity of the observation equation. The filter is refined in two ways as follows. The marginalization technique is employed to explore the conditionally linear substructure to reduce the computational load; specifically, the number of the needed sigma points is reduced from 15 to 5 after this technique is used. A robust technique based on Chi-square test is employed to make the filter insensitive to the uncertainties in the above constructed observation model. Numerical simulation is carried out, and the efficacy of the proposed method is validated by the simulation results.

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A Triangle Matching Algorithm for Gravity-aided Navigation for Underwater Vehicles

Cited by 15 publications

References 20 publications

Multi-AUV Underwater Cooperative Search Algorithm based on Biological Inspired Neurodynamics Model and Velocity Synthesis

Multi-AUV Underwater Cooperative Search Algorithm based on Biological Inspired Neurodynamics Model and Velocity Synthesis

A Robust Solution of Integrated SITAN with TERCOM Algorithm: Weight-Reducing Iteration Technique for Underwater Vehicles' Gravity-Aided Inertial Navigation System

Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter

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