A Novel Initial Alignment Scheme for Low-Cost INS Aided by GPS for Land Vehicle Applications

Han, Songlai; Wang, Jinling

doi:10.1017/s0373463310000214

Cited by 59 publications

(33 citation statements)

References 13 publications

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“…However, heading, compared with roll and pitch, has a poorer observability via the conventional INS/ GPS integration filter due to small coupling coefficients in the dynamic model of INS in the usually low velocities a ground vehicle encounters. See Han andWang (2008, 2010) for more details on this concept. Hence, an alternative benchmark will also be introduced for assessment of the heading solutions.…”

Section: Field-test Resultsmentioning

confidence: 99%

Improving MEMS-IMU/GPS integrated systems for land vehicle navigation applications

2015

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The cost of inertial navigation systems (INS) has decreased significantly during recent years using micro-electro-mechanical system technology in production of inertial measurement units (IMUs). However, these IMUs do not provide the accuracy and stability of their classical mechanical counterparts which limit their applications. Hence, the error control of such systems is of the great importance which is achievable using external information via an appropriate fusion algorithm. Traditionally, this external information can be derived from global positioning system (GPS). But it is well known that GPS data availability and accuracy are vulnerable to signal-degrading circumstances and satellite visibility. We introduce a standalone attitude and heading reference system (AHRS) algorithm which employs the IMU and magnetometers data in an averaging manner. The averaging method is different from a simple smoothing procedure, since it takes the rotations of the platform (during the averaging interval) into account. The proposed AHRS solution is further used to provide additional attitude updates with adaptive noise variances for the integrated INS/GPS system during GPS outages via a refined loosely coupled filtering procedure, making the error growth well restrained. Functionality of the algorithm has been assessed via a field test. The results indicate that the proposed procedure outperforms the traditional integration scheme in different situations, while the latter almost loses track of the movements of the vehicle after 60-second GPS outages.

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Section: Field-test Resultsmentioning

confidence: 99%

Improving MEMS-IMU/GPS integrated systems for land vehicle navigation applications

2015

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“…In this work, we choose the local level geographic coordinate frame as the navigation frame. Under the large azimuth misalignment, the direction cosine matrix (DCM) C can be described as follows [13,14]:…”

Section: The Establishment Of the Improved Gyrocompass Alignmentmentioning

confidence: 99%

An Improved Gyrocompass Alignment Method for Large Azimuth Misalignment

Gao

et al. 2015

Mathematical Problems in Engineering

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Due to the impact of the nonlinear factor caused by large azimuth misalignment, the conventional gyrocompass alignment method is hard to favorably meet the requirement of alignment speed under the condition of large azimuth misalignment of INS. In order to solve this problem, an improved gyrocompass alignment method is presented in this paper. The improved method is designed based on the nonlinear model for large azimuth misalignment and performed by opening the azimuth loop. The influence of the nonlinear factor on gyrocompass alignment will be reduced when opening the azimuth loop. Simulation and experimental results show that the initial alignment can be efficiently accomplished through using the improved method in the case of existing large azimuth misalignment, and in the same conditions, the alignment speed of the improved method is faster than that of the conventional one.

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“…It needs to be calibrated before a mission is conducted [21]. Supposing the error of

{italicv}_{d}^{c}

is mainly caused by the platform misalignments, the DVL measurement in error

{\overset{v}{true}}_{d}^{c}

can be described as follows:

\begin{matrix} {\overset{v}{true}}_{d}^{c} = {italicC}_{b}^{c} {italicC}_{d}^{b} v_{d} + δ {italicC}_{b}^{c} {italicC}_{d}^{b} v_{d} \\ = {italicv}_{d}^{c} + δ {italicC}_{b}^{c} {italicC}_{d}^{b} v_{d} \end{matrix}

where the perturbation of the attitude matrix

δ {italicC}_{b}^{c}

is given by [22]:

δ {italicC}_{b}^{c} = (I - {italicC}_{c}^{p}) {italicC}_{b}^{c}

…”

Section: Alignment Modelmentioning

confidence: 99%

A Novel Scheme for DVL-Aided SINS In-Motion Alignment Using UKF Techniques

Wang

et al. 2013

Sensors

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In-motion alignment of Strapdown Inertial Navigation Systems (SINS) without any geodetic-frame observations is one of the toughest challenges for Autonomous Underwater Vehicles (AUV). This paper presents a novel scheme for Doppler Velocity Log (DVL) aided SINS alignment using Unscented Kalman Filter (UKF) which allows large initial misalignments. With the proposed mechanism, a nonlinear SINS error model is presented and the measurement model is derived under the assumption that large misalignments may exist. Since a priori knowledge of the measurement noise covariance is of great importance to robustness of the UKF, the covariance-matching methods widely used in the Adaptive KF (AKF) are extended for use in Adaptive UKF (AUKF). Experimental results show that the proposed DVL-aided alignment model is effective with any initial heading errors. The performances of the adaptive filtering methods are evaluated with regards to their parameter estimation stability. Furthermore, it is clearly shown that the measurement noise covariance can be estimated reliably by the adaptive UKF methods and hence improve the performance of the alignment.

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A Novel Initial Alignment Scheme for Low-Cost INS Aided by GPS for Land Vehicle Applications

Cited by 59 publications

References 13 publications

Improving MEMS-IMU/GPS integrated systems for land vehicle navigation applications

Improving MEMS-IMU/GPS integrated systems for land vehicle navigation applications

An Improved Gyrocompass Alignment Method for Large Azimuth Misalignment

A Novel Scheme for DVL-Aided SINS In-Motion Alignment Using UKF Techniques

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