Coarse Alignment of a Ship's Strapdown Inertial Attitude Reference System Using Velocity Loci

Silson, Peter

doi:10.1109/tim.2011.2113131

Cited by 175 publications

(127 citation statements)

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“…As a result, t 2 is selected to be the end of the alignment time and t 1 is half of the alignment time in this paper. This estimation method is effective with any initial attitude error, which is similar to the work of Gu et al (2008) and Silson (2011). Besides, as the velocity of Doppler is employed to measure the linear motion, a better attitude estimate will be obtained.…”

Section: A Fa S T S I N S I N I T I a L A L I G N M E N T S C H E M Ementioning

confidence: 87%

A Fast SINS Initial Alignment Scheme for Underwater Vehicle Applications

Wang

et al. 2012

J. Navigation

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To achieve high Strapdown Inertial Navigation System (SINS) alignment accuracy within a short period of time is still a challenging issue for underwater vehicles. In this paper, a new SINS initial alignment scheme aided by the velocity derived from Doppler Velocity Log (DVL) is proposed to solve this problem. In the stage of the coarse alignment, the velocity of DVL is employed to reduce the impact of the linear motion. With a backtracking framework, the fine alignment runs with the data recorded during the process of the coarse alignment and thus will speed up the overall alignment process. In addition, by using this new scheme, it is equivalent to length the alignment time for both coarse and fine alignments, so the accuracy of the alignments will be improved. In order to reduce the volume of the data that has to be recorded, a new model for SINS fine alignment is derived in the inertial reference frame which makes it feasible for real time applications. The experimental results are presented for both unaided static and in-motion alignment using DVL aiding. It is clearly shown that the proposed method meets the requirement of SINS alignment for underwater vehicles.K E Y WO R D S 1. Inertial Alignment.

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Section: A Fa S T S I N S I N I T I a L A L I G N M E N T S C H E M Ementioning

confidence: 87%

A Fast SINS Initial Alignment Scheme for Underwater Vehicle Applications

Wang

et al. 2012

J. Navigation

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“…Although the interval of the interleaved integration is set to be the GPS-sample time in [10], it can be extended to a more general form with arbitrary length. We can IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS VOL.…”

Section: B Velocity Integration Formula For Vector Observations Consmentioning

confidence: 99%

Optimization-based alignment for strapdown inertial navigation system: comparison and extension

Chang

2016

IEEE Trans. Aerosp. Electron. Syst.

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“…Step 1: Compute α , β , χ , λ and γ according to (20), (25) and (26); 14 Step 2: Set 0 k  and start with a good estimate   Step 4: Solve   ,   x according to (38);…”

Section: Batch Algorithm For Joint Attitude and Parameter Estimation mentioning

confidence: 99%

“…In contrast to the Kalman filtering, a novel optimization-based approach to solve attitude alignment was initiated by our group [12] in the swaying case and recently extended to the on-the-move alignment by us and other groups [10,[13][14][15]. The approach poses the attitude alignment as an attitude optimization problem using infinite vector observations and is advantageous in handling those scenarios that have no prior initial attitude information available.…”

Section: A New Technique For Ins/gnss Attitude and Parameter Estimatimentioning

confidence: 99%

“…Our recent work of in-flight coarse alignment [10,11] clearly shows that the presence of the lever arm causes slow convergence and degradation of attitude estimation. It is desirable to find a way to simultaneously solve the problems of the lever arm and attitude alignment, for a wide spectrum of INS/GNSS application scenarios.In contrast to the Kalman filtering, a novel optimization-based approach to solve attitude alignment was initiated by our group [12] in the swaying case and recently extended to the on-the-move alignment by us and other groups [10,[13][14][15]. The approach poses the attitude alignment as an attitude optimization problem using infinite vector observations and is advantageous in handling those scenarios that have no prior initial attitude information available.…”

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A New Technique for INS/GNSS Attitude and Parameter Estimation Using Online Optimization

Wang

2014

IEEE Trans. Signal Process.

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Abstract-Integration of inertial navigation system (INS) and global navigation satellite system (GNSS) is usually implemented in engineering applications by way of Kalman-like filtering. This form of INS/GNSS integration is prone to attitude initialization failure, especially when the host vehicle is moving freely. This paper proposes an online constrained-optimization method to simultaneously estimate the attitude and other related parameters including GNSS antenna's lever arm and inertial sensor biases. This new technique benefits from self-initialization in which no prior attitude or sensor measurement noise information is required. Numerical results are reported to validate its effectiveness and prospect in high accurate INS/GNSS applications.Index Terms-Inertial navigation, satellite navigation, velocity integration formula, lever arm, online Reference frame unification is a pre-condition for any accurate information blending of multiple sensors.This work was supported in part by the Fok Ying Tung Foundation (131061), National Natural Science Foundation of China (61174002), the Foundation for the Author of National Excellent Doctoral Dissertation of People's Republic of China (FANEDD 200897) and Program for New Century Excellent Talents in University (NCET-10-0900). A New Technique for INS/GNSS Attitude and Parameter Estimation Using Online Optimization 2For the case of INS/GNSS integration, there is an unavoidable displacement, usually called as the lever arm, between their respective sensing points of INS and GNSS [1]. The magnitude of the lever arm is significant for many applications. For example, when the GNSS antenna is mounted outside on the roof to better receive satellite signals, the INS is usually installed inside the carrier for reasons like easy maintenance. It is difficult or impossible, however, to precisely measure the lever arm vector in a designated frame, taking account of the virtual attributes of the sensing points and the frame axes [2,3]. Lever arm uncertainty acts as a major error source of INS/GNSS in accurate applications, e.g., pose determination in airborne direct georeferencing [4] and airborne gravity measuring [5].A good practice is to accommodate and estimate the lever arm within the extended Kalman filter (EKF) in INS/GNSS integration [2,6,7]. In addition to the knowledge of noise statistics, the Kalman filtering method relies heavily on a roughly known initial attitude that is only achievable under benign situations such as when the carrier is stationary or moving straight. If not properly initiated, however, INS/GNSS integration based on Kalman filtering would be subjected to failure [1,8,9]. These situations are not uncommon in practice, for example when the carrier is moving freely or the duration of benign situations is not long enough to reach a good initial attitude alignment. That is to say, the lever arm estimation is conditioned on a good initial attitude.On the other hand, to obtain a good initial attitude inversely requires a small INS/GNSS lever arm effect. ...

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Coarse Alignment of a Ship's Strapdown Inertial Attitude Reference System Using Velocity Loci

Cited by 175 publications

References 9 publications

A Fast SINS Initial Alignment Scheme for Underwater Vehicle Applications

A Fast SINS Initial Alignment Scheme for Underwater Vehicle Applications

Optimization-based alignment for strapdown inertial navigation system: comparison and extension

A New Technique for INS/GNSS Attitude and Parameter Estimation Using Online Optimization

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