A fast compass alignment method for SINS based on saved data and repeated navigation solution

Liu, Xixiang; Xu, Xiaosu; Wang, Lihui; Liu, Yiting

doi:10.1016/j.measurement.2013.07.013

Cited by 35 publications

(16 citation statements)

References 6 publications

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“…Observing (11), (12) and (13), we find that ˛(s) and (s) are both independent of north acceleration A N . That is to say, acceleration does not have influence on misalignment angle in this novel gyrocompass alignment method.…”

Section: Acceleration Compensation For Gyrocompass Alignmentmentioning

confidence: 76%

“…But while acceleration exists, the performance of this compensation method is poor because of the negative acceleration effect [10,11]. Liu [12] proposed that the acceleration can be obtained through differential of EM-Log velocity, and then it can be used to compensate gyrocompass alignment loop. Because the sampling frequency of EM-Log is low (usually 10 Hz), the acceleration obtained through differential has large noise [13].…”

Section: Introductionmentioning

confidence: 99%

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A novel EM-Log aided gyrocompass alignment for in-motion marine SINS

Sun

Xia

Ben

et al. 2015

Optik - International Journal for Light and Electron Optics

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Section: Acceleration Compensation For Gyrocompass Alignmentmentioning

confidence: 76%

Section: Introductionmentioning

confidence: 99%

A novel EM-Log aided gyrocompass alignment for in-motion marine SINS

Sun

Xia

Ben

et al. 2015

Optik - International Journal for Light and Electron Optics

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“…In general, the relationships between alignment errors and sensor errors are often expressed in the navigation frame because only the analysis of alignment errors in the navigation frame is meaningful, since the final results of alignment need to be expressed in the navigation frame. For many alignment approaches (for instance, gyrocompass alignment and optimum alignment), the relationships can be written as [ 16 , 17 , 18 , 19 ]:

where

is the east alignment error,

is the north alignment error,

is the up alignment error,

represents the east accelerometer error,

represents the north accelerometer error, and

represents the east FOG error. By utilizing the perturbation method, the correlation between

and

in this paper can be described as:

where

is the error matrix related to

, and

denotes the error matrix of

.…”

Section: Error Analysis and Optimal Parameter Designmentioning

confidence: 99%

Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System

Wang

Chen

et al. 2015

Sensors

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Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm.

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“…In the fine alignment procedure, gyrocompass alignment, Kalman filter, and parameter identification method are the mostly used techniques to deal with alignment problems in SINS [15][16][17]. Gyrocompass alignment based on compass effect is an important fine alignment method with the properties of interference suppression and lower computational complexity [18,19], but it needs to set longer damping time constant and always costs much more time to finish the alignment process [20,21].…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification Method for SINS Initial Alignment under Inertial Frame

Han¹,

Guo²,

Zhou³

2016

Mathematical Problems in Engineering

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The performance of a strapdown inertial navigation system (SINS) largely depends on the accuracy and rapidness of the initial alignment. The conventional alignment method with parameter identification has been already applied widely, but it needs to calculate the gyroscope drifts through two-position method; then the time of initial alignment is greatly prolonged. For this issue, a novel self-alignment algorithm by parameter identification method under inertial frame for SINS is proposed in this paper. Firstly, this coarse alignment method using the gravity in the inertial frame as a reference is discussed to overcome the limit of dynamic disturbance on a rocking base and fulfill the requirement for the fine alignment. Secondly, the fine alignment method by parameter identification under inertial frame is formulated. The theoretical analysis results show that the fine alignment model is fully self-aligned with no external reference information and the gyrodrifts can be estimated in real time. The simulation results demonstrate that the proposed method can achieve rapid and highly accurate initial alignment for SINS.

show abstract

A fast compass alignment method for SINS based on saved data and repeated navigation solution

Cited by 35 publications

References 6 publications

A novel EM-Log aided gyrocompass alignment for in-motion marine SINS

A novel EM-Log aided gyrocompass alignment for in-motion marine SINS

Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System

Parameter Identification Method for SINS Initial Alignment under Inertial Frame

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