An Adaptive Initial Alignment Algorithm Based on Variance Component Estimation for a Strapdown Inertial Navigation System for AUV

Dong, Qianhui; Li, Yibing; Sun, Qian; Zhang, Ya

doi:10.3390/sym9080129

Cited by 11 publications

(6 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, lots of researchers also focus on the improved algorithms, such as adaptive filtering and robust filtering. For instance, an adaptive covariance estimation algorithm is developed to promote the attitude measurement performance [17]. In [18] and [19], a robust extended Kalman filtering (REKF) is adopted to suppress the external interferences.…”

Section: Introductionmentioning

confidence: 99%

Dual-antenna GNSS-aided robust MEMS IMU initial alignment under the earth-centered-earth-fixed frame

Zhang,

Tang,

Deng

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

The micro-electro-mechanical system (MEMS), with its small size, low cost and low power, has attracted widespread attentions in recent year, and the initial alignment of the inertial measurement unit (IMU) is an indispensable step before the navigation computation. In the traditional alignment methods with only the velocity measurements, the yaw angle is subject to divergence under low dynamic scenarios, and the measurements are also susceptible to the external environments. Furthermore, the navigation frame (n frame) is usually chosen as the reference frame. Although intuitive, it is more computationally complex compared with the earth-centered-earth-fixed frame (e frame). Therefore, to improve the alignment performance and computational efficiency, a robust MEMS IMU initial alignment method with yaw assistance under the e frame is proposed. In this method, to address the issues of the yaw divergency and computational inefficiency in the traditional methods, the relationship between the yaw angle, derived from dual-antenna GNSS baseline solution, and IMU error is derived and incorporated into the state space model with e frame as the reference frame. Besides, a robust extend Kalman filtering (REKF) is adopted to further improve the system’s performance of outlier resistance, whose robust factors are determined by Institute of Geodesy and Geophysics (IGG)-Ⅲ model. To validate the performance of the proposed method, two field experiments with the velocity of about 0.7 m s-1 and 1.5 m s-1 was conducted, and the collected data were processed for contrastive analysis. The results show that the effectiveness of the proposed method at suppressing yaw angle divergence and improving the alignment accuracy by resisting outliers under low dynamic scenarios compared with the traditional method. Moreover, the elapsed time is reduced by about 11% when the reference frame in data processing is switched from the n frame to the e frame.

show abstract

Section: Introductionmentioning

confidence: 99%

Dual-antenna GNSS-aided robust MEMS IMU initial alignment under the earth-centered-earth-fixed frame

Zhang,

Tang,

Deng

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…The accuracy of the initial alignment is directly related to the working precision of the inertial navigation system. Therefore, the rapid and accurate initial alignment becomes a research hotspot [ 3 – 5 ]. For an inertial navigation system, the initial alignment is to determine an initial value such as an attitude matrix at the initial moment.…”

Section: Introductionmentioning

confidence: 99%

An Initial Alignment Technology of Shearer Inertial Navigation Positioning Based on a Fruit Fly-Optimized Kalman Filter Algorithm

Wang

et al. 2020

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

The shearer is one of the core equipment of the fully mechanized coal face. The fast and accurate positioning of the shearer is the prerequisite for its memory cutting, intelligent height adjustment, and intelligent speed adjustment. Inertial navigation technology has many advantages such as strong autonomy, good concealment, and high reliability. The accurate positioning of the shearer based on inertial navigation can not only determine its operating position but also measure the direction of movement. However, when inertial navigation is used to locate the shearer in motion, the cumulative errors will occur, resulting in inaccurate positioning of the shearer. The accuracy of the initial alignment is directly related to the working precision of the inertial navigation system. In order to improve the efficiency and accuracy of initial alignment, an improved initial alignment method is proposed in this paper, which uses a fruit fly-optimized Kalman filter algorithm for initial alignment. In order to improve the filtering performance, the fruit fly-optimized Kalman filter algorithm uses an improved fruit fly algorithm to realize the adaptive optimization of system noise variance. Finally, simulation and experiments verify the effectiveness of the fruit fly-optimized Kalman filter algorithm.

show abstract

“…The heart of initial alignment is mainly about the determination of the attitude matrix between the body frame and the reference navigation frame [13]. The process of alignment is generally composed of two consecutive phases: coarse alignment and fine alignment [14], [15].…”

Section: Introductionmentioning

confidence: 99%

Research on the Compensation Strategy of the Initial Alignment of the SINS Based on the Dynamic Model of the Shearer

Chen

Yang

et al. 2019

IEEE Access

View full text Add to dashboard Cite

The strap-down inertial navigation system (SINS) is a commonly used sensor for autonomous underground navigation that can be used for shearer positioning under a coal mine. To overcome the performance degradation of the existing initial alignment algorithm based on an inertial frame with strong vibration conditions in underground coal mines, a novel initial alignment compensation strategy based on the dynamic model of the shearer is presented. This strategy mainly compensates for the linear vibration caused by the harsh environment based on the dynamic model of the shearer. Meanwhile, this strategy can effectively estimate the linear velocity of the shearer's fuselage and avoid the error caused by the system disturbance assumption. According to the shearer dynamics model, the linear velocity spectrum of the shearer's fuselage was determined. Then, based on the vibration characteristics, the initial alignment compensation model of the SINS was derived and the initial attitude angle was obtained. The simulation and experimental results show that the proposed compensation strategy can effectively improve the convergence speed and accuracy of the initial alignment and lay a foundation for the unmanned work of the shearer. INDEX TERMS Strap-down inertial navigation system, initial alignment, shearer, dynamic model of shearer, error compensation strategy.

show abstract

An Adaptive Initial Alignment Algorithm Based on Variance Component Estimation for a Strapdown Inertial Navigation System for AUV

Cited by 11 publications

References 28 publications

Dual-antenna GNSS-aided robust MEMS IMU initial alignment under the earth-centered-earth-fixed frame

Dual-antenna GNSS-aided robust MEMS IMU initial alignment under the earth-centered-earth-fixed frame

An Initial Alignment Technology of Shearer Inertial Navigation Positioning Based on a Fruit Fly-Optimized Kalman Filter Algorithm

Research on the Compensation Strategy of the Initial Alignment of the SINS Based on the Dynamic Model of the Shearer

Contact Info

Product

Resources

About