An Improved Strapdown Inertial Navigation System Initial Alignment Algorithm for Unmanned Vehicles

Zhang, Ya; Yu, Fashan; Gao, Wei; Wang, Yanyan

doi:10.3390/s18103297

Cited by 22 publications

(14 citation statements)

References 33 publications

(35 reference statements)

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“…The strap-down inertial navigation system (SINS) has been widely used in the determination of attitude, velocity and position of an object based on the dead-reckoning by making use of the measurements provided by the inertial measurement unit (IMU) [1][2][3]. To reduce the long-time navigation error mainly caused by the bias of accelerometers and gyroscopes, the SINS is often integrated with the global positioning system (GPS), which constructs the SINS/GPS integrated navigation system [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System

Zhang

et al. 2020

Sensors

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The optimization-based alignment (OBA) methods, which are implemented by the optimal attitude estimation using vector observations—also called double-vectors—have proven to be effective at solving the in-flight alignment (IFA) problem. However, the traditional OBA methods are not applicable for the low-cost strap-down inertial navigation system (SINS) since the error of double-vectors will be accumulated over time due to the substantial drift of micro-electronic- mechanical system (MEMS) gyroscope. Moreover, the existing optimal estimation method is subject to a large computation burden, which results in a low alignment speed. To address these issues, in this article we propose a new fast IFA method based on modified double-vectors construction and the gradient descent method. To be specific, the modified construction method is implemented by reducing the integration interval and identifying the gyroscope bias during the construction procedure, which improves the accuracy of double-vectors and IFA; the gradient descent scheme is adopted to estimate the optimal attitude of alignment without complex matrix operation, which results in the improvement of alignment speed. The effect of different sizes of mini-batch on the performance of the gradient descent method is also discussed. Extensive simulations and vehicle experiments demonstrate that the proposed method has better accuracy and faster alignment speed than the related traditional methods for the low-cost SINS/global positioning system (GPS) integrated navigation system

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Section: Introductionmentioning

confidence: 99%

A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System

Zhang

et al. 2020

Sensors

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“…In the initial alignment, using the output information of the inertial component, the appropriate filtering method is selected for initial alignment. Then, the misalignment angle between the calculated navigation coordinate system and the real navigation coordinate system is estimated to correct the attitude matrix, so that the calculated coordinate system and the real coordinate system are obtained as close as possible [ 6 , 7 ]. Kalman filtering (KF) has a good application for linear system filtering, but Kalman filter (KF) cannot filter nonlinear systems.…”

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

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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.

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“…Due to its advantages of complete autonomy, undisturbed, large-amount of output information, and robust real-time performance, the Inertial Navigation System (INS) has irreplaceable benefits in both military and civilian fields, and the application requirements continue to promote the development of inertial sensors. Since the accuracy of gyroscopes and accelerometers directly affects the accuracy of positioning and attitude output of Strapdown Inertial Navigation Systems (SINSs) [1,2,3,4], the development of inertial navigation technology can approximately rely on the advance of two inertial sensor technologies, especially for the gyroscope.…”

Section: Introductionmentioning

confidence: 99%

A Novel Monitoring Navigation Method for Cold Atom Interference Gyroscope

Zhang

Gao

et al. 2019

Sensors

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The implementation principle of a typical three-pulse cold atom interference gyroscope is introduced in this paper. Based on its configuration and current research status, the problems of cold atom interference gyro are pointed out. The data-rate is insufficient, and it is difficult to achieve high dynamic measurement. Then, based on these two limitations, a novel design of the monitoring navigation system of the cold atom interference gyroscope (CAIG) and an intermediate-grade inertial measurement unit (IMU) was proposed to obtain the long-term position result without GPS signals, such as the Inertial Navigation System (INS) in underwater vehicles. While the CAIG was used as the external gyro, the bias of IMU and the misalignment angle between the CAIG-frame and the IMU-frame are obtained through filtering technique. The simulation test and field test demonstrated the improvements of the long-term positioning accuracy of the INS.

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An Improved Strapdown Inertial Navigation System Initial Alignment Algorithm for Unmanned Vehicles

Cited by 22 publications

References 33 publications

A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System

A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System

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

A Novel Monitoring Navigation Method for Cold Atom Interference Gyroscope

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