Improved calibration of IMU biases in analytic coarse alignment for AHRS

Lu, Jiazhen; Lei, Chaohua; Li, Baoguo; Wen, Ting

doi:10.1088/0957-0233/27/7/075105

Cited by 14 publications

(10 citation statements)

References 16 publications

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“…Several literatures have elaborated on the steps taken to handle the occurrences of drifts in its output. Amongst such are as reported in [21], [22], [23] that introduces the application of Attitude and Heading Reference System (AHRS) sensor fusion algorithm which utilizes the Quaternion estimation such as to filter out the aforementioned drift effect [24], [25]. This is done by rotating the body frame vector into inertial frame vector using the rotation matrix defined as:…”

Section: Hardware Descriptionmentioning

confidence: 99%

Linear Differential Driven Wheel Mobile Robot Based on MPU9250 and Optical Encoder

Rustam¹,

Tahir²,

Yassin³

et al. 2022

TEM Journal

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In this paper, the operability of a custombuilt differential drive wheel mobile robot was evaluated using a self-driving algorithm in practical application. Several key parameters need to be realized by the WMR to enable succinct self-driving algorithm evaluations and parameter derivations. The main components of the WMR development were examined in this work, specifically parameter derivations, hardware implementation, steering algorithm and WMR operability. The result obtained indicate that with proper design and careful calibration of sensors, the required driving parameters could be realized. This enables the WMR to potentially serve as data collection platform for future evaluation of self-driving algorithms.

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Section: Hardware Descriptionmentioning

confidence: 99%

Linear Differential Driven Wheel Mobile Robot Based on MPU9250 and Optical Encoder

Rustam¹,

Tahir²,

Yassin³

et al. 2022

TEM Journal

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“…The performance of SINS depends on the accuracy and rapidity of the initial alignment process, which can be divided into coarse alignment and fine alignment [5,6]. Coarse alignment is important since it provides a rapidly alignment result for the fine alignment.…”

Section: Introductionmentioning

confidence: 99%

An Improved Coarse Alignment Algorithm for Odometer-Aided SINS Based on the Optimization Design Method

Zhang

Luo

Fang

et al. 2018

Sensors

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An improved coarse alignment (ICA) algorithm is proposed in this paper with a focus on improving alignment accuracy of odometer-aided strapdown inertial navigation system (SINS) under variable velocity and variable acceleration condition. In the proposed algorithm, the outputs of inertial sensors and odometer in a sampling interval are linearized rather than assumed to be a constant, which improves the accuracy of the vector observations and the precision of coarse alignment. Simulation and field test results illustrate that, under variable velocity and variable acceleration condition, the proposed algorithm can obtain a better alignment performance than conventional coarse alignment method.

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“…SINS is widely used in aviation, marine, land vehicle navigation and positioning because of its advantage of complete autonomy [ 3 , 4 ]. The SINS capability depends on the accuracy and rapidity of initial alignment process which is one of the key technologies in SINS [ 5 , 6 ]. The research about static base initial alignment has been done very well [ 7 , 8 ], however, how to complete the initial alignment of the inertial navigation system on moving base becomes an urgent problem to be solved.…”

Section: Introductionmentioning

confidence: 99%

An Optimization-Based Initial Alignment and Calibration Algorithm of Land-Vehicle SINS In-Motion

Gao

Ren

Chen

et al. 2018

Sensors

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For a running freely land-vehicle strapdown inertial navigation system (SINS), the problems of self-calibration and attitude alignment need to be solved simultaneously. This paper proposes a complete alignment algorithm for the land vehicle navigation using Inertial Measurement Units (IMUs) and an odometer. A self-calibration algorithm is proposed based on the global observability analysis to calibrate the odometer scale factor and IMU misalignment angle, and the initial alignment and calibration method based on optimal algorithm is established to estimate the attitude and other system parameters. This new algorithm has the capability of self-initialization and calibration without any prior attitude and sensor noise information. Computer simulation results show that the performance of the proposed algorithm is superior to the extended Kalman filter (EKF) method during the oscillating attitude motions, and the vehicle test validates its advantages.

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Improved calibration of IMU biases in analytic coarse alignment for AHRS

Cited by 14 publications

References 16 publications

Linear Differential Driven Wheel Mobile Robot Based on MPU9250 and Optical Encoder

Linear Differential Driven Wheel Mobile Robot Based on MPU9250 and Optical Encoder

An Improved Coarse Alignment Algorithm for Odometer-Aided SINS Based on the Optimization Design Method

An Optimization-Based Initial Alignment and Calibration Algorithm of Land-Vehicle SINS In-Motion

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