Gyroscopic drift compensation by using low cost sensors for improved attitude determination

Ali, Syed Muhammad Dildar; Bhatti, Umar Iqbal; Munawwar, K.; Al‐Saggaf, Ubaid M.; Mansoor, Shoaib; Ali, Jamshaid

doi:10.1016/j.measurement.2017.11.003

Cited by 11 publications

(3 citation statements)

References 18 publications

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“…In equation ( 14), the STFT amplitude of the signal x (t) with demodulation factor at IF (t ′ ) is introduced, as shown in equation (15),…”

Section: Inlstft Algorithm Principlementioning

confidence: 99%

“…The traditional method for measuring the roll angle of HSFC can be divided into two steps. Firstly, by calibrating the calibration parameters and error compensation model of the measuring elements, the output reliability of the measuring elements can be improved in the literature [14][15][16][17][18]. Secondly, * Author to whom any correspondence should be addressed.…”

Section: Introductionmentioning

confidence: 99%

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A novel method for measuring roll angle

Zhang,

Gao,

Wang

et al. 2024

Meas. Sci. Technol.

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The precise measurement of the spin speed of a high-speed autonomous unmanned aerial vehicle (HAS-UAV) is a key element in mastering flight stability, and the measurement of roll angle is the key to determining the accuracy of navigation control systems. We put forward a novel method for measuring roll angle. This method starts from the time-frequency domain analysis (TFDA) of the output signal of the geomagnetic sensor, extracts the time-frequency ridge of the time-frequency matrix (TFM) to obtain the spin speed of the HSA-UAV, and reconstructs the output signal of the geomagnetic sensor. It can calculate the roll angle when the calibration parameters of the geomagnetic sensor are unknown and have good engineering practical value. In addition, we also propose an improved nonlinear short-time Fourier transform (INLSTFT) with high-frequency resolution and a forward penalty dynamic path ridge-extraction method (FPDPRM) with frequency jump suppression to extract instantaneous frequency (IF) in the TFM.

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“…In equation ( 14), the STFT amplitude of the signal x (t) with demodulation factor at IF (t ′ ) is introduced, as shown in equation (15),…”

Section: Inlstft Algorithm Principlementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A novel method for measuring roll angle

Zhang,

Gao,

Wang

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

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“…Filament connections are employed as little as possible in connecting the gyro motors in airtight cases with the outside, wherein the goal is to increase the gyro motor's sensitivity based on the gyroscopes' performance and calculations. Gyro motors are mostly symmetrical to improve the gyroscope precision; however, additional measuring transducers are added that requires an overall redesigning of the structure of the gyro motor case, incurring a huge cost and which does not apply to the gyroscopes [15,16]. There is a need to propose a suitable method and discover an algorithm to evaluate and predict gyro motor states.…”

Section: Introductionmentioning

confidence: 99%

Gyro Motor State Evaluation and Prediction Using the Extended Hidden Markov Model

Dong

Wang²,

Tseng

et al. 2020

Symmetry

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This study extracted the featured vectors in the same way from testing data and substituted these vectors into a trained hidden Markov model to get the log likelihood probability. The log likelihood probability was matched with the time–probability curve from where the gyro motor state evaluation and prediction were realized. A core component of gyroscopes is linked to the reliability of the inertia system to conduct gyro motor state evaluation and prediction. This study features the vectors’ extraction from full life cycle gyro motor data and completes the training model to feature the vectors according to the time sequence and extraction to full life cycle data undergoing hidden Markov model training. This proposed model applies to full life cycle gyro motor data for validation, compared with traditional hidden Markov model predictive methods and health condition-trained data. The results suggest precise evaluation and prediction and provide an important basis for gyro motor repair and replacement strategies.

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