Experience with Allan variance method for MEMS gyroscope performance characterization

Vágner, Martin; Beneš, Petr; Havránek, Zdeněk

doi:10.1109/i2mtc.2012.6229362

Cited by 15 publications

(10 citation statements)

References 3 publications

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“…The coefficient of determination R calculated with the two methods are listed in TABLE V and TABLE VI 6 3.2473 10 u From TABLE V and TABLE VI, the effectiveness of Allan variance segmented circular fitting method also with better accuracy of curve fitting is demonstrated . At the same time, the good repeatability of the proposed method is illustrated.…”

Section: ¦ ¦mentioning

confidence: 97%

“…Commonly used curve fitting methods are least square fitting method and piecewise regression fitting method. Xu et al studied the ring laser gyroscope random error using least square fitting method with Allan standard deviation [5], and Martin et al also used the same method to research the random characteristic of MEMS gyroscope [6]. However, in Xu's study, the random walk coefficient estimation is negative because Least square fitting method is a global fitting method but not optimal.…”

Section: Introductionmentioning

confidence: 99%

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Allan variance segmented circular fitting method for laser gyroscopes random error analysis

Shen

Meng

2014

Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference

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The curve fitting process is the key process of Allan variance algorithm which is an effective method for laser gyroscope random error analysis. The traditional piecewise regression method leads to the fitting curve shift up because the cross-impact among the five kinds of random errors in Allan variance hasn't been taken into consideration especially in the case of long correlation time, which will leads to the random error characteristic of Laser Gyroscope can't been evaluated accurately. This paper proposes an Allan variance segmented circular fitting method, which improves the accuracy of curve fitting and especially reduces the fitting error in long correlation time. The proposed method is applied to 7-hour experimental static data analysis of laser gyroscopes, and the random error coefficients estimated with modified Allan variance algorithm can converge with better stability.

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Section: ¦ ¦mentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Allan variance segmented circular fitting method for laser gyroscopes random error analysis

Shen

Meng

2014

Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference

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“…With the zero-bias output normalized to zero, the data in an angular rate range with good linearity were selected to perform linear fitting, so that a scaling factor was obtained, as shown in Figure 14 . In addition, after the gyroscope worked stably for 30 min, the gyroscope zero-bias output was collected for 1 h and the zero-bias performance was analyzed by the Allan variance [ 25 ]. The zero-bias output under 45° AFD-RM real-time mode-matching is shown in Figure 15 , and the Allan variance curve under the four conditions is shown in Figure 16 .…”

Section: Experimental Analysismentioning

confidence: 99%

MEMS Gyroscope Automatic Real-Time Mode-Matching Method Based on Phase-Shifted 45° Additional Force Demodulation

Zhao

et al. 2018

Sensors

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In order to solve the problem where existing mode-matching methods in microelectromechanical systems (MEMS) vibrating gyroscopes fail to meet real-time and reliability requirements, this paper presents a novel method to accomplish automatic and real-time mode-matching based on phase-shifted 45° additional force demodulation (45° AFD-RM). The phase-shifted 45° additional force signal has the same frequency as the quadrature force signal, but it is phase-shifted by 45° and applied to the sense mode. In addition, two-way phase-shifted 45° demodulations are used at the sense-mode detection output to obtain a phase metric that is independent of the Coriolis force and can reflect the mode-matching state. Then, this phase metric is used as a control variable to adaptively control the tuning voltage, so as to change the sense-mode frequency through the negative stiffness effect and ultimately achieve real-time mode-matching. Simulation and experimental results show that the proposed 45° AFD-RM method can achieve real-time matching. The mode frequency split is controlled within 0.1 Hz, and the gyroscope scale factor, zero-bias instability, and angle random walk are effectively improved.

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“…The Allan variance method is commonly used to describe the noise and long-term stability of MEMS gyroscopes [5,[7][8][9][10]. It indeed gives a synthetic representation of the different noise contributions of the system, that become visible as a function of the observation time intervals.…”

Section: Fig 6: Gyroscope Output Acquired During a Frequency Sweep Fmentioning

confidence: 99%

Vibrations rejection in gyroscopes based on piezoresistive nanogauges

Giacci

Dellea

Longoni

et al. 2015

2015 Transducers - 2015 18th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS)

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The work discusses the effects of vibrations on the performance of rate gyroscopes in terms of Allan variance, and presents the results of vibrations rejection on a Z-axis gyroscope based on piezoresistive nano-gauge sensing elements. In a comparative analysis with a consumer offthe-shelf gyroscope, the proposed device shows a 10-fold better angle random walk (ARW) under no vibrations, and at least a 100-fold better Allan variance, when acquired under vibration amplitude of ±6 g (gravity units), at frequencies up to 10 kHz.

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Experience with Allan variance method for MEMS gyroscope performance characterization

Cited by 15 publications

References 3 publications

Allan variance segmented circular fitting method for laser gyroscopes random error analysis

Allan variance segmented circular fitting method for laser gyroscopes random error analysis

MEMS Gyroscope Automatic Real-Time Mode-Matching Method Based on Phase-Shifted 45° Additional Force Demodulation

Vibrations rejection in gyroscopes based on piezoresistive nanogauges

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