MEMS IMU Error Mitigation Using Rotation Modulation Technique

Du, Shuang; Sun, Wei; Gao, Yang

doi:10.3390/s16122017

Cited by 47 publications

(68 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The un‐converged estimates of d X and d Y indicate the low estimability of d E and d N , and so is the accelerometer biases γ X and γ Y . Due to the failed estimation of sensor biases, their modulation leads to the oscillating attitude errors , as shown in the figure. The only error state that can be estimated is γ Z .…”

Section: Estimability Analysis and Experimental Resultsmentioning

confidence: 98%

“…For the low‐cost MEMS IMUs, the gyro biases are usually much more significant than the ones in high‐end IMUs. For instance, the bias instability error for a MEMS IMU can be hundreds degrees per hour . Therefore,

d_{E} > > ω_{ie} cos L ε_{U} + \frac{ω_{ie} sin L}{g} γ_{E}

and

d_{N} > > \frac{ω_{ie} sin L}{g} γ_{N}

, which makes their estimability higher than other unobservable errors.…”

Section: Observability Analysis Of Inertial Systemsmentioning

confidence: 99%

“…where the superscript n represents the navigation frame; δv n = [δv E δv N δv U ] T is the velocity errors in the navigation frame; The analytic estimation algorithm is derived based on the differential equations in (1) for each error state (except for the velocity error states), as shown in equations (2)- (10). According to Rhee et al [51], an observable state is able to be expressed as a linear combination of observable states.…”

Section: Observability Analysis For the Non-rotating Systemmentioning

confidence: 99%

See 2 more Smart Citations

Self‐alignment and calibration of a MEMS IMU: Improving observability and estimability by rotary motions of IMU

2019

Asian Journal of Control

Self Cite

View full text Add to dashboard Cite

The stationary self-alignment and calibration (SSAC) for a low-cost MEMS IMU is quite challenging due to the poor observability of an inertial system under static condition and the significant sensor errors of MEMS inertial sensors. This research proposes to employ IMU rotations to improve the system observability and estimability regarding the SSAC of a low-cost MEMS IMU.IMU rotations about the X, Y, and Z axes are employed in this paper. The analytic estimation algorithm for each error state is derived and the observability of the system with IMU rotation is analyzed. As the observability analysis will not provide clues about how well an error state can be estimated, the estimability analysis is also conducted based on the eigenvalues and eigenvectors from the covariance matrix in the Kalman filter. Tests are conducted with a tri-axial turntable to verify the improvements on system observability and estimability brought by IMU rotations. Of both theoretical analysis and results indicated with proper IMU rotations, only azimuth error still remains unobservable, and the IMU rotation also significantly improves the estimability of all error states, including the unobservable azimuth.

show abstract

Section: Estimability Analysis and Experimental Resultsmentioning

confidence: 98%

d_{E} > > ω_{ie} cos L ε_{U} + \frac{ω_{ie} sin L}{g} γ_{E}

and

d_{N} > > \frac{ω_{ie} sin L}{g} γ_{N}

, which makes their estimability higher than other unobservable errors.…”

Section: Observability Analysis Of Inertial Systemsmentioning

confidence: 99%

Section: Observability Analysis For the Non-rotating Systemmentioning

confidence: 99%

See 1 more Smart Citation

Self‐alignment and calibration of a MEMS IMU: Improving observability and estimability by rotary motions of IMU

2019

Asian Journal of Control

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the numerical simulation, both the GPS data and INS data contain errors. The error in terms of the GPS latitude, longitude and height is 10 m. To make this numerical simulation more challenging, we assume that the INS uses a low-precision MEMS gyroscope [26,27] and that the angle drift ratio is

20^{\circ} /

h. In addition, we assume that the INS has been working for 60 s after the initial alignment.…”

Section: Numerical Simulation Resultsmentioning

confidence: 99%

Angle Measurement of Objects outside the Linear Field of View of a Strapdown Semi-Active Laser Seeker

Zheng

Chen

Zhou

2018

Sensors

View full text Add to dashboard Cite

The accurate angle measurement of objects outside the linear field of view (FOV) is a challenging task for a strapdown semi-active laser seeker and is not yet well resolved. Considering the fact that the strapdown semi-active laser seeker is equipped with GPS and an inertial navigation system (INS) on a missile, in this work, we present an angle measurement method based on the fusion of the seeker’s data and GPS and INS data for a strapdown semi-active laser seeker. When an object is in the nonlinear FOV or outside the FOV, by solving the problems of space consistency and time consistency, the pitch angle and yaw angle of the object can be calculated via the fusion of the last valid angles measured by the seeker and the corresponding GPS and INS data. The numerical simulation results demonstrate the correctness and effectiveness of the proposed method.

show abstract

“…It has also been studied in the low-cost MEMS IMUs in recent years [14,25]. From the frequency domain, there is a more intuitive understanding of the rotation modulation.…”

Section: Principle and Theoretical Modelmentioning

confidence: 99%

A Novel MEMS Gyro North Finder Design Based on the Rotation Modulation Technique

Zhang

Zhou

Song

et al. 2017

Sensors

View full text Add to dashboard Cite

Gyro north finders have been widely used in maneuvering weapon orientation, oil drilling and other areas. This paper proposes a novel Micro-Electro-Mechanical System (MEMS) gyroscope north finder based on the rotation modulation (RM) technique. Two rotation modulation modes (static and dynamic modulation) are applied. Compared to the traditional gyro north finders, only one single MEMS gyroscope and one MEMS accelerometer are needed, reducing the total cost since high-precision gyroscopes and accelerometers are the most expensive components in gyro north finders. To reduce the volume and enhance the reliability, wireless power and wireless data transmission technique are introduced into the rotation modulation system for the first time. To enhance the system robustness, the robust least square method (RLSM) and robust Kalman filter (RKF) are applied in the static and dynamic north finding methods, respectively. Experimental characterization resulted in a static accuracy of 0.66° and a dynamic repeatability accuracy of 1°, respectively, confirming the excellent potential of the novel north finding system. The proposed single gyro and single accelerometer north finding scheme is universal, and can be an important reference to both scientific research and industrial applications.

show abstract

MEMS IMU Error Mitigation Using Rotation Modulation Technique

Cited by 47 publications

References 16 publications

Self‐alignment and calibration of a MEMS IMU: Improving observability and estimability by rotary motions of IMU

Self‐alignment and calibration of a MEMS IMU: Improving observability and estimability by rotary motions of IMU

Angle Measurement of Objects outside the Linear Field of View of a Strapdown Semi-Active Laser Seeker

A Novel MEMS Gyro North Finder Design Based on the Rotation Modulation Technique

Contact Info

Product

Resources

About