Analysis of the Improvement in Accuracy Using Multiple Gyros

2015 ◽  
Author(s):  
Shuyang Li ◽  
Yizhou Wang ◽  
Masayoshi Tomizuka
Keyword(s):  
Kalman Filter ◽  
Angular Velocity ◽  
Numerical Simulations ◽  
Unbiased Estimator ◽  
Rate Estimate ◽  
Electromechanical Systems ◽  
Velocity Signal ◽  
Bias Drift ◽  
Velocity Estimate ◽  
Mems Gyroscopes

The possibility to improve the accuracy of angular velocity estimate by optimally combining multiple individual micro electromechanical systems (MEMS) gyroscopes is analyzed in this paper. Kalman filter (KF) is used to fuse the numerous measurements into a single improved rate estimate. Based on the virtual gyro idea, a revised approach can give an unbiased estimator regardless of the true angular velocity signal. Numerical simulations are performed to demonstrate the desirable performance, reducing the bias drift and noise.

Simulation of athlete gait recognition based on spectral features and machine learning

2020 ◽  
pp. 1-12
Author(s):  
Linuo Wang
Keyword(s):  
Machine Learning ◽  
Angular Velocity ◽  
Gait Recognition ◽  
Spectral Feature ◽  
Velocity Signal ◽  
Comparison Results ◽  
Computer Vision Technology ◽  
Feature Technology ◽  
Leg Movement ◽  
Recognition Efficiency

The current technology related to athlete gait recognition has shortcomings such as complicated equipment and high cost, and there are also certain problems in recognition accuracy and recognition efficiency. In order to improve the efficiency of athletes’ gait recognition, this paper studies the different recognition technologies of athletes based on machine learning and spectral feature technology and applies computer vision technology to sports. Moreover, according to the calf angular velocity signal, the occurrence of leg movement is detected in real time, and the gait cycle is accurately divided to reduce the influence of the signal unrelated to the behavior on the recognition process. In addition, this study proposes a gait behavior recognition method based on event-driven strategies. This method uses a gyroscope as the main sensor and uses a wearable sensor node to collect the angular velocity signals of the legs and waist. In addition, this study analyzes the performance of the algorithm proposed by this paper through experimental research. The comparison results show that the method proposed by this paper has improved the number of recognition action types and accuracy and has certain advantages from the perspective of computation and scalability.

Stability of Ring-Type MEMS Gyroscopes Subjected to Stochastic Angular Speed Fluctuation

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Samuel F. Asokanthan ◽  
Soroush Arghavan ◽  
Mohamed Bognash
Keyword(s):  
Angular Velocity ◽  
Degrees Of Freedom ◽  
Microelectromechanical Systems ◽  
Damping Ratio ◽  
Operating Conditions ◽  
System Stability ◽  
System Response ◽  
Ring Type ◽  
Mems Gyroscopes ◽  
The Stability

Effect of stochastic fluctuations in angular velocity on the stability of two degrees-of-freedom ring-type microelectromechanical systems (MEMS) gyroscopes is investigated. The governing stochastic differential equations (SDEs) are discretized using the higher-order Milstein scheme in order to numerically predict the system response assuming the fluctuations to be white noise. Simulations via Euler scheme as well as a measure of largest Lyapunov exponents (LLEs) are employed for validation purposes due to lack of similar analytical or experimental data. The response of the gyroscope under different noise fluctuation magnitudes has been computed to ascertain the stability behavior of the system. External noise that affect the gyroscope dynamic behavior typically results from environment factors and the nature of the system operation can be exerted on the system at any frequency range depending on the source. Hence, a parametric study is performed to assess the noise intensity stability threshold for a number of damping ratio values. The stability investigation predicts the form of threshold fluctuation intensity dependence on damping ratio. Under typical gyroscope operating conditions, nominal input angular velocity magnitude and mass mismatch appear to have minimal influence on system stability.

scholarly journals Model-Based Analysis of Yo-yo Throwing Motion on Single-Link Manipulator

2020 ◽  
Vol 32 (4) ◽  
pp. 822-831
Author(s):  
Hokuto Miyakawa ◽  
◽  
Takuma Nemoto ◽  
Masami Iwase
Keyword(s):  
Angular Velocity ◽  
Numerical Simulations ◽  
Integrated Model ◽  
Analysis Method ◽  
Model Based ◽  
Single Link ◽  
Throwing Motion ◽  
Model Based Analysis

This paper presents a method for analyzing the throwing motion of a yo-yo based on an integrated model of a yo-yo and a manipulator. Our previous integrated model was developed by constraining a model of a white painted commercial yo-yo and a model of a plain single-link manipulator with certain constraining conditions placed between two models. However, for the yo-yo model, the collisions between the string and the axle of the yo-yo were not taken into account. To avoid this problem, we estimate some of the yo-yo parameters from the experiments, thereby preserving the functionality of the model. By applying the new integrated model with the identified parameters, we analyze the throwing motion of the yo-yo through numerical simulations. The results of which show the ranges of the release angle and the angular velocity of the joint of the manipulator during a successful throw. In conclusion, the proposed analysis method is effective in analyzing the throwing motion of a manipulator.

scholarly journals Angular velocity fusion of the microelectromechanical system inertial measurement unit array based on extended Kalman filter with correlated system noises

2020 ◽  
pp. 002029402091770
Author(s):  
Li Xing ◽  
Xiaowei Tu ◽  
Weixing Qian ◽  
Yang Jin ◽  
Pei Qi
Keyword(s):  
Kalman Filter ◽  
Angular Velocity ◽  
Extended Kalman Filter ◽  
Inertial Measurement Unit ◽  
Angular Rate ◽  
The State ◽  
Measurement Unit ◽  
Fusion Method ◽  
Microelectromechanical System ◽  
Inertial Measurement

The paper proposes an angular velocity fusion method of the microelectromechanical system inertial measurement unit array based on the extended Kalman filter with correlated system noises. In the proposed method, an adaptive model of the angular velocity is built according to the motion characteristics of the vehicles and it is regarded as the state equation to estimate the angular velocity. The signal model of gyroscopes and accelerometers in the microelectromechanical system inertial measurement unit array is used as the measurement equation to fuse and estimate the angular velocity. Due to the correlation of the state and measurement noises in the presented fusion model, the traditional extended Kalman filter equations are optimized, so as to accurately and reliably estimate the angular velocity. By simulating angular rates in different motion modes, such as constant and change-in-time angular rates, it is verified that the proposed method can reliably estimate angular rates, even when the angular rate has been out of the microelectromechanical system gyroscope measurement range. And results show that, compared with the traditional angular rate fusion method of microelectromechanical system inertial measurement unit array, it can estimate angular rates more accurately. Moreover, in the kinematic vehicle experiments, the performance advantage of the proposed method is also verified and the angular rate estimation accuracy can be increased by about 1.5 times compared to the traditional method.

scholarly journals A Novel Method for Estimating Knee Angle Using Two Leg-Mounted Gyroscopes for Continuous Monitoring with Mobile Health Devices

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2759 ◽  
Author(s):  
Eric Allseits ◽  
Kyoung Kim ◽  
Christopher Bennett ◽  
Robert Gailey ◽  
Ignacio Gaunaurd ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Knee Joint ◽  
Convergent Validity ◽  
Continuous Monitoring ◽  
Joint Angle ◽  
Characteristic Point ◽  
Accelerometer Data ◽  
Knee Angle ◽  
Velocity Signal ◽  
Knee Joint Angle

Tele-rehabilitation of patients with gait abnormalities could benefit from continuous monitoring of knee joint angle in the home and community. Continuous monitoring with mobile devices can be restricted by the number of body-worn sensors, signal bandwidth, and the complexity of operating algorithms. Therefore, this paper proposes a novel algorithm for estimating knee joint angle using lower limb angular velocity, obtained with only two leg-mounted gyroscopes. This gyroscope only (GO) algorithm calculates knee angle by integrating gyroscope-derived knee angular velocity signal, and thus avoids reliance on noisy accelerometer data. To eliminate drift in gyroscope data, a zero-angle update derived from a characteristic point in the knee angular velocity is applied to every stride. The concurrent validity and construct convergent validity of the GO algorithm was determined with two existing IMU-based algorithms, complementary and Kalman filters, and an optical motion capture system, respectively. Bland–Altman analysis indicated a high-level of agreement between the GO algorithm and other measures of knee angle.

scholarly journals Improved Pedestrian Positioning with Inertial Sensor Based on Adaptive Gradient Descent and Double-Constrained Extended Kalman Filter

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Miaoxin Ji ◽  
Jinhao Liu ◽  
Xiangbo Xu ◽  
Yuyang Guo ◽  
Zhenchun Lu
Keyword(s):  
Kalman Filter ◽  
Angular Velocity ◽  
Extended Kalman Filter ◽  
Gradient Descent ◽  
Measurement Noise ◽  
Measurement Unit ◽  
Alignment Algorithm ◽  
Extended Kalman Filtering ◽  
Attitude Error ◽  
Gradient Descent Algorithm

The Foot-mounted Inertial Pedestrian-Positioning System (FIPPS) based on the Micro-Inertial Measurement Unit (MIMU) is a good choice for the forest fire fighters when the Global Navigation Satellite System is unavailable. Zero Velocity Update (ZUPT) provides a solution for reducing cumulative positioning errors caused by the integral calculation of the inertial navigation. However, the performance of ZUPT is highly affected by the low accuracy and high noise of the MIMU. The accuracy of conventional ZUPT for attitude alignment is reduced by the zero offset of acceleration and the drift of a gyroscope during the standing phase. An initial alignment algorithm based on Adaptive Gradient Descent Algorithm (AGDA) is proposed. In the stepping phase, the extended Kalman filter (EKF) is often used to correct attitude and position in track estimation. However, the measurement noise of the EKF is influenced by the high-frequency acceleration and angular velocity. Thus, the accuracy of the attitude and position will decrease. A double-constrained extended Kalman filtering (DEKF) is proposed. An adaptive parameter positively correlated with the acceleration and angular velocity is set, and the measurement noise in the DEKF is adaptively adjusted. The performance of the proposed method is verified by implementing the pedestrian test trajectory using MPU-9150 MIMU manufactured by InvenSense. The results show that the attitude error of the AGDA is 33.82% less than that of the conventional GDA. The attitude error of DEKF is 21.70% less than that of the conventional EKF. The experimental results verify the effectiveness and applicability of the proposed method.

Comparison of Angular Velocity Estimation Performance of GR-INS to Order of Kalman Filter

2018 ◽  
Vol 24 (10) ◽  
pp. 979-986
Author(s):  
Junhak Lee ◽  
Heyone Kim ◽  
Sang Heon Oh ◽  
Jae Chul Do ◽  
Chang Woo Nam ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Angular Velocity ◽  
Velocity Estimation ◽  
Estimation Performance ◽  
Angular Velocity Estimation

The Application of Parametric Excitation in MEMS Gyroscopes

2013 ◽  
Author(s):  
Barry J. Gallacher ◽  
Zhongxu Hu ◽  
Kiran Mysore Harish ◽  
Stephen Bowles ◽  
Harry Grigg
Keyword(s):  
Angular Velocity ◽  
Parametric Excitation ◽  
Signal To Noise Ratio ◽  
Parametric Amplification ◽  
Signal To Noise ◽  
Primary Mode ◽  
Harmonic Forcing ◽  
Mode Of Operation ◽  
Mems Gyroscopes ◽  
Secondary Mode

Parametric excitation, via electrostatic stiffness modulation, can be exploited in resonant MEMS gyroscopes. In the case of the Rate gyroscope, which is by far the most common type of MEMS gyro, parametric excitation may be used to amplify either the primary mode of the gyro or the response to the angular rate. Both approaches will be discussed. In the more complex mode of operation, known as “Rate Integrating” the output of the gyro is angle directly as opposed to angular velocity in the case of Rate gyro. In this rate integrating mode of operation parametric excitation does offer an effective energy control used to initiate, sustain the vibration and minimise damping perturbations. Parametric amplification of the primary mode of the rate gyroscope is presented and supported with experimental results. In this implementation parametric excitation is combined with external harmonic forcing of the primary mode in order to reduce electrical feedthrough of the driving signal to the sense electrodes. A practical parametric excitation scheme implemented using Digital Signal Processing has been developed to enable either amplification of the primary mode of the gyroscope or amplification of the response to the applied angular velocity. Parametric amplification of the primary mode of the gyroscope is achieved by frequency tracking and regulation of the amplitudes of the harmonic forcing and parametric excitation to maintain a desired parametric gain by closed loop PID control. Stable parametric amplification of the primary mode by a factor of 20 is demonstrated experimentally. This has important benefits regarding the minimisation of electrical feedthrough of the drive signal to the sense electrodes of the secondary mode. By taking advantage of the phase dependence of parametric amplification and the orthogonality of the Coriolis force and quadrature forcing, the response to the applied angular velocity may be parametrically amplified by applying excitation of a particular phase directly to the sensing mode. The major advantage of parametric amplification applied to MEMs gyroscopes is that it can mechanically amplify the Coriolis response before being picked off electrically. This is particularly advantageous for sensors where electronic noise is the major noise contributor. In this case parametric amplification can significantly improve the signal to noise ratio of the secondary mode by an amount approximately equal to the parametric amplification. Preliminary rate table tests performed in open loop demonstrate a magnification of the signal to noise ratio of the secondary mode by a factor of 9.5.

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