Particle Filter with Novel Nonlinear Error Model for Miniature Gyroscope-Based Measurement While Drilling Navigation

Li, Tao; Yuan, Gannan; Li, Wang

doi:10.3390/s16030371

Cited by 14 publications

(6 citation statements)

References 50 publications

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“…Both EKF and UKF use standard Kalman form for post-updates but differ in the propagation of covariance and premeasurement updates. Apart from these, Particle Filter (PF) has also been a state estimator of choice in UAV applications [9]. Particle filter is based on Monte Carlo simulation and it is also known as optimal recursive Bayesian filtering method.…”

Section: Introductionmentioning

confidence: 99%

Estimation of airship states and model uncertainties using nonlinear estimators

Wasim,

Ali,

Afzal Awan

et al. 2024

Mehran Univ. res. j. eng. technol.

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This Airships are lighter than air vehicles and due to their growing number of applications, they are becoming attractive for the research community. Most of the applications require an airship autonomous flight controller which needs an accurate model and state information. Usually, airship states are affected by noise and states information can be lost in the case of sensor's faults, while airship model is affected by model inaccuracies and model uncertainties. This paper presents the application of nonlinear and Bayesian estimators for estimating the states and model uncertainties of neutrally buoyant airship. It is considered that minimum sensor measurements are available, and data is corrupted with process and measurement noise. A novel lumped model uncertainty estimation approach is formulated where airship model is augmented with six extra state variables capturing the model uncertainty of the airship. The designed estimator estimates the airship model uncertainty along with its states. Nonlinear estimators, Extended Kalman Filter and Unscented Kalman Filter are designed for estimating airship attitude, linear velocities, angular velocities and model uncertainties. While Particle filter is designed for the estimation of airship attitude, linear velocities and angular velocities. Simulations have been performed using nonlinear 6-DOF simulation model of experimental airship for assessing the estimator performances. 1−𝜎 uncertainty bound and error analysis have been performed for the validation. A comparative study of the estimator's performances is also carried out.

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Section: Introductionmentioning

confidence: 99%

Estimation of airship states and model uncertainties using nonlinear estimators

Wasim,

Ali,

Afzal Awan

et al. 2024

Mehran Univ. res. j. eng. technol.

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“…Microelectromechanical Systems (MEMS) gyroscopes have been employed successfully in many sensor applications [ 1 ], including roll-over detection for safe driving in the automotive industry [ 2 , 3 ], rotation rate measurement for high-end gaming in consumer electronics [ 4 ], human motion tracking in Virtual Reality (VR) and Augmented Reality (AR) applications [ 5 ], drilling guidance in oil or gas exploration [ 6 ], north finding [ 7 ], space applications [ 8 ], and navigation applications [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Performance of Quad Mass Gyroscope in the Angular Rate Mode

2021

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In this paper, the characterization and analysis of a silicon micromachined Quad Mass Gyroscope (QMG) in the rate mode of operation are presented. We report on trade-offs between full-scale, linearity, and noise characteristics of QMGs with different Q-factors. Allan Deviation (ADEV) and Power Spectral Density (PSD) analysis methods were used to evaluate the performance results. The devices in this study were instrumented for the rate mode of operation, with the Open-Loop (OL) and Force-to-Rebalance (FRB) configurations of the sense mode. For each method of instrumentation, we presented constraints on selection of control parameters with respect to the Q-factor of the devices. For the high Q-factor device of over 2 million, and uncompensated frequency asymmetry of 60 mHz, we demonstrated bias instability of 0.095∘/hr and Angle Random Walk (ARW) of 0.0107∘/√hr in the OL mode of operation and bias instability of 0.065∘/hr and ARW of 0.0058∘/√hr in the FRB mode of operation. We concluded that in a realistic MEMS gyroscope with imperfections (nearly matched, but non-zero frequency asymmetry), a higher Q-factor would increase the frequency stability of the drive axis resulting in an improved noise performance, but has challenges in implementation of digital control loops.

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“…When the modeling error of the system is described by the density function, Gordon et al developed the particle filter (PF), employing the density function of the error as the objective function [ 13 , 14 ]. The PF can solve general non-Gaussian problems [ 15 ]. However, since PF is based on conditional probability density, the implementation of PF relies on a large number of particle samplings, which makes the calculation complexity high [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Three State Estimation Fusion Methods Based on the Characteristic Function Filtering

Yuan

Wen

Qiu

et al. 2021

Sensors

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There are three state estimation fusion methods for a class of strong nonlinear measurement systems, based on the characteristic function filter, namely the centralized filter, parallel filter, and sequential filter. Under ideal communication conditions, the centralized filter can obtain the best state estimation accuracy, and the parallel filter can simplify centralized calculation complexity and improve feasibility; in addition, the performance of the sequential filter is very close to that of the centralized filter and far better than that of the parallel filter. However, the sequential filter can tolerate non-ideal conditions, such as delay and packet loss, and the first two filters cannot operate normally online for delay and will be invalid for packet loss. The performance of the three designed fusion filters is illustrated by three typical cases, which are all better than that of the most popular Extended Kalman Filter (EKF) performance.

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Particle Filter with Novel Nonlinear Error Model for Miniature Gyroscope-Based Measurement While Drilling Navigation

Cited by 14 publications

References 50 publications

Estimation of airship states and model uncertainties using nonlinear estimators

Estimation of airship states and model uncertainties using nonlinear estimators

Performance of Quad Mass Gyroscope in the Angular Rate Mode

Three State Estimation Fusion Methods Based on the Characteristic Function Filtering

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