Ballistic Roll Estimation using EKF Frequency Tracking and Adaptive Noise Cancellation

Allik, Bethany; Ilg, Mark; Zurakowski, Ryan

doi:10.1109/taes.2013.6621835

Cited by 24 publications

(10 citation statements)

References 11 publications

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“…The main diagonal vectorŝ( = , , ) and̂( = , , , , , ) are estimated in initial calibration process. The compensated data 1 for initial calibration process are calculated in (7).…”

Section: Compounded Calibration Of Low Cost Micro Imumentioning

confidence: 99%

“…According to the principle of accelerometer measuring gravity, the accelerometer could be used for calculating the pitch and roll angles precisely in stationary or low dynamic condition [6]. Magnetometer sensor, which is manufactured by making use of alloy resistance having sensitive response to direction magnetic field, could be used for calculating the yaw angle in AHRS or estimating the ballistic roll in the projectile [7,8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Compounded Calibration Based on FNN and Attitude Estimation Method Using Intelligent Filtering for Low Cost MEMS Sensor Application

Lei

Guan

2019

Mathematical Problems in Engineering

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Micro electro mechanical system (MEMS) inertial sensors have advantages, including small size and low power consumption. The performances of Micro Inertial measurement unit (IMU), which is composed of MEMS inertial sensors, degrade, and error, will become larger in high dynamic environment. In order to solve the problem, a novel combined calibration method for compensating the deterministic error of MEMS sensors is proposed. Considering the rotation of different sensitive axes in high dynamic and low dynamic environment, the compounded calibration based on fuzzy neural network (FNN) is adopted to identify the coupling coefficients to eliminate the adverse coupling effects between different rotation axes. Furthermore, the self-developed Micro IMU and magnetometer are applied in attitude estimation system. Considering the large attitude error occurred in most cases, the approach utilizing the estimation of error quaternion vector could avoid the calculation error due to inaccurate modeling in the skew symmetric matrix that comprises attitude error vector components. The intelligent Kalman filter (IKF) based on complexity state equation of error quaternion is designed to improve the performance by adjusting the parameters of filter on line. The experimental results show that the proposed approach could have a higher level of stability and accuracy in comparison to other attitude estimation algorithms.

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“…The main diagonal vectorŝ( = , , ) and̂( = , , , , , ) are estimated in initial calibration process. The compensated data 1 for initial calibration process are calculated in (7).…”

Section: Compounded Calibration Of Low Cost Micro Imumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Compounded Calibration Based on FNN and Attitude Estimation Method Using Intelligent Filtering for Low Cost MEMS Sensor Application

Lei

Guan

2019

Mathematical Problems in Engineering

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“…Roll estimation is necessary to resolve the target error components in the fixed-plane (i.e., nonrolling) coordinate system. Numerous authors have studied roll angle estimation for smart weapons based on magnetometer [21][22][23] or infrared sensor measurements [24,25]. For this study, it is assumed that some source of roll feedback is available, and thus the target error components can be transformed into the fixed-plane frame according to…”

Section: Detector Modelingmentioning

confidence: 99%

Flight Control of a Small-Diameter Spin-Stabilized Projectile Using Imager Feedback

Fresconi

Rogers

2015

Journal of Guidance, Control, and Dynamics

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Small-diameter gun-launched projectiles pose a challenging platform on which to implement closed-loop guidance and control. This paper presents a novel imager-based guidance and control algorithm for small-diameter spinstabilized projectiles. The control law is specifically formulated to rely on feedback only from a strapdown detector and roll angle sensors. Following introduction of the projectile nonlinear dynamic model, an integrated guidance and control algorithm is presented in which control commands are computed directly from detector feedback using a gainscheduled proportional control. Time-varying controller gains are derived through a surrogate modeling approach, and controller performance is further enhanced through use of an observer that filters unwanted angular motion components from detector feedback. Example closed-loop flight simulations demonstrate performance of the proposed control system, and Monte Carlo analysis shows a factor of 2 accuracy improvement for the closed-loop system over ballistic flight. Results indicate that delivery system improvements are achievable in small, gyroscopically stabilized projectiles containing low-cost guidance elements using the proposed integrated guidance and control approach.

show abstract

“…Roll estimation is necessary to resolve the target error components in the fixed-plane (i.e., nonrolling) coordinate system. Numerous authors have studied roll angle estimation for smart weapons based on magnetometer [21][22][23] or infrared sensor measurements [24][25]. For this study, it is assumed that some source of roll feedback is available, and thus the target error components can be transformed into the fixed-plane frame according to,…”

Section: Detector Modelingmentioning

confidence: 99%

Guidance and Control of a Man Portable Precision Munition Concept

Fresconi

Rogers

2015

AIAA Atmospheric Flight Mechanics Conference

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Small diameter, gun-launched projectiles pose a challenging platform on which to implement closed-loop guidance and control. This paper presents a novel imager-based guidance and control algorithm for small diameter, spin-stabilized projectiles. The control law is specifically formulated to rely on feedback only from a strap-down detector and roll angle sensors.Following introduction of the projectile nonlinear dynamic model, an integrated guidance and control algorithm is presented in which control commands are computed directly from detector feedback using a gain-scheduled proportional control. Time-varying controller gains are derived through a surrogate modeling approach, and controller performance is further enhanced through use of an observer that filters unwanted angular motion components from detector feedback.Example closed-loop flight simulations demonstrate performance of the proposed control system, and Monte Carlo analysis shows a factor of two accuracy improvement for the closed-loop system over ballistic flight. Results indicate that delivery system improvements are achievable in small, gyroscopically-stabilized projectiles containing low cost guidance elements using the proposed integrated guidance and control approach. mass [kg]This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. AIAA SciTech I moment of inertia matrix [kg-m 2 ] , ⁄ total velocity of projectile with respect to the wind, velocity of center of gravity with respect to inertial frame in body-fixed coordinates [m/s] atmospheric density [kg/m 3 ] dynamic pressure at projectile mass center [N/m 2 ] q M dynamic pressure at wing actuator center of pressure [N/m 2 ] Mach number √ pitch angle-of-attack [rad] √ yaw angle-of-attack [rad] √ √ total angle-of-attack [rad] aerodynamic roll angle [rad] , , aerodynamic forces acting on projectile [N] , , gravity forces acting on projectile [N] , , aerodynamic moments acting on projectile [Nm] , , total, zero-yaw, and yaw-dependent axial force coefficient , , , total, trim, linear and nonlinear normal force coefficient roll damping moment coefficient , , , total, trim, linear and nonlinear pitching moment coefficient pitch damping moment coefficient Magnus force coefficient Magnus moment coefficient , , , Wind actuator aerodynamic coefficients , axial center-of-pressure, radial CP [m] → vector from center-of-gravity to i th moveable Downloaded by NANYANG TECHNICAL UNIVERSITY on October 1, 2015 | http://arc.aiaa.org | aerodynamic surface center-of-pressure [m] , , , Φ, Earth-fixed commanded, Earth-fixed control, body-fixed control, relative, and stowed roll angles [rad] 1 0 0 0 Φ Φ 0 Φ Φ transformation matrix from body-fixed to moveable aerodynamic surface coordinates transformation matrix from body-fixed to Earthfixed coordinates transformation matrix from body-fixed to wing surface coordinates transformation matrix from velocity vector coordinates to Earth-fixed coordinates , , inertial position [m] , , inertial translational veloc...

show abstract

Ballistic Roll Estimation using EKF Frequency Tracking and Adaptive Noise Cancellation

Cited by 24 publications

References 11 publications

Compounded Calibration Based on FNN and Attitude Estimation Method Using Intelligent Filtering for Low Cost MEMS Sensor Application

Compounded Calibration Based on FNN and Attitude Estimation Method Using Intelligent Filtering for Low Cost MEMS Sensor Application

Flight Control of a Small-Diameter Spin-Stabilized Projectile Using Imager Feedback

Guidance and Control of a Man Portable Precision Munition Concept

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