The adaptive Gaussian mixtures unscented Kalman filter for attitude determination using light curves

Cabrera, David Vallverdu; Utzmann, Jens; Förstner, Roger

doi:10.1016/j.asr.2022.11.027

Cited by 10 publications

(2 citation statements)

References 20 publications

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“…CPU, GPU, and Field programmable gate array (FPGA) were tested to observe the performance of the 2D Gaussian Filter. Fixed-point arithmetic is used to create a 2D Gaussian Filter in FPGA, proven to speed up processing [87].…”

Section: Image Filteringmentioning

confidence: 99%

Image Processing Systems for Unmanned Aerial Vehicle: State-of-the-art

Mokhtar,

Sultan,

Shahar

et al. 2023

Preprint

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The dependence on Unmanned Aerial Vehicles (UAVs) has dramatically increased in many sectors around the globe. UAVs are in high demand, and their technology is developing quickly due to their sophisticated ability to handle various issues. UAVs are capable of replacing labor-intensive tasks with conducive and safe regulation. Additional tools or sensors need to be added to the UAVs system to ensure the implementation of UAVs able to serve into industrial level. The paper aims to consolidate and present a thorough understanding of the various stages of image processing pipelines deployed in UAV applications, including image acquisition, preprocessing, feature extraction, object detection and tracking, and decision-making processes. Throughout this paper, several aspects were deliberate such as strengths, limitations, and performance metrics of existing approaches, this paper seeks to provide researchers, engineers, and practitioners with valuable insights into the challenges and opportunities of image processing systems for UAVs. Ultimately, the synthesis of this knowledge will contribute to enhancing the effective-ness, autonomy, and applicability of UAVs in diverse fields such as surveillance, agriculture, disaster management, and environmental monitoring.

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Section: Image Filteringmentioning

confidence: 99%

Image Processing Systems for Unmanned Aerial Vehicle: State-of-the-art

Mokhtar,

Sultan,

Shahar

et al. 2023

Preprint

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show abstract

“…Ref. [17] used the GMM to capture the nonlinearities of the light-curve measurement model with the adaptive unscented Kalman filter for the attitude determination. Therefore, the GMMbased extended Kalman filter is applied to predict the non-Gaussian process noise under the blurred star image in this paper.…”

Section: Introductionmentioning

confidence: 99%

GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances

Kim

Zewge

Bang

et al. 2023

Sensors

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Star images from star trackers are usually defocused to capture stars over an exposure time for better centroid measurements. While a satellite is maneuvering, the star point on the screen of the camera is affected by the satellite, which results in the degradation of centroid measurement accuracy. Additionally, this could result in a worse star vector outcome. For geostationary satellites, onboard thrusters are used to maintain or change orbit parameters under orbit disturbances. Since there is misalignment in the thruster and torque is generated by an impulsive shape signal from the torque command, it is difficult to generate target torque; in addition, it also impacts the star image because the impulsive torque creates a sudden change in the angular velocity in the satellite dynamics. This makes the noise of the star image non-Gaussian, which may require introducing a method for dealing with non-Gaussian measurement noise. To meet this goal, in this study, an adaptive extended Kalman filter is implemented to predict measurement vectors with predicted states. The GMM (Gaussian mixture model) is connected in this sequence, giving weighting parameters to each Gaussian density and resulting in the better prediction of measurement vectors. Simulation results show that the GMM-EKF exhibits a better performance than the EKF for attitude estimation, with 30% improvement in performance. Therefore, the GMM-EKF could be a more attractive approach for use with geostationary satellites during station-keeping maneuvers.

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Multi-objective optimization for robust attitude determination of satellite with narrow bound theory

Yang,

Liu

2024

Advances in Space Research

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The adaptive Gaussian mixtures unscented Kalman filter for attitude determination using light curves

Cited by 10 publications

References 20 publications

Image Processing Systems for Unmanned Aerial Vehicle: State-of-the-art

Image Processing Systems for Unmanned Aerial Vehicle: State-of-the-art

GMM-Based Adaptive Extended Kalman Filter Design for Satellite Attitude Estimation under Thruster-Induced Disturbances

Multi-objective optimization for robust attitude determination of satellite with narrow bound theory

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