Article
Automation & Control Systems
Kevin Coleman, He Bai, Clark N. Taylor
Summary: This paper addresses the estimation problem of invariant nonlinear systems subject to dynamic additive disturbances. Two sets of sufficient conditions are identified to maintain the invariant properties of the systems under disturbances. The conditions are applied to a unicycle model and two different Invariant Extended Kalman filters (IEKFs) are designed for estimating the state of the unicycle and disturbances based on position measurements. The benefits of including covariance correction in IEKFs and the performances of the two designs are demonstrated through Monte-Carlo simulations.
Article
Engineering, Aerospace
Xingyu Zhou, Tong Qin, Linzhi Meng
Summary: This paper proposes a polynomial representation-based method for orbit determination of spacecraft with unknown maneuver. The method uses polynomials to represent the unknown maneuver and improves convergence and robustness through polynomial transformations. The Extended Kalman Filter is used to process incoming observation data and compensate for the unknown maneuver. Numerical simulations and Monte Carlo simulations show that the proposed method achieves high accuracy and efficiency, with potential applications for tracking maneuvering space targets.
Article
Engineering, Aerospace
Alejandro Pastor, Guillermo Escribano, Manuel Sanjurjo-Rivo, Diego Escobar
Summary: This paper proposes two novel and operationally feasible methodologies for maneuver detection and estimation in order to address correlation issues in the cataloging of Resident Space Objects. These methods, based on optimal control approach, not only provide maneuver estimation but also tackle the track association problem. Results from optical scenarios demonstrate the capabilities and performance of the proposed methods.
JOURNAL OF THE ASTRONAUTICAL SCIENCES
(2022)
Article
Engineering, Aerospace
Xingyu Zhou, Tong Qin, Mingjiang Ji, Dong Qiao
Summary: This paper proposes a novel framework for efficiently solving continuously maneuvering spacecraft orbit determination (OD) problems. It combines the Long Short-Term Memory (LSTM) neural network and filter algorithms. The LSTM is trained to detect unknown maneuvers and estimate coefficients of a polynomial representation for a more accurate estimation. The framework is successfully applied to solve Low-Earth-orbit and Middle-Earth-orbit OD problems, accurately tracking maneuvering targets and estimating unknown maneuvers. Numerical simulations show the LSTM can be applied to scenarios with common features to the training dataset.
Article
Engineering, Electrical & Electronic
Zeyang Dai, Lei Jing
Summary: The paper introduces a novel low-power consumption orientation estimation method, demonstrating good performance in MARG sensors through a lightweight quaternion-based Extended Kalman Filter (LEKF). Experimental results show that the proposed filter exhibits good stability and efficiency in various application scenarios.
IEEE SENSORS JOURNAL
(2021)
Article
Automation & Control Systems
German Pizarro, Pablo Poblete, Gabriel Droguett, Javier Pereda, Felipe Nunez
Summary: This article presents a technique based on Kalman filtering for estimating the capacitor voltage and converter current of modular multilevel converters (MMCs). The proposed approach operates in both open and closed-loop and eliminates the need for voltage sensors per submodule, reducing complexity and costs.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Li Chen, Shiyu Zhou, Weidong Wang
Summary: This letter presents a beam tracking algorithm that combines spatial information and beam training to improve tracking accuracy. A novel channel evolution model and training beam design are proposed to mitigate estimation errors and improve tracking accuracy. Simulation results validate the performance of the proposed algorithm.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Biomedical
Nishant Gupta, Patrizia Simmen, Daniel Trachsel, Andreas Haeberlin, Kerstin Jost, Thomas Niederhauser
Summary: An auto-regulated adaptive extended Kalman filter (AA-EKF) was developed to accurately extract respiratory activity from neonatal esophageal observations. Results showed that AA-EKF achieved lower respiratory rate error and comparable performance to literature reported values.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Robotics
Matthew Gardner, Yan-Bin Jia
Summary: This article investigates the problem of dynamically estimating the state of an object during its free flight using image frames from two high-speed cameras. The estimation is achieved through constrained Kalman filtering and graph matching-based techniques.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Engineering, Marine
Asra Nusrat, Yaan Li, Chunyan Cheng, Hafeezullah Qazi, Lingji Xu
Summary: This paper discusses the problem of tracking a moving source using noisy bearing measurements from a distant observer, focusing on optimizing observer trajectories to minimize target state estimation errors. A new optimization method for passive tracking is proposed, which proves to be more efficient compared to traditional approaches.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Jiho Song, Seong-Hwan Hyun, Jong-Ho Lee, Jeongsik Choi, Seong-Cheol Kim
Summary: This study develops joint vehicle tracking and RSU selection algorithms to improve the performance of V2I communications. By measuring vehicle tracking performance and maximizing tracking performance, the proposed algorithms outperform conventional signal-to-noise ratio-based tracking systems.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Aerospace
Jingshuai Huang, Zhihui Li, Da Liu, Quanshun Yang, Jianwen Zhu
Summary: An adaptive method for state estimation is proposed in this paper to track a maneuvering hypersonic glide target with model uncertainties. The method models unknown aerodynamic accelerations as the Singer model with a small maneuver frequency. When the real motion mode deviates from the default model, the maneuver frequency is adaptively enlarged to reduce the model error. The proposed method shows stronger robustness and higher estimation accuracy than conventional methods in the presence of model uncertainties, with significantly less computation burden than the multiple-model method.
AEROSPACE SCIENCE AND TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Andressa Apio, Jorge O. Trierweiler, Marcelo Farenzena
Summary: Two new formulations for the extended Kalman filter are proposed in this work, and their computational costs and performance are compared with other existing techniques. The MW-REKF technique showed the smoothest and most robust behavior among all methodologies, while having a relatively lower computational cost compared to other methods like CEKF and MHE.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Dongliang Jing, Yongzhao Li, Andrew W. Eckford
Summary: This paper investigates a mobile molecular communication system in a realistic blood-vessel-type flow regime, where two mobile nanomachines, a transmitter and a receiver, move with a positive drift velocity and Brownian motion. To estimate the distance between the transmitter and receiver considering the nonlinear movement of nanomachines, an extended Kalman filter is used. Power control is employed to keep the number of received molecules stable by adjusting the number of transmitted molecules based on the distance and residual molecules in the channel. The optimal detection threshold is obtained by minimizing the error probability, and simulation results validate the performance of the scheme.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Engineering, Aerospace
Lorenzo Porcelli, Alejandro Pastor, Alejandro Cano, Guillermo Escribano, Manuel Sanjurjo-Rivo, Diego Escobar, Pierluigi Di Lizia
Summary: This paper introduces a novel approach to tackle the problem of maneuver detection and estimation of Resident Space Objects (RSOs) in the space environment. The proposed methodology aims to increase the flexibility of real-time cataloging systems and has been validated through testing in a simulated maintenance chain.
