Article
Automation & Control Systems
Zhijin Chen, Branko Ristic, Jeremie Houssineau, Du Yong Kim
Summary: This paper focuses on bearings-only tracking using passive sensors, adopting possibility functions to represent uncertainties instead of probability distributions. It explores the design of reward functions based on possibility theory and shows that the proposed framework outperforms the Bayesian probabilistic framework in the presence of model mismatch.
Article
Automation & Control Systems
Haonan Jiang, Yuanli Cai, Zhenhua Yu
Summary: This work explores the observability problem in bearings-only tracking (BOT) and proposes a series of metrics based on the condition number to quantitatively describe the observability degree and evaluate the tracking performance. The metrics can also be applied to sensor trajectory optimization and sensor configuration to enhance the tracking performance.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Haoran Hu, Shuxin Chen, Hao Wu, Renke He
Summary: This paper investigates robust methods for continuous-discrete filtering systems in bearings-only tracking. By establishing a continuous-discrete target tracking model and evaluating the performance of proposed robust algorithms, the paper fills the research gap in this field. Simulation results show that the algorithms have good adaptability to different measurement environments.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
S. Koteswara Rao
Summary: A research work was conducted to recommend maneuvers online based on understanding the scenario, as an alternative to the commonly used S-maneuver in the maritime environment. Object motion parameters were estimated using one selected acceptance criteria and evaluated against multiple scenarios.
IETE JOURNAL OF RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Haonan Jiang, Xiaotong Wang, Yifan Deng, Yingjie Zhang
Summary: This article discusses the problem of tracking multiple sensors' bearings-only tracking (BOT) under measurement uncertainty. To effectively track the target while reducing communication times and maintaining estimation accuracy, a novel distributed bias-compensated pseudolinear information filter with event-triggered communication mechanism and hybrid-consensus-based fusion strategy is proposed. Each sensor transmits its local information to neighboring sensors only when it is considered valuable for fusion based on normalized innovation. The stability of the proposed algorithm is proven, and simulation results demonstrate its effectiveness and robustness.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Jarrad Courts, Adrian Wills, Thomas Schon
Summary: This paper addresses the state estimation problem in nonlinear state-space models by developing an assumed Gaussian solution based on variational inference. By formulating the problem as an optimization problem and solving it using first- and second-order derivatives, the approach is applicable to both Gaussian and non-Gaussian probabilistic models in nonlinear systems. The method outperforms alternative assumed Gaussian approaches in challenging scenarios like target tracking using von Mises-Fisher distribution.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Environmental Sciences
Zihao Huang, Shijin Chen, Chengpeng Hao, Danilo Orlando
Summary: In bearings-only target tracking, the pseudo-linear Kalman filter (PLKF) is popular for stability and low computational burden, but suffers from bias problems due to correlated measurement vector and noise; an unbiased PLKF algorithm (UB-PLKF) is proposed to address this issue, along with a velocity-constrained version (VC-PLKF) to further improve performance, outperforming other methods in both non-manoeuvring and manoeuvring scenarios according to simulations.
Article
Engineering, Electrical & Electronic
S. Koteswara Rao, M. Kavitha Lakshmi, Kausar Jahan, G. Naga Divya, B. Omkar Lakshmi Jagan
Summary: This research focuses on the evolution of acceptance criterion for target motion parameter estimation in actual scenarios. Mathematical modeling is used along with an unscented Kalman filter to estimate the parameters. The acceptance criterion is derived based on the covariance matrix and standard deviation of errors in the estimated parameters.
IETE JOURNAL OF RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Shan Zhong, Bei Peng, Lingqiang Ouyang, Xinyue Yang, Hongyu Zhang, Gang Wang
Summary: This article presents a framework for a pseudolinear Kalman filter (PLKF) based on the maximum correntropy criterion for the bearings-only target tracking problem in non-Gaussian environments. The proposed estimation method, including several algorithms, outperforms the traditional Kalman filter in non-Gaussian noise environments.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Aerospace
Yingjie Zhang, Jian Lan, Mahendra Mallick, X. Rong Li
Summary: The article introduces a new filtering method based on uncorrelated conversion, which can effectively perform nonlinear filtering. The constructed pseudomeasurement is uncorrelated with the original measurement, improving the efficiency of information utilization. Simulation results demonstrate that this method has better estimation accuracy compared to traditional particle filters at nearly the same computational cost.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2021)
Article
Automation & Control Systems
Shuai Zhang, Zi-Yun Wang, Yan Wang, Zhi-Cheng Ji
Summary: This study proposes a zonotopic set-valued observer based state estimation algorithm for nonlinear models with unknown but bounded noises. The algorithm wraps the unknown noise term in a zonotope during each recursive step, and uses second-order polynomial Stirling interpolation and a method that combines sequence updating and tightening strips to improve the estimation accuracy and reduce error accumulation.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2022)
Article
Chemistry, Analytical
Hadar Shalev, Itzik Klein
Summary: This paper introduces a deep-learning based framework for bearings-only target tracking, demonstrating improved accuracy compared to the iterative least squares algorithm. The framework is applicable for any bearings-only target tracking task and showcases the advantages of a data-driven approach.
Article
Automation & Control Systems
Gennady Yurievich Kulikov, Maria Vyacheslavovna Kulikova
Summary: This article addresses the issue of square-rooting in continuous-discrete Gaussian filters and proposes two MATLAB-based solutions. The main problem is the potential negativity of weights, which prevents the application of orthogonal square-rooting schemes. By using the J$$ J $$-orthogonal square-rooting technique, new algorithms are developed for various continuous-discrete Gaussian filters.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Engineering, Electrical & Electronic
Sanjeev Arulampalam, Branko Ristic, Thia Kirubarajan
Summary: The paper explores the impact of neglecting signal propagation delay on the performance of a maximum likelihood estimator in bearings-only fusion with heterogeneous sensors. The analysis and simulation results indicate that neglecting propagation delay leads to performance degradation, and a bias-compensated MLE approach is proposed to improve performance towards the lower bound.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Engineering, Electrical & Electronic
Bin Zhang, Yung C. Shin
Summary: An adaptive Gaussian mixture filter is proposed in this paper to accurately estimate the state distribution of highly nonlinear dynamic systems by refining Gaussian mixture models based on the local severity of nonlinearity.
Article
Economics
Arindam Kundu, Sumit Kumar, Nutan Kumar Tomar
COMPUTATIONAL ECONOMICS
(2019)
Article
Automation & Control Systems
Rahul Radhakrishnan, Shovan Bhaumik, Nutan Kumar Tomar
ASIAN JOURNAL OF CONTROL
(2019)
Article
Engineering, Aerospace
Abhinoy Kumar Singh, Sumit Kumar, Nagendra Kumar, Rahul Radhakrishnan
Summary: This article presents a modified Bayesian approximation filtering method to deal with measurements altered due to cyber-attacks. By introducing modified measurement models and redesigning the traditional nonlinear Gaussian filtering method, the proposed method is able to effectively handle the presence of false data and improve estimation accuracy.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Chemistry, Analytical
Asfia Urooj, Aastha Dak, Branko Ristic, Rahul Radhakrishnan
Summary: This paper proposes a maximum correntropy criterion (MCC) based framework for tackling the angles-only target tracking (AoT) problem in a non Gaussian environment. Three new estimation algorithms are developed and their performance is evaluated, showing improved accuracy compared to conventional methods in the presence of non Gaussian measurement noise.
Article
Automation & Control Systems
Juhi Jaiswal, Thomas Berger, Nutan Kumar Tomar
Summary: This paper presents a novel characterization of partial impulse observability in linear descriptor systems, providing a simple rank condition involving the system coefficient matrices and Wong sequences.
SYSTEMS & CONTROL LETTERS
(2022)
Article
Automation & Control Systems
Jaffar Ali Lone, Nutan Kumar Tomar, Shovan Bhaumik
Summary: This letter investigates cell-level state of charge (SOC) estimation in a parallel connected lithium-ion (Li-ion) battery pack under a reduced sensing scenario. The dynamics of parallel connected battery packs require solving differential algebraic equations (DAEs). A novel functional observer, designed under milder conditions, is proposed for estimating individual cell SOCs and local currents in a battery pack. The simulation results demonstrate the fast convergence and effectiveness of the proposed approach in estimating the SOC of two cylindrical Li-ion battery cells.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Shreya Das, Shovan Bhaumik
Summary: This letter proposes an ownship maneuver to improve the accuracy of state estimation when tracking a target with bearing only measurements. By maximizing the Fisher information matrix, the recommended maneuver leads to a reduced Cramer-Rao lower bound (CRLB) and improved estimator accuracy. It also considers certain heuristics to maintain safety and prevent the target from entering blind zones.
IEEE SENSORS LETTERS
(2023)
Article
Computer Science, Information Systems
Pabitra Kumar Tunga, Juhi Jaiswal, Nutan Kumar Tomar
Summary: This paper addresses the problem of estimating a functional vector for a class of linear time-invariant descriptor systems with unknown inputs. The proposed observer has an order less than or equal to the dimension of the functional vector to be estimated. The existence of functional ODE observers is proved under simple rank conditions on the system coefficient matrices. Numerical examples are included to illustrate the proposed theory and algorithm.
Proceedings Paper
Engineering, Marine
Shreya Das, Kundan Kumar, Rahul Radhakrishnan, Shovan Bhaumik
Summary: In this paper, the shifted Rayleigh filter (SRF) is modified to improve its tracking performance in bearing-only measurement. The proposed range parameterized shifted Rayleigh filter (RP-SRF) is applied to underwater target motion analysis (TMA) and compared with other filters. The simulation results show that RP-SRF outperforms its competitors in terms of accuracy for underwater bearing-only tracking.
Proceedings Paper
Automation & Control Systems
Aastha Dak, Rahul Radhakrishnan
Summary: This paper investigates the interception of high velocity spiralling targets and proposes a method based on nonlinear state estimators for generating interceptor missile accelerations. The performance of different estimators in combination with the PNG law is evaluated through comparisons.
Proceedings Paper
Automation & Control Systems
Rahul Radhakrishnan, Urooj Asfia, Shambhunath Sharma
Summary: In this study, Gaussian sum state estimation algorithms are applied to the problem of three-dimensional angles-only target tracking, and compared with conventional algorithms. The results show that Gaussian sum filters achieve higher estimation accuracy.
Article
Automation & Control Systems
Juhi Jaiswal, Nutan Kumar Tomar
Summary: This letter studies the design of functional observers for linear time-invariant descriptor systems which are not necessarily square and regular. A novel characterization for the existence of functional observers is presented using a set of simplified rank conditions on the system coefficient matrices. The proposed conditions are less restrictive than the existing ones. The derivation is purely algebraic and an observer-based controller is designed as an illustration.
IEEE CONTROL SYSTEMS LETTERS
(2022)
Article
Computer Science, Information Systems
Kundan Kumar, Shovan Bhaumik, Paresh Date
Summary: This paper introduces a new extended Kalman filter that linearizes nonlinear functions and approximates first-order polynomial coefficients for computing states' mean and covariance. Compared to traditional extended Kalman filters, the proposed filter achieves better performance with significantly reduced computing cost.
