Article
Engineering, Marine
Fei Deng, Carlos Levi, Hongdong Yin, Menglan Duan
Summary: The study proposes an optimized UKF algorithm to improve the estimation precision of hydrodynamic coefficients for an AUV, in combination with three KF algorithms for verification. The research enhances the adaptability and prediction performance of the identification approach and demonstrates the superior accuracy of OUKF compared to EKF and UKF in the presence of ARMA noisy model.
Article
Automation & Control Systems
Alexander Meyer Sjoberg, Olav Egeland
Summary: This paper proposes an unscented Kalman filter method for matrix Lie groups, which can handle data more efficiently and provides a new analytical solution on the Lie group SE(3).
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Li Li, Mingyang Fan, Yuanqing Xia, Cui Zhu
Summary: This paper focuses on distributed fusion estimation for a multi-sensor nonlinear stochastic system, proposing an event-trigger mechanism and unscented Kalman filters for fusion estimation. It establishes boundedness conditions for fusion estimation error covariance through a recursive algorithm and trigger threshold. An ideal compromise between communication rate and estimation performance is achieved.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Engineering, Electrical & Electronic
Elnaz Moradi, Reza Mohseni
Summary: This paper proposes the problem of linear frequency modulated (LFM) or chirp signal analysis and suggests solutions based on signal state-space model and different versions of the Kalman filter. Compared with traditional methods, the proposed approaches have advantages in estimation performance and convergence, which are demonstrated through numerical simulations.
SIGNAL IMAGE AND VIDEO PROCESSING
(2023)
Article
Automation & Control Systems
Jozsef Kuti, Imre J. Rudas, Huijun Gao, Peter Galambos
Summary: This article introduces a generic computational relaxation method for optimizing the filtering operation in Unscented Kalman filter-based applications, which improves the performance of advanced robotics and autonomous vehicles. The practical merit of the proposed method is demonstrated through real-world examples, showing significant advantages and reduced computational demand.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Aerospace
Xiaohua Li, Bo Lu, Wasiq Ali, Jun Su, Haiyan Jin
Summary: The paper introduces a probabilistic multiple hypothesis tracker (PMHT) algorithm based on batch recursive extended Rauch-Tung-Striebel smoother (RTSS) to effectively handle the nonlinearity in passive Doppler and bearing measurements in multiple-target tracking.
INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING
(2021)
Article
Biodiversity Conservation
Rui Xiao, Yuxiang Guo, Zhonghao Zhang, Yansheng Li
Summary: Urban agglomeration is a mature form of spatial organization in the process of urbanization, often found in areas with prominent ecological and environmental problems. Assessing the ecosystem health of urban agglomeration in previous stages is crucial for its sustainable development. In this study, a hidden Markov Model and unscented Kalman filtering method are used to monitor and predict the ecosystem health of the Shanghai-Hangzhou Bay Urban Agglomeration (SHBUA). The findings demonstrate the effectiveness and accuracy of the proposed prediction schemes in assessing the ecosystem health of urban agglomerations.
ECOLOGICAL INDICATORS
(2022)
Article
Engineering, Electrical & Electronic
Nasim Hajati, Amin Rezaeizadeh
Summary: This article presents a PDR-based navigation device that utilizes a pedestrian's walking pattern to identify individuals, does not rely on GNSS signals or beacons, and utilizes an IMU for attitude estimation and position calculation using a step detection algorithm. Experimental results show a 0.96% error for a 4.7km outdoor walk.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Engineering, Electrical & Electronic
Cole Woods, Vishesh Vikas
Summary: Measurement of joint angles is important for the control of robotic systems and monitoring human gait. This study proposes a dynamic model and three methods to estimate joint angles using an array of accelerometers and the equivalence of acceleration at the joint. Simulations and experiments confirm that model-based filtering methods perform better than the analytical approach, and placing accelerometers at the ends of the links minimizes estimation error.
IEEE SENSORS JOURNAL
(2022)
Article
Automation & Control Systems
Li Keyi, Guo Zhengkun, Zhou Gongjian
Summary: This paper proposes a state estimation method based on the proper dynamic model in the R-D plane, using range measurements to obtain accurate range and Doppler estimates. The unscented Kalman filter is utilized to handle the strong nonlinearity, and two filtering initialization methods are derived.
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS
(2022)
Article
Engineering, Civil
Hoyeoul Park, Chan-Gyu Kim, Kibum Kim, Sang-hun Lee
Summary: This study developed a real-time state estimation of the skydiving physics model using the unscented Kalman filter (UKF). The UKF was able to predict falling altitudes with various error ranges and was influenced by fluctuations in falling velocity and missing datasets. The study also monitored wind velocity and heart rate, and found low correlations between skydiving activities and heart rate.
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS
(2022)
Article
Automation & Control Systems
Wansong Liu, Xiao Liang, Minghui Zheng
Summary: This article introduces a novel dynamic model informed motion prediction method that takes into account the impact of muscle force on motion prediction, using an unscented Kalman filter (UKF) to predict the state of the dynamic model for future arm motion.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Automation & Control Systems
Yan Wang, Chen Lv, Yongjun Yan, Pai Peng, Faan Wang, Liwei Xu, Guodong Yin
Summary: This article proposes an integrated scheme for estimating tire-road friction coefficient (TRFC) by combining a strong tracking unscented Kalman filter and an interactive multiple model unscented Kalman filter. Real-time experiments on a mass-produced vehicle demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed approach has better estimation accuracy than the existing ones under various driving scenarios.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Chen Qian, Qingwei Chen, Yifei Wu, Jian Guo, Yang Gao
Summary: A novel M-estimation based sparse grid quadrature filter (MSGQF) is proposed to improve the robust performance of the nonlinear system. The MSGQF outperforms other filters when abnormal measurement values appear, providing significant performance improvement in the robustness of the nonlinear system.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Engineering, Electrical & Electronic
Zhongjie Ren, Wenjie You, Jieyu Qian, Yexin Zhang, Ke Cui, Lei Kong, Yunxia Huang, Rihong Zhu
Summary: This article proposes a method based on an unscented Kalman filter for interferometric fiber sensors, which overcomes the limitations of traditional phase unwrapping methods and has been successfully verified for its feasibility. The method can expand the measurement range of phase signals and show better performance in both time and frequency domains.
IEEE SENSORS JOURNAL
(2022)
Editorial Material
Engineering, Aerospace
Yaakov Bar-Shalom, Peter Willett
IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE
(2022)
Article
Engineering, Aerospace
Nicola Forti, Leonardo M. Millefiori, Paolo Braca, Peter Willett
Summary: This article presents a Bayesian approach for sequential detection of anomalies in the motion of a target and joint tracking. The developed Bayesian framework combines random finite set (RFS) theory and optimal joint input and state estimation to update a hybrid state that incorporates kinematic state and unknown control input. A Gaussian-mixture hybrid Bernoulli filter (GM-HBF) is proposed for dynamic anomaly detection in the maritime domain characterized by linear Gaussian target dynamics.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2022)
Article
Engineering, Civil
Nicola Forti, Enrica d'Afflisio, Paolo Braca, Leonardo M. Millefiori, Peter Willett, Sandro Carniel
Summary: This paper discusses the successful application of automatic maritime anomaly detection tools in real-world situations, such as the grounding event of the container vessel Ever Given in the Suez Canal. The detector processes AIS reports, radar information, and contextual data to identify deviations from expected navigation behavior and could have triggered an alert 19 minutes before the grounding event based on recorded AIS data.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Christopher Franzini, Francesco A. N. Palmieri, Peter Willett, Yaakov Bar-Shalom
Summary: This article discusses and extends two approaches for target detection and motion parameter estimation in a challenging underwater multipath environment. The simpler ML-PMHT algorithm is found to be the better choice for practical use in complex scenarios.
IEEE JOURNAL OF OCEANIC ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Nicola Forti, Enrica D'Afflisio, Paolo Braca, Leonardo M. Millefiori, Peter Willett
Summary: The maritime domain is entering a new era of intelligence with advancements in automation, robotics, perception, artificial intelligence, and digitalization. Smart ship infrastructure and technology will revolutionize maritime transportation, improving safety, cost efficiency, and sustainability.
PROCEEDINGS OF THE IEEE
(2022)
Editorial Material
Engineering, Aerospace
Peter Willett
Summary: Interview with Peter Willett took place on Thursday, July 14, 2022, at his residence in Dallas, GA, following a delicious southern dinner prepared by Dale Blair and Kathleen Thompson. This edited version is available in a full video format at https://ieee-aess.org/presentation/aess-historical-interview-daleblair-peter-willett.
IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE
(2023)
Article
Engineering, Electrical & Electronic
Wei Liu, Martin Haardt, Maria S. Greco, Christoph F. Mecklenbraeuker, Peter Willett
Summary: This article provides a general introduction and overview of the sensor array and multichannel signal processing field, as well as the activities of the IEEE Signal Processing Society Sensor Array and Multichannel Technical Committee. It presents the main technological advances in five subareas over the past 25 years, including beamforming, DOA estimation, sensor location optimization, target/source localization based on sensor arrays, and MIMO arrays. It also discusses six recent developments and potential future research directions in SAM, such as graph signal processing for sensor networks and machine learning for sensor arrays.
IEEE SIGNAL PROCESSING MAGAZINE
(2023)
Article
Engineering, Aerospace
Zijiao Tian, Andrew Finelli, Benny Milgrom, Kaipei Yang, Yaakov Bar-Shalom, Peter Willett
Summary: This article presents an effective method to enhance the resolution for two closely-spaced targets. By jointly estimating the positions and intensities of the targets based on the original frame and the offset frame, it determines whether the targets can be resolved or not using a hypothesis test. Simulations show that adding offset to the image provides more information and enhances the resolution probability compared to frames without offset.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Engineering, Aerospace
Samuele Capobianco, Nicola Forti, Leonardo Maria Millefiori, Paolo Braca, Peter Willett
Summary: Recent deep learning methods can accurately predict future vessel positions using historical AIS data, but quantifying prediction uncertainty is crucial in maritime surveillance. This article explores how recurrent encoder-decoder neural networks can not only predict but also yield a corresponding prediction uncertainty by incorporating Bayesian modeling of uncertainties.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Engineering, Aerospace
Kaipei Yang, Yaakov Bar-Shalom, Peter Willett, Shawn Hunt
Summary: In this work, the order statistic estimation and lidar bounding box (BB) centroid estimation for autonomous vehicles are studied. The estimated BB centroid is used as measurement in object tracking, and the estimation of measurement noise variance is proposed due to unavailability from the sensor manufacturer. The performance of the proposed methods is demonstrated through experiments using real data for autonomous driving applications, showing superiority over the max-min average approach.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Engineering, Aerospace
Francesco A. A. Palmieri, Christopher Franzini, Peter Willett, Yaakov Bar-Shalom
Summary: We analyze the likelihood distribution for a multipath model without a target and focus on the peculiarities of the ML-PMHT when multiple peaks emerge. We study the separated peaks analytically and propose a numerical algorithm based on sampling for the general case. The final distribution is used to compute a parameter-dependent false alarm probability threshold.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Paolo Braca, Leonardo M. Millefiori, Augusto Aubry, Stefano Marano, Antonio De Maio, Peter Willett
Summary: In this study, we investigate the performance of Machine Learning (ML) classification techniques and provide mathematical conditions for exponential decay of error probabilities using large deviations theory. We establish the convergence of the Data-Driven Decision Function (D3F) statistic to a Gaussian distribution and derive approximate error probability curves. Theoretical findings are validated through numerical simulations and real-world data from a maritime radar system.
IEEE OPEN JOURNAL OF SIGNAL PROCESSING
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Zhengyu Wan, Wei Liu, Peter Willett
Summary: This paper proposes a non-coherent source localization method based on distributed sensor arrays, which can achieve localization with only magnitude information. Compared to traditional methods, it performs better in the presence of phase errors.
2022 IEEE 12TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM)
(2022)
Proceedings Paper
Acoustics
Zachariah Sutton, Peter Willett, Stefano Marano
Summary: This work formalizes the test statistic based on censored and quantized data, focusing on cases that require very low communication cost. The measurements and labels are quantized in a coarse manner (e.g., 2-bit values), and censoring is used to control the expected communication cost.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Proceedings Paper
Acoustics
Andrew Finelli, Peter Willett, Yaakov Bar-Shalom, Stefano Marano
Summary: This study explores the use of the Lempel-Ziv (LZ77) procedure to detect transients in surveillance data. The algorithm is characterized by phrase lengths that are asymptotically distributed as Gaussian random variables, allowing for the formulation of quickest detection problems based on statistics of the encoded output. The study specifies procedures for source-agnostic transient detection using locally optimal statistics to augment a Page CUSUM test, and demonstrates an application to acoustic data.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
