Article
Nanoscience & Nanotechnology
Weiyi Chen, Fan He, Haidi Dong
Summary: A new adaptive variable structure IMM filtering and smoothing (AVSIMMFS) algorithm is proposed in this paper, and simulation results show that the tracking performance of the AVSIMMFS algorithm is better than that of other methods.
Article
Automation & Control Systems
Zhang Zhuanhua, Zhou Gongjian
Summary: This paper studies a state estimation algorithm for maneuvering targets with trajectory shapes independent of dynamic characteristics. The algorithm separates the modeling of target trajectory and dynamic characteristics and calculates the parameter vector using least squares. Numerical experiments show that the proposed algorithm outperforms traditional coupled model-based algorithms in the presence of target maneuvers.
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS
(2022)
Article
Chemistry, Analytical
Ghawas Ali Shah, Sumair Khan, Sufyan Ali Memon, Mohsin Shahzad, Zahid Mahmood, Uzair Khan
Summary: The proposed fixed lag smoothing IMM-IPDA method utilizes the advantages of fixed lag smoothing algorithm to track maneuvering target in cluttered environment, showing superior performance compared to other recent algorithms in terms of mode probabilities, target trajectory state and target existence state.
Article
Environmental Sciences
Fansen Zhou, Yidi Wang, Wei Zheng, Zhao Li, Xin Wen
Summary: The newly developed near-space vehicle has high speed and strong maneuverability. Satellite tracking platforms equipped with Synthetic Aperture Radars (SARs) have the potential to track these vehicles continuously. To enhance tracking stability and accuracy, and to lower the computational burden, a Fast Distributed Multiple-Model (FDMM) nonlinearity estimation algorithm for satellites has been proposed.
Article
Engineering, Electrical & Electronic
Mohsen Ebrahimi, Mahdi Ardeshiri, Sedigheh Alaie Khanghah
Summary: This paper reviews and analyzes the maneuvering target tracking model and proposes an improved algorithm for accurately estimating the target's state in the presence of measurement noise. The proposed method uses the multiple-model Interacting Multiple Model algorithm and introduces higher-order Markov models to describe the system behavior. The results show that the algorithm performs well in target tracking.
DIGITAL SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Shan He, Panlong Wu, Xingxiu Li, Yuming Bo, Peng Yun
Summary: In this article, an expectation maximization-based adaptive modified unbiased minimum-variance estimation algorithm is proposed for highly maneuvering target tracking with model mismatch. The algorithm integrates the virtual maneuvering noise and the first-order Markov process model to quantitatively describe the maneuvering acceleration. It improves the accuracy of maneuvering acceleration estimation by adaptively estimating the mean and covariance of virtual maneuvering noise using the expectation maximization algorithm.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Aerospace
Zhuanhua Zhang, Gongjian Zhou
Summary: This paper presents a new estimation algorithm that models the target trajectory and dynamic characteristics separately, and accurately estimates unknown control points defining the B-spline curves to achieve better tracking performance for maneuvering targets in complex environments.
AEROSPACE SCIENCE AND TECHNOLOGY
(2021)
Article
Geochemistry & Geophysics
Wen Bin Yang, Yue Bin Wang, Dan Li, Jian Qiu Zhang
Summary: In this article, a generalized matched filtering method driven by the Bayesian motion trajectory inference (BMTI) is proposed to address the defocusing issues caused by range cell and Doppler frequency migrations initiated by maneuvering targets. The method infers target motion trajectories and refocuses echo energies using a modified Bayesian filter and a matched filter bank designed by the inferred trajectories.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Computer Science, Artificial Intelligence
Liang-Qun Li, Xi-yang Zhan, Wei-Xin Xie, Zong-Xiang Liu
Summary: This paper presents an interacting T-S fuzzy semantic model estimator (ITS-FSM) for maneuvering target tracking, which integrates a probabilistic switching model and an efficient maximum entropy fuzzy clustering method to achieve accurate estimation. The proposed algorithm demonstrates effectiveness in handling non-Gaussian noise based on experiments on three simulation datasets.
Article
Geochemistry & Geophysics
Qin Tang, Jing Liang
Summary: In this article, a complete system for tracking highly maneuvering multitargets in the case of multisensors asynchronous sampling is constructed, which is divided into three modules: space-time calibration, point-trajectory data association, and trajectory data fusion. An improved least-squares virtual fusion method and adaptive K-nearest neighbors algorithm are used to enhance tracking accuracy, showing accurate performance for moving maneuvering multitargets tracking in complex situations.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Electrical & Electronic
Wen Zhang, Xuanzhi Zhao, Zengli Liu, Kang Liu, Bo Chen
Summary: Handling the nonlinearity between the measurement and kinematic states is the core issue in target tracking based on radar or sonar. This paper proposes a new filter with a linear structure to achieve nonlinear tracking by integrating information in the polar coordinate system. The new filter effectively improves the tracking accuracy, and different posterior Cramer- Rao lower bounds (PCRLBs) for fusion estimation in Cartesian coordinates and polar coordinates are given and compared.
Article
Engineering, Electrical & Electronic
Jun Wan, Zaoyun He, Xiaoheng Tan, Dong Li, Hongqing Liu, Yuxiang Shu, Zhanye Chen
Summary: Maneuvering target poses a significant threat to radar detection applications, as the complex unknown motions between the radar and the target adversely affect target coherent integration. This study proposes a fast nonparametric estimation method for coherent integration of maneuvering targets. The method eliminates quadratic range cell migration using the second-order Keystone transform, removes complex low- and high-order Doppler frequency broadenings through a modified range frequency reversal process, and corrects residual range cell migration using an improved time-scaled transform without parameter search or estimation.
Article
Engineering, Multidisciplinary
Shangbin Jiao, Jinghang Du, Yujun Li, Yuxing Li
Summary: The IABBSCA-IMM algorithm proposed in this study effectively addresses the issues of model probability lag and low accuracy in the traditional IMM algorithm by improving parameter adaptation and optimizing filtering parameters.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Ziying Hu, Wei Wang, Fuwang Dong
Summary: In this study, an accurate imaging and motion estimation method based on multiple-input-multiple-out (MIMO) radar is proposed to tackle the image deterioration problem in radar imaging for ship target. By establishing a multidimensional signal model and employing a preprocessing strategy based on the space-time adaptive processing (STAP) theory, sea clutter interference can be effectively reduced.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Chemistry, Analytical
Mahendra Mallick, Xiaoqing Tian, Yun Zhu, Mark Morelande
Summary: This study considers the state estimation of a maneuvering target in 3D using bearing and elevation measurements from a passive infrared search and track sensor. The target moves with nearly constant turn in the XY-plane and nearly constant velocity along the Z-axis. The first and second-order Taylor approximations are used to discretize the continuous-time model, and the cubature Kalman filter is employed for state estimation. Numerical results show that the second-order Taylor approximation provides the best accuracy using either polar velocity or Cartesian velocity-based models.
