Cover image for Non-Cooperative Target Tracking, Fusion and Control Algorithms and Advances
Non-Cooperative Target Tracking, Fusion and Control Algorithms and Advances
Title:
Non-Cooperative Target Tracking, Fusion and Control Algorithms and Advances
Author:
Jing, Zhongliang. author.
ISBN:
9783319907161
Personal Author:
Physical Description:
XIX, 340 p. 142 illus., 80 illus. in color. online resource.
Series:
Information Fusion and Data Science,
Contents:
Introduction -- Part I Multi-Target Tracking -- Gaussian mixture CPHD filter with gating technique -- Detection-guided multi-target Bayesian filter -- On the sensor order in sequential integrated probability data association filter -- New method for dynamic bias estimation: Gaussian mean shift registration -- Part II Visual Target Tracking -- Learning-based appearance model for probabilistic visual tracking -- Incremental visual tracking with L1 norm approximation and Grassmann update -- A dual-kernel-based tracking approach for visual target -- Kernel joint visual tracking and recognition based on structured sparse representation -- Part III Image Fusion and Deblurring -- A simple method to build oversampled filter banks and tight frames -- Multi-focus image fusion using pulse coupled neural network -- Evaluation of focus measures in multi-focus image fusion -- Multi-modality image fusion via generalized Riesz-wavelet transformation -- A sparse proximal Newton splitting method for constrained image deblurring -- Part IV Control of Spacecraft Maneuvers -- Maneuver-aided active satellite tracking using six-DOF optimal dynamic inversion control -- Dynamic optimal sliding-mode control for six-DOF follow-up robust tracking of active satellite -- Redundant adaptive robust tracking of active satellite and error evaluation.
Abstract:
This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing.
Added Corporate Author:
Holds: Copies: