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.
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 l³"
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