{"product_id":"tracking-and-kalman-filtering-made-easy-isbn-9780471184072","title":"Tracking and Kalman Filtering Made Easy","description":"A unique, easy-to-use guide to radar tracking and Kalmanfiltering\u003cbr\u003e \u003cbr\u003e This book presents the first truly accessible treatment of radartracking; Kalman, Swerling, and Bayes filters for linear andnonlinear ballistic and satellite tracking systems; and thevoltage-processing methods (Givens, Householder, and Gram-Schmidt)for least-squares filtering to correct for computer round-offerrors. Tracking and Kalman Filtering Made Easy emphasizes thephysical and geometric aspects of radar filters as well as thebeauty and simplicity of their mathematics. An abundance of designequations, procedures, and curves allows readers to design trackingfilters quickly and test their performance using only a pocketcalculator!\u003cbr\u003e \u003cbr\u003e The text incorporates problems and solutions, figures andphotographs, and astonishingly simple derivations for variousfilters. It tackles problems involving clutter returns, redundanttarget detections, inconsistent data, track-start and track-droprules, data association, matched filtering, tracking with chirpwaveform, and more. The book also covers useful techniques such asthe moving target detector (MTD) clutter rejection technique. Allexplanations are given in clear and simple terms, including:\u003cbr\u003e * The voltage-processing approach to least-squares filtering\u003cbr\u003e * The correlation between such procedures as discrete orthogonalLegendre polynomial (DOLP) and voltage processing\u003cbr\u003e * The mathematical sameness of tracking and estimation problems onthe one hand, and sidelobe canceling and adaptive array processingon the other\u003cbr\u003e * The massively parallel systolic array sidelobe canceler processor\u003cbr\u003e * Important computational accuracy issues\u003cbr\u003e * An appended comparison between the Kalman and the Swerlingfilters, written by Dr. Peter Swerling\u003cbr\u003e \u003cbr\u003e Tracking and Kalman Filtering Made Easy is invaluable forengineers, scientists, and mathematicians involved in trackingfilter design. Its straightforward approach makes it an excellenttextbook for senior-undergraduate and first-year graduate courses. TRACKING, PREDICTION, AND SMOOTHING BASICS.\u003cbr\u003e \u003cbr\u003e g and g-h-k Filters.\u003cbr\u003e \u003cbr\u003e Kalman Filter.\u003cbr\u003e \u003cbr\u003e Practical Issues for Radar Tracking.\u003cbr\u003e \u003cbr\u003e LEAST-SQUARES FILTERING, VOLTAGE PROCESSING, ADAPTIVE ARRAYPROCESSING, AND EXTENDED KALMAN FILTER.\u003cbr\u003e \u003cbr\u003e Least-Squares and Minimum-Variance Estimates for LinearTime-Invariant Systems.\u003cbr\u003e \u003cbr\u003e Fixed-Memory Polynomial Filter.\u003cbr\u003e \u003cbr\u003e Expanding- Memory (Growing-Memory) Polynomial Filters.\u003cbr\u003e \u003cbr\u003e Fading-Memory (Discounted Least-Squares) Filter.\u003cbr\u003e \u003cbr\u003e General Form for Linear Time-Invariant System.\u003cbr\u003e \u003cbr\u003e General Recursive Minimum-Variance Growing-Memory Filter (Bayes andKalman Filters without Target Process Noise).\u003cbr\u003e \u003cbr\u003e Voltage Least-Squares Algorithms Revisited.\u003cbr\u003e \u003cbr\u003e Givens Orthonormal Transformation.\u003cbr\u003e \u003cbr\u003e Householder Orthonormal Transformation.\u003cbr\u003e \u003cbr\u003e Gram--Schmidt Orthonormal Transformation.\u003cbr\u003e \u003cbr\u003e More on Voltage-Processing Techniques.\u003cbr\u003e \u003cbr\u003e Linear Time-Variant System.\u003cbr\u003e \u003cbr\u003e Nonlinear Observation Scheme and Dynamic Model (Extended KalmanFilter).\u003cbr\u003e \u003cbr\u003e Bayes Algorithm with Iterative Differential Correction forNonlinear Systems.\u003cbr\u003e \u003cbr\u003e Kalman Filter Revisited.\u003cbr\u003e \u003cbr\u003e Appendix.\u003cbr\u003e \u003cbr\u003e Problems.\u003cbr\u003e \u003cbr\u003e Symbols and Acronyms.\u003cbr\u003e \u003cbr\u003e Solution to Selected Problems.\u003cbr\u003e \u003cbr\u003e References.\u003cbr\u003e \u003cbr\u003e Index. ELI BROOKNER, DSc, is a Consulting Scientist with Raytheon Company in Sudbury, Massachusetts. Over a long and distinguished career, he has conceived and\/or designed numerous radar systems, including Wake Measurement Radar and the first TWT radar put into space. A world-renowned teacher and lecturer, he is editor and principal contributor of three previous books: Radar Technology, Aspects of Modern Radar, and Practical Phased Array Antenna Systems.  A unique, easy-to-use guide to radar tracking and Kalman filtering  \u003cp\u003eThis book presents the first truly accessible treatment of radar tracking; Kalman, Swerling, and Bayes filters for linear and nonlinear ballistic and satellite tracking systems; and the voltage-processing methods (Givens, Householder, and Gram-Schmidt) for least-squares filtering to correct for computer round-off errors. Tracking and Kalman Filtering Made Easy emphasizes the physical and geometric aspects of radar filters as well as the beauty and simplicity of their mathematics. An abundance of design equations, procedures, and curves allows readers to design tracking filters quickly and test their performance using only a pocket calculator!\u003c\/p\u003e \u003cp\u003eThe text incorporates problems and solutions, figures and photographs, and astonishingly simple derivations for various filters. It tackles problems involving clutter returns, redundant target detections, inconsistent data, track-start and track-drop rules, data association, matched filtering, tracking with chirp waveform, and more. The book also covers useful techniques such as the moving target detector (MTD) clutter rejection technique. All explanations are given in clear and simple terms, including:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eThe voltage-processing approach to least-squares filtering\u003c\/li\u003e \u003cli\u003eThe correlation between such procedures as discrete orthogonal Legendre polynomial (DOLP) and voltage processing\u003c\/li\u003e \u003cli\u003eThe mathematical sameness of tracking and estimation problems on the one hand, and sidelobe canceling and adaptive array processing on the other\u003c\/li\u003e \u003cli\u003eThe massively parallel systolic array sidelobe canceler processor\u003c\/li\u003e \u003cli\u003eImportant computational accuracy issues\u003c\/li\u003e \u003cli\u003eAn appended comparison between the Kalman and the Swerling filters, written by Dr. Peter Swerling\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eTracking and Kalman Filtering Made Easy is invaluable for engineers, scientists, and mathematicians involved in tracking filter design. Its straightforward approach makes it an excellent textbook for senior-undergraduate and first-year graduate courses.\u003c\/p\u003e","brand":"Wiley-Interscience","offers":[{"title":"Default Title","offer_id":47990400549093,"sku":"NP9780471184072","price":206.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780471184072.jpg?v=1761787677","url":"https:\/\/k12savings.com\/products\/tracking-and-kalman-filtering-made-easy-isbn-9780471184072","provider":"K12savings","version":"1.0","type":"link"}