Spelling suggestions: "subject:"kalman, filtering"" "subject:"kalman, iltering""
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Tracking maneuvering targets via semi-Markov maneuver modeling.Gholson, Norman Hamilton, January 1977 (has links)
Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1977. / Also available via the Internet.
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Nonlinear filtering and system identification algorithms for autonomous systems /Brunke, Shelby Scott, January 2001 (has links)
Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (leaves 131-139).
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Development of multisensor fusion techniques with gating networks applied to reentry vehiclesDubois-Matra, Olivier. January 2003 (has links) (PDF)
Thesis (Ph. D.)--University of Texas at Austin, 2003. / Vita. Includes bibliographical references. Available also from UMI Company.
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Autonomous visual tracking of stationary targets using small unmanned aerial vehicles /Prince, Robert A. January 2004 (has links) (PDF)
Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, June 2004. / Thesis advisor(s): Isaac I. Kaminer. Includes bibliographical references (p. 69). Also available online.
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Design and simulation of a three-axis stabilized satellite and Kalman filter rate estimator /Vitalich, John. January 2003 (has links) (PDF)
Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2003. / Thesis advisor(s): Hal A. Titus. Includes bibliographical references (p. 89-90). Also available online.
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Advanced navigation algorithms for precision landingZanetti, Renato, 1978- 29 August 2008 (has links)
Not available
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System-Level Algorithm Design for Radionavigation using UWB WaveformsIltis, Ronald A. 10 1900 (has links)
A radiolocation/navigation system is considered in which mobile nodes use ultra-wideband (UWB) radios to obtain inter-node ranges via round-trip travel time (RTT). Each node is also assumed to contain an inertial measurement unit (IMU) which generates 2D position estimates subject to Gaussian drift and additive noise errors. The key problem in such a system is obtaining 2 or 3-D position estimates from the nonlinear UWB range measurements and fusing the resulting UWB and IMU estimates. The system presented uses a Steepest Descent Random Start (SDRS) algorithm to solve the nonlinear positioning problem. It is shown that SDRS is a stable algorithim under a realistic communications reciprocity assumption. The SDRS estimates are then treated as measurements by the navigation Kalman filter. The navigation filter also processes separate IMU-derived position estimates to update node position/velocity. Simulation results for an urban corridor are given showing < 6 m. rms position errors.
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Identification of linear systems using periodic inputsCarew, Burian January 1974 (has links)
No description available.
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A study of an on-line recursive filter applied to a milling circuit.Barker, Ian James. January 1975 (has links)
No abstract available. / Thesis (Ph.D.)-University of Natal, Durban,1975.
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On-line estimation and control of molecular weight distributionAdebekun, Aderinola Kolawole 05 1900 (has links)
No description available.
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