EC3310: Optimal Estimation: Sensor and Data Association - NPS Online
Optimal Estimation: Sensor and Data Association
Course #EC3310
Est.imated Completion Time: 3 months
POC: NPS Online Support
Overview
The subject of this course is optimal estimation and Kalman filtering with extensions to sensor fusion and data association. Main topics include the theory of optimal and recursive estimation in linear (Kalman filter) and nonlinear (extended Kalman filter) systems, with applications to target tracking. Topics directly related to applications, such as basic properties of sensors, target tracking models, multihypothesis data association algorithms, reduced order probabilistic models and heuristic techniques, will also be discussed. Examples and projects will be drawn from radar, EW, and ASW systems.
Security clearance: Secret
Included in degrees & certificates
- 284
Prerequisites
- EC2320
- EC2010
- MA2043
Learning Outcomes
· Theory of Least Squares Estimation in Linear Models
· Kalman Filter Theory: Optimal Estimation in Linear Dynamic Systems
· Extended Kalman Filter Theory in Nonlinear Dynamic Systems
· Applications of the theory in Sensor Fusion and Target Tracking
Application Deadlines
No upcoming deadlines.
Academic Calendar
No upcoming events.