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Nonlinear Kalman Filters (and Parameter Estimation)
As a follow-on course to "Linear Kalman Filter Deep Dive", this course derives the steps of the extended Kalman filter and the sigma-point Kalman filter for estimating the state of nonlinear dynamic systems. You will learn how to implement these filters in Octave code and compare their results. You will be introduced to adaptive methods to tune Kalman-filter noise-uncertainty covariances online. You will learn how to estimate the parameters of a state-space model using nonlinear Kalman filters.
Duration
4 Months
Institution
University of Colorado System
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into University of Colorado System.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$274
Total Est. Investment
$274
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Nonlinear Kalman Filters (and Parameter Estimation) program at University of Colorado System are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.