Particle Filters (and Navigation)
By Coursera
on Coursera
· Technology
About This Course
As the final course in the Applied Kalman Filtering specialization, you will learn how to develop the particle filter for solving strongly nonlinear state-estimation problems. You will learn about the Monte-Carlo integration and the importance density. You will see how to derive the sequential importance sampling method to estimate the posterior probability density function of a system’s state. You will encounter the degeneracy problem for this method and learn how to solve it via resampling. You will learn how to implement a robust particle-filter in Octave code and will apply it to an indoor-navigation problem.
Instructor
University of Colorado System
Frequently Asked Questions
How much does Particle Filters (and Navigation) cost?
Particle Filters (and Navigation) costs $49. Check the course page for current pricing and available discounts.
Who teaches Particle Filters (and Navigation)?
Particle Filters (and Navigation) is taught by University of Colorado System, University of Colorado System.
What skill level is Particle Filters (and Navigation) for?
This course is designed for advanced learners.