How to visualize EKF predictions?

[sashankvempati]

Hello,

I am trying to implement the code for the EKF (https://pyro.ai/examples/ekf.html). I would like to create a visualization like the one shown in Figure 1 at the end of the page (titled "True track and EKF prediction with error"). When I try to print out the state values, it is displaying that is an EKFState object stored in a specific address.

1. What steps should I do to make a visualization of the EKF prediction?
2. Additionally, If I want to use a list of predicted measurement functions where/ how can I pass those values through the EKF in the code to get the predictions?

I appreciate any help!

[tare]

Please see this discussion. As mentioned there, you'll probably find stats_tools.py and demo_extended_kalman_filter.py rather useful. Anyway, you need to use the properties of EKFState listed here. Indeed, this example is somewhat limited and has some inconsistencies.