SIS Particle Filter Python Implementation
Particle filter is a Bayesian filter. Any Bayesian filter requires process and measurement models so you also need to define them.
If you will use bootstrap particle filter, you just create initial samples with initial parameters from Gaussian distribution. Then, you propagate the particles using process model. This is your so called &quot;prediction&quot; step.
After obtaining your measurements for each time step, you calculate the weights. Using those weights you perform resampling.