Improved Particle Filter Using Clustering Similarity of the State Trajectory with Application to Nonlinear Estimation: Theory, Modeling, and Applications

Algorithm 1

Standard particle filter.

Step 1. Particle initialization

At time , for

Sample

At time , for

Step 2. Sequential importance sampling

Predict , sample

Evaluate the normalized importance weights

, and

Step 3. Resampling strategy

Calculate effective samples

Compare resampling threshold

    if

, and

   else

Step 4. State estimation