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

<div>Comparison of state estimation based on different algorithms in the non-Gaussian noise environment. Note: SIR = sequential importance resampling; APF = auxiliary particle filter; GPF = Gaussian particle filter; CSPF = clustering similarity particle filter.</div>

Journal of Sensors

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Figure 2: Improved Particle Filter Using Clustering Similarity of the State Trajectory with Application to Nonlinear Estimation: Theory, Modeling, and Applications 

Figure 2 | Improved Particle Filter Using Clustering Similarity of the State Trajectory with Application to Nonlinear Estimation: Theory, Modeling, and Applications 