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

Table 1

Mean and variance of RMSE for five nonlinear algorithms running 100 times under both the Gaussian and non-Gaussian noise models.

Filter estimation	SIR	APF	GPF	ECSPF	CCSPF
RMSE mean (Gaussian)	3.4771	3.4368	3.5677	1.1003	1.2027
RMSE variance (Gaussian)	0.0171	0.0135	0.0221	0.0025	0.0045
RMSE mean (non-Gaussian)	4.3332	4.3939	4.4726	1.9273	2.0941
RMSE variance (non-Gaussian)	0.0222	0.0155	0.0235	0.0108	0.0133

Note: SIR = sequential importance resampling; APF = auxiliary particle filter; GPF = Gaussian particle filter; ECSPF = Euclidean distance clustering similarity particle filter; CCSPF = Chebyshev distance clustering similarity particle filter; RMSE = root mean squared error.