PF	Particle Filtering
MC	Monte Carlo
PMCMC	Particle Markov Chain Monte Carlo
SMC	Sequential Monte Carlo
SMC2	Sequential Monte Carlo Square
SIS	Sequential Importance Sampling
SIR	Sampling Importance Resampling
APF	Adaptive PF
CRLB	Cramér–Rao Lower Bound
CPF	Cognitive PF
SPF	Standard PF
MSE	Mean Square Error
PAC	Perception-action Cycle
BCRB	Bayesian Cramér–Rao lower bound
BIM	Bayesian Fisher Information Matrix
MMSE	Minimum MSE
SNR	Signal-to-noise Ratio
LFM	Linear Frequency Modulation
RMSE	Root Mean Square Error
PCRB	Posterior Cramér–Rao Bound
CRPF	Cost-reference Particle Filter
WPS	Weighted-particle Set
PMF	Probability Mass Function
CCRPF	Cognitive Cost-reference Particle Filter
PDF	Probability Density Function
ARMSE	Average Root Mean Square Error
FIM	Fisher Information Matrix
KLD	Kullback–Leibler Distance
GRNN	General Regression Neural Network
CKF	Cubature Kalman Filter
CD-CKF	Continuous-Discrete Cubature Kalman Filter