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A new algorithm based on Bayesian methods for automatic tracking of multiaspect targets in cluttered image sequences is described. The findings indicate that the proposed algorithms outperform the association of a bank of template correlators and a Kalman filter in adverse scenarios of low target-to-clutter radio and uncertainty in the true target aspect.

This paper introduces new algorithms for joint blind equalization and decoding of convolutionally coded communication systems operating on frequency-selective channels. The proposed method is based on particle filters (PF), recursively approximating maximum a posteriori (MAP) estimates of the transmitted data without explicitly determining channel parameters. Further elaborating on previous works, we assume that both the channel order and the noise variance are unknown random variables, and develop a new formulation for PF weight propagation which allows these quantities to be analytically integrated out. We verify via numerical simulations that the proposed methods lead to near optimal performance, closely approximating that of algorithms that require exact knowledge of all channel parameters. [ABSTRACT FROM AUTHOR]

We present in this correspondence an improved sequential Monte Carlo (SMC) filter for ballistic target tracking with random, time-varying ballistic coefficient. The proposed tracker is a sampling/importance resampling (SIR) filter that uses an optimized importance function to combat particle degeneracy, and also incorporates an additional measurement-driven Markov chain Monte Carlo (MCMC) move step to prevent particle impoverishment. Simulation results show that, using significantly fewer particles than previously reported in the literature for similar tracking problems, the root mean-square error (RMSE) curves for the proposed optimized SIR filter approach the square root of the ideal posterior Cramér-Rao lower bound (PCRLB). [ABSTRACT FROM AUTHOR]

Proposes a Bayesian algorithm for automatic tracking of cluttered targets in sequences of two-dimensional digital images. Conventional approaches to target tracking from images; Adaptation of sequential importance sampling (SIS) in the algorithm; Discussion on SIS.

Provides information on a study addressing the question of which rapid random models are equivalent to the discrete cosine transform (DCT) and discrete sine transform (DST). Second-order equivalence between the discrete sine transform (DST) and the discrete cosine transform (DCT); Theoretical background; Derivation of the equivalence; Conclusions.