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We consider the problem of estimating a variable number of parameters with adynamic nature. A familiar example is finding the position of moving targetsusing sensor array observations. The problem is challenging in cases whereeither the observations are not reliable or the parameters evolve rapidly.Inspired by the sparsity based techniques, we introduce a novel Bayesian modelfor the problems of interest and study its associated recursive Bayesianfilter. We propose an algorithm approximating the Bayesian filter, maintaininga reasonable amount of calculations. We compare by numerical evaluation theresulting technique to state-of-the-art algorithms in different scenarios. In ascenario with a low SNR, the proposed method outperforms other complextechniques.

A Novel Sparsity-Based Approach to Recursive Estimation of Dynamic Parameter Sets