  This paper presents a novel sparse signal detection scheme designed for a
correlated Markovian Bernoulli-Gaussian sparse signal model, which can
equivalently be viewed as a block sparse signal model. Despite the inherent
complexity of the model, our approach yields a closed-form detection criterion.
Theoretical analyses of the proposed detector are provided, including the
computation of false alarm probability and detection probability through
closed-form formulas. Simulation results compellingly demonstrate the
advantages of our proposed detector compared to an existing detector in the
literature.
