Fluctuating Targets Detection Using Space-Time Diversity

In this paper, we consider the fluctuating targets detection problem in a distributed multi-sensor network. A multi-sensor multi-frame track-before-detect (MS-MF-TBD) procedure is proposed to sufficiently make use of the target energy diversity in space and time dimensions (space-time diversity). Two MS-MF-TBD methods, the multi-sensor maximum likelihood-probabilistic data association (MS-ML-PDA) and the multi-sensor dynamic programming based TBD (MS-DP-TBD), are derived, and a number of simulation experiments under different target fluctuation models are performed. Through these simulations, we demonstrate that by using the space-time diversity, MS-MF-TBD methods can efficiently detect the fluctuating targets, achieving significant detection performance gains in comparison to either the single sensor TBD methods or the conventional multi-sensor detection methods.