  A sequential detection and tracking (SDT) approach is proposed for detection
and tracking of very low signal-to-noise (SNR) objects. The proposed approach
is compared with two existing particle filter track-before-track (TBD) methods.
It is shown that the former outperforms the latter. A conventional detection
and tracking (CDT) approach, based on one-data-frame thresholding, is
considered as a benchmark for comparison. Simulations demonstrate the
performance.
