A Unified Analysis for Dynamic Programming Track-Before-Detect Algorithms: Error Convergence and Spatial Uncertainty (opens in new tab)

The Dynamic Programming Track-Before-Detect (DP-TBD) class of algorithms is a core approach to the small low signal-to-noise ratio (SNR) target detection problem. These methods detect targets by recursively accumulating data through a sequence of iterative maximizations, a process that has traditionally limited their theoretical analysis. We propose a novel spatial analysis for the general DP-TBD class of algorithms where we derive a fundame...