An Effective TBD Algorithm for the Detection of Infrared Dim-Small Moving Target in the Sky Scene

An effective algorithm for the detection of dim-small moving target in the infrared (IR) image sequence is described in this paper, which is based on the idea of Track-Before-Detect (TBD). To deal with the low signal to noise ratio (SNR) and high false alarm rate of the IR target detection in the sky scene, two of the Track-Before-Detect (TBD) methods are introduced: dynamic programming (DP) for the SNR enhancement by energy accumulation, and multistage hypothesis testing (MSHT) to lower the false alarm rate by threshold judgment. Furthermore, constraints as the stabilization of the energy and the continuity of the movement of IR dim-small target are applied to avoid the energy scatter. And based on MSHT, most of the false trajectories are eliminated to reduce the calculated amount and save the storage space. Simulation shows good results for the detection of IR dim-small moving target based on the algorithm we proposed.