Performance analysis of dim moving point target detection algorithms

The paper studies the performance comparison of track-before-detect (TBD) and detect-before-track (DBT) multi-frame detection algorithms for the detection of weak moving point targets in infrared image sequence data collected from a scanning sensor. The models for TBD and DBT are presented. We analyse and compare topics such as computational effort, minimum SNR that can be detected, the detection gain, upper bounds for the TBD process and the interrelationships and tradeoffs between these features. Our results indicate that the performance of TBD is superior to that of DBT in all respects for low SNR. However, while computationally simple, the DBT algorithm can have a reasonable performance only for high SNR. Simulations verify the results of the analysis and the conclusions drawn.