摘要
The problem of detecting and tracking point targets in a sequence of infrared images with very low signalto-noise ratio (SNR) is investigated in this paper. A track before detect algorithm for infrared (IR) point target is developed based on particle filter. The particle filter is used to estimate the state of the target in track stage. The unnormalized weights of the output of the filter are used to approximately construct the likelihood ratio for hypothesis test in detection stage. Experiment results with the real image sequences that SNR is about 2.0 show that the proposed algorithm can successfully detect and track point target.
The problem of detecting and tracking point targets in a sequence of infrared images with very low signalto-noise ratio (SNR) is investigated in this paper. A track before detect algorithm for infrared (IR) point target is developed based on particle filter. The particle filter is used to estimate the state of the target in track stage. The unnormalized weights of the output of the filter are used to approximately construct the likelihood ratio for hypothesis test in detection stage. Experiment results with the real image sequences that SNR is about 2.0 show that the proposed algorithm can successfully detect and track point target.
基金
This work was jointly supported by National Natural Science Foundation of China (No. 60375008)China PH.D Discipline Special Foundation (No. 20020248029)China Aviation Science Foundation (No. 02D57003)Aerospace Supporting Technology Foundation (No.2003-1.3 02)EXPO Technologies Special Project of National Key Technologies R&D Programme (No.2004BA908B07)Shanghai Key Technologies Preresearch Project (No. 035115009).
