Track before detect for point targets with particle filter in infrared image sequences

• 作 者: 胡洪涛 敬忠良 胡士强
• 机 构: Institute of Aerospace Information and Control School of Electric,Information and Electrical Enginee
• 出 处: Chinese Optics Letters
• 发表日期: 2005年06期
• 关键词: likelihood detecting weights hypothesis frames pixel handle Probability Bayesian

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 The unnormalized weights of the output of the filter are used to approximate 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.