Detection and Tracking Algorithms for IRST
Sushil Kumar · 2004
Infrared search and track system is an integral part of modern weaponry. The detection and tracking algorithm forms the heart of an IRST system and their effectiveness plays an important role in determining performance of the system. This report studies various detection and tracking algorithms for multiple point targets in noisy environment resulting in very low signal to noise ratio. Target detection is carried out using spatial-temporal techniques needing multiple frames, since targets are assumed to be irresolvable in a single image frame. The tracking algorithms are classified in the basis of different approaches for data selection and model selection. Data selection and model selection is used for tracking multiple targets in dense clutter environment. An overview of the Interacting Multiple Model Expectation Maximization algorithm, and brief description of Multiple Hypothesis Tracking and Joint Probabilistic Data Association Filter algorithm is also presented.