Anti-jamming performance evaluation of infrared aerial target tracking algorithm based on image sequences complexity

Amid increasingly complex aerial Infrared Countermeasure (IRCM) scenarios, the demand for robust anti-jamming capability in Infrared (IR) imaging-guided missiles has grown significantly. Consequently, reliable evaluation of this capability is crucial for advancing IR air-to-air missile systems. This paper proposes a hierarchical evaluation framework for assessing the anti-jamming performance of infrared target tracking algorithms based on the complexity of infrared image sequences. A comprehensive metric, termed Complexity of Infrared Image Sequence (CIRIS), is developed to quantify the operational difficulty from both intra-frame and inter-frame perspectives, including confusion degree of global background, loss degree of target information, influence degree of local background, change degree of object size, and change degree of object position. An IRCM dataset is constructed using a simulation platform and stratified by CIRIS levels to represent diverse jamming scenarios. Tracking algorithms are then evaluated based on their performance across different CIRIS levels. Experimental results on representative algorithms validate the effectiveness and discriminative power of the proposed framework. The CIRIS-driven evaluation paradigm provides a practical foundation for algorithm development and system-level testing of IR tracking systems in adversarial environments.