To address the issues of static nature, strong subjectivity, and insufficient real-time adaptability in traditional combat effectiveness evaluation, this paper proposes an improved analytic hierarchy process (AHP)-based dynamic assessment method for ground unit combat effectiveness. By embedding the OODA loop, construct a closed-loop system of ‘data collection - model reconstruction - weight update - feedback optimization’. Utilize simulation-based exercises to collect multi-source data in real-time, dynamically adjust judgment matrices and indicator weights based on battlefield situation changes, and update models for dynamic evaluation. In ground unit offensive scenarios, set up diverse simulated battlefield environments for control experiments, collect multi-dimensional effectiveness data to validate the methodology. The results demonstrate that this method can effectively quantify combat effectiveness in complex operational environments, addressing the latency issues of traditional static assessment approaches. It can provide a reference for evaluating combat effectiveness of ground units.