Mobile augmented reality (AR) advertising has emerged as a sensor-integrated application combining smartphone-based visual sensing, motion tracking, and interactive feedback to deliver immersive experiences. However, limited attention has been paid to how sensing-driven three-dimensional (3D) presentation and interaction jointly affect user perception and behavior from a measurement perspective. In this study, we aim to develop and validate a sensor-enabled structural evaluation framework for mobile AR advertising by examining the relationships among seven constructs: 3D presentation quality, interaction quality, perceived informativeness, immersion, perceived ease of use, attitude toward the advertisement, and usage intention. In this study, we propose a sensor-enabled structural evaluation framework linking 3D presentation and interaction qualities—derived from mobile sensing and rendering processes—to perceived informativeness, immersion, perceived ease of use, attitude, and usage intention. A questionnaire with 28 items across seven constructs was administered after a mobile AR task, yielding valid responses from 350 participants. The measurement model demonstrated satisfactory reliability, validity, and overall fit. Structural equation modeling results indicate that 3D presentation quality significantly enhances perceived informativeness, while interaction quality improves perceived ease of use. Perceived informativeness and immersion positively affect attitude, and both perceived ease of use and attitude increase usage intention. Mediation analysis further confirms that perceived informativeness, perceived ease of use, and attitude act as key transmission pathways. These findings suggest that the effectiveness of mobile AR advertising depends on not only technology deployment but also how sensor-generated information is transformed into clear and responsive user experiences. In this study, we contribute a validated framework linking sensing mechanisms, perceptual processes, and behavioral outcomes, and highlight the importance of optimizing sensor responsiveness and information representation in AR systems. However, the result of this study was limited to a smartphone-based AR prototype and a questionnaire-based cross-sectional evaluation conducted within a controlled experimental environment. In addition, engineering-level sensing indicators such as tracking error, registration stability, and system latency were not directly incorporated into the structural model. Future studies will therefore focus on integrating objective sensing-performance metrics, multimodal interaction data, and more diverse AR application scenarios to establish a more comprehensive sensor-enabled evaluation framework for immersive interactive systems.