## 4 Discussion and Implication
### Accuracy Achieved, Advantages, and Practical Implications  
This pilot study demonstrates the feasibility and potential benefits of using a single RTK GNSS receiver to capture step-by-step running parameters in an outdoor environment. By validating the proposed methods against well-established reference systems (3D video and IMUs), we highlight the possibility of obtaining high-resolution data with minimal drift over an entire 400 m sprint. Although we tested only two collegiate athletes, these findings establish a foundation for larger-scale investigations and support the practical application of RTK GNSSs in regular training environments. The high sampling rate and positional accuracy of the RTK GNSS enabled precise estimation of the _SF_, _SL_, and _running velocity_, even at the high speeds characteristic of sprinting events. The RTK GNSS provided centimeter-level accuracy in horizontal positioning, with a reported precision well below 1 cm [18]. This level of precision is critical for capturing the minute variations in stride parameters which occur during high-speed sprints.  
Our findings suggest that the RTK GNSS overcomes the limitations associated with traditional wearable sensors like IMUs and insole sensors, which often face challenges due to cumulative sensor errors and drift over time, especially during high-speed movements [14; 16]. Specifically, in the track segments where 3D camera analysis was conducted (the curved and straight sections), the GNSS-based measurements of the _SF_ and _SL_ showed strong agreement with the camera-based measurements (Table 1, Figure 3A-F). Over the entire 400 m sprint, the GNSS-derived total times closely matched the times recorded by the 2D camera, demonstrating minimal cumulative error, with a 99.95% match for Subject A and a 99.99% match for Subject B. These results indicate that the RTK GNSS maintained consistent accuracy throughout the 400 m distance and effectively addressed the drift issues commonly encountered with IMUs. Unlike IMUs, which can suffer from error accumulation, leading to inaccurate distance measurements over short distances, the RTK GNSS provided stable measurements for both the _SF_ (through precise identification of IC timing) and distance covered (_SL_ and total cumulative distance). This dual capability means that a single GNSS unit can measure timing events (like an IMU) and accurately quantify distance without complex calibration procedures or data processing algorithms [17].  
By measuring the _SL_ at high velocities, accurately detecting foot contact events, and consistently measuring the cumulative distance over an entire sprint, the RTK GNSS approach underscores its potential for robust and reliable performance analysis in real-world training. The absence of drift over the 400 m distance allowed for precise, continuous, and detailed per-step analysis, as illustrated in Figure 6, which captures dynamic changes in running parameters beyond traditional average-based methods [6]. This detailed insight offers significant advantages in optimizing training programs and enhancing athletic performance by providing timely information on running mechanics, fatigue effects, and potential biomechanical asymmetries.  
Compared with prior research utilizing low sampling rate devices [19], our single high sampling rate (100 Hz) RTK GNSS approach effectively overcomes the limitationsof IMU-based systems, such as cumulative errors and drift [14; 15; 16]. This high-frequency GNSS enables the precise calculation of running parameters, including the _SL_ and running velocity, on a per-step basis throughout the entire 400 m sprint, which are capabilities not achievable with existing wearable solutions [9; 10; 11; 13]. By reducing system complexity and eliminating the need for additional devices like IMUs, our method offers a simplified, drift-free solution with a high sampling rate, thereby enhancing both the practicality and accuracy of stride analysis in real-world outdoor training environments.