Spatial filtering is used for real-time velocity measurement due to its computational efficiency. However, this method can be noisy in real measurement environments, requiring the averaging of a substantial number of measurements to achieve reliable results, which compromises temporal resolution. This study proposes enhancing the spatial filtering algorithm by implementing Kalman filtering for pipe flow profile measurements. Kalman filtering is expected to mitigate the noise issue more effectively than traditional methods like low-pass filtering while maintaining or improving the temporal resolution of measurements.
No takes yet. Share an insight, caveat, or question.
Otto et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: