Real-time Corrections to Multiple Channel Response Functions for Time-Correlating Transient Data

Interpretation of observed phenomena from time series is often complicated by measured quantities being only indirect indicators of a system's state. Information about a system may be filtered by properties of the transmission medium, or by the manner inwhich the information is collected. Multiple time series, though possibly concurrent, may be acquired differently, with different averaging or delay effects that render them unsuitable to be combined into more direct measures of the system's state. We willapply multichannel time series analysis to develop response function identification techniques to synchronize feedback data in real time. We propose to benchmark these techniques under simulated environments, including short-burst data transmission oradaptive flow control in a wind tunnel testing environment. Techniques that are found to be the most widely applicable and most robust will be considered for accuracy and speed improvements.The Phase I technical objectives are: (1) Develop software implementations of time delay and time scale compensation techniques to synchronize multichannel data, and (2) Benchmark the compensation techniques for speed, accuracy, and robustness. Thecompleted objectives will provide a basis for selecting accurate and robust algorithms for military and commercial applications.Wind tunnel testing; flight test systems; communication systems; image restoration.