Time-frequency multitaper methods applied to rumble strip noise

Spectral estimation techniques are important tools in different fields of acoustics such as speech processing or traffic noise. In traffic noise typically conventional techniques are used such as third octave band filterbanks and long term averages. Certain situations where e.g. the acoustical events are short and have strong tonal components may, however, require more sophisticated methods of analysis. An example of such a situation are rumble strips which are a safety measure to keep cars from running off the road. Rumble strips typically consist of grooves milled at regular intervals next to the outermost traffic lanes, i.e. on the hard shoulder. Thus, when a vehicle passes over the grooves a signal with strong tonal components is produced which should warn the driver from the imminent danger of running of the road. Here, the potential of different multitaper methods is investigated using a recording of a car passing over such a rumble strip. The main interest is whether the tonal components can be reliably detected. In multitaper approaches the time-frequency analysis is performed using different orthogonal window functions. The time-frequency representations for each window are then combined to form a single estimate of the spectrum. To detect the tonal parts, different approaches using either the conventional multitaper method as well as combining multitaper with reassignment or synchrosqueezing are investigated. The comparison is done using either simple combinations of the modified spectrograms or applying random projections to the multiple short-term Fourier transforms before the reassignment/synchrosqueezing as recently suggested. The results illustrate that the different methods applied in this work are well suited for the analysis of the rumble strip data.