I would like to ask what could be the easiest way to detect the presence and beginning (no more, no less) of under-damped harmonic signal in a collect of ultrasound data. I have some acquired data which is presented in 2-D image form, where vertical axis are related with time. Under-damped harmonic signal, which I need to detect, looks like here, but of course it is noised.
I would like to detect presence of this kind of signal automatically. Currently I've developed algorithm, which calculates short-time Fourier transform for every vertical line of image, collect values of five the most often frequencies for every short-time window, and chooses the vertical line with the most harmonically nature - with the most repeated frequencies. Unfortunately in this solution every time one of the line is chosen. I can use some kind of threshold for sure, but i don't think so it's good solution. However, it isn't the most important problem - my algorithm calculate which line has under-damped harmonic signal, no where it starts. Second problem is that this solution is too slow for my purpose - 20 times per second.
I have tried to make my own research but solutions like Kalman filter, or estimation by least squares method, in my opinion, it's like attempting to kill ant by tank - I need smaller caliber method. Currently I don't need to know features of signal like values of angular frequencies and amplitudes.
Any ideas signal-processing community? Thanks in advance.