Abstract
Cross-correlation is an accurate method which can be used to find time shift between two signals. However, this method necessitates a high usage of microcontroller (MCU) resources. This situation occurs in a microprocessor system dedicated to evaluate speed values of cars driving on roads. Cross-correlation and the other computational methods aiming to use a reduced amount of operations on sampled data are discussed. The accuracy of the evaluated speed as well as the execution time of the program code are presented for each method. The usage of the centers of mass in two discrete signals as a speed detection method resulted in the root mean square error up to 3 times larger in comparison with the cross-correlation method. Finally, the combination of two methods was used: center of mass?for designating result quickly and then cross-correlation with a limited lag range. This sped up the MCU program code execution 15-70 times and it provided good speed evaluation accuracy.
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