Performance Evaluation of Cross Correlation Functions Based on Correlation Filters

This paper proposes performance evaluation of cross correlation (CC) functions using signal-to-noise ratio (SNR) and peak-to-correlation energy (PCE) from the viewpoint of correlation filters. Correlation functions can be thought as the output from the correlation filters. Maximizing SNR leads to matched filters, whereas maximizing PCE results in the inverse filters. We derive SNR and PCE of the classical CC functions in order to evaluate their performance as correlation functions.