A new signal adaptive approach to positive time-frequency distributions with suppressed interference terms

Quadratic time varying-spectral analysis methods that achieve a high resolution jointly in time and frequency generally suffer from interference terms that obscure the true location of the auto components in the resulting time-frequency representation. Unfortunately, there is no general mathematical model available for an exact distinction between cross-terms and auto-terms. Consequently an attempt to suppress interference can only rely on a few qualitative properties which are commonly associated with cross terms. Most of the reduced interference distributions that have been developed so far exploit the fact that cross terms tend to oscillate and can hence be suppressed by a properly chosen two-dimensional low pass filter. Besides the fact that cross-terms oscillate, they are also known to be responsible for all negative density values of a time-frequency distribution. None of the currently existing methods addresses this characteristic. In this paper we introduce an entirely new approach that achieves a significant interference reduction by specifically exploiting the negative density structure of cross-terms