Time-Frequency Signal Representations using Interpolations in Joint-Variable Domains

Abstract-Time-frequency representations are a powerful tool for analyzing Doppler and microDoppler signals. These signals are frequently encountered in various radar applications. Data interpolators play a unique role in time-frequency signal representations under missing samples. When applied in the instantaneous autocorrelation domain over the time variable, the low-pass filter characteristic underlying linear interpolators lends itself to cross-terms reduction in the ambiguity domain. This is in contrast to interpolation performed over the lag variable or a direct interpolation of the raw data. We demonstrate the interpolator performance in both the time-domain and time-lag domain and compare it with sparse signal reconstruction, which exploits the local sparsity property assumed by most Doppler radar signals