KEYWORDS: Polarization, Polarimetry, Time-frequency analysis, Sensors, Signal processing, Matrices, Interference (communication), Array processing, Antennas, Signal to noise ratio
Time-frequency distributions (TFDs) have evolved to be a powerful
technique for nonstationary signal analysis and synthesis. With
the use of a multi-sensor array, spatial time-frequency
distributions (STFDs) have been developed and successfully applied
to high-resolution direction-of-arrival (DOA) estimation and blind
recovery of the source waveforms. In this paper, the polarimetric
dimension is introduced to the STFDs resulting in the spatial
polarimetric time-frequency distributions (SPTFDs) as a platform
for the processing of non-stationary polarized signals. In the
SPTFD platform, polarized signals are decomposed (projected) into
two orthogonal polarization components, such as horizontal and
vertical, and later processed in a manner where their polarization
characteristics are exploited. This empowers the STFDs with
additional degrees of freedom and improves the robustness of the
signal and noise subspaces, and therefore, serving to enhance DOA
estimation, signal recovery, and source separation performance. To
demonstrate the advantages of the SPTFDs, the polarimetric
time-frequency MUSIC (PTF-MUSIC) method for DOA estimation is
proposed based on the SPTFD platform and is shown to outperform
the time-frequency, polarimetric, and conventional MUSIC methods.
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