Time-Frequency Multi-Invariance ESPRIT for DOA Estimation

In this letter, a new ESPRIT-type algorithm is presented for estimating the direction of arrival (DOA). We reconstruct the received signal to form a time-frequency
$(t{\hbox{-}}f)$
data model with a multi-invariance (MI) property, and then a
$t{\hbox{-}}f$
MI Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) algorithm for DOA estimation is proposed. This algorithm constructs a spatial
$t{\hbox{-}}f$
distribution matrix in terms of variable temporal and frequency points and combines multiple subarrays rearranged from a uniform linear array (ULA) to estimate far-field narrowband signals. Considering the model of multiple narrowband chirp sources, simulation results illustrate that
$t{\hbox{-}}f$
MI-ESPRIT outperforms
$t{\hbox{-}}f$
ESPRIT and MI-ESPRIT under different signal-to-noise ratio (SNR) and snapshot numbers.