Abstract
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.
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