Highly Accurate Multi-Invariance ESPRIT for DOA Estimation with a Sparse Array

Abstract EN

This paper proposes a multi-invariance ESPRIT-based method for estimation of 2D direction (MIMED) of multiple non-Gaussian monochromatic signals using cumulants.

In the MIMED, we consider an array geometry containing sparse L-shaped diversely polarized vector sensors plus an arbitrarily-placed single polarized scalar sensor.

Firstly, we define a set of cumulant matrices to construct two matrix blocks with multi-invariance property.

Then, we develop a multi-invariance ESPRIT-based algorithm with aperture extension using the defined matrix blocks to estimate two-dimensional directions of the signals.

The MIMED can provide highly accurate and unambiguous direction estimates by extending the array element spacing beyond a half-wavelength.

Finally, we present several simulation results to demonstrate the superiority of the MIMED.