Robust moving target detection for FDA-MIMO radar with steering vector mismatches

This paper studies a robust moving target detection problem for frequency diverse array multiple-input multiple -output (FDA-MIMO) radar with a target embedded in Gaussian clutter with an unknown covariance matrix. We focus on the case of signal mismatch where the errors exist in the transmit-receive vector and Doppler steering vector. To solve the above detection problem, we adopt the subspace approach, where the true and nominal transmit-receive and Doppler steering vectors are assumed to lie in four-dimensional and two-dimensional subspaces, respectively, for the special framework for FDA-MIMO radar. At the detector design stage, we propose three robust adaptive detectors based on the one-step generalized likelihood ratio test (GLRT), two-step GLRT, and Wald test, respectively, with the training data free. The proposed detectors own the constant false alarm rate (CFAR) property against the clutter covariance matrix. The numerical examples validate the effectiveness of the proposed detectors.

Automated summary

This paper studies the robust moving target detection problem in FDA-MIMO radar with an unknown covariance matrix in Gaussian clutter. The proposed approach adopts the subspace method and proposes three robust adaptive detectors, which are validated to be effective.