  This paper proposes a super-resolution harmonic retrieval method for
uncorrelated strictly non-circular signals, whose covariance and
pseudo-covariance present Toeplitz and Hankel structures, respectively.
Accordingly, the augmented covariance matrix constructed by the covariance and
pseudo-covariance matrices is not only low rank but also jointly
Toeplitz-Hankel structured. To efficiently exploit such a desired structure for
high estimation accuracy, we develop a low-rank Toeplitz-Hankel covariance
reconstruction (LRTHCR) solution employed over the augmented covariance matrix.
Further, we design a fitting error constraint to flexibly implement the LRTHCR
algorithm without knowing the noise statistics. In addition, performance
analysis is provided for the proposed LRTHCR in practical settings. Simulation
results reveal that the LRTHCR outperforms the benchmark methods in terms of
lower estimation errors.
