  We study the problem of estimating the frequencies of several complex
sinusoids with constant amplitude (CA) (also called constant modulus) from
multichannel signals of their superposition. To exploit the CA property for
frequency estimation in the framework of atomic norm minimization (ANM), we
introduce multiple positive-semidefinite block matrices composed of Hankel and
Toeplitz submatrices and formulate the ANM problem as a convex structured
low-rank approximation (SLRA) problem. The proposed SLRA is a semidefinite
programming and has substantial differences from existing such formulations
without using the CA property. The proposed approach is termed as SLRA-based
ANM for CA frequency estimation (SACA). We provide theoretical guarantees and
extensive simulations that validate the advantages of SACA.
