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We study the problem of estimating the frequencies of several complexsinusoids with constant amplitude (CA) (also called constant modulus) frommultichannel signals of their superposition. To exploit the CA property forfrequency estimation in the framework of atomic norm minimization (ANM), weintroduce multiple positive-semidefinite block matrices composed of Hankel andToeplitz submatrices and formulate the ANM problem as a convex structuredlow-rank approximation (SLRA) problem. The proposed SLRA is a semidefiniteprogramming and has substantial differences from existing such formulationswithout using the CA property. The proposed approach is termed as SLRA-basedANM for CA frequency estimation (SACA). We provide theoretical guarantees andextensive simulations that validate the advantages of SACA.

Multichannel Frequency Estimation with Constant Amplitude via Convex Structured Low-Rank Approximation