A Novel Method for Beampattern Synthesis With Auto-Determined Minimum Mainlobe Width

This communication presents a beampattern synthesis method with auto-determined minimum mainlobe width named reweighted domino norm and spectral factorization (RD-SF). To improve the computational efficiency, a RD- l₁ norm is constructed to solve monotonic sparse optimization problems without monotonicity constraints. In addition, a spectral factorization (SF)-based method without rank 1 constraint is also used to solve the nonconvex constraints of shaped beampattern. On the basis of RD-SF method, we utilize a two-step spatial response variation (SRV) scheme to synthesize frequency-invariant (FI) broadband beampattern. It is regarded as the broadband version of the RD-SF method, named RD-SF-broadband (RD-SF-B). This scheme avoids redundant SRV constraints while maintaining an undistorted mainlobe. Moreover, the approximation error does not need to be set. Simulation results are shown to verify the effectiveness of our proposed algorithm.