研究目的
Investigating the adaptation of the least-square solution for frequency invariant beamforming to arbitrary planar arrays, focusing on decoupling spatial and spectral constraints for steerable beamforming.
研究成果
The paper successfully extends the frequency invariant least square algorithm to generic planar arrays, demonstrating the method's applicability through examples of squared and spiral arrays. Future research will explore the effects of noise on the condition number and further investigate steering properties for azimuth and elevation.
研究不足
The method exhibits trade-offs between high and low frequency resolution and may show abnormalities in beam pattern symmetry and gain for certain array designs. The condition number of the matrix (??????+????)??????? varies with frequency, indicating potential convergence issues at low frequencies.
1：Experimental Design and Method Selection:
The study employs a least-square solution for frequency invariant beamforming, utilizing spherical harmonics polynomials to decouple spatial and spectral constraints.
2：Sample Selection and Data Sources:
The methodology is applied to arbitrary planar arrays, with examples given for squared and spiral array geometries.
3：List of Experimental Equipment and Materials:
The implementation is numerically performed in Matlab?, focusing on the computation of basis functions and optimal coefficients for frequency invariant response.
4：Experimental Procedures and Operational Workflow:
The array response is approximated using virtual sensor modeling, transforming planar arrays into virtual linear sensors for independent azimuth and elevation steering.
5：Data Analysis Methods:
The condition number of the matrix (??????+????)??????? is analyzed versus frequency to assess the method's performance.
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