Joint Estimation of Frequency, 2D Direction of Arrival, and Polarization Using Minimum Constraint Arrays

Minimum constraint arrays enable joint estimation of frequency, two-dimensional direction of arrival, and polarization parameters, making this approach widely applicable in signal processing systems. The minimum constraint array method represents an array signal processing technique capable of achieving precise signal estimation and analysis. A key advantage lies in its ability to extract meaningful information from signals while simultaneously mitigating noise interference. Implementation typically involves constructing optimal array geometries and applying covariance matrix processing with eigenvalue decomposition to separate signal subspaces. The algorithm often incorporates ESPRIT or MUSIC-based techniques for parameter extraction, where code implementation would require careful calibration of array manifolds and polarization sensitivity patterns. This efficient signal processing technique finds extensive applications in radar systems, communication networks, and acoustic wave analysis domains, particularly where multi-parameter estimation from limited sensor arrays is essential.