研究目的
To compute a set of low-sidelobe beamforming weights for an airborne, electronically-steered phased-array radar using an in-flight stochastic optimization routine.
研究成果
The proposed iterative clutter calibration (ICC) method effectively computes low-sidelobe beamforming weights for airborne phased-array radars without relying on precise antenna calibration. The method is computationally inexpensive and scales well to large arrays, making it practical for in-flight calibration.
研究不足
The algorithm requires a strong clutter return in the sidelobe region for effective calibration. The performance may vary depending on the homogeneity of the ground clutter environment.
1：Experimental Design and Method Selection:
The methodology involves an iterative stochastic optimization routine performed over a number of coherent processing intervals (CPIs) to adjust beamforming weights based on observed radar ground clutter.
2：Sample Selection and Data Sources:
The algorithm uses digitized radar sum beam data from in-flight measurements of ground clutter.
3：List of Experimental Equipment and Materials:
Airborne, electronically-steered phased-array radar with digital control for the weights applied to each antenna element on transmit and receive.
4：Experimental Procedures and Operational Workflow:
The algorithm iteratively adjusts the beamformer weights until the sidelobe clutter power is at or near the noise floor, using a stochastic optimization algorithm (SPSA) for rapid convergence.
5：Data Analysis Methods:
The objective function is based on an estimate of signal-to-clutter-plus-noise-ratio (SCNR), with modifications to ensure rapid convergence of the SPSA algorithm.
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