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 stochastic optimization algorithm effectively generates low-sidelobe beamforming weights for poorly calibrated phased array antennas, with modifications significantly speeding up convergence time. The method is practical for real-time in-flight calibration, achieving good results in simulation.
研究不足
The algorithm requires a strong clutter return in the sidelobe region for calibration and may need recalibration due to component drift or replacement. The performance is dependent on the relative scaling properties of the independent variables over which the optimization is performed.
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 and observes ground clutter during flight.
3：List of Experimental Equipment and Materials:
Airborne, electronically-steered phased-array radar with digital control for weights applied to each antenna element.
4：Experimental Procedures and Operational Workflow:
The algorithm iteratively adjusts beamformer weights until sidelobe clutter power is at or near the noise floor, using a new CPI of data collection for each evaluation.
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.
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