Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
100K - 1M
License:
Commit History
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Verified signatureThe RadPat-50K dataset can be regenerated from first principles using standard array factor formulations. The following procedure was used: 1. Environment Setup Install Python (≥3.9) along with the required packages: numpy, scipy, matplotlib, and pandas. 2. Array Configuration A uniform linear array (ULA) was considered with varying numbers of elements and inter-element spacings. The number of elements was selected from N = {4, 8, 12, 16, 24, 32, 48, 64}. Inter-element spacings were chosen from values such as 0.25λ, 0.5λ, 0.75λ, and 1λ. Steering angles were selected from −60°, −45°, −30°, −15°, 0°, 15°, 30°, 45°, and 60°. 3. Weighting Schemes Multiple excitation tapers were applied to control sidelobe levels and beamwidth. The following weighting functions were used: uniform, binomial, cosine, Kaiser, Hamming, Hann, Blackman, and exponential. 4. Pattern Computation For each configuration, the array factor was computed and radiation patterns were generated in both rectangular (dB vs. an…65f23b8