📡RadPat-50K: A Large-Scale Benchmark for Antenna Array Radiation Patterns

📡 RadPat-50K: A Large-Scale Benchmark for Antenna Array Radiation Patterns RadPat-50K is a large-scale synthetic dataset of 50,000 radiation patterns generated for Uniform Linear Arrays (ULA).Each sample includes polar plots and rectangular plots of the array factor, along with metadata for design and performance parameters. 📊 Dataset Highlights Size: 50,000 radiation patterns Array Elements (N): 4, 8, 12, 16, 24, 32, 48, 64 Element Spacing (λ): 0.25, 0.5, 0.75, 1.0 Steering Angles (°): –60, –45, –30, –15, 0, 15, 30, 45, 60 Weighting Schemes: Uniform Binomial Cosine Kaiser Hamming Hann Blackman Exponential Variations (for diversity): ⚡ Amplitude noise 📐 Phase noise 🎯 Steering jitter 🔬 Applications This dataset is well-suited for research in machine learning, deep learning, and signal processing, including: 📑 Antenna pattern classification 🎛️ Beamforming analysis 🚨 Grating lobe detection 🏗️ Data-driven array design 🧾 Metadata per Record Each radiation pattern entry includes: Antenna parameters: number of elements, element spacing, steering angle, weighting scheme Noise parameters: amplitude noise, phase noise, steering jitter 🧾 Performance Metrics 📡 Directivity 📏 Half-Power Beamwidth (HPBW) 📐 Main Lobe Angle 🤖 Benchmark Potential RadPat-50K provides a standardized benchmark for: Training and evaluating classification & regression models Developing robust antenna array designs under noise conditions Advancing AI-driven RF and antenna research