CARLA ? C-Shenron based Simualtor for Sensor data generation.
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<title>C-Shenron Physics Architecture Deep-Dive</title>
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<div class="subtitle">Radar Physics Engine v4.2</div>
<h1>C-Shenron Deep Architecture</h1>
<p>From Raw LiDAR Scents to Synthetic FMCW Realities</p>
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<div class="pipeline-grid">
<div class="step-card">
<div class="step-num">01</div>
<div class="step-title">Scene Ingestion</div>
<p>Converts raw Semantic LiDAR into physical material properties. Vehicles become <span class="highlight">High-Permittivity Metal</span>, Foliage becomes <span class="highlight">Diffuse Carbon</span>.</p>
<div class="code-snippet">map_carla_semantic_lidar_latest()<br>→ Recovered Tags via .view(np.uint32)</div>
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<div class="step-num step-num-alt">02</div>
<div class="step-title">Physics Modeling</div>
<p>Calculates the <span class="highlight">Fresnel Reflection</span> loss based on incident angles. Handles Specular (mirror) vs Diffuse (scattering) coefficients.</p>
<div class="code-snippet">Sceneset.specularpoints()<br>Pr = (Pt * G² * λ² * σ) / ((4π)³ * R⁴)</div>
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<div class="step-card">
<div class="step-num">03</div>
<div class="step-title">FMCW Synthesis</div>
<p>Synthesizes raw Analog-to-Digital samples. Models the <span class="highlight">Beat Frequency</span> ($f_{beat}$) across multiple Rx antennas & chirps.</p>
<div class="code-snippet">heatmap_gen_fast.py<br>signal = exp(j * 2π * f_beat * t)</div>
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<div class="step-num">04</div>
<div class="step-title">DSP Pipeline</div>
<p>Processes the raw signal through Range/Doppler FFTs and <span class="highlight">CA-CFAR Detection</span> to generate the final synthetic PointCloud.</p>
<div class="code-snippet">RadarProcessor.cal_doppler_fft()<br>N=256, Np=128 (Configurable)</div>
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<div class="debug-section">
<h2>⚡ Today's Optimization Discoveries</h2>
<p style="color: var(--text-secondary); margin-bottom: 30px;">Summary of the hardware-to-model alignment fixes applied in Iteration 05.</p>
<div class="debug-grid">
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<h3>Detected Failure</h3>
<p>The <b>'Cos(Cos)' Bug</b> in Sceneset.py. The engine was calculating <i>np.cos(angles)</i> on values that were already cosines. <b>Result:</b> 46% energy loss on every bounce.</p>
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<div class="fix-box">
<h3>Engineering Fix</h3>
<p>Removed the double-dampening logic. Physics engine now correctly interprets incident angles from CARLA, restoring realistic metallic RCS signatures.</p>
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<div class="bug-box">
<h3>Detected Failure</h3>
<p>The <b>'Stationary Reality' Bug</b>. Moving targets appeared stationary or dragged behind the car. <b>Result:</b> Radial velocity was being zeroed out due to incorrect bit-interpretations.</p>
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<div class="fix-box">
<h3>Engineering Fix</h3>
<p>Synchronized World-Pose and LiDAR-Tick via <i>recorder.py</i> update. High-fidelity Doppler detection now tracks dynamic NPC movement at 64Hz.</p>
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<h2>🛠️ Hardware Support Matrix</h2>
<div class="table-container">
<table>
<thead>
<tr>
<th>Radar Model</th>
<th>Frequency</th>
<th>Chirps (Np)</th>
<th>Samples (N)</th>
<th>Logic Layer</th>
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</thead>
<tbody>
<tr>
<td><span class="highlight">AWRL1432 BOOST</span></td>
<td>77-81 GHz</td>
<td>128</td>
<td>256</td>
<td><span class="tag tag-physics">Rich Physics</span></td>
</tr>
<tr>
<td><span class="highlight">TI Cascade Array</span></td>
<td>77-81 GHz</td>
<td>3 (Fast)</td>
<td>256</td>
<td><span class="tag tag-signal">Phase-Prime</span></td>
</tr>
<tr>
<td><span class="highlight">Generic Radarbook</span></td>
<td>24 GHz</td>
<td>128</td>
<td>256</td>
<td><span class="tag tag-physics">Standard</span></td>
</tr>
</tbody>
</table>
</div>
<footer>
Fox CARLA ADAS Simulation Project | Automated Sync by Antigravity AI<br>
© 2026 SHENRON INTEGRATION LOGS
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