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feat(physics): Implement true 1/R^4 radar range equation via area integration and millimeter phase jitter
feat(physics): Implement true 1/R^4 radar range equation via area integration and millimeter phase jitter
This physics engine overhaul introduces two major fidelity upgrades to the Shenron pipeline: 1. Physical Area Integration: Tethers incident power natively to the solid angle expanding physical area (dTheta*dPhi*R^2) ensuring cross-section energy output scales independently of LiDAR point cloud resolution. 2. Millimeter Jitter: Maps physical property roughness (e.g., 5mm concrete, 50um metal) as a sub-wavelength Gaussian distance distorter. This fractures the 'perfect mathematical mirror' bug inherent to flat CARLA meshes by substituting naive coherent summation (N^2) with physical diffuse Rayleigh scattering (N). Includes addition of interactive 3-slide HTML and dark-mode simulation presentation decks for project reporting.main
5 changed files with 808 additions and 3 deletions
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23scripts/ISOLATE/e2e_agent_sem_lidar2shenron_package/shenron/Sceneset.py
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</head> |
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<body> |
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<!-- Slide 1: Title --> |
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<div class="slide slide-title"> |
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<div class="company-logo">FOX <span style="color:var(--text-main);">ADAS</span></div> |
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<div style="background: rgba(255,255,255,0.7); padding: 60px; border-radius: 24px; backdrop-filter: blur(10px); border: 2px solid white; box-shadow: 0 10px 40px rgba(0,0,0,0.05);"> |
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<h1>High-Fidelity Deterministic<br><span class="highlight">Radar Simulation</span></h1> |
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<p>Moving from bounding-box emulation to mathematically pure, hardware-configurable physics validating the Shenron Pipeline.</p> |
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</div> |
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</div> |
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<!-- Slide 2: The Vision & Physical Approach --> |
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<div class="slide"> |
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<h2>The Physical Foundation: 1/R⁴ Physics</h2> |
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<div class="body-grid-2"> |
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<div> |
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<p>Standard simulator bounding-boxes bypass the complex realities of electromagnetic propagation. The Shenron engine enforces strict free-space physics for absolute accuracy.</p> |
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<div class="card" style="margin-bottom: 30px;"> |
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<h3><i class="card-icon fa-solid fa-bolt"></i> Milestone R4: Pure Physics</h3> |
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<p>We abandoned artificial density and distance normalizations. All generated scatterers now strictly follow the <span class="bold highlight">Radar Range Equation (1/R⁴)</span>. A building at distance naturally drops in power compared to a vehicle up close.</p> |
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</div> |
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<div class="card"> |
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<h3><i class="card-icon fa-solid fa-car-burst"></i> Deterministic Coordinate Control</h3> |
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<p>Standard Traffic Manager leads to high variance. Using a <span class="bold">Spawn-and-Move</span> logic with enforced Velocity overrides guarantees complex scenarios (like left-turn cut-ins) occur at the exact same millisecond every run.</p> |
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<div> |
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<i class="fa-solid fa-atom"></i> |
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<div class="title">Insert Screenshot: 1/R⁴ Contrast</div> |
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<div class="instructions">Provide a side-by-side or CFAR output showing how distant heavy clutter is naturally attenuated while the closer vehicle is correctly highlighted due to the inverse square law path loss.</div> |
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</div> |
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<!-- Slide 3: Unprecedented Configurability --> |
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<h2>Unprecedented Configurability: "Knobs & Dials"</h2> |
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<div class="body-grid-2"> |
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<div> |
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<p>The Shenron architecture eliminates hardcoded physical scalars. Instead, it exposes a "Control Panel" mimicking real hardware tuning. <span class="bold">If we do it on the test track, we can do it in the simulation.</span></p> |
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<h3>Supported Hardware Profiles</h3> |
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<div style="margin-bottom: 20px;"> |
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<span class="tag">TI AWRL1432 (ADAS)</span> |
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<span class="tag">Radarbook (Research)</span> |
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<span class="tag">TI Cascade (MIMO)</span> |
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</div> |
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<ul style="margin-top: 30px;"> |
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<li><span class="highlight">Bandwidth (B) & Chirps:</span> Accurately adjust range and doppler resolution directly reflecting radar specifications.</li> |
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<li><span class="highlight">System Gain Calibration (110dB):</span> Modify the global signal chain gain ($P_t G_t G_r$) without touching the core physics engine.</li> |
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<li><span class="highlight">Antenna Arrays (nRx/nTx):</span> Instantly swap between 6 virtual receivers (1432) or 8 virtual receivers (Radarbook) to measure DSP beamforming limits.</li> |
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<li><span class="highlight">Noise Amplitude:</span> Dynamically inject AWGN thermal noise to test CFAR floor robustness.</li> |
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</ul> |
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</div> |
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<div> |
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<div class="title">Insert Code/UI Screenshot: Customizing Radar</div> |
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<div class="instructions">Please insert a screenshot showing `ConfigureRadar.py` or the specific JSON payload being passed via the dashboard to demonstrate how easily we swap between a 1432 profile and a Radarbook profile.</div> |
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</div> |
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</div> |
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</div> |
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</div> |
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<!-- Slide 4: Deep Observability & Metrology --> |
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<div class="slide"> |
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<h2>Deep Observability: The Metrology Suite</h2> |
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<div class="body-grid-2"> |
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<div> |
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<p>Instead of treating synthetic radar output as a "black box," our new pipeline visualizes the entire signal chain. This allows engineers to cross-validate ADC output against physical ground truth.</p> |
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<div class="alert-box success"> |
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<h4>The "Radar Blue" Standard</h4> |
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<p>We instituted phase-preserving <span class="bold">Doppler-Slice Synthesis</span> to replace artifact-heavy coherent integration, resulting in pristine, sharp heatmaps.</p> |
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</div> |
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<ul> |
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<li><span class="bold">Range-Doppler (RD):</span> Extracts target separation and velocity, preventing velocity zeroing.</li> |
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<li><span class="bold">Range-Azimuth (RA):</span> Confirms azimuthal accuracy utilizing Zero-Tilt Symmetry (120° FOV perfectly aligned to boresight).</li> |
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<li><span class="bold">CFAR Gate:</span> Visualizes adaptive thresholds distinguishing targets from the synthesized noise floor.</li> |
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</ul> |
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</div> |
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<div> |
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<div class="image-placeholder"> |
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<i class="fa-solid fa-layer-group"></i> |
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<div class="title">Insert Screenshot: 3-Plot Metrology Suite</div> |
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<div class="instructions">Insert a screenshot of the Foxglove layout showing the 3 core metrology graphs (RD, RA, and CFAR) running alongside the 3D Pointcloud view to illustrate deep observability.</div> |
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</div> |
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</div> |
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</div> |
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</div> |
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<!-- Slide 5: Major Breakthroughs & Bug Squashing Engine --> |
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<div class="slide"> |
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<h2>Major Breakthroughs & Bug Squashing Engine</h2> |
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<p>Achieving this level of physical simulation required identifying and tearing down several legacy miscalculations that corrupted early models.</p> |
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<div class="body-grid-2"> |
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<div class="card"> |
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<h3><i class="fa-solid fa-satellite-dish"></i> The Isotropic Illumination Fix</h3> |
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<p>The deepest physics problem resolved. Early simulation allowed side-targets at 80° to return 100% power, masking forward vehicles. <br><br>We implemented <span class="highlight">Horizontal (Azimuth) & Vertical (Elevation) Directional Gain Patterns</span>. Clutter at wide angles is now correctly attenuated by ~15-20 dB, letting the true target dominate.</p> |
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</div> |
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<div class="card" style="display: flex; gap: 20px; flex-direction: column;"> |
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<div> |
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<h4><i class="fa-solid fa-bug" style="color:var(--color-danger); margin-right:8px;"></i> The Cos(Cos) Reflection Error</h4> |
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<p style="font-size:22px; margin-bottom:0;">Recovered 46% of lost signal energy by tracking down a double-cosine application in the Open3D coordinate translation pipeline.</p> |
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</div> |
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<div style="height:1px; background:var(--border-light); width:100%;"></div> |
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<div> |
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<h4><i class="fa-solid fa-bug" style="color:var(--color-danger); margin-right:8px;"></i> Floating Point Data Packing</h4> |
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<p style="font-size:22px; margin-bottom:0;">Resolved the infamous "0.0 velocity" bug by utilizing `np.view(np.uint32)` to correctly deserialize perfectly packed 32-bit semantic tags.</p> |
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</div> |
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</div> |
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</div> |
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<!-- Slide 6: The Full Automation Pipeline --> |
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<div class="slide"> |
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<h2>The Full Automation Pipeline</h2> |
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<p>A completely automated workflow enabling one-click testbenches, fully orchestrated via a web dashboard.</p> |
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<div class="image-placeholder horizontal" style="background-image: linear-gradient(rgba(248, 250, 252, 0.9), rgba(248, 250, 252, 0.9)), url('assets/pipeline_bg.png'); background-size: cover; background-position: center;"> |
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<i class="fa-solid fa-network-wired" style="color: var(--accent-primary);"></i> |
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<div class="title">Insert Graphic/Screenshot: Pipeline & Dashboard</div> |
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<div class="instructions" style="color:var(--text-main);"> |
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Place a diagram or screenshot here showing the flow:<br><br> |
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<b>1. GUI Dashboard (with Hardware GPU Idle Mode)</b> → <b>2. CARLA Simulator</b> → <b>3. Shenron Physics</b> → <b>4. MCAP Serializer</b> → <b>5. Foxglove Studio</b> |
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</div> |
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</div> |
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<div style="margin-top: 40px; text-align: center;"> |
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<p>From deterministic scenario configuration to a 3D Foxglove validation pointcloud — without manual intervention.</p> |
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<title>3 Slide Fox ADAS Presentation</title> |
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|
flex-direction: column; |
||||
|
align-items: center; |
||||
|
padding: 40px 0; |
||||
|
gap: 40px; |
||||
|
} |
||||
|
|
||||
|
/* 1800x900 Rigid Container */ |
||||
|
.slide { |
||||
|
width: 1800px; |
||||
|
height: 900px; |
||||
|
background: linear-gradient(170deg, var(--slide-bg-top) 0%, var(--slide-bg-bottom) 100%); |
||||
|
border: 1px solid rgba(255, 255, 255, 0.1); |
||||
|
position: relative; |
||||
|
display: flex; |
||||
|
flex-direction: column; |
||||
|
padding: 80px 120px; |
||||
|
overflow: hidden; |
||||
|
flex-shrink: 0; |
||||
|
} |
||||
|
|
||||
|
/* Inner subtle glow line behind title */ |
||||
|
.slide::before { |
||||
|
content: ''; |
||||
|
position: absolute; |
||||
|
top: 200px; |
||||
|
left: 100px; |
||||
|
right: 100px; |
||||
|
height: 1px; |
||||
|
background: linear-gradient(90deg, transparent, rgba(255,255,255,0.4), transparent); |
||||
|
} |
||||
|
|
||||
|
/* Typography */ |
||||
|
h1 { |
||||
|
font-size: 64px; |
||||
|
font-weight: 700; |
||||
|
color: var(--accent-yellow); |
||||
|
margin-bottom: 70px; |
||||
|
} |
||||
|
|
||||
|
.white-text { color: var(--text-main); } |
||||
|
|
||||
|
h3 { font-size: 32px; font-weight: 600; margin-bottom: 20px; color: var(--text-main); } |
||||
|
p { font-size: 26px; line-height: 1.6; color: var(--text-secondary); margin-bottom: 20px; } |
||||
|
|
||||
|
/* Lists */ |
||||
|
ul { list-style: none; padding: 0; margin-bottom: 40px;} |
||||
|
li { |
||||
|
font-size: 28px; |
||||
|
line-height: 1.5; |
||||
|
color: var(--text-main); |
||||
|
margin-bottom: 30px; |
||||
|
display: flex; |
||||
|
align-items: flex-start; |
||||
|
gap: 15px; |
||||
|
} |
||||
|
|
||||
|
li i { |
||||
|
color: var(--text-main); |
||||
|
font-size: 30px; |
||||
|
margin-top: 5px; |
||||
|
background: rgba(255,255,255,0.1); |
||||
|
padding: 6px; |
||||
|
border-radius: 50%; |
||||
|
border: 2px solid var(--accent-yellow); |
||||
|
color: var(--accent-yellow); |
||||
|
} |
||||
|
|
||||
|
.li-desc { |
||||
|
font-size: 22px; |
||||
|
color: var(--text-secondary); |
||||
|
margin-top: 8px; |
||||
|
display: block; |
||||
|
} |
||||
|
|
||||
|
/* ----- Slide 1 Elements ----- */ |
||||
|
.s1-grid { |
||||
|
display: flex; |
||||
|
height: 100%; |
||||
|
flex-direction: column; |
||||
|
} |
||||
|
|
||||
|
.s1-images { |
||||
|
display: flex; |
||||
|
gap: 40px; |
||||
|
margin-top: auto; |
||||
|
justify-content: flex-start; |
||||
|
height: 350px; |
||||
|
} |
||||
|
|
||||
|
.img-box { |
||||
|
flex: 1; |
||||
|
background: rgba(0,0,0,0.5); |
||||
|
border: 2px solid rgba(255,255,255,0.2); |
||||
|
position: relative; |
||||
|
display: flex; |
||||
|
align-items: center; |
||||
|
justify-content: center; |
||||
|
color: rgba(255,255,255,0.5); |
||||
|
font-size: 24px; |
||||
|
} |
||||
|
|
||||
|
.img-caption { |
||||
|
position: absolute; |
||||
|
bottom: -40px; |
||||
|
width: 100%; |
||||
|
text-align: center; |
||||
|
font-size: 24px; |
||||
|
font-weight: 600; |
||||
|
color: var(--text-main); |
||||
|
} |
||||
|
|
||||
|
/* ----- Slide 2 Elements ----- */ |
||||
|
.s2-flow { |
||||
|
display: flex; |
||||
|
align-items: center; |
||||
|
justify-content: space-between; |
||||
|
margin-top: 40px; |
||||
|
margin-bottom: 60px; |
||||
|
background: rgba(255,255,255,0.03); |
||||
|
padding: 30px; |
||||
|
border-radius: 12px; |
||||
|
border: 1px solid rgba(255,255,255,0.05); |
||||
|
} |
||||
|
|
||||
|
.flow-node { |
||||
|
text-align: center; |
||||
|
display: flex; |
||||
|
flex-direction: column; |
||||
|
align-items: center; |
||||
|
gap: 15px; |
||||
|
flex: 1; |
||||
|
} |
||||
|
|
||||
|
.flow-node .label { |
||||
|
font-size: 24px; |
||||
|
font-weight: 600; |
||||
|
} |
||||
|
|
||||
|
.flow-arrow i { |
||||
|
color: var(--accent-yellow); |
||||
|
font-size: 40px; |
||||
|
} |
||||
|
|
||||
|
.flow-box { |
||||
|
width: 250px; |
||||
|
height: 150px; |
||||
|
background: rgba(0,0,0,0.4); |
||||
|
border: 1px solid rgba(255,255,255,0.2); |
||||
|
display: flex; |
||||
|
align-items: center; |
||||
|
justify-content: center; |
||||
|
font-size: 20px; |
||||
|
color: rgba(255,255,255,0.5); |
||||
|
} |
||||
|
|
||||
|
.s2-bullets { |
||||
|
display: flex; |
||||
|
flex-direction: column; |
||||
|
align-items: center; |
||||
|
gap: 25px; |
||||
|
margin-top: 40px; |
||||
|
} |
||||
|
|
||||
|
.s2-bullet-line { |
||||
|
display: flex; |
||||
|
align-items: center; |
||||
|
width: 80%; |
||||
|
gap: 20px; |
||||
|
} |
||||
|
|
||||
|
.s2-bullet-line::before, .s2-bullet-line::after { |
||||
|
content: ''; |
||||
|
flex-grow: 1; |
||||
|
height: 1px; |
||||
|
background: rgba(255,255,255,0.3); |
||||
|
} |
||||
|
|
||||
|
.s2-bullet-text { |
||||
|
font-size: 32px; |
||||
|
font-weight: 600; |
||||
|
text-align: center; |
||||
|
} |
||||
|
|
||||
|
.s2-bullet-subtext { |
||||
|
font-size: 20px; |
||||
|
color: var(--text-secondary); |
||||
|
text-align: center; |
||||
|
font-weight: 400; |
||||
|
width: 80%; |
||||
|
margin: 0 auto; |
||||
|
margin-top: -15px; |
||||
|
margin-bottom: 10px; |
||||
|
} |
||||
|
|
||||
|
/* ----- Slide 3 Elements ----- */ |
||||
|
.s3-header { |
||||
|
text-align: center; |
||||
|
margin-bottom: 100px; |
||||
|
} |
||||
|
|
||||
|
.s3-cards { |
||||
|
display: grid; |
||||
|
grid-template-columns: 1fr 1fr 1fr; |
||||
|
gap: 40px; |
||||
|
margin-bottom: 80px; |
||||
|
} |
||||
|
|
||||
|
.s3-card { |
||||
|
background: linear-gradient(180deg, rgba(255,255,255,0.08) 0%, rgba(255,255,255,0.02) 100%); |
||||
|
border-top: 2px solid rgba(255,255,255,0.2); |
||||
|
border-left: 1px solid rgba(255,255,255,0.05); |
||||
|
border-right: 1px solid rgba(255,255,255,0.05); |
||||
|
border-bottom: 2px solid rgba(0,0,0,0.5); |
||||
|
padding: 40px 30px; |
||||
|
display: flex; |
||||
|
flex-direction: column; |
||||
|
align-items: center; |
||||
|
box-shadow: 0 20px 40px rgba(0,0,0,0.5); |
||||
|
} |
||||
|
|
||||
|
.card-icon-top { |
||||
|
background: linear-gradient(135deg, #2563eb, #1d4ed8); |
||||
|
width: 60px; |
||||
|
height: 60px; |
||||
|
display: flex; |
||||
|
align-items: center; |
||||
|
justify-content: center; |
||||
|
border-radius: 8px; |
||||
|
margin-bottom: 30px; |
||||
|
border: 2px solid rgba(255,255,255,0.5); |
||||
|
transform: translateY(-70px); |
||||
|
position: absolute; |
||||
|
} |
||||
|
.card-icon-top i { color: white; font-size: 30px; } |
||||
|
|
||||
|
.s3-card h3 { |
||||
|
font-size: 32px; |
||||
|
text-align: center; |
||||
|
min-height: 80px; |
||||
|
margin-top: 20px; |
||||
|
} |
||||
|
|
||||
|
.s3-card ul { |
||||
|
width: 100%; |
||||
|
margin-top: 20px; |
||||
|
margin-bottom: 0; |
||||
|
} |
||||
|
|
||||
|
.s3-card li { |
||||
|
font-size: 20px; |
||||
|
margin-bottom: 20px; |
||||
|
display: flex; |
||||
|
align-items: flex-start; |
||||
|
gap: 15px; |
||||
|
} |
||||
|
|
||||
|
.s3-card li::before { |
||||
|
content: '•'; |
||||
|
color: var(--accent-yellow); |
||||
|
font-size: 30px; |
||||
|
line-height: 20px; |
||||
|
} |
||||
|
.s3-card li i { display: none; } |
||||
|
|
||||
|
.s3-footer { |
||||
|
text-align: center; |
||||
|
font-size: 32px; |
||||
|
font-weight: 600; |
||||
|
margin-top: auto; |
||||
|
color: var(--text-secondary); |
||||
|
} |
||||
|
.s3-footer span { color: var(--accent-yellow); } |
||||
|
|
||||
|
</style> |
||||
|
</head> |
||||
|
<body> |
||||
|
|
||||
|
<!-- Slide 1: Deterministic ADAS Simulation --> |
||||
|
<div class="slide"> |
||||
|
<h1>Deterministic ADAS Simulation</h1> |
||||
|
|
||||
|
<div class="s1-grid"> |
||||
|
<ul> |
||||
|
<li> |
||||
|
<i class="fa-solid fa-check"></i> |
||||
|
<div> |
||||
|
From Random to Repeatable Deterministic Scenarios |
||||
|
<span class="li-desc">Bypassing Traffic Manager variance, we utilize direct `set_target_velocity` coordinate control to guarantee exact "Spawn-and-Move" maneuvers—such as cut-ins—execute flawlessly at the same millisecond every run.</span> |
||||
|
</div> |
||||
|
</li> |
||||
|
<li> |
||||
|
<i class="fa-solid fa-check"></i> |
||||
|
<div> |
||||
|
Unprecedented Physics-Accurate Radar Simulation |
||||
|
<span class="li-desc">Standard bounding boxes fail complex realities. We returned to the laws of electromagnetism, implementing true 1/R⁴ power-decay physics and material-based Fresnel reflections.</span> |
||||
|
</div> |
||||
|
</li> |
||||
|
<li> |
||||
|
<i class="fa-solid fa-check"></i> |
||||
|
<div> |
||||
|
Real-Time Multi-Sensor Metrology |
||||
|
<span class="li-desc">Synchronously tracking RGB, LiDAR, and phase-preserving Doppler-Slice Radar data perfectly aligned at 30 FPS for visual ground truth comparison.</span> |
||||
|
</div> |
||||
|
</li> |
||||
|
</ul> |
||||
|
|
||||
|
<div class="s1-images"> |
||||
|
<div class="img-box" style="width: 700px;"> |
||||
|
[ Insert Image: CARLA RGB/Game View ] |
||||
|
<div class="img-caption">CARLA Simulation</div> |
||||
|
</div> |
||||
|
<div class="img-box" style="width: 700px;"> |
||||
|
[ Insert Image: Radar Heatmap (Foxglove) ] |
||||
|
<div class="img-caption">Shenron Radar</div> |
||||
|
</div> |
||||
|
</div> |
||||
|
</div> |
||||
|
</div> |
||||
|
|
||||
|
|
||||
|
<!-- Slide 2: Physics-Based Shenron Engine --> |
||||
|
<div class="slide"> |
||||
|
<h1><span class="white-text">Shenron:</span> Physics-Based Radar Engine</h1> |
||||
|
|
||||
|
<div class="s2-flow"> |
||||
|
<div class="flow-node"> |
||||
|
<div class="label">CARLA & Synchronizer</div> |
||||
|
<div class="flow-box">[ Graphic or Logo ]</div> |
||||
|
</div> |
||||
|
|
||||
|
<div class="flow-arrow"><i class="fa-solid fa-arrow-right"></i></div> |
||||
|
|
||||
|
<div class="flow-node"> |
||||
|
<div class="label">Shenron Physics Engine</div> |
||||
|
<div class="flow-box">[ CPU/GPU Graphic ]</div> |
||||
|
</div> |
||||
|
|
||||
|
<div class="flow-arrow"><i class="fa-solid fa-arrow-right"></i></div> |
||||
|
|
||||
|
<div class="flow-node"> |
||||
|
<div class="label">Radar Signal Processing</div> |
||||
|
<div class="flow-box">[ Heatmap / DSP ]</div> |
||||
|
</div> |
||||
|
|
||||
|
<div class="flow-arrow"><i class="fa-solid fa-arrow-right"></i></div> |
||||
|
|
||||
|
<div class="flow-node"> |
||||
|
<div class="label">ADAS-Ready Output</div> |
||||
|
<div class="flow-box">[ Point Cloud / MCAP ]</div> |
||||
|
</div> |
||||
|
</div> |
||||
|
|
||||
|
<div class="s2-bullets"> |
||||
|
<div class="s2-bullet-line"> |
||||
|
<div class="s2-bullet-text">1/R⁴ Accurate Spatial Decay Physics</div> |
||||
|
</div> |
||||
|
<div class="s2-bullet-subtext">Dropped artificial density variables. Reflected energy now strictly attenuates by the inverse square law, forcing massive background structures to cede dominance to near-field targets.</div> |
||||
|
|
||||
|
<div class="s2-bullet-line"> |
||||
|
<div class="s2-bullet-text">Directional Antenna Pattern Modeling</div> |
||||
|
</div> |
||||
|
<div class="s2-bullet-subtext">Resolved the "Isotropic Illumination" limit by implementing true Azimuth & Elevation gain logic. Radar blind-spots act realistically, attenuating 80° side-wall clutter by ~20dB.</div> |
||||
|
|
||||
|
<div class="s2-bullet-line"> |
||||
|
<div class="s2-bullet-text">Modular Hardware-Matched Pipeline</div> |
||||
|
</div> |
||||
|
<div class="s2-bullet-subtext">The "Knobs and Dials" philosophy completely separates base physics from simulation parameters. Easily swap profiles between AWRL1432, Radarbook, and MIMO Cascade hardware.</div> |
||||
|
</div> |
||||
|
</div> |
||||
|
|
||||
|
|
||||
|
<!-- Slide 3: Validation --> |
||||
|
<div class="slide"> |
||||
|
<div class="s3-header"> |
||||
|
<h1 style="margin-bottom: 0;">From <span class="white-text">Simulation</span> to Validation</h1> |
||||
|
</div> |
||||
|
|
||||
|
<div class="s3-cards"> |
||||
|
<!-- Card 1 --> |
||||
|
<div class="s3-card" style="position: relative;"> |
||||
|
<div class="card-icon-top"><i class="fa-solid fa-check"></i></div> |
||||
|
<h3>Physics-Driven<br>Metrology Accuracy</h3> |
||||
|
<ul> |
||||
|
<li>Zero-Tilt Symmetry guarantees 120° FOV precision right down the boresight.</li> |
||||
|
<li>Doppler-Slice phase continuity resolves standard blur, delivering sharp "Radar Blue" PointCloud clusters.</li> |
||||
|
</ul> |
||||
|
</div> |
||||
|
|
||||
|
<!-- Card 2 --> |
||||
|
<div class="s3-card" style="position: relative;"> |
||||
|
<div class="card-icon-top"><i class="fa-solid fa-check"></i></div> |
||||
|
<h3>Real-World Hardware<br>Calibration Logic</h3> |
||||
|
<ul> |
||||
|
<li>110dB System Gain tuning aligns exact radar spec hardware profiles.</li> |
||||
|
<li>Modifiable Bandwidth (B), Chirp Repetition, and virtual receiver sets to replicate DSP behavior dynamically.</li> |
||||
|
</ul> |
||||
|
</div> |
||||
|
|
||||
|
<!-- Card 3 --> |
||||
|
<div class="s3-card" style="position: relative;"> |
||||
|
<div class="card-icon-top"><i class="fa-solid fa-check"></i></div> |
||||
|
<h3>Automated Core<br>Testing Platform</h3> |
||||
|
<ul> |
||||
|
<li>GUI Dashboard orchestrating idle-mode GPU utilization for Shenron rendering safely.</li> |
||||
|
<li>Direct pipeline translating serialized JSONL/NPY data into FOXGLOVE MCAP standards.</li> |
||||
|
</ul> |
||||
|
</div> |
||||
|
</div> |
||||
|
|
||||
|
<div class="s3-footer"> |
||||
|
Bridging the <span>Gap</span> from Research to Real-World Deployment |
||||
|
</div> |
||||
|
</div> |
||||
|
|
||||
|
</body> |
||||
|
</html> |
||||
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