feat(shenron): gain recalibration and visualization stability

- [Radar Cfg] Increase gain by +10dB (110dB -> 120dB) for all radar models in ConfigureRadar.py
- [Root Cause] Compensate for the SNR drop caused by restoring the 1/R^4 physics law (Iteration 37), which removed the artificial R^2 area boost and made RD maps 'hazy' or 'out of focus'.

- [Viz] Update SYSTEM_GAIN_OFFSET from 68.0 to 78.0 in plots.py and test_shenron.py
- [Viz] Increase dynamic range clipping ceiling from 45dB to 55dB
- [Root Cause] Prevents RA heatmap saturation. The +10dB gain increase caused signals to hit the previous 45dB hard-clip ceiling, making the dynamic plots look identical to the static ones (blown out).

scripts/ISOLATE/e2e_agent_sem_lidar2shenron_package/ConfigureRadar.py

@@ -25,7 +25,7 @@ class radar():
             self.chirps = 3  # 128
             self.nRx = 86 #16  # number of antennas(virtual antennas included, AOA dim)
             self.noise_amp = 0.005  #0.0001(concrete+metal)  # 0.00001(metal) #0.005(after skyward data)
-            self.gain = 10 ** (110 / 10) # Calibrated for Iteration 16
+            self.gain = 10 ** (120 / 10) # Recalibrated (+10dB) to compensate for 1/R^4 physics fix (Iteration 37)
             self.angle_fft_size = 256
 
             self.range_res = self.c / (2 * self.B)  # range resolution
@@ -70,7 +70,7 @@ class radar():
             self.chirps = 128
             self.nRx = 8  # number of antennas(virtual antennas included, AOA dim)
             self.noise_amp = 0.005  
-            self.gain = 10 ** (110 / 10) # Calibrated for Iteration 16
+            self.gain = 10 ** (120 / 10) # Recalibrated (+10dB) to compensate for 1/R^4 physics fix (Iteration 37)
             self.angle_fft_size = 256
 
             self.range_res = self.c / (2 * self.B)  # range resolution
@@ -115,7 +115,7 @@ class radar():
             self.chirps = 128    # Increased to match 2TX MIMO frame depth for 3dB processing gain
             self.nRx = 6 
             self.noise_amp = 0.005
-            self.gain = 10 ** (110 / 10) # Calibrated for Iteration 16
+            self.gain = 10 ** (120 / 10) # Recalibrated (+10dB) to compensate for 1/R^4 physics fix (Iteration 37)
             self.angle_fft_size = 256
 
             self.range_res = self.c / (2 * self.B)

scripts/ISOLATE/sim_radar_utils/plots.py

@@ -104,11 +104,16 @@ def postprocess_ra(ra_heatmap, range_axis, smooth_sigma=1.0):
     ra = np.clip(ra, 1e-9, None)
 
     # 2. Physics-based dynamic range compression (Linear -> Log)
-    SYSTEM_GAIN_OFFSET = 68.0 
+    # SYSTEM_GAIN_OFFSET: Accounts for the absolute scale of the simulated signal.
+    # Must be updated when radar.gain changes. Formula: 10*log10(gain) - reference_offset
+    # Baseline: gain=10^(110/10) -> offset=68.0
+    # After +10dB recalibration: gain=10^(120/10) -> offset=78.0
+    SYSTEM_GAIN_OFFSET = 78.0
     ra_db = 10 * np.log10(ra) - SYSTEM_GAIN_OFFSET
     
-    # 3. Fixed dynamic range clipping (-5 to 45 dB)
-    ra_db = np.clip(ra_db, -5, 45)
+    # 3. Fixed dynamic range clipping (-5 to 55 dB)
+    # Upper limit raised from 45 to 55 dB to provide headroom after gain recalibration.
+    ra_db = np.clip(ra_db, -5, 55)
 
     # 4. Optional Gaussian smoothing
     if smooth_sigma > 0:

scripts/test_shenron.py

@@ -309,7 +309,7 @@ def run_testbench(iter_name):
             render_engines[r_type] = {
                 'rd': FastHeatmapEngine(extent=[-max_vel_cfg, max_vel_cfg, 0, max_r_cfg], cmap='viridis', title=f'{r_type.upper()} Range-Doppler', xlabel='Doppler Velocity [m/s]', ylabel='Range [m]', ylim=[0, 120], interpolation='bicubic'),
                 'cfar': FastHeatmapEngine(extent=[-max_vel_cfg, max_vel_cfg, 0, max_r_cfg], cmap='plasma', title=f'{r_type.upper()} CFAR Noise Threshold', xlabel='Doppler Velocity [m/s]', ylabel='Range [m]', ylim=[0, 120], interpolation='bicubic'),
-                'ra_static': FastHeatmapEngine(extent=[-display_limit_cfg, display_limit_cfg, 0, display_limit_cfg], cmap='jet', vmin=-5, vmax=45, title=f'{r_type.upper()} Range-Azimuth (Absolute)', xlabel='Lateral distance [m]', ylabel='Longitudinal distance [m]', aspect='equal'),
+                'ra_static': FastHeatmapEngine(extent=[-display_limit_cfg, display_limit_cfg, 0, display_limit_cfg], cmap='jet', vmin=-5, vmax=55, title=f'{r_type.upper()} Range-Azimuth (Absolute)', xlabel='Lateral distance [m]', ylabel='Longitudinal distance [m]', aspect='equal'),
                 'ra_dyn': FastHeatmapEngine(extent=[-display_limit_cfg, display_limit_cfg, 0, display_limit_cfg], cmap='jet', title=f'{r_type.upper()} Range-Azimuth (Dynamic)', xlabel='Lateral distance [m]', ylabel='Longitudinal distance [m]', aspect='equal')
             }
 
@@ -433,7 +433,7 @@ def run_testbench(iter_name):
                         rd_data = np.load(rd_p)
                         # Apply log conversion minus identical system gain offset to maintain -5 to 45 scaling
                         # Simple 10*log10 - SYSTEM_GAIN_OFFSET
-                        rd_db = 10 * np.log10(np.clip(rd_data, 1e-9, None)) - 68.0 
+                        rd_db = 10 * np.log10(np.clip(rd_data, 1e-9, None)) - 78.0  # Updated offset: +10dB from gain recalibration
                         
                         # Flip UD so Range 0 (ego) is at the bottom. Use Cached Renderer.
                         b64 = render_engines[r_type]['rd'].render(np.flipud(rd_db))