feat: CI test suite phases A+B, WaveformConfig separation, dead golden code cleanup
- Phase A: Remove self-blessing golden test from FPGA regression, wire MF co-sim (4 scenarios) into run_regression.sh, add opcode count guards to cross-layer tests (+3 tests) - Phase B: Add radar_params.vh parser and architectural param consistency tests (+7 tests), add banned stale-value pattern scanner (+1 test) - Separate WaveformConfig.range_resolution_m (physical, bandwidth-dependent) from bin_spacing_m (sample-rate dependent); rename all callers - Remove 151 lines of dead golden generate/compare code from tb_radar_receiver_final.v; testbench now runs structural + bounds only - Untrack generated MF co-sim CSV files, gitignore tb/golden/ directory CI: 256 tests total (168 python + 40 cross-layer + 27 FPGA + 21 MCU), all green
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@@ -169,7 +169,7 @@ class RadarDataWorker(QThread):
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The FPGA already does: FFT, MTI, CFAR, DC notch.
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Host-side DSP adds: clustering, tracking, geo-coordinate mapping.
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Bin-to-physical conversion uses RadarSettings.range_resolution
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Bin-to-physical conversion uses RadarSettings.range_bin_spacing
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and velocity_resolution (should be calibrated to actual waveform).
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"""
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targets: list[RadarTarget] = []
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@@ -180,7 +180,7 @@ class RadarDataWorker(QThread):
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# Extract detections from FPGA CFAR flags
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det_indices = np.argwhere(frame.detections > 0)
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r_res = self._settings.range_resolution
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r_res = self._settings.range_bin_spacing
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v_res = self._settings.velocity_resolution
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for idx in det_indices:
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@@ -559,7 +559,7 @@ class ReplayWorker(QThread):
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# Target extraction
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targets = self._extract_targets(
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frame,
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range_resolution=self._waveform.range_resolution_m,
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bin_spacing=self._waveform.bin_spacing_m,
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velocity_resolution=self._waveform.velocity_resolution_mps,
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gps=self._gps,
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)
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