fix: regenerate golden hex for dual-16pt Doppler and add real-data TBs to regression

Regenerate all real-data golden reference hex files against the current
dual 16-point FFT Doppler architecture (staggered-PRI sub-frames).
The old hex files were generated against the previous 32-point single-FFT
architecture and caused 2048/2048 mismatches in both strict real-data TBs.

Changes:
- Regenerate doppler_ref_i/q.hex, fullchain_doppler_ref_i/q.hex, and all
  downstream golden files (MTI, DC notch, CFAR) via golden_reference.py
- Add tb_doppler_realdata (exact-match, ADI CN0566 data) to regression
- Add tb_fullchain_realdata (exact-match, decim->Doppler chain) to regression
- Both TBs now pass: 2048/2048 bins exact match, MAX_ERROR=0
- Update CI comment: 23 -> 25 testbenches
- Fill in STALE_NOTICE.md with regeneration instructions

Regression: 25/25 pass, 0 fail, 0 skip. ruff check: 0 errors.

.github/workflows/ci-tests.yml

@@ -67,7 +67,7 @@ jobs:
         working-directory: 9_Firmware/9_1_Microcontroller/tests
 
   # ===========================================================================
-  # FPGA RTL Regression (23 testbenches + lint)
+  # FPGA RTL Regression (25 testbenches + lint)
   # ===========================================================================
   fpga-regression:
     name: FPGA Regression

9_Firmware/9_2_FPGA/run_regression.sh

@@ -403,6 +403,18 @@ run_test "DDC Chain (NCO→CIC→FIR)" \
     tb/tb_ddc_cosim.v ddc_400m.v nco_400m_enhanced.v \
     cic_decimator_4x_enhanced.v fir_lowpass.v cdc_modules.v
 
+# Real-data co-simulation: committed golden hex vs RTL (exact match required).
+# These catch architecture mismatches (e.g. 32-pt → dual 16-pt Doppler FFT)
+# that self-blessing golden-generate/compare tests cannot detect.
+run_test "Doppler Real-Data (ADI CN0566, exact match)" \
+    tb/tb_doppler_realdata.vvp \
+    tb/tb_doppler_realdata.v doppler_processor.v xfft_16.v fft_engine.v
+
+run_test "Full-Chain Real-Data (decim→Doppler, exact match)" \
+    tb/tb_fullchain_realdata.vvp \
+    tb/tb_fullchain_realdata.v range_bin_decimator.v \
+    doppler_processor.v xfft_16.v fft_engine.v
+
 if [[ "$QUICK" -eq 0 ]]; then
     # Golden generate
     run_test "Receiver (golden generate)" \

9_Firmware/9_2_FPGA/tb/cosim/real_data/hex/STALE_NOTICE.md

@@ -0,0 +1,42 @@
+# Golden Reference Hex Files
+
+These hex files are **committed golden references** for strict bit-exact
+real-data regression tests (`tb_doppler_realdata.v`, `tb_fullchain_realdata.v`).
+
+## When to regenerate
+
+Regenerate whenever the Doppler processing pipeline changes:
+
+- `doppler_processor.v` (FFT size, window, sub-frame structure)
+- `xfft_16.v` / `fft_engine.v` (butterfly arithmetic, twiddle lookup)
+- `range_bin_decimator.v` (decimation mode, peak detection logic)
+- `fft_twiddle_16.mem` (twiddle factor ROM)
+
+## How to regenerate
+
+```bash
+cd 9_Firmware/9_2_FPGA
+python3 tb/cosim/real_data/golden_reference.py
+# Then copy the Doppler-specific files:
+python3 -c "
+import numpy as np, os, shutil
+h = 'tb/cosim/real_data/hex'
+# Regenerate packed stimulus from range FFT npy
+ri = np.load(f'{h}/range_fft_all_i.npy')
+rq = np.load(f'{h}/range_fft_all_q.npy')
+with open(f'{h}/doppler_input_realdata.hex','w') as f:
+    for c in range(32):
+        for r in range(64):
+            i=int(ri[c,r])&0xFFFF; q=int(rq[c,r])&0xFFFF
+            f.write(f'{(q<<16)|i:08X}\n')
+shutil.copy2(f'{h}/doppler_map_i.hex', f'{h}/doppler_ref_i.hex')
+shutil.copy2(f'{h}/doppler_map_q.hex', f'{h}/doppler_ref_q.hex')
+"
+```
+
+## Architecture
+
+Generated against the **dual 16-point FFT** Doppler architecture
+(2 staggered-PRI sub-frames x 16-point Hamming-windowed FFT).
+
+Source data: ADI CN0566 Phaser radar (10.525 GHz X-band FMCW, 4 MSPS).

9_Firmware/9_2_FPGA/tb/cosim/real_data/hex/detections.txt

@@ -1,291 +1,361 @@
 # AERIS-10 Golden Reference Detections
 # Threshold: 10000
 # Format: range_bin doppler_bin magnitude
-0 0 44371
+0 0 35364
-0 1 24165
+0 1 16147
-0 31 17748
+0 15 11821
-1 0 34391
+0 16 24536
-1 1 17923
+0 17 11208
-1 31 18610
+0 31 10122
-2 0 28512
+1 0 25697
-2 1 13818
+1 1 12174
-2 31 15787
+1 15 13421
-3 0 47402
+1 16 20002
-3 1 25214
+1 17 11568
-3 31 23504
+1 31 11299
-4 0 51870
+2 0 16788
-4 1 32733
+2 16 20207
-4 31 31545
+2 31 10711
-5 0 31752
+3 0 29174
-5 1 13486
+3 1 13965
-5 31 19300
+3 15 13305
-6 0 63406
+3 16 31517
-6 1 33383
+3 17 13478
-6 31 36672
+3 31 14101
-7 0 37576
+4 0 41986
-7 1 21215
+4 1 19241
-7 31 27773
+4 15 21030
-8 0 14823
+4 16 39714
-10 0 30062
+4 17 17538
-10 1 13616
+4 31 20394
-10 31 17149
+5 0 23766
+5 1 11599
+5 15 14843
+5 16 18211
+5 31 12009
+6 0 42015
+6 1 21423
+6 15 21018
+6 16 47402
+6 17 22815
+6 31 22736
+7 0 32152
+7 1 15393
+7 15 14318
+7 16 28911
+7 17 13876
+7 31 17156
+8 0 11067
+10 0 18848
+10 15 10020
+10 16 20027
+10 31 10048
 11 0 65534
-11 1 60963
+11 1 37617
-11 2 14848
+11 2 14940
-11 3 12082
+11 15 43078
-11 4 18060
+11 16 65534
-11 29 10045
+11 17 39344
-11 30 20661
+11 31 45926
-11 31 65536
+12 0 58975
-12 0 65536
+12 1 22078
-12 1 44569
+12 15 34440
-12 4 11189
+12 16 59096
-12 30 13936
+12 17 22512
-12 31 57036
+12 31 28677
-13 0 47038
+13 0 38442
-13 1 40212
+13 1 29490
-13 2 14655
+13 15 37679
-13 4 10242
+13 16 44951
-13 30 14945
+13 17 27726
-13 31 40237
+13 31 39144
-14 0 65534
+14 0 52660
-14 1 43568
+14 1 27797
-14 3 10974
+14 2 13534
-14 4 11491
+14 15 39671
-14 30 15272
+14 16 57929
-14 31 57983
+14 17 24160
-15 0 34501
+14 31 31478
-15 1 22496
+15 0 30021
-15 31 25197
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-16 0 32784
+15 15 17232
-16 1 19309
+15 16 29524
-16 31 14005
+15 17 13424
-17 0 23063
+15 31 17850
-17 1 13730
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-18 0 17087
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-18 1 12092
+16 31 13046
-19 0 65535
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-19 1 49084
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-19 2 11399
+17 16 13182
-19 30 13119
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-19 31 48411
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-20 0 65509
+19 1 29069
-20 1 37881
+19 15 29418
-20 31 35014
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-21 0 39614
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-21 1 23389
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-21 31 22417
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-22 31 15278
+20 16 45472
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+20 17 21749
-23 1 29247
+20 31 21614
-23 31 33561
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-24 31 20937
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-25 1 54580
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-25 2 20278
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-25 31 59445
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-26 0 58162
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-26 1 46544
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-26 3 10127
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-26 31 44711
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 27 0 65535
 27 1 65535
-27 2 44599
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-27 3 17124
+27 16 65535
-27 28 15139
+27 17 65535
-27 29 26067
+27 31 58334
-27 30 54631
-27 31 65535
 28 0 65535
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-28 2 43056
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-28 3 14647
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-28 4 11808
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-28 29 15256
-28 30 50518
 28 31 65535
 29 0 65535
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-29 2 28859
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-29 3 19523
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-29 4 21765
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-29 5 12687
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-29 27 13175
+29 17 45898
-29 28 19619
+29 18 10817
-29 29 24365
+29 31 60442
-29 30 48682
+30 0 44530
-29 31 65535
+30 1 36909
-30 0 55399
+30 2 14573
-30 1 46683
+30 15 43430
-30 2 21192
+30 16 51839
-30 3 15905
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-30 4 18003
+30 31 47866
-30 29 11105
+31 0 40957
-30 30 22360
+31 1 52081
-30 31 40830
+31 2 12755
-31 0 46504
+31 15 42794
-31 1 44346
+31 16 41071
-31 2 34200
+31 17 50472
-31 3 20677
+31 18 11556
-31 4 18570
+31 31 43866
-31 5 10430
+32 0 35747
-31 29 12684
+32 1 19597
-31 30 31778
+32 15 25173
-31 31 36195
+32 16 39213
-32 0 39540
+32 17 21782
-32 1 36657
+32 31 29106
-32 31 35394
+33 0 34216
-33 0 35482
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-33 1 32886
+33 15 42368
-33 2 15041
+33 16 38638
-33 28 10103
+33 17 40522
-33 29 11617
+33 31 45908
-33 30 17465
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-33 31 34603
+34 1 17165
-34 0 47950
+34 15 16488
-34 1 25855
+34 16 26972
-34 31 23198
+34 17 12089
+34 31 13576
 35 0 65536
-35 1 63059
+35 1 42536
-35 2 24416
+35 15 61612
-35 30 27412
+35 16 65536
-35 31 65534
+35 17 43084
-36 0 65535
+35 31 60807
-36 1 41914
+36 0 55831
-36 2 11341
+36 1 26499
-36 30 11276
+36 15 28393
-36 31 41419
+36 16 50059
-38 0 63253
+36 17 24420
-38 1 46689
+36 31 23905
-38 2 13576
+38 0 52721
-38 30 14208
+38 1 33692
-38 31 49979
+38 15 32463
-39 0 33480
+38 16 53145
-39 1 25439
+38 17 37178
-39 31 23094
+38 31 30632
-40 0 52003
+39 0 32288
-40 1 47059
+39 1 19461
-40 2 13164
+39 15 20183
-40 31 37992
+39 16 27198
+39 17 16723
+39 31 14041
+40 0 47793
+40 1 29861
+40 15 23082
+40 16 43109
+40 17 30298
+40 31 31219
 41 0 65536
-41 1 65534
+41 1 57642
-41 2 25844
+41 15 52984
-41 3 14580
+41 16 65536
-41 4 12743
+41 17 57420
-41 30 22231
+41 31 57035
-41 31 65534
+42 0 46393
-42 0 52097
+42 1 24862
-42 1 45022
+42 15 27123
-42 2 10317
+42 16 44734
-42 28 11984
+42 17 25836
-42 29 10182
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-42 30 13078
+43 0 65535
-42 31 40477
+43 1 43056
-43 0 61723
+43 13 10481
-43 1 48104
+43 14 22074
-43 2 17623
+43 15 24792
-43 3 10105
+43 16 39506
-43 28 28331
+43 17 36481
-43 29 24102
+43 30 24870
-43 31 45085
+43 31 39062
 44 0 65535
 44 1 65535
-44 2 60795
+44 2 19166
-44 3 25438
+44 3 21321
-44 27 39330
+44 13 32864
-44 28 60025
+44 14 41461
-44 29 52445
+44 15 65535
-44 30 35091
+44 16 65535
+44 17 58493
+44 19 13967
+44 29 29756
+44 30 54069
 44 31 65535
 45 0 65535
-45 1 65535
+45 1 58886
-45 2 27652
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-45 3 14416
+45 15 65116
-45 4 10622
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-45 27 16323
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-45 28 40935
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-45 31 65535
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-46 2 14924
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 58 0 65535
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+58 1 35008
-58 2 14110
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-59 29 12652
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-62 31 18083
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-63 1 40428
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-63 28 11884
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-63 29 13271
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-63 30 14869
+62 17 11146
-63 31 52574
+62 31 10180
+63 0 58324
+63 1 25269
+63 15 32920
+63 16 54165
+63 17 27625
+63 31 29816

9_Firmware/9_2_FPGA/tb/cosim/real_data/hex/fullchain_cfar_det.hex

@@ -76,22 +76,50 @@
 0
 0
 0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
 1
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
 1
 1
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
+0
 1
 0
 0
@@ -2018,31 +2046,3 @@
 0
 0
 0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0

9_Firmware/9_2_FPGA/tb/cosim/real_data/hex/fullchain_cfar_detections.txt

@@ -2,7 +2,7 @@
 # Chain: decim -> MTI -> Doppler -> DC notch(w=2) -> CA-CFAR
 # CFAR: guard=2, train=8, alpha=0x30, mode=CA
 # Format: range_bin doppler_bin magnitude threshold
-2 27 40172 38280
+2 14 57128 48153
-2 28 65534 40749
+2 29 20281 15318
-2 29 58080 31302
+2 30 44783 22389
-2 30 16565 13386
+3 26 19423 19422

9_Firmware/9_2_FPGA/tb/cosim/real_data/hex/fullchain_detections.txt

@@ -2,188 +2,210 @@
 # Threshold: 10000
 # Format: range_bin doppler_bin magnitude
 0 0 65534
-0 1 59350
+0 1 28729
-0 2 16748
+0 2 18427
-0 4 18802
+0 3 14971
-0 29 10539
+0 14 11972
-0 30 18526
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-0 31 65536
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+0 31 45926
 1 0 65535
 1 1 65535
-1 2 37002
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-1 4 12412
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-1 5 14956
+1 10 10505
-1 6 12586
+1 12 12931
-1 7 11607
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-1 8 11379
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-1 24 11725
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-1 28 17218
+1 17 65535
-1 29 32939
+1 31 55887
-1 30 58888
-1 31 65535
 2 0 65535
 2 1 65535
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-2 3 25438
+2 3 21321
-2 27 39330
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-2 28 60025
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-2 30 35091
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+2 19 13967
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 2 31 65535
-3 0 65535
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-11 31 24250
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-12 1 14298
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-12 31 13970
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-13 0 13062
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-20 0 47569
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-20 1 33826
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-20 31 35752
+11 15 12669
-21 0 47804
+11 16 30129
-21 1 21420
+11 17 14340
-21 31 30292
+11 31 12767
-22 0 14968
+12 0 12892
-26 0 16086
+12 16 15956
-26 31 10462
+13 16 10903
-30 0 16628
+17 0 11395
-30 1 10044
+17 16 10440
-38 0 23453
+19 0 11910
-38 1 13989
+19 16 12017
-38 31 10672
+20 0 42212
-39 0 31656
+20 1 17994
-39 1 17367
+20 15 23540
-39 31 17314
+20 16 42519
-40 0 19156
+20 17 15949
-40 1 10817
+20 31 23792
-40 31 10083
+21 0 19822
-45 0 25385
+21 2 13933
-45 1 11685
+21 3 12130
-45 31 14673
+21 13 11590
-46 0 12576
+21 14 14794
-46 4 10141
+21 15 14160
-46 28 12358
+21 16 36543
-47 0 19657
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