Both live and replay paths used the legacy single-PRI extractor with the
LONG-PRI v_res placeholder, which yielded wrong velocities for the SHORT
and MEDIUM sub-frames. PR-Q.5 already provided extract_targets_from_frame_crt
(48-bin, 3-PRI Chinese-Remainder-Theorem unfolding) — this PR wires it in.
Changes:
- workers.py imports extract_targets_from_frame_crt at module scope.
- RadarDataWorker._run_host_dsp delegates to the CRT extractor and then
applies GPS pitch correction + DBSCAN clustering + Kalman tracking
on the returned targets. Inline det_indices loop and
velocity_resolution_long_mps placeholder removed.
- ReplayWorker.__init__ binds _extract_targets to the CRT extractor;
_emit_frame call simplifies to (frame, waveform, gps=).
- 32-bin legacy recordings still work via the CRT extractor's internal
fallback to extract_targets_from_frame.
- Module docstring stale "(64x32)" -> "(512x48)".
- Dropped unused `import numpy as np` from workers.py (no remaining users).
Tests (TestWorkersRouteThroughCrt, +4):
- 3-PRI detection produces CONFIRMED + alias_set (was UNKNOWN before).
- GPS pitch correction applied post-CRT to elevation.
- Both clustering+tracking off → returns [] (no DSP work).
- ReplayWorker._extract_targets is exactly the CRT function reference.
Regression: 232/232 (test_v7 115 + test_GUI_V65_Tk 117). Ruff clean.
Closes audit P-6 / task PR-Q.6 — C-5 host wiring complete (PR-Q.7 dashboard
display column is the remaining piece).
Audit P-1 (2026-05-02): _frame_queue, _acquisition, and frame counters
were stranded inside set_waveform() due to indentation drift. The
dashboard constructs RadarDataWorker and calls .start() directly
without ever calling set_waveform, so live FT2232H acquisition crashes
with AttributeError on first frame access in run().
Move the init block back into __init__; set_waveform now only sets
self._waveform. Add TestRadarDataWorkerInit covering both:
- attrs present after bare __init__ (no set_waveform required)
- set_waveform does not reset runtime counters
Test result: test_v7 102/102 PASS in radar_venv (was 100/100 + 2 new).
cosim_dir revival:
- gen_realdata_hex.py: also emit decimated_range_{i,q}.npy (48x512)
and doppler_map_{i,q}.npy (512x48) at production dimensions; the
same Python pipeline that produces the RTL .hex stimuli now writes
the .npy intermediates v7.replay COSIM_DIR loads. Replaces the
workflow lost when golden_reference.py was deleted in e8b495c
- test_v7.py: update test_get_frame_cosim shape from pre-PR-O.6
(64,32) to (NUM_RANGE_BINS, NUM_DOPPLER_BINS)
- check in 4 .npy reference files (~400 KB, deterministic SCENE_SEED=42)
Ruff lint cleanup (was 66 errors; now 0):
- pyproject.toml: ignore T20 in tb/cosim/**.py (CLI tools)
- compare_independent.py: drop redundant int() casts (RUF046),
swap try/except scipy import for importlib.util.find_spec,
remove dead duplicate np import, ASCII-ize comment unicode,
wrap E501 format strings
- fpga_reference.py: drop unused fs arg from nco_reference,
collapse if/else to ternary, mark _out_im unused
- v7/processing.py: ASCII-ize x in docstring, collapse if-branches
- {dashboard,software_fpga,workers,radar_protocol}.py: wrap E501
- test_v7.py: ASCII-ize comment unicode, _alias renames where unused
Result: test_v7 100/100 (0 skips on radar_venv, was 9 graceful
skips); 5 cosim_dir orphan tests now active and passing.
Refactor v7.WaveformConfig from single-PRI to PR-Q's 3-PRI staggered
ladder (SHORT 175 us / MEDIUM 161 us / LONG 167 us) and update the
host-side bulk-frame parser dimension to match the FPGA's 48-bin
Doppler output (RP_NUM_DOPPLER_BINS = 48). The parser was rejecting
every production frame with n_doppler != 32, masking the PR-F widening
end-to-end.
WaveformConfig:
- pri_short_s/pri_medium_s/pri_long_s replace single pri_s
- n_doppler_bins 32 -> 48; new num_subframes=3
- Per-subframe velocity_resolution_{short,medium,long}_mps
- Per-subframe max_velocity_{short,medium,long}_mps
- extended_max_velocity_mps_crt(K=6) for 3-PRI alias-resolution ceiling
- Drop pri_s, velocity_resolution_mps, max_velocity_mps (no aliases)
Other:
- radar_protocol.NUM_DOPPLER_BINS 32 -> 48 (NUM_CELLS auto 16384 -> 24576;
BULK_FRAME_MAX_SIZE flows from NUM_CELLS, no other edits needed)
- v7/dashboard.py constant + stale "(64x32)" title replaced with f-string
- v7/processing.py 32-bin fallback -> 48
- v7/workers.py: derive doppler_center from frame.shape; LONG-PRI v_res
used as conservative single-PRI placeholder until PR-Q.5 lands the
CRT extractor (markers in place at both call sites)
- test_v7.py: TestWaveformConfig rewritten (8 tests, per-subframe + CRT
extension); TestExtractTargetsFromFrame center 16 -> 24
Local tests:
TestWaveformConfig 8/8 PASS
TestExtractTargetsFromFrame 6/6 PASS
test_GUI_V65_Tk 117/0/2 PASS
RadarDataWorker (live capture path) was converting bin indices to physical
units using RadarSettings placeholders (range_resolution=6.0,
velocity_resolution=1.0). The 1.0 m/s velocity figure was a stub — the
correct value at 167us PRI / 16-chirp sub-frame / 10.5 GHz carrier is
~5.34 m/s, so reported velocities were off by ~5.3x.
ReplayWorker already used WaveformConfig.range_resolution_m and
velocity_resolution_mps; this commit applies the same pattern to the live
worker. WaveformConfig defaults match the AERIS-10 3 km mode parameters.
A set_waveform() hook is provided so the dashboard can swap configs when
range-mode switching is wired through.
Verified: 83/83 v7 GUI tests pass.
- Bandwidth 500 MHz -> 20 MHz, sample rate 4 MHz -> 100 MHz (DDC output)
- Range formula: deramped FMCW -> matched-filter c/(2*Fs)*decimation
- Velocity formula: use PRI (167 us) and chirps_per_subframe (16)
- Carrier frequency: 10.525 GHz -> 10.5 GHz per radar_scene.py
- Range per bin: 4.8 m -> 24 m, max range: 307 m -> 1536 m
- Fix simulator target spawn range to match new coverage (50-1400 m)
- Remove dead BANDWIDTH constant, add SAMPLE_RATE to V65 Tk
- All 174 tests pass, ruff clean
Add SoftwareFPGA class that imports golden_reference functions to
replicate the FPGA pipeline in software, enabling bit-accurate replay
of raw IQ, FPGA co-sim, and HDF5 recordings through the same
dashboard path as live data.
New modules: software_fpga.py, replay.py (ReplayEngine + 3 loaders)
Enhanced: WaveformConfig model, extract_targets_from_frame() in
processing, ReplayWorker with thread-safe playback controls,
dashboard replay UI with transport controls and dual-dispatch
FPGA parameter routing.
Removed: ReplayConnection (from radar_protocol, hardware, dashboard,
tests) — replaced by the unified replay architecture.
150/150 tests pass, ruff clean.
- workers.py: Only emit playbackStateChanged on state transitions to
prevent stale 'playing' signal from overwriting pause button text
- dashboard.py: Force C locale on all QDoubleSpinBox instances so
comma-decimal locales don't break numeric input; add missing
'Saturation' legend label to AGC chart
- map_widget.py: Enable LocalContentCanAccessRemoteUrls and set HTTP
base URL so Leaflet CDN tiles/scripts load correctly in QtWebEngine
State machine fixes:
1. Raw IQ replay EOF now calls _stop_radar() to fully restore UI
2. Worker thread finished signal triggers UI recovery on crash/exit
3. _stop_radar() stops demo simulator to prevent cross-mode interference
4. _stop_demo() correctly identifies Mock mode via combo text
5. Demo start no longer clobbers status bar when acquisition is running
6. _stop_radar() resets playback button text, frame counter, file label
7. _start_raw_iq_replay() error path cleans up stale controller/worker
8. _refresh_gui() preserves Raw IQ paused status instead of overwriting
Map/location:
- RawIQReplayWorker now receives _radar_position (GPSData ref) so
targets get real lat/lon projected from the virtual radar position
- Added heading control to Map tab sidebar (0-360 deg, wrapping)
- Manual lat/lon/heading changes in Map tab apply to replay targets
Ruff clean, 120/120 tests pass.
Add a 4th connection mode to the V7 dashboard that loads raw complex IQ
captures (.npy) and runs the full FPGA signal processing chain in software:
quantize → AGC → Range FFT → Doppler FFT → MTI → DC notch → CFAR.
Implementation (7 steps):
- v7/agc_sim.py: bit-accurate AGC runtime extracted from adi_agc_analysis.py
- v7/processing.py: RawIQFrameProcessor (full signal chain) + shared
extract_targets_from_frame() for bin-to-physical conversion
- v7/raw_iq_replay.py: RawIQReplayController with thread-safe playback
state machine (play/pause/stop/step/seek/loop/FPS)
- v7/workers.py: RawIQReplayWorker (QThread) emitting same signals as
RadarDataWorker + playback state/index signals
- v7/dashboard.py: mode combo entry, playback controls UI, dynamic
RangeDopplerCanvas that adapts to any frame size
Bug fixes included:
- RangeDopplerCanvas no longer hardcodes 64x32; resizes dynamically
- Doppler centre bin uses n_doppler//2 instead of hardcoded 16
- Shared target extraction eliminates duplicate code between workers
Ruff clean, 120/120 tests pass.
