fix: range calibration, demo/radar mutual exclusion, AGC analysis refactor

Bug #1 — Range calibration for Raw IQ Replay:
- Add WaveformConfig dataclass (models.py) with FMCW waveform params
  (fs, BW, T_chirp, fc) and methods to compute range/velocity resolution
- Add waveform parameter spinboxes to playback controls (dashboard.py)
- Auto-parse waveform params from ADI phaser filename convention
- Create replay-specific RadarSettings with correct calibration instead
  of using FPGA defaults (781.25 m/bin → 0.334 m/bin for ADI phaser)
- Add 4 unit tests validating WaveformConfig math

Bug #2 — Demo + radar mutual exclusion:
- _start_demo() now refuses if radar is running (_running=True)
- _start_radar() stops demo first if _demo_mode is active
- Demo buttons disabled while radar/replay is running, re-enabled on stop

Bug #3 — Refactor adi_agc_analysis.py:
- Remove 60+ lines of duplicated AGC functions (signed_to_encoding,
  encoding_to_signed, clamp_gain, apply_gain_shift)
- Import from v7.agc_sim canonical implementation
- Rewrite simulate_agc() to use process_agc_frame() in a loop
- Rewrite process_frame_rd() to use quantize_iq() from agc_sim
This commit is contained in:
Jason
2026-04-14 03:19:58 +05:45
parent a16472480a
commit 609589349d
5 changed files with 270 additions and 131 deletions
+34 -127
View File
@@ -32,83 +32,24 @@ from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
from v7.agc_sim import (
encoding_to_signed,
apply_gain_shift,
quantize_iq,
AGCConfig,
AGCState,
process_agc_frame,
)
# ---------------------------------------------------------------------------
# FPGA AGC parameters (rx_gain_control.v reset defaults)
# ---------------------------------------------------------------------------
AGC_TARGET = 200 # host_agc_target (8-bit, default 200)
AGC_ATTACK = 1 # host_agc_attack (4-bit, default 1)
AGC_DECAY = 1 # host_agc_decay (4-bit, default 1)
AGC_HOLDOFF = 4 # host_agc_holdoff (4-bit, default 4)
ADC_RAIL = 4095 # 12-bit ADC max absolute value
# ---------------------------------------------------------------------------
# Gain encoding helpers (match RTL signed_to_encoding / encoding_to_signed)
# ---------------------------------------------------------------------------
def signed_to_encoding(g: int) -> int:
"""Convert signed gain (-7..+7) to gain_shift[3:0] encoding.
[3]=0, [2:0]=N → amplify (left shift) by N
[3]=1, [2:0]=N → attenuate (right shift) by N
"""
if g >= 0:
return g & 0x07
return 0x08 | ((-g) & 0x07)
def encoding_to_signed(enc: int) -> int:
"""Convert gain_shift[3:0] encoding to signed gain."""
if (enc & 0x08) == 0:
return enc & 0x07
return -(enc & 0x07)
def clamp_gain(val: int) -> int:
"""Clamp to [-7, +7] (matches RTL clamp_gain function)."""
return max(-7, min(7, val))
# ---------------------------------------------------------------------------
# Apply gain shift to IQ data (matches RTL combinational logic)
# ---------------------------------------------------------------------------
def apply_gain_shift(frame_i: np.ndarray, frame_q: np.ndarray,
gain_enc: int) -> tuple[np.ndarray, np.ndarray, int]:
"""Apply gain_shift encoding to 16-bit signed IQ arrays.
Returns (shifted_i, shifted_q, overflow_count).
Matches the RTL: left shift = amplify, right shift = attenuate,
saturate to ±32767 on overflow.
"""
direction = (gain_enc >> 3) & 1 # 0=amplify, 1=attenuate
amount = gain_enc & 0x07
if amount == 0:
return frame_i.copy(), frame_q.copy(), 0
if direction == 0:
# Left shift (amplify)
si = frame_i.astype(np.int64) * (1 << amount)
sq = frame_q.astype(np.int64) * (1 << amount)
else:
# Arithmetic right shift (attenuate)
si = frame_i.astype(np.int64) >> amount
sq = frame_q.astype(np.int64) >> amount
# Count overflows (post-shift values outside 16-bit signed range)
overflow_i = (si > 32767) | (si < -32768)
overflow_q = (sq > 32767) | (sq < -32768)
overflow_count = int((overflow_i | overflow_q).sum())
# Saturate to ±32767
si = np.clip(si, -32768, 32767).astype(np.int16)
sq = np.clip(sq, -32768, 32767).astype(np.int16)
return si, sq, overflow_count
# ---------------------------------------------------------------------------
# Per-frame AGC simulation (bit-accurate to rx_gain_control.v)
# Per-frame AGC simulation using v7.agc_sim (bit-accurate to RTL)
# ---------------------------------------------------------------------------
def simulate_agc(frames: np.ndarray, agc_enabled: bool = True,
@@ -126,79 +67,46 @@ def simulate_agc(frames: np.ndarray, agc_enabled: bool = True,
n_frames = frames.shape[0]
# Output arrays
out_gain_enc = np.zeros(n_frames, dtype=int) # gain_shift encoding [3:0]
out_gain_signed = np.zeros(n_frames, dtype=int) # signed gain for plotting
out_peak_mag = np.zeros(n_frames, dtype=int) # peak_magnitude[7:0]
out_sat_count = np.zeros(n_frames, dtype=int) # saturation_count[7:0]
out_gain_enc = np.zeros(n_frames, dtype=int)
out_gain_signed = np.zeros(n_frames, dtype=int)
out_peak_mag = np.zeros(n_frames, dtype=int)
out_sat_count = np.zeros(n_frames, dtype=int)
out_sat_rate = np.zeros(n_frames, dtype=float)
out_rms_post = np.zeros(n_frames, dtype=float) # RMS after gain shift
out_rms_post = np.zeros(n_frames, dtype=float)
# AGC internal state
agc_gain = 0 # signed, -7..+7
holdoff_counter = 0
agc_was_enabled = False
# AGC state — managed by process_agc_frame()
state = AGCState(
gain=encoding_to_signed(initial_gain_enc),
holdoff_counter=0,
was_enabled=False,
)
for i in range(n_frames):
frame = frames[i]
# Quantize to 16-bit signed (ADC is 12-bit, sign-extended to 16)
frame_i = np.clip(np.round(frame.real), -32768, 32767).astype(np.int16)
frame_q = np.clip(np.round(frame.imag), -32768, 32767).astype(np.int16)
frame_i, frame_q = quantize_iq(frames[i])
# --- PRE-gain peak measurement (RTL lines 133-135, 211-213) ---
abs_i = np.abs(frame_i.astype(np.int32))
abs_q = np.abs(frame_q.astype(np.int32))
max_iq = np.maximum(abs_i, abs_q)
frame_peak_15bit = int(max_iq.max()) # 15-bit unsigned
peak_8bit = (frame_peak_15bit >> 7) & 0xFF # Upper 8 bits
# --- Determine effective gain ---
agc_active = agc_enabled and (i >= enable_at_frame)
# AGC enable transition (RTL lines 250-253)
if agc_active and not agc_was_enabled:
agc_gain = encoding_to_signed(initial_gain_enc)
holdoff_counter = AGC_HOLDOFF
# Build per-frame config (enable toggles at enable_at_frame)
config = AGCConfig(enabled=agc_active)
effective_enc = signed_to_encoding(agc_gain) if agc_active else initial_gain_enc
agc_was_enabled = agc_active
# --- Apply gain shift + count POST-gain overflow (RTL lines 114-126, 207-209) ---
shifted_i, shifted_q, frame_overflow = apply_gain_shift(
frame_i, frame_q, effective_enc)
frame_sat = min(255, frame_overflow)
result = process_agc_frame(frame_i, frame_q, config, state)
# RMS of shifted signal
rms = float(np.sqrt(np.mean(
shifted_i.astype(np.float64)**2 + shifted_q.astype(np.float64)**2)))
result.shifted_i.astype(np.float64)**2
+ result.shifted_q.astype(np.float64)**2)))
total_samples = frame_i.size + frame_q.size
sat_rate = frame_overflow / total_samples if total_samples > 0 else 0.0
sat_rate = result.overflow_raw / total_samples if total_samples > 0 else 0.0
# --- Record outputs ---
out_gain_enc[i] = effective_enc
out_gain_signed[i] = agc_gain if agc_active else encoding_to_signed(initial_gain_enc)
out_peak_mag[i] = peak_8bit
out_sat_count[i] = frame_sat
# Record outputs
out_gain_enc[i] = result.gain_enc
out_gain_signed[i] = result.gain_signed
out_peak_mag[i] = result.peak_mag_8bit
out_sat_count[i] = result.saturation_count
out_sat_rate[i] = sat_rate
out_rms_post[i] = rms
# --- AGC update at frame boundary (RTL lines 226-246) ---
if agc_active:
if frame_sat > 0:
# Clipping: reduce gain immediately (attack)
agc_gain = clamp_gain(agc_gain - AGC_ATTACK)
holdoff_counter = AGC_HOLDOFF
elif peak_8bit < AGC_TARGET:
# Signal too weak: increase gain after holdoff
if holdoff_counter == 0:
agc_gain = clamp_gain(agc_gain + AGC_DECAY)
else:
holdoff_counter -= 1
else:
# Good range (peak >= target, no sat): hold, reset holdoff
holdoff_counter = AGC_HOLDOFF
return {
"gain_enc": out_gain_enc,
"gain_signed": out_gain_signed,
@@ -217,8 +125,7 @@ def process_frame_rd(frame: np.ndarray, gain_enc: int,
n_range: int = 64,
n_doppler: int = 32) -> np.ndarray:
"""Range-Doppler magnitude for one frame with gain applied."""
frame_i = np.clip(np.round(frame.real), -32768, 32767).astype(np.int16)
frame_q = np.clip(np.round(frame.imag), -32768, 32767).astype(np.int16)
frame_i, frame_q = quantize_iq(frame)
si, sq, _ = apply_gain_shift(frame_i, frame_q, gain_enc)
iq = si.astype(np.float64) + 1j * sq.astype(np.float64)
+33
View File
@@ -69,6 +69,39 @@ class TestRadarSettings(unittest.TestCase):
self.assertEqual(s.max_distance, 50000)
class TestWaveformConfig(unittest.TestCase):
"""WaveformConfig — range/velocity resolution from waveform params."""
def test_adi_phaser_range_resolution(self):
"""ADI CN0566 defaults: 4MSPS, 500MHz BW, 300µs chirp, 1079 samples."""
wf = _models().WaveformConfig() # ADI phaser defaults
r_res = wf.range_resolution(n_samples=1079)
# Expected: c * fs / (2 * N * slope) = 3e8 * 4e6 / (2 * 1079 * 1.667e12)
# ≈ 0.334 m/bin
self.assertAlmostEqual(r_res, 0.334, places=2)
def test_adi_phaser_velocity_resolution(self):
"""ADI phaser: 256 chirps, 1079 samples at 4 MSPS."""
wf = _models().WaveformConfig()
v_res = wf.velocity_resolution(n_samples=1079, n_chirps=256)
# λ * fs / (2 * N * M) = 0.03 * 4e6 / (2 * 1079 * 256) ≈ 0.217 m/s/bin
self.assertAlmostEqual(v_res, 0.217, places=2)
def test_max_range(self):
wf = _models().WaveformConfig()
max_r = wf.max_range(n_range_bins=64, n_samples=1079)
# 0.334 * 64 ≈ 21.4 m
self.assertAlmostEqual(max_r, 21.4, places=0)
def test_plfm_defaults_differ(self):
"""PLFM FPGA defaults (781.25 m/bin) must NOT equal ADI phaser."""
default_settings = _models().RadarSettings()
wf = _models().WaveformConfig()
r_res = wf.range_resolution(n_samples=1079)
self.assertNotAlmostEqual(default_settings.range_resolution, r_res,
places=0) # 781 vs 0.33
class TestGPSData(unittest.TestCase):
def test_to_dict(self):
g = _models().GPSData(latitude=41.9, longitude=12.5,
+2 -1
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@@ -11,6 +11,7 @@ top-level imports:
from .models import (
RadarTarget,
RadarSettings,
WaveformConfig,
GPSData,
ProcessingConfig,
TileServer,
@@ -66,7 +67,7 @@ except ImportError: # PyQt6 not installed (e.g. CI headless runner)
__all__ = [ # noqa: RUF022
# models
"RadarTarget", "RadarSettings", "GPSData", "ProcessingConfig", "TileServer",
"RadarTarget", "RadarSettings", "WaveformConfig", "GPSData", "ProcessingConfig", "TileServer",
"DARK_BG", "DARK_FG", "DARK_ACCENT", "DARK_HIGHLIGHT", "DARK_BORDER",
"DARK_TEXT", "DARK_BUTTON", "DARK_BUTTON_HOVER",
"DARK_TREEVIEW", "DARK_TREEVIEW_ALT",
+160 -3
View File
@@ -23,6 +23,7 @@ commands sent over FT2232H.
"""
import time
import re
import logging
from collections import deque
from pathlib import Path
@@ -43,7 +44,7 @@ from matplotlib.backends.backend_qtagg import FigureCanvasQTAgg
from matplotlib.figure import Figure
from .models import (
RadarTarget, RadarSettings, GPSData, ProcessingConfig,
RadarTarget, RadarSettings, WaveformConfig, GPSData, ProcessingConfig,
DARK_BG, DARK_FG, DARK_ACCENT, DARK_HIGHLIGHT, DARK_BORDER,
DARK_TEXT, DARK_BUTTON, DARK_BUTTON_HOVER,
DARK_TREEVIEW, DARK_TREEVIEW_ALT,
@@ -84,6 +85,41 @@ def _make_dspin() -> QDoubleSpinBox:
return sb
def _parse_waveform_from_filename(name: str) -> WaveformConfig | None:
"""Try to extract waveform params from ADI phaser filename convention.
Expected pattern fragments (order-independent):
``<N>MSPS`` or ``<N>MSps`` → sample rate in MHz
``<N>M`` (followed by _ or end) → bandwidth in MHz
``<N>u`` (followed by _ or end) → chirp duration in µs
Returns a WaveformConfig with parsed values (defaults for un-parsed),
or None if nothing recognisable was found.
"""
cfg = WaveformConfig() # ADI phaser defaults
found = False
# Sample rate: "4MSPS" or "4MSps"
m = re.search(r"(\d+)M[Ss][Pp][Ss]", name)
if m:
cfg.sample_rate_hz = float(m.group(1)) * 1e6
found = True
# Bandwidth: "500M" (must NOT be followed by S for MSPS)
m = re.search(r"(\d+)M(?![Ss])", name)
if m:
cfg.bandwidth_hz = float(m.group(1)) * 1e6
found = True
# Chirp duration: "300u"
m = re.search(r"(\d+)u", name)
if m:
cfg.chirp_duration_s = float(m.group(1)) * 1e-6
found = True
return cfg if found else None
# =============================================================================
# Range-Doppler Canvas (matplotlib)
# =============================================================================
@@ -483,6 +519,55 @@ class RadarDashboard(QMainWindow):
self._playback_frame.setVisible(False)
ctrl_layout.addWidget(self._playback_frame, 2, 0, 1, 10)
# -- Waveform config row (Raw IQ replay only) -----------------------
self._waveform_frame = QFrame()
self._waveform_frame.setStyleSheet(
f"background-color: {DARK_ACCENT}; border-radius: 4px;")
wf_layout = QHBoxLayout(self._waveform_frame)
wf_layout.setContentsMargins(8, 4, 8, 4)
wf_layout.addWidget(QLabel("Waveform:"))
wf_layout.addWidget(QLabel("fs (MHz):"))
self._wf_fs_spin = _make_dspin()
self._wf_fs_spin.setRange(0.1, 100.0)
self._wf_fs_spin.setValue(4.0)
self._wf_fs_spin.setDecimals(2)
self._wf_fs_spin.setToolTip("ADC sample rate in MHz")
wf_layout.addWidget(self._wf_fs_spin)
wf_layout.addWidget(QLabel("BW (MHz):"))
self._wf_bw_spin = _make_dspin()
self._wf_bw_spin.setRange(1.0, 5000.0)
self._wf_bw_spin.setValue(500.0)
self._wf_bw_spin.setDecimals(1)
self._wf_bw_spin.setToolTip("Chirp bandwidth in MHz")
wf_layout.addWidget(self._wf_bw_spin)
wf_layout.addWidget(QLabel("T (us):"))
self._wf_chirp_spin = _make_dspin()
self._wf_chirp_spin.setRange(1.0, 10000.0)
self._wf_chirp_spin.setValue(300.0)
self._wf_chirp_spin.setDecimals(1)
self._wf_chirp_spin.setToolTip("Chirp duration in microseconds")
wf_layout.addWidget(self._wf_chirp_spin)
wf_layout.addWidget(QLabel("fc (GHz):"))
self._wf_fc_spin = _make_dspin()
self._wf_fc_spin.setRange(0.1, 100.0)
self._wf_fc_spin.setValue(10.0)
self._wf_fc_spin.setDecimals(2)
self._wf_fc_spin.setToolTip("Carrier frequency in GHz")
wf_layout.addWidget(self._wf_fc_spin)
self._wf_res_label = QLabel("")
self._wf_res_label.setStyleSheet(f"color: {DARK_INFO}; font-size: 10px;")
wf_layout.addWidget(self._wf_res_label)
wf_layout.addStretch()
self._waveform_frame.setVisible(False)
ctrl_layout.addWidget(self._waveform_frame, 3, 0, 1, 10)
layout.addWidget(ctrl)
# ---- Display area (range-doppler + targets table) ------------------
@@ -1294,6 +1379,10 @@ class RadarDashboard(QMainWindow):
def _start_radar(self):
"""Start radar data acquisition using production protocol."""
# Mutual exclusion: stop demo if running
if self._demo_mode:
self._stop_demo()
try:
mode = self._mode_combo.currentText()
@@ -1362,6 +1451,8 @@ class RadarDashboard(QMainWindow):
self._start_btn.setEnabled(False)
self._stop_btn.setEnabled(True)
self._mode_combo.setEnabled(False)
self._demo_btn_main.setEnabled(False)
self._demo_btn_map.setEnabled(False)
self._status_label_main.setText(f"Status: Running ({mode})")
self._sb_status.setText(f"Running ({mode})")
self._sb_mode.setText(mode)
@@ -1413,7 +1504,10 @@ class RadarDashboard(QMainWindow):
self._start_btn.setEnabled(True)
self._stop_btn.setEnabled(False)
self._mode_combo.setEnabled(True)
self._demo_btn_main.setEnabled(True)
self._demo_btn_map.setEnabled(True)
self._playback_frame.setVisible(False)
self._waveform_frame.setVisible(False)
self._pb_play_btn.setText("Play")
self._pb_frame_label.setText("Frame: 0 / 0")
self._pb_file_label.setText("")
@@ -1441,9 +1535,44 @@ class RadarDashboard(QMainWindow):
self._replay_controller = RawIQReplayController()
info = self._replay_controller.load_file(npy_path)
# -- Waveform calibration: try to parse from filename -----------
parsed_wf = _parse_waveform_from_filename(Path(npy_path).name)
if parsed_wf is not None:
self._wf_fs_spin.setValue(parsed_wf.sample_rate_hz / 1e6)
self._wf_bw_spin.setValue(parsed_wf.bandwidth_hz / 1e6)
self._wf_chirp_spin.setValue(parsed_wf.chirp_duration_s / 1e-6)
self._wf_fc_spin.setValue(parsed_wf.center_freq_hz / 1e9)
logger.info("Waveform params parsed from filename: %s", parsed_wf)
# Build waveform config from (possibly updated) spinboxes
wfc = self._waveform_config_from_ui()
range_res = wfc.range_resolution(info.n_samples)
vel_res = wfc.velocity_resolution(info.n_samples, info.n_chirps)
n_range_out = min(64, info.n_samples)
max_range = range_res * n_range_out
# Create replay-specific RadarSettings with correct calibration
replay_settings = RadarSettings(
system_frequency=wfc.center_freq_hz,
range_resolution=range_res,
velocity_resolution=vel_res,
max_distance=max_range,
map_size=max_range * 1.2,
coverage_radius=max_range * 1.2,
)
logger.info(
"Replay calibration: range_res=%.4f m/bin, vel_res=%.4f m/s/bin, "
"max_range=%.1f m",
range_res, vel_res, max_range,
)
# Update coverage/map spinboxes to match replay scale
self._coverage_spin.setValue(replay_settings.coverage_radius / 1000)
self._update_waveform_res_label(info.n_samples, info.n_chirps)
# Create frame processor
self._iq_processor = RawIQFrameProcessor(
n_range_out=min(64, info.n_samples),
n_range_out=n_range_out,
n_doppler_out=min(32, info.n_chirps),
)
@@ -1493,7 +1622,7 @@ class RadarDashboard(QMainWindow):
controller=self._replay_controller,
processor=self._iq_processor,
host_processor=self._processor,
settings=self._settings,
settings=replay_settings,
gps_data_ref=self._radar_position,
)
self._replay_worker.frameReady.connect(self._on_frame_ready)
@@ -1518,7 +1647,10 @@ class RadarDashboard(QMainWindow):
self._start_btn.setEnabled(False)
self._stop_btn.setEnabled(True)
self._mode_combo.setEnabled(False)
self._demo_btn_main.setEnabled(False)
self._demo_btn_map.setEnabled(False)
self._playback_frame.setVisible(True)
self._waveform_frame.setVisible(True)
self._pb_frame_label.setText(f"Frame: 0 / {info.n_frames}")
self._pb_file_label.setText(
f"{Path(npy_path).name} "
@@ -1568,6 +1700,27 @@ class RadarDashboard(QMainWindow):
if self._replay_controller is not None:
self._replay_controller.set_loop(checked)
def _waveform_config_from_ui(self) -> WaveformConfig:
"""Build a WaveformConfig from the waveform spinboxes."""
return WaveformConfig(
sample_rate_hz=self._wf_fs_spin.value() * 1e6,
bandwidth_hz=self._wf_bw_spin.value() * 1e6,
chirp_duration_s=self._wf_chirp_spin.value() * 1e-6,
center_freq_hz=self._wf_fc_spin.value() * 1e9,
)
def _update_waveform_res_label(self, n_samples: int, n_chirps: int) -> None:
"""Update the waveform resolution info label."""
wfc = self._waveform_config_from_ui()
r_res = wfc.range_resolution(n_samples)
v_res = wfc.velocity_resolution(n_samples, n_chirps)
n_r = min(64, n_samples)
max_r = r_res * n_r
self._wf_res_label.setText(
f"Range: {r_res:.3f} m/bin | Vel: {v_res:.3f} m/s/bin | "
f"Max range: {max_r:.1f} m ({n_r} bins)"
)
@pyqtSlot(str)
def _on_playback_state_changed(self, state_str: str):
if state_str == "playing":
@@ -1591,6 +1744,10 @@ class RadarDashboard(QMainWindow):
def _start_demo(self):
if self._simulator:
return
# Mutual exclusion: do not start demo while radar/replay is running
if self._running:
logger.warning("Cannot start demo while radar is running")
return
self._simulator = TargetSimulator(self._radar_position, self)
self._simulator.targetsUpdated.connect(self._on_demo_targets)
self._simulator.start(500)
+41
View File
@@ -96,6 +96,47 @@ class RadarTarget:
return asdict(self)
@dataclass
class WaveformConfig:
"""FMCW waveform parameters for bin-to-physical-unit conversion.
Defaults are for the ADI CN0566 phaser (10 GHz, 500 MHz BW, 300 µs chirp,
4 MSPS ADC). For the PLFM FPGA waveform the values differ — but the FPGA
pipeline hardcodes its own bin widths, so this config is only used for
Raw IQ Replay (host-side FFT processing).
"""
sample_rate_hz: float = 4e6 # ADC sample rate (Hz)
bandwidth_hz: float = 500e6 # Chirp bandwidth (Hz)
chirp_duration_s: float = 300e-6 # Chirp sweep time (s)
center_freq_hz: float = 10e9 # Carrier frequency (Hz)
# --- derived quantities (need n_samples, n_chirps from file) ---
def range_resolution(self, n_samples: int) -> float:
"""Metres per range bin for an N-point range FFT.
range_per_bin = c · fs / (2 · N · slope)
where slope = BW / T_chirp.
"""
c = 299_792_458.0
slope = self.bandwidth_hz / self.chirp_duration_s
return c * self.sample_rate_hz / (2.0 * n_samples * slope)
def velocity_resolution(self, n_samples: int, n_chirps: int) -> float:
"""m/s per Doppler bin for an M-chirp Doppler FFT.
vel_per_bin = λ · fs / (2 · N · M)
where λ = c / fc, N = n_samples (PRI = N/fs), M = n_chirps.
"""
c = 299_792_458.0
wavelength = c / self.center_freq_hz
return wavelength * self.sample_rate_hz / (2.0 * n_samples * n_chirps)
def max_range(self, n_range_bins: int, n_samples: int) -> float:
"""Maximum unambiguous range for the given bin count."""
return self.range_resolution(n_samples) * n_range_bins
@dataclass
class RadarSettings:
"""Radar system display/map configuration.