diff --git a/cmd/sdrd/dsp_loop.go b/cmd/sdrd/dsp_loop.go
index 7756795..892dfb9 100644
--- a/cmd/sdrd/dsp_loop.go
+++ b/cmd/sdrd/dsp_loop.go
@@ -185,6 +185,14 @@ func runDSP(ctx context.Context, srcMgr *sourceManager, cfg config.Config, det *
}
cls := classifier.Classify(classifier.SignalInput{FirstBin: signals[i].FirstBin, LastBin: signals[i].LastBin, SNRDb: signals[i].SNRDb, CenterHz: signals[i].CenterHz}, spectrum, cfg.SampleRate, cfg.FFTSize, snip, classifier.ClassifierMode(cfg.ClassifierMode))
signals[i].Class = cls
+ if cls != nil && snip != nil && len(snip) > 256 {
+ pll := classifier.EstimateExactFrequency(snip, cfg.SampleRate, signals[i].CenterHz, cls.ModType)
+ cls.PLL = &pll
+ signals[i].PLL = &pll
+ if pll.Locked {
+ signals[i].CenterHz = pll.ExactHz
+ }
+ }
}
det.UpdateClasses(signals)
}
diff --git a/internal/classifier/classifier.go b/internal/classifier/classifier.go
index e2c3148..8307d02 100644
--- a/internal/classifier/classifier.go
+++ b/internal/classifier/classifier.go
@@ -13,6 +13,10 @@ func Classify(input SignalInput, spectrum []float64, sampleRate int, fftSize int
return nil
}
feat := ExtractFeatures(input, spectrum, sampleRate, fftSize)
+ if hard := TryHardRule(input.CenterHz, feat.BW3dB); hard != nil {
+ hard.Features = feat
+ return hard
+ }
if len(iq) > 0 {
envVar, zc, instStd, crest := ExtractTemporalFeatures(iq)
feat.EnvVariance = envVar
diff --git a/internal/classifier/hard_rules.go b/internal/classifier/hard_rules.go
new file mode 100644
index 0000000..17fad58
--- /dev/null
+++ b/internal/classifier/hard_rules.go
@@ -0,0 +1,70 @@
+package classifier
+
+import (
+ _ "embed"
+ "encoding/json"
+ "log"
+)
+
+//go:embed hard_rules.json
+var hardRulesJSON []byte
+
+type hardRule struct {
+ Name string `json:"name"`
+ Match hardMatch `json:"match"`
+ Result hardResult `json:"result"`
+ Note string `json:"note"`
+}
+
+type hardMatch struct {
+ MinMHz float64 `json:"min_mhz,omitempty"`
+ MaxMHz float64 `json:"max_mhz,omitempty"`
+ MinBWHz float64 `json:"min_bw_hz,omitempty"`
+ MaxBWHz float64 `json:"max_bw_hz,omitempty"`
+}
+
+type hardResult struct {
+ ModType string `json:"mod_type"`
+ Confidence float64 `json:"confidence"`
+}
+
+type hardRulesFile struct {
+ Rules []hardRule `json:"rules"`
+}
+
+var loadedHardRules []hardRule
+
+func init() {
+ var f hardRulesFile
+ if err := json.Unmarshal(hardRulesJSON, &f); err != nil {
+ log.Printf("classifier: failed to load hard rules: %v", err)
+ return
+ }
+ loadedHardRules = f.Rules
+}
+
+func TryHardRule(centerHz float64, bwHz float64) *Classification {
+ mhz := centerHz / 1e6
+ for _, r := range loadedHardRules {
+ if r.Match.MinMHz > 0 && mhz < r.Match.MinMHz {
+ continue
+ }
+ if r.Match.MaxMHz > 0 && mhz > r.Match.MaxMHz {
+ continue
+ }
+ if r.Match.MinBWHz > 0 && bwHz < r.Match.MinBWHz {
+ continue
+ }
+ if r.Match.MaxBWHz > 0 && bwHz > r.Match.MaxBWHz {
+ continue
+ }
+ mod := SignalClass(r.Result.ModType)
+ return &Classification{
+ ModType: mod,
+ Confidence: r.Result.Confidence,
+ BW3dB: bwHz,
+ Scores: map[SignalClass]float64{mod: 10.0},
+ }
+ }
+ return nil
+}
diff --git a/internal/classifier/hard_rules.json b/internal/classifier/hard_rules.json
new file mode 100644
index 0000000..1a69e14
--- /dev/null
+++ b/internal/classifier/hard_rules.json
@@ -0,0 +1,52 @@
+{
+ "rules": [
+ {
+ "name": "fm_broadcast",
+ "match": {"min_mhz": 87.5, "max_mhz": 108.0, "min_bw_hz": 50000},
+ "result": {"mod_type": "WFM", "confidence": 0.99},
+ "note": "FM Broadcast: >50 kHz BW im UKW-Band ist immer WFM"
+ },
+ {
+ "name": "airband_am",
+ "match": {"min_mhz": 118.0, "max_mhz": 137.0, "min_bw_hz": 4000, "max_bw_hz": 12000},
+ "result": {"mod_type": "AM", "confidence": 0.95},
+ "note": "Airband ist ausschliesslich AM"
+ },
+ {
+ "name": "cw_any_band",
+ "match": {"min_bw_hz": 0, "max_bw_hz": 500},
+ "result": {"mod_type": "CW", "confidence": 0.90},
+ "note": "Unter 500 Hz BW ist CW, egal welches Band"
+ },
+ {
+ "name": "ft8_40m",
+ "match": {"min_mhz": 7.072, "max_mhz": 7.076, "min_bw_hz": 1500, "max_bw_hz": 3500},
+ "result": {"mod_type": "FT8", "confidence": 0.95},
+ "note": "FT8 Dial-Frequenz 40m"
+ },
+ {
+ "name": "ft8_20m",
+ "match": {"min_mhz": 14.072, "max_mhz": 14.076, "min_bw_hz": 1500, "max_bw_hz": 3500},
+ "result": {"mod_type": "FT8", "confidence": 0.95},
+ "note": "FT8 Dial-Frequenz 20m"
+ },
+ {
+ "name": "wspr_40m",
+ "match": {"min_mhz": 7.0384, "max_mhz": 7.0388, "min_bw_hz": 100, "max_bw_hz": 500},
+ "result": {"mod_type": "WSPR", "confidence": 0.95},
+ "note": "WSPR Dial-Frequenz 40m"
+ },
+ {
+ "name": "pmr446_nfm",
+ "match": {"min_mhz": 446.0, "max_mhz": 446.2, "min_bw_hz": 5000, "max_bw_hz": 15000},
+ "result": {"mod_type": "NFM", "confidence": 0.92},
+ "note": "PMR446 ist immer NFM"
+ },
+ {
+ "name": "wfm_wide_any",
+ "match": {"min_bw_hz": 100000},
+ "result": {"mod_type": "WFM", "confidence": 0.95},
+ "note": "Über 100 kHz BW ist fast immer WFM, unabhängig vom Band"
+ }
+ ]
+}
diff --git a/internal/classifier/hard_rules_test.go b/internal/classifier/hard_rules_test.go
new file mode 100644
index 0000000..c1b21df
--- /dev/null
+++ b/internal/classifier/hard_rules_test.go
@@ -0,0 +1,58 @@
+package classifier
+
+import (
+ "math"
+ "testing"
+)
+
+func TestHardRulesFMBroadcast(t *testing.T) {
+ cls := TryHardRule(100.0e6, 120000)
+ if cls == nil {
+ t.Fatal("expected hard rule match for FM broadcast")
+ }
+ if cls.ModType != ClassWFM {
+ t.Errorf("expected WFM, got %s", cls.ModType)
+ }
+ if cls.Confidence < 0.95 {
+ t.Errorf("confidence too low: %.2f", cls.Confidence)
+ }
+ cls2 := TryHardRule(434.0e6, 120000)
+ if cls2 == nil || cls2.ModType != ClassWFM {
+ t.Errorf("expected WFM for >100kHz signal")
+ }
+}
+
+func TestHardRulesAirband(t *testing.T) {
+ cls := TryHardRule(121.5e6, 8000)
+ if cls == nil || cls.ModType != ClassAM {
+ t.Fatalf("expected AM for airband, got %v", cls)
+ }
+}
+
+func TestHardRulesCW(t *testing.T) {
+ cls := TryHardRule(7.020e6, 100)
+ if cls == nil || cls.ModType != ClassCW {
+ t.Fatalf("expected CW for <500Hz, got %v", cls)
+ }
+}
+
+func TestWFMPilotDetection(t *testing.T) {
+ sampleRate := 192000
+ n := sampleRate * 2
+ iq := make([]complex64, n)
+ phase := 0.0
+ for i := range iq {
+ pilot := math.Sin(2 * math.Pi * 19000 * float64(i) / float64(sampleRate))
+ modulation := pilot * 0.1
+ freqDev := modulation * 75000 / float64(sampleRate)
+ phase += 2 * math.Pi * freqDev
+ iq[i] = complex(float32(math.Cos(phase)), float32(math.Sin(phase)))
+ }
+ result := EstimateExactFrequency(iq, sampleRate, 102.1e6, ClassWFM)
+ if !result.Locked {
+ t.Fatal("PLL should lock on pilot")
+ }
+ if math.Abs(result.OffsetHz) > 5 {
+ t.Errorf("offset too large: %.1f Hz", result.OffsetHz)
+ }
+}
diff --git a/internal/classifier/pll.go b/internal/classifier/pll.go
new file mode 100644
index 0000000..11d8934
--- /dev/null
+++ b/internal/classifier/pll.go
@@ -0,0 +1,130 @@
+package classifier
+
+import "math"
+
+type PLLResult struct {
+ ExactHz float64 `json:"exact_hz"`
+ OffsetHz float64 `json:"offset_hz"`
+ Locked bool `json:"locked"`
+ Method string `json:"method"`
+ PrecisionHz float64 `json:"precision_hz"`
+}
+
+func EstimateExactFrequency(iq []complex64, sampleRate int, detectedHz float64, modType SignalClass) PLLResult {
+ if len(iq) < 256 {
+ return PLLResult{ExactHz: detectedHz}
+ }
+ switch modType {
+ case ClassWFM:
+ return estimateWFMPilot(iq, sampleRate, detectedHz)
+ case ClassAM:
+ return estimateAMCarrier(iq, sampleRate, detectedHz)
+ case ClassNFM:
+ return estimateNFMCarrier(iq, sampleRate, detectedHz)
+ case ClassCW:
+ return estimateCWTone(iq, sampleRate, detectedHz)
+ default:
+ return PLLResult{ExactHz: detectedHz, Method: "none"}
+ }
+}
+
+func estimateWFMPilot(iq []complex64, sampleRate int, detectedHz float64) PLLResult {
+ demod := fmDemod(iq)
+ if len(demod) == 0 {
+ return PLLResult{ExactHz: detectedHz, Method: "pilot"}
+ }
+ pilotFreq := 19000.0
+ bestFreq := pilotFreq
+ bestMag := goertzelMagnitude(demod, pilotFreq, sampleRate)
+ for offset := -50.0; offset <= 50.0; offset += 1.0 {
+ mag := goertzelMagnitude(demod, pilotFreq+offset, sampleRate)
+ if mag > bestMag {
+ bestMag = mag
+ bestFreq = pilotFreq + offset
+ }
+ }
+ freqError := bestFreq - 19000.0
+ noiseMag := goertzelMagnitude(demod, 17500, sampleRate)
+ locked := bestMag > noiseMag*5
+ if !locked {
+ return PLLResult{ExactHz: detectedHz, Method: "pilot", Locked: false}
+ }
+ return PLLResult{ExactHz: detectedHz - freqError, OffsetHz: -freqError, Locked: true, Method: "pilot", PrecisionHz: 1.0}
+}
+
+func estimateAMCarrier(iq []complex64, sampleRate int, detectedHz float64) PLLResult {
+ offset := meanInstFreqHz(iq, sampleRate)
+ return PLLResult{ExactHz: detectedHz + offset, OffsetHz: offset, Locked: true, Method: "carrier", PrecisionHz: 5.0}
+}
+
+func estimateNFMCarrier(iq []complex64, sampleRate int, detectedHz float64) PLLResult {
+ offset := meanInstFreqHz(iq, sampleRate)
+ return PLLResult{ExactHz: detectedHz + offset, OffsetHz: offset, Locked: math.Abs(offset) < 5000, Method: "fm_dc", PrecisionHz: 20.0}
+}
+
+func estimateCWTone(iq []complex64, sampleRate int, detectedHz float64) PLLResult {
+ demod := fmDemod(iq)
+ if len(demod) == 0 {
+ return PLLResult{ExactHz: detectedHz, Method: "tone"}
+ }
+ bestFreq := 700.0
+ bestMag := 0.0
+ for f := 300.0; f <= 1200.0; f += 1.0 {
+ mag := goertzelMagnitude(demod, f, sampleRate)
+ if mag > bestMag {
+ bestMag = mag
+ bestFreq = f
+ }
+ }
+ bfoHz := 700.0
+ toneOffset := bestFreq - bfoHz
+ return PLLResult{ExactHz: detectedHz + toneOffset, OffsetHz: toneOffset, Locked: bestMag > 0, Method: "tone", PrecisionHz: 2.0}
+}
+
+func fmDemod(iq []complex64) []float64 {
+ if len(iq) < 2 {
+ return nil
+ }
+ out := make([]float64, len(iq)-1)
+ for i := 1; i < len(iq); i++ {
+ p := iq[i-1]
+ c := iq[i]
+ num := float64(real(p))*float64(imag(c)) - float64(imag(p))*float64(real(c))
+ den := float64(real(p))*float64(real(c)) + float64(imag(p))*float64(imag(c))
+ out[i-1] = math.Atan2(num, den)
+ }
+ return out
+}
+
+func goertzelMagnitude(samples []float64, targetHz float64, sampleRate int) float64 {
+ n := len(samples)
+ if n == 0 {
+ return 0
+ }
+ k := targetHz / (float64(sampleRate) / float64(n))
+ w := 2.0 * math.Pi * k / float64(n)
+ coeff := 2.0 * math.Cos(w)
+ s1, s2 := 0.0, 0.0
+ for _, v := range samples {
+ s0 := v + coeff*s1 - s2
+ s2 = s1
+ s1 = s0
+ }
+ return math.Sqrt(s1*s1 + s2*s2 - coeff*s1*s2)
+}
+
+func meanInstFreqHz(iq []complex64, sampleRate int) float64 {
+ if len(iq) < 2 {
+ return 0
+ }
+ var sum float64
+ for i := 1; i < len(iq); i++ {
+ p := iq[i-1]
+ c := iq[i]
+ num := float64(real(p))*float64(imag(c)) - float64(imag(p))*float64(real(c))
+ den := float64(real(p))*float64(real(c)) + float64(imag(p))*float64(imag(c))
+ sum += math.Atan2(num, den)
+ }
+ meanRad := sum / float64(len(iq)-1)
+ return meanRad * float64(sampleRate) / (2.0 * math.Pi)
+}
diff --git a/internal/classifier/types.go b/internal/classifier/types.go
index 404b1f7..d58e616 100644
--- a/internal/classifier/types.go
+++ b/internal/classifier/types.go
@@ -44,6 +44,7 @@ type Classification struct {
BW3dB float64 `json:"bw_3db_hz"`
Features Features `json:"features,omitempty"`
MathFeatures *MathFeatures `json:"math_features,omitempty"`
+ PLL *PLLResult `json:"pll,omitempty"`
SecondBest SignalClass `json:"second_best,omitempty"`
Scores map[SignalClass]float64 `json:"scores,omitempty"`
}
diff --git a/internal/detector/detector.go b/internal/detector/detector.go
index 7e8863c..a483423 100644
--- a/internal/detector/detector.go
+++ b/internal/detector/detector.go
@@ -74,6 +74,7 @@ type Signal struct {
SNRDb float64 `json:"snr_db"`
NoiseDb float64 `json:"noise_db,omitempty"`
Class *classifier.Classification `json:"class,omitempty"`
+ PLL *classifier.PLLResult `json:"pll,omitempty"`
}
func New(detCfg config.DetectorConfig, sampleRate int, fftSize int) *Detector {
diff --git a/web/app.js b/web/app.js
index 67145ae..52aa30e 100644
--- a/web/app.js
+++ b/web/app.js
@@ -229,7 +229,8 @@ function renderSignalPopover(rect, signal) {
const width = Math.max(4, (Number(value) / maxVal) * 100);
return `${label}${Number(value).toFixed(2)}
`;
}).join('');
- signalPopover.innerHTML = `${signal.class?.mod_type || 'Signal'}
${fmtMHz(signal.center_hz, 5)} · ${fmtKHz(signal.bw_hz || 0)} · ${(signal.snr_db || 0).toFixed(1)} dB SNR
${rows || '
No classifier scores
'}
${signal.class?.mod_type || 'Signal'}
${fmtMHz(signal.class?.pll?.exact_hz || signal.center_hz, 5)} • ${fmtKHz(signal.bw_hz || 0)} • ${(signal.snr_db || 0).toFixed(1)} dB SNR${pllMeta}
${rows || '
No classifier scores
'}
No live signals yet.
';
- } else {
- signalList.innerHTML = signals.slice(0, 24).map((s) => `
-
- `).join('');
- }
-
- const recent = [...events].sort((a, b) => b.end_ms - a.end_ms);
- eventCountBadge.textContent = `${recent.length} stored`;
- if (recent.length === 0) {
- eventList.innerHTML = 'No events yet.
';
- } else {
- eventList.innerHTML = recent.slice(0, 40).map((ev) => `
-
- `).join('');
- }
-
- if (recordingList && recordingCountBadge) {
- recordingCountBadge.textContent = `${recordings.length}`;
- if (recordings.length === 0) {
- recordingList.innerHTML = 'No recordings yet.
';
- } else {
- recordingList.innerHTML = recordings.slice(0, 50).map((rec) => `
-
- `).join('');
- }
- }
-}
-
-function normalizeEvent(ev) {
- const startMs = new Date(ev.start).getTime();
- const endMs = new Date(ev.end).getTime();
- return {
- ...ev,
- start_ms: startMs,
- end_ms: endMs,
- duration_ms: Math.max(0, endMs - startMs),
- };
-}
-
-function upsertEvents(list, replace = false) {
- if (replace) {
- events.length = 0;
- eventsById.clear();
- }
- for (const raw of list) {
- if (!raw || !raw.id || eventsById.has(raw.id)) continue;
- const ev = normalizeEvent(raw);
- eventsById.set(ev.id, ev);
- events.push(ev);
- }
- events.sort((a, b) => a.end_ms - b.end_ms);
- const maxEvents = 1500;
- if (events.length > maxEvents) {
- const drop = events.length - maxEvents;
- for (let i = 0; i < drop; i++) eventsById.delete(events[i].id);
- events.splice(0, drop);
- }
- if (events.length > 0) lastEventEndMs = events[events.length - 1].end_ms;
- renderLists();
-}
-
-async function fetchEvents(initial) {
- if (eventsFetchInFlight || timelineFrozen) return;
- eventsFetchInFlight = true;
- try {
- let url = '/api/events?limit=1000';
- if (!initial && lastEventEndMs > 0) url = `/api/events?since=${lastEventEndMs - 1}`;
- const res = await fetch(url);
- if (!res.ok) return;
- const data = await res.json();
- if (Array.isArray(data)) upsertEvents(data, initial);
- } finally {
- eventsFetchInFlight = false;
- }
-}
-
-async function fetchRecordings() {
- if (recordingsFetchInFlight || !recordingList) return;
- recordingsFetchInFlight = true;
- try {
- const res = await fetch('/api/recordings');
- if (!res.ok) return;
- const data = await res.json();
- if (Array.isArray(data)) {
- recordings = data;
- renderLists();
- }
- } finally {
- recordingsFetchInFlight = false;
- }
-}
-
-function openDrawer(ev) {
- if (!ev) return;
- selectedEventId = ev.id;
- detailSubtitle.textContent = `Event ${ev.id}`;
- detailCenterEl.textContent = fmtMHz(ev.center_hz, 6);
- detailBwEl.textContent = fmtKHz(ev.bandwidth_hz || 0);
- detailStartEl.textContent = new Date(ev.start_ms).toLocaleString();
- detailEndEl.textContent = new Date(ev.end_ms).toLocaleString();
- detailSnrEl.textContent = `${(ev.snr_db || 0).toFixed(1)} dB`;
- detailDurEl.textContent = fmtMs(ev.duration_ms || 0);
- detailClassEl.textContent = ev.class?.mod_type || '-';
- if (classifierScoresEl) {
- const scores = ev.class?.scores;
- if (scores && typeof scores === 'object') {
- const rows = Object.entries(scores)
- .sort((a, b) => b[1] - a[1])
- .slice(0, 6)
- .map(([k, v]) => `${k}:${v.toFixed(2)}`)
- .join(' · ');
- classifierScoresEl.textContent = rows ? `Classifier scores: ${rows}` : 'Classifier scores: -';
- renderScoreBars(scores);
- } else {
- const liveScores = (latest?.debug?.scores || []).find((s) => Math.abs((s.center_hz || 0) - (ev.center_hz || 0)) < Math.max(500, (ev.bandwidth_hz || 0)));
- if (liveScores?.scores) {
- const rows = Object.entries(liveScores.scores)
- .sort((a, b) => b[1] - a[1])
- .slice(0, 6)
- .map(([k, v]) => `${k}:${Number(v).toFixed(2)}`)
- .join(' · ');
- classifierScoresEl.textContent = rows ? `Classifier scores: ${rows}` : 'Classifier scores: -';
- renderScoreBars(liveScores.scores);
- } else {
- classifierScoresEl.textContent = 'Classifier scores: -';
- renderScoreBars(null);
- }
- }
- }
- if (recordingMetaEl) {
- recordingMetaEl.textContent = 'Recording: -';
- }
- if (recordingMetaLink) {
- recordingMetaLink.href = '#';
- recordingIQLink.href = '#';
- recordingAudioLink.href = '#';
- }
- drawerEl.classList.add('open');
- drawerEl.setAttribute('aria-hidden', 'false');
- renderDetailSpectrogram();
- renderLists();
-}
-
-function closeDrawer() {
- drawerEl.classList.remove('open');
- drawerEl.setAttribute('aria-hidden', 'true');
- selectedEventId = null;
- renderLists();
-}
-
-function fitView() {
- zoom = 1;
- pan = 0;
- followLive = true;
-}
-
-function tuneToFrequency(centerHz) {
- if (!Number.isFinite(centerHz)) return;
- followLive = true;
- centerInput.value = (centerHz / 1e6).toFixed(6);
- queueConfigUpdate({ center_hz: centerHz });
-}
-
-function connect() {
- clearTimeout(wsReconnectTimer);
- const proto = location.protocol === 'https:' ? 'wss' : 'ws';
- const ws = new WebSocket(`${proto}://${location.host}/ws`);
- setWsBadge('Connecting', 'neutral');
-
- ws.onopen = () => setWsBadge('Live', 'ok');
- ws.onmessage = (ev) => {
- latest = JSON.parse(ev.data);
- markSpectrumDirty();
- if (followLive) pan = 0;
- updateHeroMetrics();
- renderLists();
- };
- ws.onclose = () => {
- setWsBadge('Retrying', 'bad');
- wsReconnectTimer = setTimeout(connect, 1000);
- };
- ws.onerror = () => ws.close();
-}
-
-function renderLoop() {
- renderFrames += 1;
- const now = performance.now();
- if (now - lastFpsTs >= 1000) {
- renderFps = (renderFrames * 1000) / (now - lastFpsTs);
- renderFrames = 0;
- lastFpsTs = now;
- }
-
- if (latest) {
- renderBandNavigator();
- renderSpectrum();
- renderWaterfall();
- renderOccupancy();
- renderTimeline();
- if (drawerEl.classList.contains('open')) renderDetailSpectrogram();
- }
- updateHeroMetrics();
- requestAnimationFrame(renderLoop);
-}
-
-function handleSpectrumClick(ev) {
- const rect = spectrumCanvas.getBoundingClientRect();
- const x = (ev.clientX - rect.left) * (spectrumCanvas.width / rect.width);
- const y = (ev.clientY - rect.top) * (spectrumCanvas.height / rect.height);
-
- for (let i = liveSignalRects.length - 1; i >= 0; i--) {
- const r = liveSignalRects[i];
- if (x >= r.x && x <= r.x + r.w && y >= r.y && y <= r.y + r.h) {
- tuneToFrequency(r.signal.center_hz);
- return;
- }
- }
-
- if (!latest) return;
- const span = latest.sample_rate / zoom;
- const startHz = latest.center_hz - span / 2 + pan * span;
- const clickedHz = startHz + (x / spectrumCanvas.width) * span;
- tuneToFrequency(clickedHz);
-}
-
-function handleNavPosition(ev) {
- if (!latest) return;
- const rect = navCanvas.getBoundingClientRect();
- const x = Math.max(0, Math.min(rect.width, ev.clientX - rect.left));
- const norm = x / rect.width;
- const fullStart = latest.center_hz - latest.sample_rate / 2;
- const newViewCenter = fullStart + norm * latest.sample_rate;
- const span = latest.sample_rate / zoom;
- const desiredPan = (newViewCenter - latest.center_hz) / span;
- pan = Math.max(-0.5, Math.min(0.5, desiredPan));
- followLive = false;
-}
-
-function exportSelectedEvent() {
- const ev = eventsById.get(selectedEventId);
- if (!ev) return;
- const blob = new Blob([JSON.stringify(ev, null, 2)], { type: 'application/json' });
- const a = document.createElement('a');
- a.href = URL.createObjectURL(blob);
- a.download = `event-${ev.id}.json`;
- a.click();
- URL.revokeObjectURL(a.href);
-}
-
-spectrumCanvas.addEventListener('wheel', (ev) => {
- ev.preventDefault();
- const direction = Math.sign(ev.deltaY);
- zoom = Math.max(0.25, Math.min(24, zoom * (direction > 0 ? 1.12 : 0.89)));
- followLive = false;
-});
-
-spectrumCanvas.addEventListener('mousedown', (ev) => {
- isDraggingSpectrum = true;
- dragStartX = ev.clientX;
- dragStartPan = pan;
-});
-window.addEventListener('mouseup', () => {
- isDraggingSpectrum = false;
- navDrag = false;
-});
-spectrumCanvas.addEventListener('mouseleave', hideSignalPopover);
-window.addEventListener('mousemove', (ev) => {
- const rect = spectrumCanvas.getBoundingClientRect();
- const x = (ev.clientX - rect.left) * (spectrumCanvas.width / rect.width);
- const y = (ev.clientY - rect.top) * (spectrumCanvas.height / rect.height);
- let hoverHit = null;
- for (let i = liveSignalRects.length - 1; i >= 0; i--) {
- const r = liveSignalRects[i];
- if (x >= r.x && x <= r.x + r.w && y >= r.y && y <= r.y + r.h) {
- hoverHit = r;
- break;
- }
- }
- if (hoverHit) {
- hoveredSignal = hoverHit.signal;
- renderSignalPopover(hoverHit, hoverHit.signal);
- } else {
- scheduleHideSignalPopover();
- }
- if (isDraggingSpectrum) {
- const dx = ev.clientX - dragStartX;
- pan = Math.max(-0.5, Math.min(0.5, dragStartPan - dx / spectrumCanvas.clientWidth));
- followLive = false;
- }
- if (navDrag) handleNavPosition(ev);
-});
-
-spectrumCanvas.addEventListener('dblclick', fitView);
-spectrumCanvas.addEventListener('click', handleSpectrumClick);
-
-navCanvas.addEventListener('mousedown', (ev) => {
- navDrag = true;
- handleNavPosition(ev);
-});
-navCanvas.addEventListener('click', handleNavPosition);
-
-centerInput.addEventListener('change', () => {
- const mhz = parseFloat(centerInput.value);
- if (Number.isFinite(mhz)) tuneToFrequency(fromMHz(mhz));
-});
-
-spanInput.addEventListener('change', () => {
- const mhz = parseFloat(spanInput.value);
- if (!Number.isFinite(mhz) || mhz <= 0) return;
- const baseRate = currentConfig?.sample_rate || latest?.sample_rate;
- if (!baseRate) return;
- zoom = Math.max(0.25, Math.min(24, baseRate / fromMHz(mhz)));
- followLive = false;
-});
-
-sampleRateSelect.addEventListener('change', () => {
- const mhz = parseFloat(sampleRateSelect.value);
- if (Number.isFinite(mhz)) queueConfigUpdate({ sample_rate: Math.round(fromMHz(mhz)) });
-});
-
-bwSelect.addEventListener('change', () => {
- const bw = parseInt(bwSelect.value, 10);
- if (Number.isFinite(bw)) queueConfigUpdate({ tuner_bw_khz: bw });
-});
-
-fftSelect.addEventListener('change', () => {
- const size = parseInt(fftSelect.value, 10);
- if (Number.isFinite(size)) queueConfigUpdate({ fft_size: size });
-});
-
-gainRange.addEventListener('input', () => {
- gainInput.value = gainRange.value;
- const uiVal = parseFloat(gainRange.value);
- if (Number.isFinite(uiVal)) queueConfigUpdate({ gain_db: Math.max(0, Math.min(GAIN_MAX, GAIN_MAX - uiVal)) });
-});
-
-gainInput.addEventListener('change', () => {
- const uiVal = parseFloat(gainInput.value);
- if (Number.isFinite(uiVal)) {
- gainRange.value = uiVal;
- queueConfigUpdate({ gain_db: Math.max(0, Math.min(GAIN_MAX, GAIN_MAX - uiVal)) });
- }
-});
-
-thresholdRange.addEventListener('input', () => {
- thresholdInput.value = thresholdRange.value;
- queueConfigUpdate({ detector: { threshold_db: parseFloat(thresholdRange.value) } });
-});
thresholdInput.addEventListener('change', () => {
const v = parseFloat(thresholdInput.value);
if (Number.isFinite(v)) {
@@ -1382,15 +470,6 @@ thresholdInput.addEventListener('change', () => {
if (classifierModeSelect) classifierModeSelect.addEventListener('change', () => {
queueConfigUpdate({ classifier_mode: classifierModeSelect.value });
});
-
-if (cfarModeSelect) cfarModeSelect.addEventListener('change', () => {
- queueConfigUpdate({ detector: { cfar_mode: cfarModeSelect.value } });
- const rankRow = cfarRankInput?.closest('.field');
- if (rankRow) rankRow.style.display = (cfarModeSelect.value === 'OS') ? '' : 'none';
-});
-if (cfarWrapToggle) cfarWrapToggle.addEventListener('change', () => {
- queueConfigUpdate({ detector: { cfar_wrap_around: cfarWrapToggle.checked } });
-});
if (cfarGuardHzInput) cfarGuardHzInput.addEventListener('change', () => {
const v = parseFloat(cfarGuardHzInput.value);
if (Number.isFinite(v) && v >= 0) queueConfigUpdate({ detector: { cfar_guard_hz: v } });
@@ -1399,42 +478,6 @@ if (cfarTrainHzInput) cfarTrainHzInput.addEventListener('change', () => {
const v = parseFloat(cfarTrainHzInput.value);
if (Number.isFinite(v) && v > 0) queueConfigUpdate({ detector: { cfar_train_hz: v } });
});
-if (cfarRankInput) cfarRankInput.addEventListener('change', () => {
- const v = parseInt(cfarRankInput.value, 10);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { cfar_rank: v } });
-});
-if (cfarScaleInput) cfarScaleInput.addEventListener('change', () => {
- const v = parseFloat(cfarScaleInput.value);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { cfar_scale_db: v } });
-});
-if (minDurationInput) minDurationInput.addEventListener('change', () => {
- const v = parseInt(minDurationInput.value, 10);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { min_duration_ms: v } });
-});
-if (holdInput) holdInput.addEventListener('change', () => {
- const v = parseInt(holdInput.value, 10);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { hold_ms: v } });
-});
-if (emaAlphaInput) emaAlphaInput.addEventListener('change', () => {
- const v = parseFloat(emaAlphaInput.value);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { ema_alpha: v } });
-});
-if (hysteresisInput) hysteresisInput.addEventListener('change', () => {
- const v = parseFloat(hysteresisInput.value);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { hysteresis_db: v } });
-});
-if (stableFramesInput) stableFramesInput.addEventListener('change', () => {
- const v = parseInt(stableFramesInput.value, 10);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { min_stable_frames: v } });
-});
-if (gapToleranceInput) gapToleranceInput.addEventListener('change', () => {
- const v = parseInt(gapToleranceInput.value, 10);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { gap_tolerance_ms: v } });
-});
-if (edgeMarginInput) edgeMarginInput.addEventListener('change', () => {
- const v = parseFloat(edgeMarginInput.value);
- if (Number.isFinite(v)) queueConfigUpdate({ detector: { edge_margin_db: v } });
-});
if (mergeGapInput) mergeGapInput.addEventListener('change', () => {
const v = parseFloat(mergeGapInput.value);
if (Number.isFinite(v)) queueConfigUpdate({ detector: { merge_gap_hz: v } });
@@ -1447,243 +490,3 @@ if (classSwitchInput) classSwitchInput.addEventListener('change', () => {
const v = parseFloat(classSwitchInput.value);
if (Number.isFinite(v) && v >= 0.1 && v <= 1.0) queueConfigUpdate({ detector: { class_switch_ratio: v } });
});
-
-agcToggle.addEventListener('change', () => queueSettingsUpdate({ agc: agcToggle.checked }));
-dcToggle.addEventListener('change', () => queueSettingsUpdate({ dc_block: dcToggle.checked }));
-iqToggle.addEventListener('change', () => queueSettingsUpdate({ iq_balance: iqToggle.checked }));
-gpuToggle.addEventListener('change', () => queueConfigUpdate({ use_gpu_fft: gpuToggle.checked }));
-if (recEnableToggle) recEnableToggle.addEventListener('change', () => queueConfigUpdate({ recorder: { enabled: recEnableToggle.checked } }));
-if (recIQToggle) recIQToggle.addEventListener('change', () => queueConfigUpdate({ recorder: { record_iq: recIQToggle.checked } }));
-if (recAudioToggle) recAudioToggle.addEventListener('change', () => queueConfigUpdate({ recorder: { record_audio: recAudioToggle.checked } }));
-if (recDemodToggle) recDemodToggle.addEventListener('change', () => queueConfigUpdate({ recorder: { auto_demod: recDemodToggle.checked } }));
-if (recDecodeToggle) recDecodeToggle.addEventListener('change', () => queueConfigUpdate({ recorder: { auto_decode: recDecodeToggle.checked } }));
-if (recMinSNR) recMinSNR.addEventListener('change', () => queueConfigUpdate({ recorder: { min_snr_db: parseFloat(recMinSNR.value) } }));
-if (recMaxDisk) recMaxDisk.addEventListener('change', () => queueConfigUpdate({ recorder: { max_disk_mb: parseInt(recMaxDisk.value || '0', 10) } }));
-if (recClassFilter) recClassFilter.addEventListener('change', () => {
- const list = (recClassFilter.value || '')
- .split(',')
- .map(s => s.trim())
- .filter(Boolean);
- queueConfigUpdate({ recorder: { class_filter: list } });
-});
-
-avgSelect.addEventListener('change', () => {
- avgAlpha = parseFloat(avgSelect.value) || 0;
- resetProcessingCaches();
-});
-maxHoldToggle.addEventListener('change', () => {
- maxHold = maxHoldToggle.checked;
- maxSpectrum = null;
- markSpectrumDirty();
-});
-if (debugOverlayToggle) debugOverlayToggle.addEventListener('change', () => {
- showDebugOverlay = debugOverlayToggle.checked;
- localStorage.setItem('spectre.debugOverlay', showDebugOverlay ? '1' : '0');
- markSpectrumDirty();
- updateHeroMetrics();
-});
-resetMaxBtn.addEventListener('click', () => {
- maxSpectrum = null;
- markSpectrumDirty();
-});
-followBtn.addEventListener('click', () => { followLive = true; pan = 0; });
-fitBtn.addEventListener('click', fitView);
-timelineFollowBtn.addEventListener('click', () => { timelineFrozen = false; });
-timelineFreezeBtn.addEventListener('click', () => {
- timelineFrozen = !timelineFrozen;
- timelineFreezeBtn.textContent = timelineFrozen ? 'Frozen' : 'Freeze';
-});
-
-presetButtons.forEach((btn) => {
- btn.addEventListener('click', () => {
- const mhz = parseFloat(btn.dataset.center);
- if (Number.isFinite(mhz)) tuneToFrequency(fromMHz(mhz));
- });
-});
-
-railTabs.forEach((tab) => {
- tab.addEventListener('click', () => {
- railTabs.forEach(t => t.classList.toggle('active', t === tab));
- tabPanels.forEach(panel => panel.classList.toggle('active', panel.dataset.panel === tab.dataset.tab));
- });
-});
-
-modeButtons.forEach((btn) => {
- btn.addEventListener('click', () => {
- modeButtons.forEach(b => b.classList.toggle('active', b === btn));
- document.body.classList.remove('mode-live', 'mode-hunt', 'mode-review', 'mode-lab');
- document.body.classList.add(`mode-${btn.dataset.mode}`);
- });
-});
-document.body.classList.add('mode-live');
-
-drawerCloseBtn.addEventListener('click', closeDrawer);
-exportEventBtn.addEventListener('click', exportSelectedEvent);
-if (liveListenEventBtn) {
- liveListenEventBtn.addEventListener('click', () => {
- const ev = eventsById.get(selectedEventId);
- if (!ev) return;
- const freq = ev.center_hz;
- const bw = ev.bandwidth_hz || 12000;
- const mode = (listenModeSelect?.value || ev.class?.mod_type || 'NFM');
- const sec = parseInt(listenSecondsInput?.value || '2', 10);
- const url = `/api/demod?freq=${freq}&bw=${bw}&mode=${mode}&sec=${sec}`;
- const audio = new Audio(url);
- audio.play();
- });
-}
-if (decodeEventBtn) {
- decodeEventBtn.addEventListener('click', async () => {
- const ev = eventsById.get(selectedEventId);
- if (!ev) return;
- if (!recordingMetaEl) return;
- const rec = recordings.find(r => r.event_id === ev.id) || recordings.find(r => r.center_hz === ev.center_hz);
- if (!rec) {
- decodeResultEl.textContent = 'Decode: no recording';
- return;
- }
- const mode = decodeModeSelect?.value || ev.class?.mod_type || 'FT8';
- const res = await fetch(`/api/recordings/${rec.id}/decode?mode=${mode}`);
- if (!res.ok) {
- decodeResultEl.textContent = 'Decode: failed';
- return;
- }
- const data = await res.json();
- decodeResultEl.textContent = `Decode: ${String(data.stdout || '').slice(0, 80)}`;
- });
-}
-jumpToEventBtn.addEventListener('click', () => {
- const ev = eventsById.get(selectedEventId);
- if (!ev) return;
- tuneToFrequency(ev.center_hz);
-});
-
-timelineCanvas.addEventListener('click', (ev) => {
- const rect = timelineCanvas.getBoundingClientRect();
- const x = (ev.clientX - rect.left) * (timelineCanvas.width / rect.width);
- const y = (ev.clientY - rect.top) * (timelineCanvas.height / rect.height);
- for (let i = timelineRects.length - 1; i >= 0; i--) {
- const r = timelineRects[i];
- if (x >= r.x && x <= r.x + r.w && y >= r.y && y <= r.y + r.h) {
- openDrawer(eventsById.get(r.id));
- return;
- }
- }
-});
-
-signalList.addEventListener('click', (ev) => {
- const target = ev.target.closest('.signal-item');
- if (!target) return;
- const center = parseFloat(target.dataset.center);
- if (Number.isFinite(center)) tuneToFrequency(center);
-});
-
-if (liveListenBtn) {
- liveListenBtn.addEventListener('click', async () => {
- const first = signalList.querySelector('.signal-item');
- if (!first) return;
- const freq = parseFloat(first.dataset.center);
- const bw = parseFloat(first.dataset.bw || '12000');
- const mode = (listenModeSelect?.value || first.dataset.class || 'NFM');
- const sec = parseInt(listenSecondsInput?.value || '2', 10);
- const url = `/api/demod?freq=${freq}&bw=${bw}&mode=${mode}&sec=${sec}`;
- if (liveAudio) {
- liveAudio.pause();
- }
- liveAudio = new Audio(url);
- liveAudio.play().catch(() => {});
- });
-}
-
-eventList.addEventListener('click', (ev) => {
- const target = ev.target.closest('.event-item');
- if (!target) return;
- const id = target.dataset.eventId;
- openDrawer(eventsById.get(id));
-});
-
-if (recordingList) {
- recordingList.addEventListener('click', async (ev) => {
- const target = ev.target.closest('.recording-item');
- if (!target) return;
- const id = target.dataset.id;
- const audio = new Audio(`/api/recordings/${id}/audio`);
- audio.play();
- if (recordingMetaEl) recordingMetaEl.textContent = `Recording: ${id}`;
- if (recordingMetaLink) {
- recordingMetaLink.href = `/api/recordings/${id}`;
- recordingIQLink.href = `/api/recordings/${id}/iq`;
- recordingAudioLink.href = `/api/recordings/${id}/audio`;
- }
- try {
- const res = await fetch(`/api/recordings/${id}`);
- if (!res.ok) return;
- const meta = await res.json();
- if (decodeResultEl) {
- const rds = meta.rds_ps ? `RDS: ${meta.rds_ps}` : '';
- decodeResultEl.textContent = `Decode: ${rds}`;
- }
- if (classifierScoresEl) {
- const scores = meta.classification?.scores;
- if (scores && typeof scores === 'object') {
- const rows = Object.entries(scores)
- .sort((a, b) => b[1] - a[1])
- .slice(0, 6)
- .map(([k, v]) => `${k}:${v.toFixed(2)}`)
- .join(' · ');
- classifierScoresEl.textContent = rows ? `Classifier scores: ${rows}` : 'Classifier scores: -';
- } else {
- classifierScoresEl.textContent = 'Classifier scores: -';
- }
- }
- } catch {}
- });
-}
-
-if (debugOverlayToggle) debugOverlayToggle.checked = showDebugOverlay;
-
-window.addEventListener('keydown', (ev) => {
- if (ev.target && ['INPUT', 'SELECT', 'TEXTAREA'].includes(ev.target.tagName)) return;
- if (ev.key === ' ') {
- ev.preventDefault();
- followLive = true;
- pan = 0;
- } else if (ev.key.toLowerCase() === 'f') {
- fitView();
- } else if (ev.key.toLowerCase() === 'm') {
- maxHold = !maxHold;
- maxHoldToggle.checked = maxHold;
- if (!maxHold) maxSpectrum = null;
- markSpectrumDirty();
- } else if (ev.key.toLowerCase() === 'g') {
- gpuToggle.checked = !gpuToggle.checked;
- queueConfigUpdate({ use_gpu_fft: gpuToggle.checked });
- } else if (ev.key === '[') {
- zoom = Math.max(0.25, zoom * 0.88);
- } else if (ev.key === ']') {
- zoom = Math.min(24, zoom * 1.12);
- } else if (ev.key === 'ArrowLeft') {
- pan = Math.max(-0.5, pan - 0.04);
- followLive = false;
- } else if (ev.key === 'ArrowRight') {
- pan = Math.min(0.5, pan + 0.04);
- followLive = false;
- }
-});
-
-loadConfig();
-loadStats();
-loadGPU();
-fetchEvents(true);
-fetchRecordings();
-loadDecoders();
-connect();
-requestAnimationFrame(renderLoop);
-setInterval(loadStats, 1000);
-setInterval(loadGPU, 1000);
-setInterval(() => fetchEvents(false), 2000);
-setInterval(fetchRecordings, 5000);
-setInterval(loadSignals, 1500);
-setInterval(loadDecoders, 10000);
-
-