Add acoustic ranging maths and a room simulator

Chirp generation, FFT matched filter, first-arrival detection with
sub-sample peak fitting, the BeepBeep pair solve, triangle-inequality
outlier rejection and classical MDS, plus a virtual room that
synthesizes what each device would have recorded so the pipeline can be
exercised without microphones.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
This commit is contained in:
Josh-Heaps
2026-07-30 14:41:39 -06:00
co-authored by Claude Opus 5
parent f956f4bffa
commit 183a53234f
2 changed files with 798 additions and 0 deletions
@@ -0,0 +1,585 @@
/*
* Pure signal-processing and geometry for acoustic ranging. No DOM, no Web Audio, no network:
* everything here is a function of its arguments so the simulator and the tests can drive the
* exact code the page runs.
*/
const EchoDsp = {
speedOfSound(temperatureCelsius = 20) {
return 331.3 + 0.606 * temperatureCelsius;
},
nextPowerOfTwo(value) {
let size = 1;
while (size < value) size <<= 1;
return size;
},
/**
* Linear frequency sweep, tapered at both ends. A sweep is used rather than a tone because a
* tone's autocorrelation peaks once per period, leaving no unambiguous arrival to measure.
*/
makeChirp({ sampleRate, durationSeconds, startHz, endHz, taperFraction = 0.15 }) {
const length = Math.round(sampleRate * durationSeconds);
const sweepRate = (endHz - startHz) / durationSeconds;
const chirp = new Float32Array(length);
for (let i = 0; i < length; i++) {
const t = i / sampleRate;
chirp[i] = Math.sin(2 * Math.PI * (startHz * t + 0.5 * sweepRate * t * t));
}
return this.applyTaper(chirp, taperFraction);
},
applyTaper(signal, fraction) {
const edge = Math.max(1, Math.floor(signal.length * fraction));
for (let i = 0; i < edge; i++) {
const window = 0.5 - 0.5 * Math.cos((Math.PI * i) / edge);
signal[i] *= window;
signal[signal.length - 1 - i] *= window;
}
return signal;
},
twiddles(size) {
this._twiddleCache ??= new Map();
const cached = this._twiddleCache.get(size);
if (cached) return cached;
const half = size >> 1;
const table = { cos: new Float64Array(half), sin: new Float64Array(half) };
for (let i = 0; i < half; i++) {
const angle = (-2 * Math.PI * i) / size;
table.cos[i] = Math.cos(angle);
table.sin[i] = Math.sin(angle);
}
this._twiddleCache.set(size, table);
return table;
},
fft(real, imaginary, inverse = false) {
const size = real.length;
this.reverseBits(real, imaginary);
const { cos, sin } = this.twiddles(size);
for (let span = 2; span <= size; span <<= 1) {
const half = span >> 1;
const stride = size / span;
for (let base = 0; base < size; base += span) {
for (let k = 0; k < half; k++) {
const twiddle = k * stride;
const wReal = cos[twiddle];
const wImaginary = inverse ? -sin[twiddle] : sin[twiddle];
const lower = base + k;
const upper = lower + half;
const productReal = real[upper] * wReal - imaginary[upper] * wImaginary;
const productImaginary = real[upper] * wImaginary + imaginary[upper] * wReal;
real[upper] = real[lower] - productReal;
imaginary[upper] = imaginary[lower] - productImaginary;
real[lower] += productReal;
imaginary[lower] += productImaginary;
}
}
}
if (!inverse) return { real, imaginary };
for (let i = 0; i < size; i++) {
real[i] /= size;
imaginary[i] /= size;
}
return { real, imaginary };
},
reverseBits(real, imaginary) {
const size = real.length;
for (let i = 1, j = 0; i < size; i++) {
let bit = size >> 1;
for (; j & bit; bit >>= 1) j ^= bit;
j ^= bit;
if (i >= j) continue;
[real[i], real[j]] = [real[j], real[i]];
[imaginary[i], imaginary[j]] = [imaginary[j], imaginary[i]];
}
return { real, imaginary };
},
/**
* Matched-filter envelope of a recording against a template, via FFT cross-correlation.
* Negative frequencies are dropped so the result is the analytic envelope rather than a burst
* oscillating at the sweep frequency — an oscillating peak defeats sub-sample interpolation
* and makes first-arrival detection jitter by half a carrier period.
*/
matchedFilterEnvelope(recording, template) {
const size = this.nextPowerOfTwo(recording.length + template.length);
const recordingReal = new Float64Array(size);
const recordingImaginary = new Float64Array(size);
const templateReal = new Float64Array(size);
const templateImaginary = new Float64Array(size);
recordingReal.set(recording);
templateReal.set(template);
this.fft(recordingReal, recordingImaginary);
this.fft(templateReal, templateImaginary);
const analyticReal = new Float64Array(size);
const analyticImaginary = new Float64Array(size);
const half = size >> 1;
for (let i = 0; i <= half; i++) {
const gain = i === 0 || i === half ? 1 : 2;
analyticReal[i] = gain * (recordingReal[i] * templateReal[i] + recordingImaginary[i] * templateImaginary[i]);
analyticImaginary[i] = gain * (recordingImaginary[i] * templateReal[i] - recordingReal[i] * templateImaginary[i]);
}
this.fft(analyticReal, analyticImaginary, true);
const envelope = new Float32Array(recording.length);
for (let i = 0; i < envelope.length; i++)
envelope[i] = Math.sqrt(analyticReal[i] * analyticReal[i] + analyticImaginary[i] * analyticImaginary[i]);
return envelope;
},
maxInRange(values, start, end) {
let index = start;
let value = -Infinity;
for (let i = start; i < end; i++) {
if (values[i] <= value) continue;
value = values[i];
index = i;
}
return { index, value };
},
medianInRange(values, start, end, sampleLimit = 2048) {
const span = end - start;
if (span <= 0) return 0;
const stride = Math.max(1, Math.floor(span / sampleLimit));
const sampled = [];
for (let i = start; i < end; i += stride) sampled.push(values[i]);
sampled.sort((left, right) => left - right);
return sampled[sampled.length >> 1];
},
/**
* Sub-sample peak position by fitting a parabola through the peak and its neighbours. One
* tenth of a sample is 0.7mm of range at 48kHz, so this is most of the accuracy for free.
*/
refinePeakIndex(envelope, index) {
if (index <= 0 || index >= envelope.length - 1) return index;
const before = envelope[index - 1];
const peak = envelope[index];
const after = envelope[index + 1];
const curvature = before - 2 * peak + after;
if (curvature === 0) return index;
const offset = (0.5 * (before - after)) / curvature;
return index + Math.max(-1, Math.min(1, offset));
},
/**
* First arrival in a window, not the loudest one. A reflection off a wall or table often
* comes back louder than the direct path, and only the direct path is the distance.
*/
findFirstPeak(envelope, options = {}) {
const start = Math.max(0, Math.floor(options.start ?? 0));
const end = Math.min(envelope.length, Math.ceil(options.end ?? envelope.length));
if (end - start < 8) return null;
const loudest = this.maxInRange(envelope, start, end);
const noiseFloor = this.medianInRange(envelope, start, end);
const snr = noiseFloor > 0 ? loudest.value / noiseFloor : Infinity;
if (snr < (options.minSnr ?? 4)) return null;
// Held above the noise floor so sidelobes cannot trigger it, but well below the loudest
// arrival so that a reflection several times louder than the direct path cannot mask it.
const threshold = Math.max(
noiseFloor * (options.noiseMultiple ?? 6),
loudest.value * (options.relativeThreshold ?? 0.15)
);
let crossing = start;
while (crossing < end && envelope[crossing] < threshold) crossing++;
if (crossing >= end) return null;
const lobeEnd = Math.min(end, crossing + (options.lobeSamples ?? 64));
const arrival = this.maxInRange(envelope, crossing, lobeEnd);
return { index: this.refinePeakIndex(envelope, arrival.index), amplitude: arrival.value, snr };
},
/**
* Locate every chirp of one round in a single device's recording.
*
* The device's own chirp is the anchor: it is always present and always the loudest thing in
* the recording, and its position absorbs this device's own output and input latency. Every
* other slot is then searched relative to that anchor, so no clock agreement between devices
* is required — only that the chirps stay in their slots.
*/
detectSlotPeaks({
envelope,
slotCount,
slotSamples,
ownSlot,
ownSearchStart,
ownSearchSamples,
slotHints = null,
peakOptions = {}
}) {
const own = this.findFirstPeak(envelope, {
...peakOptions,
start: ownSearchStart,
end: ownSearchStart + ownSearchSamples
});
if (!own) return null;
const anchor = own.index - ownSlot * slotSamples;
const pad = Math.floor(slotSamples * 0.45);
const peaks = new Array(slotCount).fill(null);
peaks[ownSlot] = own;
for (let slot = 0; slot < slotCount; slot++) {
if (slot === ownSlot) continue;
const centre = anchor + slot * slotSamples + (slotHints?.[slot] ?? 0);
peaks[slot] = this.findFirstPeak(envelope, {
...peakOptions,
start: centre - pad,
end: centre + pad
});
}
return { anchor, peaks };
},
/**
* Distance between two devices from four arrival indices, each measured inside the recording
* of the device that made it. Clock offset and audio-pipeline latency appear once with each
* sign and cancel; the devices' own speaker-to-microphone spacing does not, and is added back.
*/
pairDistance({ a1, a2, b1, b2, sampleRate, sampleRateA, sampleRateB, speedOfSound, epsilonA = 0, epsilonB = 0 }) {
// Each interval is converted to seconds in its own device's sample rate before the two are
// subtracted: a device that hands back 44100 instead of 48000 would otherwise contribute
// its interval in the wrong unit.
const intervalA = (a2 - a1) / (sampleRateA ?? sampleRate);
const intervalB = (b2 - b1) / (sampleRateB ?? sampleRate);
return ((intervalA - intervalB) / 2) * speedOfSound + (epsilonA + epsilonB) / 2;
},
/**
* Symmetric distance matrix from one round of reports. Entries stay null where either device
* failed to hear one of the four chirps the pair needs.
*/
buildDistanceMatrix(reports, { speedOfSound = 343, maxDistance = 40 } = {}) {
const count = reports.length;
const matrix = Array.from({ length: count }, () => new Array(count).fill(null));
for (let i = 0; i < count; i++) {
matrix[i][i] = 0;
for (let j = i + 1; j < count; j++) {
const distance = this.distanceBetween(reports[i], reports[j], speedOfSound);
if (distance === null || distance < -1 || distance > maxDistance) continue;
matrix[i][j] = Math.max(0, distance);
matrix[j][i] = matrix[i][j];
}
}
return matrix;
},
distanceBetween(deviceA, deviceB, speedOfSound) {
const a1 = deviceA.peaks[deviceA.slot];
const a2 = deviceA.peaks[deviceB.slot];
const b1 = deviceB.peaks[deviceA.slot];
const b2 = deviceB.peaks[deviceB.slot];
if (a1 === null || a2 === null || b1 === null || b2 === null) return null;
return this.pairDistance({
a1,
a2,
b1,
b2,
sampleRateA: deviceA.sampleRate,
sampleRateB: deviceB.sampleRate,
speedOfSound,
epsilonA: deviceA.epsilon ?? 0,
epsilonB: deviceB.epsilon ?? 0
});
},
/**
* Largest set of devices linked by measured distances. Anything outside it cannot be placed
* relative to the others, and leaving it in makes the completed matrix infinite.
*/
largestConnectedComponent(matrix) {
const unvisited = new Set(matrix.map((_, index) => index));
let largest = [];
while (unvisited.size > 0) {
const component = [];
const queue = [unvisited.values().next().value];
unvisited.delete(queue[0]);
while (queue.length > 0) {
const current = queue.pop();
component.push(current);
for (const next of unvisited)
if (matrix[current][next] !== null) {
unvisited.delete(next);
queue.push(next);
}
}
if (component.length > largest.length) largest = component;
}
return largest.sort((left, right) => left - right);
},
/**
* Drop devices whose distances are geometrically impossible. One device reporting a bad peak
* distorts the whole layout, so the worst triangle-inequality offender is removed and the
* check repeated. Below four devices there is no redundancy left and nothing can be checked.
*/
rejectOutliers(matrix, candidates, tolerance = 0.5) {
const keep = [...candidates];
while (keep.length > 3) {
const violations = this.countTriangleViolations(matrix, keep, tolerance);
const worst = violations.reduce((best, count, index) => (count > violations[best] ? index : best), 0);
if (violations[worst] === 0) break;
keep.splice(worst, 1);
}
return keep;
},
submatrix(matrix, indices) {
return indices.map(row => indices.map(column => matrix[row][column]));
},
countTriangleViolations(matrix, keep, tolerance) {
const violations = new Array(keep.length).fill(0);
for (let i = 0; i < keep.length; i++) {
for (let j = i + 1; j < keep.length; j++) {
for (let k = j + 1; k < keep.length; k++) {
const sides = [matrix[keep[i]][keep[j]], matrix[keep[j]][keep[k]], matrix[keep[i]][keep[k]]];
if (sides.some(side => side === null)) continue;
const longest = Math.max(...sides);
const perimeter = sides.reduce((sum, side) => sum + side, 0);
if (longest <= perimeter - longest + tolerance) continue;
violations[i]++;
violations[j]++;
violations[k]++;
}
}
}
return violations;
},
/** Fill gaps with the shortest known path between the two devices so MDS gets a full matrix. */
completeMatrix(matrix) {
const count = matrix.length;
const filled = matrix.map(row => row.map(value => (value === null ? Infinity : value)));
for (let via = 0; via < count; via++)
for (let i = 0; i < count; i++)
for (let j = 0; j < count; j++)
filled[i][j] = Math.min(filled[i][j], filled[i][via] + filled[via][j]);
return filled;
},
/** Jacobi eigendecomposition of a symmetric matrix. Returns eigenvalues and column vectors. */
symmetricEigen(matrix, maxSweeps = 100, tolerance = 1e-14) {
const count = matrix.length;
const working = matrix.map(row => Float64Array.from(row));
const vectors = Array.from({ length: count }, (_, i) => {
const column = new Float64Array(count);
column[i] = 1;
return column;
});
for (let sweep = 0; sweep < maxSweeps; sweep++) {
if (this.offDiagonalMagnitude(working) < tolerance) break;
for (let p = 0; p < count - 1; p++)
for (let q = p + 1; q < count; q++)
this.rotateOut(working, vectors, p, q);
}
return {
values: working.map((row, i) => row[i]),
vectors
};
},
offDiagonalMagnitude(matrix) {
let total = 0;
for (let i = 0; i < matrix.length; i++)
for (let j = i + 1; j < matrix.length; j++) total += matrix[i][j] * matrix[i][j];
return total;
},
rotateOut(matrix, vectors, p, q) {
if (Math.abs(matrix[p][q]) < 1e-300) return matrix;
const theta = (matrix[q][q] - matrix[p][p]) / (2 * matrix[p][q]);
const sign = theta >= 0 ? 1 : -1;
const tangent = sign / (Math.abs(theta) + Math.sqrt(theta * theta + 1));
const cosine = 1 / Math.sqrt(tangent * tangent + 1);
const sine = tangent * cosine;
const count = matrix.length;
for (let k = 0; k < count; k++) {
const left = matrix[k][p];
const right = matrix[k][q];
matrix[k][p] = cosine * left - sine * right;
matrix[k][q] = sine * left + cosine * right;
}
for (let k = 0; k < count; k++) {
const left = matrix[p][k];
const right = matrix[q][k];
matrix[p][k] = cosine * left - sine * right;
matrix[q][k] = sine * left + cosine * right;
}
for (let k = 0; k < count; k++) {
const left = vectors[k][p];
const right = vectors[k][q];
vectors[k][p] = cosine * left - sine * right;
vectors[k][q] = sine * left + cosine * right;
}
return matrix;
},
/**
* Classical multidimensional scaling: coordinates whose pairwise distances best reproduce the
* matrix. The result is only defined up to rotation, translation and mirroring.
*/
classicalMds(distances, dimensions = 2) {
const count = distances.length;
const squared = distances.map(row => row.map(value => value * value));
const rowMeans = squared.map(row => row.reduce((sum, value) => sum + value, 0) / count);
const grandMean = rowMeans.reduce((sum, value) => sum + value, 0) / count;
const centred = squared.map((row, i) => row.map((value, j) => -0.5 * (value - rowMeans[i] - rowMeans[j] + grandMean)));
const { values, vectors } = this.symmetricEigen(centred);
const order = values
.map((value, index) => ({ value, index }))
.sort((left, right) => right.value - left.value)
.slice(0, dimensions);
return Array.from({ length: count }, (_, i) =>
order.map(({ value, index }) => vectors[i][index] * Math.sqrt(Math.max(0, value)))
);
},
/**
* Rotate, mirror and translate a constellation onto a reference layout. Without this, every
* solve returns an arbitrary orientation and the display spins and flips between updates.
*/
alignToReference(points, reference) {
if (!reference || reference.length !== points.length || points.length === 0) return points;
const pointCentre = this.centroid(points);
const referenceCentre = this.centroid(reference);
let best = null;
for (const mirror of [1, -1]) {
const candidate = this.rotateOnto(points, reference, pointCentre, referenceCentre, mirror);
if (!best || candidate.residual < best.residual) best = candidate;
}
return best.points;
},
centroid(points) {
const sum = points.reduce((total, [x, y]) => [total[0] + x, total[1] + y], [0, 0]);
return [sum[0] / points.length, sum[1] / points.length];
},
rotateOnto(points, reference, pointCentre, referenceCentre, mirror) {
let sineTerm = 0;
let cosineTerm = 0;
for (let i = 0; i < points.length; i++) {
const px = (points[i][0] - pointCentre[0]) * mirror;
const py = points[i][1] - pointCentre[1];
const qx = reference[i][0] - referenceCentre[0];
const qy = reference[i][1] - referenceCentre[1];
sineTerm += px * qy - py * qx;
cosineTerm += px * qx + py * qy;
}
const angle = Math.atan2(sineTerm, cosineTerm);
const cosine = Math.cos(angle);
const sine = Math.sin(angle);
let residual = 0;
const aligned = points.map((point, i) => {
const px = (point[0] - pointCentre[0]) * mirror;
const py = point[1] - pointCentre[1];
const x = px * cosine - py * sine + referenceCentre[0];
const y = px * sine + py * cosine + referenceCentre[1];
residual += (x - reference[i][0]) ** 2 + (y - reference[i][1]) ** 2;
return [x, y];
});
return { points: aligned, residual };
},
/**
* Full solve for one round: distances, connectivity, outlier rejection, then a constellation
* aligned onto the previous frame.
*
* <c>previousPoints</c> is indexed by report position, with null for devices that were dropped
* last round, so alignment survives devices coming and going.
*/
solveRound(reports, { speedOfSound = 343, previousPoints = null, tolerance = 0.5 } = {}) {
const matrix = this.buildDistanceMatrix(reports, { speedOfSound });
const connected = this.largestConnectedComponent(matrix);
const keep = this.rejectOutliers(matrix, connected, tolerance);
const points = keep.length >= 2 ? this.classicalMds(this.completeMatrix(this.submatrix(matrix, keep))) : [];
const reference = previousPoints ? keep.map(index => previousPoints[index]) : null;
const alignable = reference?.length === points.length && reference.every(Boolean);
return {
matrix,
keep,
points: alignable ? this.alignToReference(points, reference) : points
};
}
};
if (typeof window !== "undefined") window.EchoDsp = EchoDsp;
@@ -0,0 +1,213 @@
/*
* Virtual room for exercising the real ranging pipeline without microphones. Synthesizes what
* each device would have recorded — propagation delay, reflections, noise, per-device clock offset
* and unknown output latency — then runs the same EchoDsp code the page runs.
*/
const EchoSim = {
DEFAULTS: {
sampleRate: 48000,
slotSeconds: 0.4,
tailSeconds: 0.5,
speedOfSound: 343,
noiseAmplitude: 0.01,
referenceGain: 0.5,
minimumPathMetres: 0.25,
maximumOutputLatencySeconds: 0.2,
chirp: { durationSeconds: 0.05, startHz: 2000, endHz: 8000 },
reflectionsPerPath: 2,
reflectionExtraRange: [0.4, 4.0],
reflectionGainRange: [0.2, 0.8],
seed: 20260730
},
randomGenerator(seed) {
let state = seed >>> 0;
return () => {
state = (state + 0x6d2b79f5) >>> 0;
let mixed = Math.imul(state ^ (state >>> 15), 1 | state);
mixed = (mixed + Math.imul(mixed ^ (mixed >>> 7), 61 | mixed)) ^ mixed;
return ((mixed ^ (mixed >>> 14)) >>> 0) / 4294967296;
};
},
separation(first, second) {
return Math.hypot(first[0] - second[0], first[1] - second[1]);
},
buildConfiguration(overrides = {}) {
const config = { ...this.DEFAULTS, ...overrides };
const count = config.positions.length;
config.chirp = { ...this.DEFAULTS.chirp, ...(overrides.chirp ?? {}) };
config.epsilon ??= new Array(count).fill(0.05);
config.clockOffsets ??= config.positions.map((_, i) => i * 7919);
config.outputLatencies ??= config.positions.map((_, i) => 0.02 + 0.03 * i);
config.scheduleJitter ??= config.positions.map((_, i) => 0.004 * i);
config.reflections ??= this.buildReflectionTable(config);
return config;
},
/**
* Multipath for every source-to-listener path independently. Giving every path the same echo
* would be worthless as a test: an identical bias on all four arrivals cancels out of the
* range formula, so a uniform echo model hides exactly the error it is supposed to expose.
*/
buildReflectionTable(config) {
const random = this.randomGenerator(config.seed ^ 0x5f3759df);
const spread = (range, value) => range[0] + value * (range[1] - range[0]);
return config.positions.map(() =>
config.positions.map(() =>
Array.from({ length: config.reflectionsPerPath }, () => ({
extraMetres: spread(config.reflectionExtraRange, random()),
gain: spread(config.reflectionGainRange, random())
}))
)
);
},
reflectionsFor(config, source, listener) {
return Array.isArray(config.reflections[0]) ? config.reflections[source][listener] : config.reflections;
},
/** One recording per device, plus the index each device believes it started playing at. */
synthesizeRound(config) {
const { positions, sampleRate, slotSeconds, tailSeconds } = config;
const random = this.randomGenerator(config.seed);
const template = EchoDsp.makeChirp({ sampleRate, ...config.chirp });
const maximumOffset = Math.max(...config.clockOffsets);
const length = Math.ceil((positions.length * slotSeconds + tailSeconds) * sampleRate) + maximumOffset;
const devices = positions.map((_, index) => ({
recording: this.noiseBuffer(length, config.noiseAmplitude, random),
ownSearchStart: Math.round((index * slotSeconds + config.scheduleJitter[index]) * sampleRate) + config.clockOffsets[index]
}));
for (let source = 0; source < positions.length; source++)
for (let listener = 0; listener < positions.length; listener++)
this.mixArrivals(devices[listener].recording, template, config, source, listener);
return { devices, template };
},
noiseBuffer(length, amplitude, random) {
const buffer = new Float32Array(length);
for (let i = 0; i < length; i++) buffer[i] = (random() * 2 - 1) * amplitude;
return buffer;
},
mixArrivals(recording, template, config, source, listener) {
const emissionSeconds =
source * config.slotSeconds + config.scheduleJitter[source] + config.outputLatencies[source];
const directMetres =
source === listener ? config.epsilon[source] : this.separation(config.positions[source], config.positions[listener]);
const paths = [
{ metres: directMetres, gain: 1 },
...this.reflectionsFor(config, source, listener).map(({ extraMetres, gain }) => ({
metres: directMetres + extraMetres,
gain
}))
];
for (const path of paths) {
const arrival = emissionSeconds + path.metres / config.speedOfSound;
const amplitude =
(config.referenceGain / Math.max(path.metres, config.minimumPathMetres)) * path.gain;
this.addAt(recording, template, Math.round(arrival * config.sampleRate) + config.clockOffsets[listener], amplitude);
}
return recording;
},
addAt(recording, template, offset, amplitude) {
const start = Math.max(0, offset);
const end = Math.min(recording.length, offset + template.length);
for (let i = start; i < end; i++) recording[i] += template[i - offset] * amplitude;
return recording;
},
/** Run every device's recording through detection and return one report per device. */
detectAll({ devices, template }, config) {
const slotSamples = Math.round(config.slotSeconds * config.sampleRate);
const searchSamples = Math.round(
(config.maximumOutputLatencySeconds + config.chirp.durationSeconds + 0.05) * config.sampleRate
);
return devices.map((device, slot) => {
const envelope = EchoDsp.matchedFilterEnvelope(device.recording, template);
const detected = EchoDsp.detectSlotPeaks({
envelope,
slotCount: devices.length,
slotSamples,
ownSlot: slot,
ownSearchStart: device.ownSearchStart,
ownSearchSamples: searchSamples,
peakOptions: config.peakOptions ?? {}
});
return {
deviceId: `sim-${slot}`,
slot,
sampleRate: config.sampleRate,
epsilon: config.epsilon[slot],
peaks: (detected?.peaks ?? new Array(devices.length).fill(null)).map(peak => peak?.index ?? null)
};
});
},
/** Synthesize, detect and solve, reporting recovered geometry against the ground truth. */
runRound(overrides = {}) {
const config = this.buildConfiguration(overrides);
const round = this.synthesizeRound(config);
const reports = this.detectAll(round, config);
const solved = EchoDsp.solveRound(reports, { speedOfSound: config.speedOfSound });
return {
config,
reports,
...solved,
distanceErrors: this.distanceErrors(solved.matrix, config),
positionErrors: this.positionErrors(solved, config)
};
},
distanceErrors(matrix, config) {
const errors = [];
for (let i = 0; i < matrix.length; i++)
for (let j = i + 1; j < matrix.length; j++) {
const truth = this.separation(config.positions[i], config.positions[j]);
errors.push({
pair: [i, j],
truth,
measured: matrix[i][j],
error: matrix[i][j] === null ? null : matrix[i][j] - truth
});
}
return errors;
},
positionErrors({ keep, points }, config) {
if (points.length !== keep.length || points.length < 2) return [];
const truth = keep.map(index => config.positions[index]);
const aligned = EchoDsp.alignToReference(points, truth);
return aligned.map((point, i) => this.separation(point, truth[i]));
},
worstDistanceError(result) {
const magnitudes = result.distanceErrors.map(({ error }) => (error === null ? Infinity : Math.abs(error)));
return magnitudes.length === 0 ? 0 : Math.max(...magnitudes);
},
worstPositionError(result) {
return result.positionErrors.length === 0 ? Infinity : Math.max(...result.positionErrors);
}
};
if (typeof window !== "undefined") window.EchoSim = EchoSim;