do not use es2015 here

This commit is contained in:
mig 2017-05-17 16:03:45 +02:00
parent 9b1b8252bb
commit 245977c2e8

145
third-party/kalman.js vendored
View file

@ -11,79 +11,78 @@
class KalmanFilter {
function KalmanFilter(params) {
/**
* Create 1-dimensional kalman filter
* @param {Number} options.R Process noise
* @param {Number} options.Q Measurement noise
* @param {Number} options.A State vector
* @param {Number} options.B Control vector
* @param {Number} options.C Measurement vector
* @return {KalmanFilter}
*/
/**
* Create 1-dimensional kalman filter
* @param {Number} options.R Process noise
* @param {Number} options.Q Measurement noise
* @param {Number} options.A State vector
* @param {Number} options.B Control vector
* @param {Number} options.C Measurement vector
* @return {KalmanFilter}
*/
constructor({R = 1, Q = 1, A = 1, B = 0, C = 1} = {}) {
this.R = typeof params.R == "undefined" ? 1 : params.R; // noise power desirable
this.Q = typeof params.Q == "undefined" ? 1 : params.Q; // noise power estimated
this.R = R; // noise power desirable
this.Q = Q; // noise power estimated
this.A = A;
this.C = C;
this.B = B;
this.cov = NaN;
this.x = NaN; // estimated signal without noise
}
/**
* Filter a new value
* @param {Number} z Measurement
* @param {Number} u Control
* @return {Number}
*/
filter(z, u = 0) {
if (isNaN(this.x)) {
this.x = (1 / this.C) * z;
this.cov = (1 / this.C) * this.Q * (1 / this.C);
}
else {
// Compute prediction
const predX = (this.A * this.x) + (this.B * u);
const predCov = ((this.A * this.cov) * this.A) + this.R;
// Kalman gain
const K = predCov * this.C * (1 / ((this.C * predCov * this.C) + this.Q));
// Correction
this.x = predX + K * (z - (this.C * predX));
this.cov = predCov - (K * this.C * predCov);
}
return this.x;
}
/**
* Return the last filtered measurement
* @return {Number}
*/
lastMeasurement() {
return this.x;
}
/**
* Set measurement noise Q
* @param {Number} noise
*/
setMeasurementNoise(noise) {
this.Q = noise;
}
/**
* Set the process noise R
* @param {Number} noise
*/
setProcessNoise(noise) {
this.R = noise;
}
this.A = typeof params.A == "undefined" ? 1 : params.A;
this.C = typeof params.C == "undefined" ? 1 : params.C;
this.B = typeof params.B == "undefined" ? 0 : params.B;
this.cov = NaN;
this.x = NaN; // estimated signal without noise
}
/**
* Filter a new value
* @param {Number} z Measurement
* @param {Number} u Control
* @return {Number}
*/
KalmanFilter.prototype.filter = function (z, u) {
if (typeof u == "undefined")
u = 0;
if (isNaN(this.x)) {
this.x = (1 / this.C) * z;
this.cov = (1 / this.C) * this.Q * (1 / this.C);
}
else {
// Compute prediction
const predX = (this.A * this.x) + (this.B * u);
const predCov = ((this.A * this.cov) * this.A) + this.R;
// Kalman gain
const K = predCov * this.C * (1 / ((this.C * predCov * this.C) + this.Q));
// Correction
this.x = predX + K * (z - (this.C * predX));
this.cov = predCov - (K * this.C * predCov);
}
return this.x;
}
/**
* Return the last filtered measurement
* @return {Number}
*/
KalmanFilter.prototype.lastMeasurement = function () {
return this.x;
}
/**
* Set measurement noise Q
* @param {Number} noise
*/
KalmanFilter.prototype.setMeasurementNoise = function (noise) {
this.Q = noise;
}
/**
* Set the process noise R
* @param {Number} noise
*/
KalmanFilter.prototype.setProcessNoise = function (noise) {
this.R = noise;
}