GHZMRNavigator/Assets/Scripts/Vuforial/KalmanLatLong.cs

using System;
using System.Collections;
using System.Collections.Generic;
using UnityEngine;

public class KalmanLatLong
{
    private float MinAccuracy = 1;

    private float Q_metres_per_second;
    private long TimeStamp_milliseconds;
    private double lat;
    private double lng;
    private float variance; // P matrix.  Negative means object uninitialised.  NB: units irrelevant, as long as same units used throughout

    public KalmanLatLong(float Q_metres_per_second) { this.Q_metres_per_second = Q_metres_per_second; variance = -1; }

    public long get_TimeStamp() { return TimeStamp_milliseconds; }
    public double get_lat() { return lat; }
    public double get_lng() { return lng; }
    public float get_accuracy() { return (float)Math.Sqrt(variance); }

    public void SetState(double lat, double lng, float accuracy, long TimeStamp_milliseconds)
    {
        this.lat = lat; this.lng = lng; variance = accuracy * accuracy; this.TimeStamp_milliseconds = TimeStamp_milliseconds;
    }

    /// <summary>
    /// Kalman filter processing for lattitude and longitude
    /// </summary>
    /// <param name="lat_measurement_degrees">new measurement of lattidude</param>
    /// <param name="lng_measurement">new measurement of longitude</param>
    /// <param name="accuracy">measurement of 1 standard deviation error in metres</param>
    /// <param name="TimeStamp_milliseconds">time of measurement</param>
    /// <returns>new state</returns>
    public void Process(double lat_measurement, double lng_measurement, float accuracy, long TimeStamp_milliseconds)
    {
        if (accuracy < MinAccuracy) accuracy = MinAccuracy;
        if (variance < 0)
        {
            // if variance < 0, object is unitialised, so initialise with current values
            this.TimeStamp_milliseconds = TimeStamp_milliseconds;
            lat = lat_measurement; lng = lng_measurement; variance = accuracy * accuracy;
        }
        else
        {
            // else apply Kalman filter methodology

            long TimeInc_milliseconds = TimeStamp_milliseconds - this.TimeStamp_milliseconds;
            if (TimeInc_milliseconds > 0)
            {
                // time has moved on, so the uncertainty in the current position increases
                variance += TimeInc_milliseconds * Q_metres_per_second * Q_metres_per_second / 1000;
                this.TimeStamp_milliseconds = TimeStamp_milliseconds;
                // TO DO: USE VELOCITY INFORMATION HERE TO GET A BETTER ESTIMATE OF CURRENT POSITION
            }

            // Kalman gain matrix K = Covarariance * Inverse(Covariance + MeasurementVariance)
            // NB: because K is dimensionless, it doesn't matter that variance has different units to lat and lng
            float K = variance / (variance + accuracy * accuracy);
            // apply K
            lat += K * (lat_measurement - lat);
            lng += K * (lng_measurement - lng);
            // new Covarariance  matrix is (IdentityMatrix - K) * Covarariance 
            variance = (1 - K) * variance;
        }
    }
}