Question

我必须实现卡尔曼滤波器以获得更好的GPS位置精度...我使用随机解决方案（Smooth GPS data）。在ValidPosition中，我有一些检查：

public boolean checkPosition(Location location) {

    if (( location != null ) &&
        (distance != 0) &&
        (distance > MINIMUM_DISTANCE) && // 10 metres

        (location.hasSpeed()) && 
        (location.getSpeed() > 0) && 
        (averageTime < HUMANSPEED) &&

        (location.hasAccuracy()) &&
        (location.getAccuracy() < MINIMUM_ACCURACY) &&
        (isBetterLocation(location, lastLocation)) // From Google example in http://developer.android.com/guide/topics/location/strategies.html#BestPerformance
            return true;
    }

    return false;
}

现在，在我的位置融合提供程序的主要课程中，我有这个：

public static final int ACCURACY_DECAYS_TIME = 3; // Metres per second

private KalmanLatLong kalmanLatLong = new KalmanLatLong(ACCURACY_DECAYS_TIME);

private ValidPosition validPosition = new ValidPosition();

@Override
public void onLocationChanged(Location location) {

    if(validPosition.checkPosition(location)) {
        kalmanLatLong.process(
                location.getLatitude(),
                location.getLongitude(),
                location.getAccuracy(),
                location.getTime());

        mCallback.handleNewLocation(location);
    }
}`

现在？我如何使用卡尔曼预测？我在Stochastically代码中写了什么？

// TODO: USE VELOCITY INFORMATION HERE TO GET A BETTER ESTIMATE OF CURRENT POSITION

由于

Answer 1

您忘记从kalmanLatLong对象返回处理结果。你需要做这样的事情：

if(validPosition.checkPosition(location)) {
    kalmanLatLong.process(
            location.getLatitude(),
            location.getLongitude(),
            location.getAccuracy(),
            location.getTime());

    location.setLatitude(kalmanLatLong.get_lat());
    location.setLongitude(kalmanLatLong.get_lng());
    location.setAccuracy(kalmanLatLong.get_accuracy());

    mCallback.handleNewLocation(location);
}

关于你的第二个问题，我不认为这是微不足道的，应该更多地基于实验数据。在大多数情况下，线性衰减的简单假设很有效。

在Android中实现带有Fusion Provider的卡尔曼滤波器用于GPS位置

1 个答案: