我有一个使用方向数据的应用程序，使用预先使用Sensor.TYPE_ORIENTAITON的API-8方法可以很好地工作。平滑数据相对容易。
我正在尝试更新代码以避免使用这种弃用的方法。新的标准方法是用Sensor.TYPE_ORIENTATION和Sensor.TYPE_ACCELEROMETER组合替换单Sensor.TYPE_MAGENTIC_FIELD。收到该数据后，会将其（通过SensorManager.getRotationMatrix()）发送至SensorManager.getOrientation()。这（理论上）返回与Sensor.TYPE_ORIENTATION相同的信息（除了不同的单位和轴方向）。
然而，这种方法似乎产生的数据比不推荐的方法（仍然有效）更加紧张（即嘈杂）。因此，如果您在同一设备上比较相同的信息，则不推荐使用的方法提供的噪声数据比当前方法少得多。
如何获得弃用方法提供的实际相同（噪声较小）数据？
让我的问题更清楚：我已经阅读了关于这个主题的各种答案，我尝试了各种过滤器：简单的KF / IIR低通，如你所说;中值滤波器在5到19点之间，但到目前为止，我还没有接近通过TYPE_ORIENTATION提供的数据平滑度。
答案 0 :(得分：7)
对传感器输出应用低通滤波器。
这是我的低通滤波器方法：
private static final float ALPHA = 0.5f;
//lower alpha should equal smoother movement
...
private float[] applyLowPassFilter(float[] input, float[] output) {
if ( output == null ) return input;
for ( int i=0; i<input.length; i++ ) {
output[i] = output[i] + ALPHA * (input[i] - output[i]);
}
return output;
}
像这样应用：
float[] mGravity;
float[] mGeomagnetic;
@Override
public void onSensorChanged(SensorEvent event) {
if (event.sensor.getType() == Sensor.TYPE_ACCELEROMETER)
mGravity = applyLowPassFilter(event.values.clone(), mGravity);
if (event.sensor.getType() == Sensor.TYPE_MAGNETIC_FIELD)
mGeomagnetic = applyLowPassFilter(event.values.clone(), mGeomagnetic);
if (mGravity != null && mGeomagnetic != null) {
float R[] = new float[9];
float I[] = new float[9];
boolean success = SensorManager.getRotationMatrix(R, I, mGravity, mGeomagnetic);
if (success) {
float orientation[] = new float[3];
SensorManager.getOrientation(R, orientation);
azimuth = -orientation[0];
invalidate();
}
}
}
这显然是指南针的代码，删除你不需要的东西。
另外，请查看此SE问题How to implement low pass filter using java
答案 1 :(得分：1)
事实证明，还有另一种，没有特别记录的方法来获取方向数据。隐藏在传感器类型列表中的是TYPE_ROTATION_VECTOR。所以，设置一个：
Sensor mRotationVectorSensor = sensorManager.getDefaultSensor(Sensor.TYPE_ROTATION_VECTOR);
sensorManager.registerListener(this, mRotationVectorSensor, SensorManager.SENSOR_DELAY_GAME);
然后：
@Override
public void onSensorChanged(SensorEvent event) {
final int eventType = event.sensor.getType();
if (eventType != Sensor.TYPE_ROTATION_VECTOR) return;
long timeNow = System.nanoTime();
float mOrientationData[] = new float[3];
calcOrientation(mOrientationData, event.values.clone());
// Do what you want with mOrientationData
}
关键机制是通过旋转矩阵从输入的旋转数据到方向矢量。稍微令人沮丧的是，方向矢量首先来自四元数据，但我无法看到如何直接传递四元数。 （如果您想知道四元数与orientatin和旋转信息的关系以及它们的使用原因，请参阅here。）
private void calcOrientation(float[] orientation, float[] incomingValues) {
// Get the quaternion
float[] quatF = new float[4];
SensorManager.getQuaternionFromVector(quatF, incomingValues);
// Get the rotation matrix
//
// This is a variant on the code presented in
// http://www.euclideanspace.com/maths/geometry/rotations/conversions/quaternionToMatrix/
// which has been altered for scaling and (I think) a different axis arrangement. It
// tells you the rotation required to get from the between the phone's axis
// system and the earth's.
//
// Phone axis system:
// https://developer.android.com/guide/topics/sensors/sensors_overview.html#sensors-coords
//
// Earth axis system:
// https://developer.android.com/reference/android/hardware/SensorManager.html#getRotationMatrix(float[], float[], float[], float[])
//
// Background information:
// https://en.wikipedia.org/wiki/Rotation_matrix
//
float[][] rotMatF = new float[3][3];
rotMatF[0][0] = quatF[1]*quatF[1] + quatF[0]*quatF[0] - 0.5f;
rotMatF[0][1] = quatF[1]*quatF[2] - quatF[3]*quatF[0];
rotMatF[0][2] = quatF[1]*quatF[3] + quatF[2]*quatF[0];
rotMatF[1][0] = quatF[1]*quatF[2] + quatF[3]*quatF[0];
rotMatF[1][1] = quatF[2]*quatF[2] + quatF[0]*quatF[0] - 0.5f;
rotMatF[1][2] = quatF[2]*quatF[3] - quatF[1]*quatF[0];
rotMatF[2][0] = quatF[1]*quatF[3] - quatF[2]*quatF[0];
rotMatF[2][1] = quatF[2]*quatF[3] + quatF[1]*quatF[0];
rotMatF[2][2] = quatF[3]*quatF[3] + quatF[0]*quatF[0] - 0.5f;
// Get the orientation of the phone from the rotation matrix
//
// There is some discussion of this at
// http://stackoverflow.com/questions/30279065/how-to-get-the-euler-angles-from-the-rotation-vector-sensor-type-rotation-vecto
// in particular equation 451.
//
final float rad2deg = (float)(180.0 / PI);
orientation[0] = (float)Math.atan2(-rotMatF[1][0], rotMatF[0][0]) * rad2deg;
orientation[1] = (float)Math.atan2(-rotMatF[2][1], rotMatF[2][2]) * rad2deg;
orientation[2] = (float)Math.asin ( rotMatF[2][0]) * rad2deg;
if (orientation[0] < 0) orientation[0] += 360;
}
这似乎使数据非常相似（我没有运行数字测试）到旧的TYPE_ORIENTATION数据：它可用于带边际过滤的设备的运动控制。
答案 2 :(得分：1)
以下是我使用 SensorManager.SENSOR_DELAY_GAME 进行快速更新的方法，即
@Override
protected void onResume() {
super.onResume();
sensor_manager.registerListener(this, sensor_manager.getDefaultSensor(Sensor.TYPE_ACCELEROMETER), SensorManager.SENSOR_DELAY_GAME);
sensor_manager.registerListener(this, sensor_manager.getDefaultSensor(Sensor.TYPE_MAGNETIC_FIELD), SensorManager.SENSOR_DELAY_GAME);
}
（效率较低）
private float[] gravity;
private float[] geomagnetic;
private float azimuth;
private float pitch;
private float roll;
@Override
public void onSensorChanged(SensorEvent event) {
if (event.sensor.getType() == Sensor.TYPE_ACCELEROMETER)
gravity = moving_average_gravity(event.values);
if (event.sensor.getType() == Sensor.TYPE_MAGNETIC_FIELD)
geomagnetic = moving_average_geomagnetic(event.values);
if (gravity != null && geomagnetic != null) {
float R[] = new float[9];
float I[] = new float[9];
boolean success = SensorManager.getRotationMatrix(R, I, gravity, geomagnetic);
if (success) {
float orientation[] = new float[3];
SensorManager.getOrientation(R, orientation);
azimuth = (float) Math.toDegrees(orientation[0]);
pitch = (float) Math.toDegrees(orientation[1]);
roll = (float) Math.toDegrees(orientation[2]);
//if(roll>-46F && roll<46F)view.setTranslationX((roll/45F)*max_translation); //tilt from -45° to 45° to x-translate a view positioned centrally in a layout, from 0 - max_translation
Log.i("TAG","azimuth: "+azimuth+" | pitch: "+pitch+" | roll: "+roll);
}
}
}
private ArrayList<Float[]> moving_gravity;
private ArrayList<Float[]> moving_geomagnetic;
private static final float moving_average_size=12;//change
private float[] moving_average_gravity(float[] gravity) {
if(moving_gravity ==null){
moving_gravity =new ArrayList<>();
for (int i = 0; i < moving_average_size; i++) {
moving_gravity.add(new Float[]{0F,0F,0F});
}return new float[]{0F,0F,0F};
}
moving_gravity.remove(0);
moving_gravity.add(new Float[]{gravity[0],gravity[1],gravity[2]});
return moving_average(moving_gravity);
}
private float[] moving_average_geomagnetic(float[] geomagnetic) {
if(moving_geomagnetic ==null){
this.moving_geomagnetic =new ArrayList<>();
for (int i = 0; i < moving_average_size; i++) {
moving_geomagnetic.add(new Float[]{0F,0F,0F});
}return new float[]{0F,0F,0F};
}
moving_geomagnetic.remove(0);
moving_geomagnetic.add(new Float[]{geomagnetic[0],geomagnetic[1],geomagnetic[2]});
return moving_average(moving_geomagnetic);
}
private float[] moving_average(ArrayList<Float[]> moving_values){
float[] moving_average =new float[]{0F,0F,0F};
for (int i = 0; i < moving_average_size; i++) {
moving_average[0]+= moving_values.get(i)[0];
moving_average[1]+= moving_values.get(i)[1];
moving_average[2]+= moving_values.get(i)[2];
}
moving_average[0]= moving_average[0]/moving_average_size;
moving_average[1]= moving_average[1]/moving_average_size;
moving_average[2]= moving_average[2]/moving_average_size;
return moving_average;
}
（更高效）
private float[] gravity;
private float[] geomagnetic;
private float azimuth;
private float pitch;
private float roll;
@Override
public void onSensorChanged(SensorEvent event) {
if (event.sensor.getType() == Sensor.TYPE_ACCELEROMETER)
gravity = LPF(event.values.clone(), gravity);
if (event.sensor.getType() == Sensor.TYPE_MAGNETIC_FIELD)
geomagnetic = LPF(event.values.clone(), geomagnetic);
if (gravity != null && geomagnetic != null) {
float R[] = new float[9];
float I[] = new float[9];
boolean success = SensorManager.getRotationMatrix(R, I, gravity, geomagnetic);
if (success) {
float orientation[] = new float[3];
SensorManager.getOrientation(R, orientation);
azimuth = (float) Math.toDegrees(orientation[0]);
pitch = (float) Math.toDegrees(orientation[1]);
roll = (float) Math.toDegrees(orientation[2]);
//if(roll>-46F && roll<46F)view.setTranslationX((roll/45F)*max_translation); //tilt from -45° to 45° to x-translate a view positioned centrally in a layout, from 0 - max_translation
Log.i("TAG","azimuth: "+azimuth+" | pitch: "+pitch+" | roll: "+roll);
}
}
}
private static final float ALPHA = 1/16F;//adjust sensitivity
private float[] LPF(float[] input, float[] output) {
if ( output == null ) return input;
for ( int i=0; i<input.length; i++ ) {
output[i] = output[i] + ALPHA * (input[i] - output[i]);
}return output;
}