Develop Reference

android+gps nmea + Location: where vertical speed?

As I know internally any GPS reciever solve equation and get X,Y,Z and VX,VY,VZ in orthogonal coordinates WGS-84 system.
But in Android API I get only VX,VY,VZ projection to north-east plane (Location::getSpeed, Location::getBearing), so
How can I get full 3d vector of speed?
Based on what getAccuracy calculated for GPS, GDOP, VDOP or what?

As I remeber, and as you can find in the android docu,
getAccuracy is related to horizontal accuracy.
From the DOP values its is more or less related to HDOP.
But the chip manufacturers, which calculate the horizontalAccuracy estimate,
do not specify how they internaly calculate that value. Nor they are willing to tell.
Your first sentence probably simplifies things. This might be valid for a
demonstration modell of a GPS receiver.
In practise speed (over ground) considers, the doppler effect, too, which then gives more precise speed than just evalution the location change per time.
"How can I get full 3d vector of speed?"
I doubt you can get it.
You can try to self caluclate by evalutaing altitude(m) change per time,
for higher vertical speeds, like airplane, that might work.

Which is a higher accuracy criteria: ACCURACY_HIGH or ACCURACY_FINE?

In the Criteria class, there are two constants, ACCURACY_HIGH and ACCURACY_FINE, which are apparently used to require the LocationManager to return higher accuracy location updates. Here is what the documentation says about each of these constants:
public static final int ACCURACY_FINE (Added in API level 1)
A constant indicating a finer location accuracy requirement
Constant Value: 1 (0x00000001)
public static final int ACCURACY_HIGH (Added in API level 9)
a constant indicating a high accuracy requirement - may be used for horizontal, altitude, speed or bearing accuracy. For horizontal and vertical position this corresponds roughly to an accuracy of less than 100 meters.
Constant Value: 3 (0x00000003)
Does anyone know which of these two constants provides (i.e. requires) the highest level of accuracy?

From what I can see in the source code, ACCURACY_FINE is grouped with ACCURACY_COARSE with constant values of 1 & 2 respectively. ACCURACY_LOW, MEDIUM and HIGH are grouped together with constant values 1, 2 & 3.
It seems that setAccuracy expects and returns either COARSE or FINE, while setVerticalAccuracy, setHorizontalAccuracy, setSpeedAccuracy and setBearingAccuracy expect LOW, MEDIUM or HIGH. Furthermore, when you call setAccuracy, it sets horizontal accuracy like so:
public void setAccuracy(int accuracy) {
if (accuracy < NO_REQUIREMENT || accuracy > ACCURACY_COARSE) {
throw new IllegalArgumentException("accuracy=" + accuracy);
}
if (accuracy == ACCURACY_FINE) {
mHorizontalAccuracy = ACCURACY_HIGH;
} else {
mHorizontalAccuracy = ACCURACY_LOW;
}
}
It's really confusing, but I hope I cleared it up for you a bit. Here's a link to the source in grepcode, you can download it and see for yourself if you don't have the source locally.

Both constants mean the highest accuracy, but are intended for different methods. From the documentation (which may have been updated since the question was asked):
ACCURACY_FINE is valid input for setAccuracy.
ACCURACY_HIGH is valid input for setBearingAccuracy, setHorizontalAccuracy, setSpeedAccuracy and setVerticalAccuracy.
I believe the idea of this modeling is that FINE and COARSE give you a choice of two opposites only, whereas LOW, MEDIUM and HIGH allow for a more subtle distinction. (The question remains, why setSpeedAccuracy ridicules that modeling by allowing only LOW and HIGH. But then, this might be a bug in either documentation or design. :) )
As mentioned by the OP, they introduced those values later, API level 9, in contrast to API level 1 for FINE-COARSE. The code found by npace simply reveals that internally the Android developers now map everything to the names and values of the LOW to HIGH value range, to get some consistency internally.

There are several criteia to determine the accuracy of the location
Once the device starts providing real-time locations, my suggestion is to check the accuracy of each result and consider rejecting those greater than a certain amount that are based on your requirements. The longer the location provider runs, and if the device has an unobstructed views of the sky and good cellular connection, then typically the accuracy will improve up to a certain point and then level off, and then it will fluctuate. Here’s a pseudo-code snippet showing how to check the accuracy of each GPS location result:
1
2
3
Here are some rough examples of accuracy thresholds . Your requirements may vary as to how these different thresholds will affect the behavior of your application; these were examples that required geocoding that converted the current location to an approximate address. Depending on the result the application gave different feedback to the user:
Rooftop <= 10 meters (desired result)
Street >10 meters and <= 100 meters (let user know it’s close but not perfect. Good enough?)
Neighborhood > 100 meters and <= 500 meters (give visual feedback that accuracy is low)
City > 500 meters and <= 2000 meters (ask user to verify city name from a list)
County > 2000 meters (prompt for manual location input)
Take into account your own unique use cases. You might completely reject any accuracy value greater than 100 meters (328 ft) if your app simply helps people find open parking lots at NFL games. You could have an app that returns a list of Dentist offices within a 5 mile (8000m) radius. Or a weather app could only need to know approximately what city you are in. These are just ideas to help get you thinking.
public void onLocationChanged(Location location) {
if(location.getAccuracy() < 100.0 && location.getSpeed() < 6.95){
//Do something
}
else{
//Continue listening for a more accurate location
}

Get more accurate GPS SNR/PNR/Elevation/Azimuth precision

Right now I am using a gpsStatus to get a list of satellites from the android SDK. I am retrieving the variables with the following methods:
float az = item.getAzimuth();
float el = item.getElevation();
int p = item.getPrn();
float s = item.getSnr();
So far I am getting values of only 1 point in precision, mostly .0, so for instance:
(173.0, 47.0, 74, 30.0) For the floating point numbers is there anyway to get more precision? I was able to use a Criteria to get more precision out of the Accuracy, Latitude, and Longitude. I need to try and get as precise data as possible for the satellite information too. Thanks.

I'm not 100% sure about this, but I believe that most (if not all) GPS receivers will only output azimuth and elevation data to the nearest degree. Similarly, SNR values are only given to the nearest integer (perhaps professional-grade receivers will give more precise SNR measurements, but I don't any smartphone-based receiver would do so.). PRNs are, of course, only integer values.
So I'm afraid that the answer to your question (if I'm correct about GPS receivers) is that it is not possible to get more accurate azimuth, elevation, and SNR info using any Android API, since the API just retrieves whatever is output by the receiver.
The only possibility I can think of to get more accurate azimuth and elevation values would be to retrieve the GPS satellite almanac from some online source, and then calculate the expected azimuth and elevation at your current location using formulae of geodesy. In other words, a not so easy task...
By the way, you mention that the output is "mostly .0", but I think if you go back and check, all values are ending in .0.

Negative altitude value

I am getting negative altitude value when finding latitude , longitude and altitude. Can anyone help me to find the reason for it ?

Short of seeing the code which produces these values, there's not much I can offer beyond general knowledge.
GPS altitudes generally use a geodetic model for an idealised sea level (the zero altitude), basically mapping an ellipsoid onto a less-than-perfectly-shaped planet (which varies anyway with things such as lunar tidal forces). See WGS84 here for more details.
The normal error is about +/- 15m, and this only applies about 95% of the time. According to the specs I remember, the other 5% of the time can have an altitude of any value.
And, of course, if your GPS doesn't have an unobstructed pathway between it and the satellites, the error range is much greater.
These potential errors are no doubt why aircraft rely more on altimeters or ILS for their near-ground activities.
As one site puts it:
What this means is that if you are walking on the seashore, and see your altitude as -15 meters, you should not be concerned.
Of course, if you're having troubles breathing, you may want to look more closely at how wet you are :-)

Well, altitude in context of GPS coordinates represents your elevation according to the sea level. So I assume your current position is just below the sea level. Yeah, this is possible ;)

The GPS altitude is the altitude above the GPS WGS84 reference elipsoid (which is different from sea level and does not take hills into account!). A negative altutude means (if it not due to a bad signal) that you are below the reference elipsoid.
Here is more information on how to get more accurate altitude: https://stackoverflow.com/a/9432382/1127492

Switch positioning settings to use Geoid model.

Android: How to get accurate altitude?

I need to get an accurate measurement of altitude using GPS only.
I tried Location.getAltitude(), but that is terribly inaccurate.
Any advice?

There are two issues with using altitude of a smartphone / tablet GPS:
The altitude is the altitude above the WGS84 reference ellipsoid. It is not the altitude above ground level or sea level. Here is more detail on that: http://www.gpspassion.com/forumsen/topic.asp?TOPIC_ID=10915. This error can be corrected; here is a description how to do that by hand: http://www.unavco.org/edu_outreach/tutorial/geoidcorr.html. The web article links to a calculator to get the Geoid height for correction; I do not know if there is also a web service available for this computation.
The GPS altitude is terribly inaccurate for relatively cheap GPS receivers. Here is an article on that: http://gpsinformation.net/main/altitude.htm. One method to cope with this kind of inaccuracy is to filter the altitude data. I used a circular array data structure to remember the last few (I used 4) altitude readings and compute the average. This sufficed to get a relatively accurate reading of vertical speed for my application.

Another way would be parsing NMEA strings. The $GPGGA sentence already contains the corrected altitude data above sea level.
So, simply create a listener to NMEA-strings for your LocationManager and parse the messages:
private GpsStatus.NmeaListener mNmeaListener = new GpsStatus.NmeaListener() {
#Override
public void onNmeaReceived(long timestamp, String nmea) {
parseNmeaString(nmea);
}
};
public void registerLocationManager(Context context) {
mLocationManager = (LocationManager) mContext.getSystemService(LOCATION_SERVICE);
mLocationManager.addNmeaListener(mNmeaListener);
}
private void parseNmeaString(String line) {
if (line.startsWith("$")) {
String[] tokens = line.split(",");
String type = tokens[0];
// Parse altitude above sea level, Detailed description of NMEA string here http://aprs.gids.nl/nmea/#gga
if (type.startsWith("$GPGGA")) {
if (!tokens[9].isEmpty()) {
mLastMslAltitude = Double.parseDouble(tokens[9]);
}
}
}
}
You can either replace the altitude of the last Location object received through a location listener, or parse the whole new location through NMEA.

Another approach is to measure the altitude from the barometer.
By using the pressure you can calculate the user's altitude. I'm uncertain of the precision level of this and whether it is more accurate than the other answer's approach.
By using the hypsometric formula you can calculate the altitude:
Variable definition:
P0: Sea-level pressure
P: Atmospheric pressure
T: Temperature
You can get the pressure in android from the environment sensors
SensorManager.getAltitude(SensorManager.PRESSURE_STANDARD_ATMOSPHERE,pressure)

If the device has a barometer, then use can that to improve the relative accuracy. I don't mean to use the barometer to compute the height in relation to the sea level, as can be found in several formulas, as this is highly dependent of the weather conditions.
What you want to do is to get the GPS-altitude when you know that the device has a good fix, with high accuracy values. At that point you fetch the barometric pressure and set that pressure as a reference.
When the pressure increases around 12 hPa, you will know that your altitude decreased by around 100 m ( https://en.wikipedia.org/wiki/Atmospheric_pressure "At low altitudes above sea level, the pressure decreases by about 1.2 kPa (12 hPa) for every 100 metres." ).
Don't take that value as an exact, but variations in the altitude determined by GPS vary a lot due to trees covering the line of sight and other factors, while the barometer will remain very precise under those conditions.
The following graph is a bike ride of around one hour and 20 minutes in duration. Starting point and end point are the same at around 477 m above sea level, determined via GPS. The measured pressure is 1015.223 hPA.
The lowest point is 377 m, with a measured pressure of 1025.119 hPa. So in that case, 100 m make a difference of 10 hPa.
The highest point is 550 m, with a measured pressure of 1007.765 hPa.
Ending point is the same height, and the exact same pressure as the starting conditions (the pressure could have varied due to the weather conditions, but it didn't). The temperature dropped around 1°C, so it was all pretty constant.
The black line containing the many variations is the altitude measured via GPS, the mirrored, but clean line, is the barometric pressure. It has very little variation in it simply because the pressure doesn't vary as wild as the GPS-quality. It is a very smooth, very precise curve. This is not due to lag. This is measured with a Bosch BME280 sensor, which is capable of detecting the closing of a door, change of floor detection, elevator direction, drones, with a noise of 0.2 Pa which equals 1.7 cm and an error of 1m at 400m of height change. These kind of sensors are integrated in some Smartphones. For example, the Pixel 3 contains a Bosch BMP380.
If you mirror the pressure graph, as is shown with the dotted black line, you will see that it very closely matches the GPS altitude. It is much more precise than GPS, but the only problem is that you can't take it as an absolute value.
The samples of GPS and pressure were both taken in 1 second intervals, so there is no curve smoothing from the d3 library causing some false impressions.
So maybe readjusting the pressure around every 10-30 minutes while you have a GPS good fix will give you a good base to perform your altitude measurements by pressure in between.

There are other ways to get the altitude than by GPS. You can use the barometer but as there isn't that many devices with a barometric sensors yet (only the new ones). I will recommend to use a web service to acquire the desired data.
Here is a question which should help you through: Get altitude by longitude and latitude in Android

For newcomers I made a library that wrap LocationManager into rxjava observables and add some observable helpers to get sea level altitutde from Nmea/GPGGA mre info here

There are libraries, such as the open-source CS-Map which provide an API that do these lookups in large tables. You specify the coordinates, and it will tell you the height offset that needs to be applied to the ellipsoidal height at that location to get the "real-world" orthometric height.
Note: Having used CS-Map before, it isn't exactly straight-forward 5-minute job to plug it in. Warning you in advance that it is more complicated than calling a single API with a set of lat-long coordinates and getting back a height. I no longer work at the company where we were doing this kind of work, so unfortunately cannot look up the code to say exactly which API to call.
Doing a google search for it right now (2019), it seems CS-Map has been merged into MetaCRS in OSGeo, the "Open Source Geospatial Foundation" project. That same search led me to this old CS-Map wiki as well as the PROJ GitHub page, where PROJ seems to be similar project to CS-Map.

I would recommend using NmeaListener, as sladstaetter
suggested in his answer. However, according to NMEA documentation, "$GPGGA" is not the only sentence you can get. You should look for any "GGA" sentence ($--GGA).
Regular expressions are great for that, e.g.:
#Override
public void onNmeaReceived(final long timestamp, final String nmea) {
final Pattern pattern = Pattern.compile("\\$..GGA,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,[^,]*,([+-]?\\d+(.\\d+)?),[^,]*,[^,]*,[^,]*,[^,]*,[^,]*$");
final Matcher matcher = pattern.matcher(nmea);
if (matcher.find()) {
final float altitude = Float.parseFloat(matcher.group(1));
// ...enjoy the altitude!
}
}