Open mikehb opened 2 months ago
betaBison
commented
2 months ago Hi @mikehb, I wonder if gnss_lib_py wasn't correctly installed based on your other issue.
It's also definitely possible we have a bug in the code or don't have observation files like yours in our testing scheme. If you're able to attach your full/cropped observation file to this issue, I'd be happy to take a look at what happens when I try to run the file myself.
mikehb
commented
2 months ago Looks like the QZSS is not supported by function add_sv_states_rinex. This the observation file which could reproduce RuntimeError: Some ephemeris data is missing.
>>> a=glp.RinexObs("/home/mikehuang/data/simple.23o")
>>> glp.add_sv_states_rinex(a)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/mikehuang/.local/lib/python3.11/site-packages/gnss_lib_py/utils/sv_models.py", line 168, in add_sv_states_rinex
raise RuntimeError('Some ephemeris data is missing')
RuntimeError: Some ephemeris data is missing
>>> 3.02 OBSERVATION DATA M: Mixed RINEX VERSION / TYPE
CONVBIN 2.4.2 20240428 043130 UTC PGM / RUN BY / DATE
log: /mnt/hgfs/ChromeCoreDownloads/BJCN/OBS_BJCN_2023111900_COMMENT
format: RTCM 3, station ID: 0 COMMENT
MARKER NAME
MARKER NUMBER
MARKER TYPE
OBSERVER / AGENCY
REC # / TYPE / VERS
ANT # / TYPE
0.0000 0.0000 0.0000 APPROX POSITION XYZ
0.0000 0.0000 0.0000 ANTENNA: DELTA H/E/N
G 8 C1C L1C C1W L1W C2W L2W C2X L2X SYS / # / OBS TYPES
R 8 C1C L1C C1P L1P C2C L2C C2P L2P SYS / # / OBS TYPES
E 2 C1X L1X SYS / # / OBS TYPES
J 4 C1C L1C C2X L2X SYS / # / OBS TYPES
S 2 C1C L1C SYS / # / OBS TYPES
C 4 C1C L1C C2C L2C SYS / # / OBS TYPES
2023 11 18 16 0 18.0000000 GPS TIME OF FIRST OBS
2023 11 18 16 15 17.0000000 GPS TIME OF LAST OBS
G SYS / PHASE SHIFT
R SYS / PHASE SHIFT
E SYS / PHASE SHIFT
J SYS / PHASE SHIFT
S SYS / PHASE SHIFT
C SYS / PHASE SHIFT
0 GLONASS SLOT / FRQ #
C1C 0.000 C1P 0.000 C2C 0.000 C2P 0.000 GLONASS COD/PHS/BIS
END OF HEADER
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> 2023 11 18 16 0 19.0000000 0 42
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> 2023 11 18 16 0 20.0000000 0 42
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> 2023 11 18 16 0 21.0000000 0 43
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> 2023 11 18 16 0 22.0000000 0 43
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> 2023 11 18 16 0 23.0000000 0 43
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> 2023 11 18 16 0 24.0000000 0 43
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J 4 37819548.233 198743114.070 37819544.374 154864746.583
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> 2023 11 18 16 0 25.0000000 0 43
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> 2023 11 18 16 0 26.0000000 0 43
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> 2023 11 18 16 0 27.0000000 0 44
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Ahh, yes you are correct. Sorry for that confusing error statement and that I didn't realize sooner that you were trying to add satellite states using the Rinex broadcast data and not the SP3/CLK precise data format.
My colleague, @kanhereashwin, was working on additional compatibility to the add_sv_states_rinex() function in our ashwin/broadcast development branch, but there is currently no timeline for completion of that feature.
An alternate approach would be to use the SP3/CLK "precise" data source instead of Rinex. I've demonstrated how to use the "precise" file types in this Google colab.
navdata = glp.RinexObs("simple.23o")
navdata_with_states = glp.add_sv_states(navdata, source="precise", verbose=True)I've attached the CSV output when using "precise" data here: navdata.csv
mikehb
commented
2 months ago I followed your google colab example, and noticed that the residuals is very large, not as what the tutorial showed, is there any thing wrong with the code or observation data? I am wondering if I can use glp's residuals as a feature of deep learning.
With RTKLIB, I can get a small pseudorange error, with following equation,
_*psr_error = raw_psr - (geometric_distance - CLIGHT svbias)**
where raw_psr is the pseudorange measurement reported by receiver hardware, sv_bias is calculated from broadcast ephemeris, and geometric_distance is caculated by RTKLIB's geodist,
/* geometric distance ----------------------------------------------------------
* compute geometric distance and receiver-to-satellite unit vector
* args : double *rs I satellilte position (ecef at transmission) (m)
* double *rr I receiver position (ecef at reception) (m)
* double *e O line-of-sight vector (ecef)
* return : geometric distance (m) (0>:error/no satellite position)
* notes : distance includes sagnac effect correction
*-----------------------------------------------------------------------------*/
extern double geodist(const double *rs, const double *rr, double *e)
{
double r;
int i;
if (norm(rs,3)<RE_WGS84) return -1.0;
for (i=0;i<3;i++) e[i]=rs[i]-rr[i];
r=norm(e,3);
for (i=0;i<3;i++) e[i]/=r;
return r+OMGE*(rs[0]*rr[1]-rs[1]*rr[0])/CLIGHT;
}for example, the [P0/P1]_residual is within a few meters,
date_time,sat,snr,P0_res,P1_res,x_sv_m,y_sv_m,z_sv_m
1700323217,G03,11500,2.429305233,0.159939319,-19932410.490,7405890.577,15699302.665
1700323217,G06,10500,5.049664315,3.602273457,5578747.079,25472663.414,4841287.832
1700323217,G14,12000,0.358602792,-4.108652949,-11615178.712,22248895.406,8439965.108
1700323217,G17,12250,-0.949575283,-6.435365330,-5538582.348,14240834.309,22168806.197
1700323217,G19,11500,-1.130671874,-8.224673990,4899558.329,16007821.112,20510298.724
1700323217,G22,12000,-0.437244881,-6.244677342,-6480842.785,21300229.686,15142469.398
1700323217,R03,10500,21.442013793,18.547232073,-23796414.534,876730.199,9276967.987
1700323217,R09,13500,14.993377291,11.062192239,4020025.492,18008845.368,17589441.135
1700323217,R16,13250,14.683513619,13.343336895,-6555382.234,24584797.190,1569233.606the date_time is the seconds since 1970/1/1 00:00:00
After modifying RTKLIB code to dump the sv position, I noticed that it has a huge difference, about 20KM along x/y/z, between RTKLIB and GLP. The RTKLIB uses broadcast ephemeris which was saved by the receiver, while GLP use SP3 downloaded from website.
Is it a bug of add_sv_states? maybe leap second is not aligned? @betaBison @kanhereashwin
Here is a piece of G03 output from GLP
gps_millis,gnss_sv_id,sv_id,gnss_id,raw_pr_m,carrier_phase,raw_doppler_hz,cn0_dbhz,signal_type,observation_code,rx_name,x_rx_m,y_rx_m,z_rx_m,x_sv_m,y_sv_m,z_sv_m,vx_sv_mps,vy_sv_mps,vz_sv_mps,b_sv_m,b_dot_sv_mps,corr_pr_m,residuals_m
1384358436000.0,G03,3,gps,21450976.137,87838183.34,,,l2,2W,BJCN,-2168641.46537,4404159.40321,4058413.91992,-19911138.39541453,7376002.118896029,15740107.749009116,1177.9897205722953,-1655.610960857457,2255.430202271433,-1700.080263911872,0.007665805999931,21449276.05673609,327.43000829592347
1384358436000.0,G03,3,gps,21450976.155,87838190.348,,,l2,2X,BJCN,-2168641.46537,4404159.40321,4058413.91992,-19911138.39541453,7376002.118896029,15740107.749009116,1177.9897205722953,-1655.610960857457,2255.430202271433,-1700.080263911872,0.007665805999931,21449276.07473609,327.4480082988739
1384358436000.0,G03,3,gps,21450975.726,84178266.901,,,l5,5Q,BJCN,-2168641.46537,4404159.40321,4058413.91992,-19911138.39541453,7376002.118896029,15740107.749009116,1177.9897205722953,-1655.610960857457,2255.430202271433,-1700.080263911872,0.007665805999931,21449275.645736087,327.0190082974732
1384358436000.0,G03,3,gps,21450978.406,112725667.707,,,l1,1C,BJCN,-2168641.46537,4404159.40321,4058413.91992,-19911138.39541453,7376002.118896029,15740107.749009116,1177.9897205722953,-1655.610960857457,2255.430202271433,-1700.080263911872,0.007665805999931,21449278.325736087,329.6990082971752
1384358437000.0,G03,3,gps,21450998.402,87838274.497,,,l2,2W,BJCN,-2168641.46537,4404159.40321,4058413.91992,-19909960.364472967,7374346.362366104,15742363.00943632,1178.0721775926115,-1655.9021317340066,2255.0906924402784,-1700.072598209906,0.0076656055363577,21449298.329401787,325.7572275660932
1384358437000.0,G03,3,gps,21450997.991,84178354.249,,,l5,5Q,BJCN,-2168641.46537,4404159.40321,4058413.91992,-19909960.364472967,7374346.362366104,15742363.00943632,1178.0721775926115,-1655.9021317340066,2255.0906924402784,-1700.072598209906,0.0076656055363577,21449297.91840179,325.3462275676429
1384358437000.0,G03,3,gps,21451000.671,112725784.686,,,l1,1C,BJCN,-2168641.46537,4404159.40321,4058413.91992,-19909960.364472967,7374346.362366104,15742363.00943632,1178.0721775926115,-1655.9021317340066,2255.0906924402784,-1700.072598209906,0.0076656055363577,21449300.59840179,328.0262275673449
1384358437000.0,G03,3,gps,21450998.419,87838281.498,,,l2,2X,BJCN,-2168641.46537,4404159.40321,4058413.91992,-19909960.364472967,7374346.362366104,15742363.00943632,1178.0721775926115,-1655.9021317340066,2255.0906924402784,-1700.072598209906,0.0076656055363577,21449298.34640179,325.7742275670171
Ahh, yes you are correct. Sorry for that confusing error statement and that I didn't realize sooner that you were trying to add satellite states using the Rinex broadcast data and not the SP3/CLK precise data format.
My colleague, @kanhereashwin, was working on additional compatibility to the
add_sv_states_rinex()function in ourashwin/broadcastdevelopment branch, but there is currently no timeline for completion of that feature.An alternate approach would be to use the SP3/CLK "precise" data source instead of Rinex. I've demonstrated how to use the "precise" file types in this Google colab.
navdata = glp.RinexObs("simple.23o") navdata_with_states = glp.add_sv_states(navdata, source="precise", verbose=True)I've attached the CSV output when using "precise" data here: navdata.csv
add_sv_states works for me
>>> staNavDataGps_states = glp.add_sv_states(staNavDataGps,source="precise", verbose=True)
ephemeris dates needed: [datetime.date(2023, 11, 18)]
FTP downloading /gnss/products/2288/COD0MGXFIN_20233220000_01D_05M_ORB.SP3.gz from gdc.cddis.eosdis.nasa.gov
using previously downloaded file:
/home/mikehuang/data/ephemeris/sp3/COD0MGXFIN_20233220000_01D_05M_ORB.SP3
ephemeris dates needed: [datetime.date(2023, 11, 18)]
FTP downloading /gnss/products/2288/COD0MGXFIN_20233220000_01D_30S_CLK.CLK.gz from gdc.cddis.eosdis.nasa.gov
using previously downloaded file:
/home/mikehuang/data/ephemeris/clk/COD0MGXFIN_20233220000_01D_30S_CLK.CLK
interpolating sp3 for G01
interpolating sp3 for G02
interpolating sp3 for G03
interpolating sp3 for G06
interpolating sp3 for G14
interpolating sp3 for G17
interpolating sp3 for G19
interpolating sp3 for G22
interpolating sp3 for G24
interpolating sp3 for G30
interpolating clk for G01
interpolating clk for G02
interpolating clk for G03
interpolating clk for G06
interpolating clk for G14
interpolating clk for G17
interpolating clk for G19
interpolating clk for G22
interpolating clk for G24
interpolating clk for G30
>>>
Describe the proposed feature My observation data has multiple signal and observation code, but add_sv_states_rinex prints 'Some ephemeris data is missing'. I have to add the sv states one by one
obs_signal=obs_data.where('gnss_id','gps').where('signal_type','l2').where('observation_code','2X') sv_states=glp.add_sv_states_rinex(obs_signal)
Motivate the proposed feature This features make it easier to use in case that multiple GNSS signals need to be considered.