Levi-always-rejoice
commented
4 months ago Why nobody answer my questions?
Closed Levi-always-rejoice closed 4 months ago
Levi-always-rejoice
commented
4 months ago Why nobody answer my questions?
smcclusky
commented
4 months ago inputs:
inputs_root: ./products/
atx_files: [ igs20.atx ] # required
igrf_files: [ tables/igrf13coeffs.txt ]
erp_files: [ finals.data.iau2000.txt ]
planetary_ephemeris_files: [ tables/DE436.1950.2050 ]
troposphere:
gpt2grid_files: [ tables/gpt_25.grd ]
tides:
ocean_tide_loading_blq_files: [ tables/OLOAD_GO.BLQ ] # required if ocean loading is applied
atmos_tide_loading_blq_files: [ tables/ALOAD_GO.BLQ ] # required if atmospheric tide loading is applied
ocean_pole_tide_loading_files: [ tables/opoleloadcoefcmcor.txt ] # required if ocean pole tide loading is applied
snx_files:
# - "*.SNX" # use a wild card to include all files matching the description in the directory
- igs_satellite_metadata.snx
- tables/sat_yaw_bias_rate.snx
- tables/qzss_yaw_modes.snx
- tables/bds_yaw_modes.snx
- IGS1R03SNX_20191950000_07D_07D_CRD.SNX
satellite_data:
# nav_files:
# - "*.rnx"
clk_files:
# - "*.CLK"
- IGS2R03FIN_20191990000_01D_30S_CLK.CLK
bsx_files:
# - "*.BIA"
#- IGS2R03FIN_20191990000_01D_01D_OSB.BIA
- TUG0R03FIN_20191990000_01D_01D_OSB.BIA
sp3_files:
# - "*.SP3"
- IGS2R03FIN_20191990000_01D_05M_ORB.SP3
gnss_observations:
gnss_observations_root: ../data/
rnx_inputs:
# - "*.rnx"
- ALIC00AUS_R_20191990000_01D_30S_MO.rnx
- DARW00AUS_R_20191990000_01D_30S_MO.rnx
- HOB200AUS_R_20191990000_01D_30S_MO.rnx
#- KARR00AUS_R_20191990000_01D_30S_MO.rnx
#- TOW200AUS_R_20191990000_01D_30S_MO.rnx
#- "M*.rnx"
outputs:
metadata:
config_description: ppp_example_gps+gal_L1L2L5
outputs_root: ./outputs/<CONFIG>
gpx:
output: true
filename: <RECEIVER>_<CONFIG>_<YYYY><DDD><HH>.GPX
trace:
level: 3
output_receivers: true
output_network: true
receiver_filename: <RECEIVER>_<CONFIG>_<YYYY><DDD><HH>.TRACE
network_filename: NETWORK_<CONFIG>_<YYYY><DDD><HH>.TRACE
output_residuals: true
output_residual_chain: true
output_config: true
# log:
# output: false
# directory: ./logs/
# filename: log<LOGTIME>.json
satellite_options:
global:
error_model: ELEVATION_DEPENDENT # {uniform,elevation_dependent}
code_sigma: 0 # Standard deviation of code measurements
phase_sigma: 0 # Standard deviation of phase measurmeents
models:
code_bias:
enable: true
phase_bias:
enable: true
# E05:
# exclude: true # Exclude satellites
# E06:
# exclude: true
receiver_options:
global:
elevation_mask: 10 # degrees
error_model: ELEVATION_DEPENDENT # {uniform,elevation_dependent}
code_sigma: 0.3 # Standard deviation of code measurements, m
phase_sigma: 0.003 # Standard deviation of phase measurmeents, m
GPS:
clock_codes: [AUTO,AUTO]
zero_dcb_codes: [AUTO,AUTO]
GAL:
zero_dcb_codes: [AUTO,AUTO]
#BDS:
# zero_dcb_codes: [AUTO,AUTO]
models:
code_bias:
enable: true
phase_bias:
enable: true
troposphere: # Tropospheric modelling accounts for delays due to refraction of light in water vapour
enable: true
models: [ gpt2 ] # List of models to use for troposphere [standard,sbas,vmf3,gpt2,cssr]
tides:
atl: true # Enable atmospheric tide loading
enable: true # Enable modelling of tidal disaplacements
opole: true # Enable ocean pole tides
otl: true # Enable ocean tide loading
solid: true # Enable solid Earth tides
spole: true # Enable solid Earth pole tides
# ALIC:
# receiver_type: "LEICA GR25" # (string)
# antenna_type: "LEIAR25.R3 NONE" # (string)
# apriori_position: [-4052052.7254, 4212835.9872,-2545104.6139] # [floats]
# aliases: [PIVOT] # set as pivot station
# models:
# eccentricity:
# enable: true
# offset: [0.0000, 0.0000, 0.0015] # [floats]
processing_options:
process_modes:
preprocessor: true # Preprocessing and quality checks
spp: true # Perform SPP on receiver data
ppp: true # Perform PPP network or end user mode
ionosphere: false # Compute Ionosphere models based on GNSS measurements
slr: false # Process SLR observations
epoch_control:
# start_epoch: 2019-07-18 00:00:00
end_epoch: 2019-07-18 23:55:00
# max_epochs: 2880
epoch_interval: 30 # seconds
wait_next_epoch: 3600 # seconds (make large for post-processing)
gnss_general:
rec_reference_system: GPS
sys_options:
GPS:
process: true
reject_eclipse: false
code_priorities: [ L1W, L1C, L2W, L5Q, L5X ]
#code_priorities: [ L1W, L1C, L2W ]
receiver_amb_pivot: true
#network_amb_pivot: true
GAL:
process: true
reject_eclipse: false
code_priorities: [ L1C, L5Q, L1X, L5X ]
#receiver_amb_pivot: true
#network_amb_pivot: true
preprocessor: # Configurations for the kalman filter and its sub processes
cycle_slips: # Cycle slips may be detected by the preprocessor and measurements rejected or ambiguities reinitialised
mw_process_noise: 0 # Process noise applied to filtered Melbourne-Wubenna measurements to detect cycle slips
slip_threshold: 0.05 # Value used to determine when a slip has occurred
preprocess_all_data: true
spp:
#always_reinitialise: false # Reset SPP state to zero to avoid potential for lock-in of bad states
max_lsq_iterations: 12 # Maximum number of iterations of least squares allowed for convergence
outlier_screening:
raim: true # Enable Receiver Autonomous Integrity Monitoring
max_gdop: 30 # Maximum dilution of precision before error is flagged
ppp_filter:
outlier_screening:
chi_square:
enable: false # Enable Chi-square test
mode: NONE # Chi-square test mode {none,innovation,measurement,state}
prefit:
max_iterations: 3 # Maximum number of measurements to exclude using prefit checks before attempting to filter
omega_test: false # Enable omega-test
sigma_check: true # Enable sigma check
sigma_threshold: 4 # Sigma threshold
postfit:
max_iterations: 10 # Maximum number of measurements to exclude using postfit checks while iterating filter
sigma_check: true # Enable sigma check
sigma_threshold: 4 # Sigma threshold
ionospheric_components: # Slant ionospheric components
common_ionosphere: true # Use the same ionosphere state for code and phase observations
use_gf_combo: false # Combine 'uncombined' measurements to simulate a geometry-free solution
use_if_combo: false # Combine 'uncombined' measurements to simulate an ionosphere-free solution
chunking:
by_receiver: false # Split large filter and measurement matrices blockwise by receiver ID to improve processing speed
by_satellite: false # Split large filter and measurement matrices blockwise by satellite ID to improve processing speed
size: 0
rts: # Rauch-Tung-Striebel (RTS) backwards smoothing
enable: true
lag: -1
inverter: LDLT # Inverter to be used within the rts processor, which may provide different performance outcomes in terms of processing time and accuracy and stability
filename: <CONFIG>_<RECEIVER>.rts
model_error_handling:
meas_deweighting: # Measurements that are outside the expected confidence bounds may be deweighted so that outliers do not contaminate the filtered solution
deweight_factor: 1000 # Factor to downweight the variance of measurements with statistically detected errors
enable: true # Enable deweighting of all rejected measurement
state_deweighting: # Any "state" errors cause deweighting of all measurements that reference the state
deweight_factor: 1000 # Factor to downweight the variance of measurements with statistically detected errors
enable: true # Enable deweighting of all referencing measurements
ambiguities:
outage_reset_limit: 300 # Wait for 5 consecutive missing epoch of data before reseting ambiguity
phase_reject_limit: 2 # Reset ambiguity after 2 large fractional residuals are found (replaces phase_reject_count:)
reset_on: # Reset ambiguities when slip is detected by the following
gf: true # GF test
lli: true # LLI test
mw: true # MW test
scdia: true # SCDIA test
estimation_parameters:
global_models:
eop:
estimated: [false] # Estimate state in kalman filter
sigma: [-1] # Apriori sigma values - if zero, will be initialised using least squares
process_noise: [0] # Process noise sigmas
eop_rates:
estimated: [false] # Estimate state in kalman filter
sigma: [-1] # Apriori sigma values - if zero, will be initialised using least squares
process_noise: [0] # Process noise sigmas
ion:
estimated: [false] # Estimate state in kalman filter
sigma: [-1] # Apriori sigma values - if zero, will be initialised using least squares
process_noise: [0] # Process noise sigmas
receivers:
global:
pos:
estimated: [true]
sigma: [100]
process_noise: [0]
pos_rate: # Velocity
estimated: [false] # [bools] Estimate state in kalman filter
sigma: [1] # [floats] Apriori sigma values - if zero, will be initialised using least squares
process_noise: [1] # [floats] Process noise sigmas
# process_noise_dt: SECOND # (enum) Time unit for process noise - sqrt_sec, sqrt_day etc
# apriori_val: [0] # [floats] Apriori state values
# mu: [0] # [floats] Desired mean value for gauss markov states
# tau: [-1] # [floats] Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk)
clock:
estimated: [true]
sigma: [1000]
process_noise: [100]
clock_rate:
estimated: [false]
sigma: [0.005]
process_noise: [1e-4]
ambiguities:
estimated: [true]
sigma: [1000]
process_noise: [0]
ion_stec: # Ionospheric slant delay
estimated: [true] # Estimate state in kalman filter
sigma: [200] # Apriori sigma values - if zero, will be initialised using least squares
process_noise: [10] # Process noise sigmas
trop:
estimated: [true]
sigma: [0.3]
process_noise: [0.0001]
trop_grads:
estimated: [true]
sigma: [0.03]
process_noise: [1.0E-6]
code_bias:
estimated: [true]
sigma: [20]
process_noise: [0]
phase_bias:
estimated: [true]
sigma: [1]
process_noise: [0]
#GPS:
# L1C:
# phase_bias:
# estimated: [true]
# sigma: [1e-9]
# process_noise: [0]
# GPS L5 phase biases are known to be non-stationary. If not included in the apriori bias file
# they need to be estimated with process noise to allow for variation with time
satellites:
GPS:
L5Q:
phase_bias:
estimated: [true]
sigma: [0.5]
process_noise: [0.0002]
L5X:
phase_bias:
estimated: [true]
sigma: [0.5]
process_noise: [0.0002]
mongo: # Mongo is a database used to store results and intermediate values for later analysis and inter-process communication
enable: primary # Enable and connect to mongo database {none,primary,secondary,both}
primary_uri: mongodb://localhost:27017 # Location and port of the mongo database to connect to
primary_database: <CONFIG>
primary_suffix: "" # Suffix to append to database elements to make distinctions between runs for comparison
# secondary_database: <CONFIG>
# secondary_suffix: "" # Suffix to append to database elements to make distinctions between runs for comparison
# secondary_uri: mongodb://localhost:27017 # Location and port of the mongo database to connect to
# output_config: NONE # Output config {none,primary,secondary,both}
output_components: primary # Output components of measurements {none,primary,secondary,both}
output_states: primary # Output states {none,primary,secondary,both}
output_measurements: primary # Output measurements and their residuals {none,primary,secondary,both}
output_test_stats: primary # Output test statistics {none,primary,secondary,both}
delete_history: primary # Drop the collection in the database at the beginning of the run to only show fresh data {none,primary,secondary,both}
output_trace: primary
#output_cumulative: primaryThank you Simon McClusky. Thank you for your detailed answer.
Dear Ginan team,
I am wondering if Ginan software could execute triple-frequency uncombined PPP. The parameters are huge and sophisticated. I have tried to use the Ginan software to produce a result of triple-frequency uncombined PPP with ambiguity fixed under the guide of Config Parameters but I failed according to the result. So my question concerning Ginan is as follows. (1) Does Ginan support PPP in triple-frequency uncombined mode? If yes, how could I configure the parameters in the YAML file that controls the number of frequency being used in the PPP processing? (2) Does Ginan support PPP-AR for triple-frequency uncombined PPP? If yes, how could I configure the parameters in the YAML file that enable PPP-AR for triple-frequency uncombined PPP? In addition, I am wondering if you provide a tutorial on debugging Ginan code?