Short-session Static and Kinematic Processing

Short-session static: GAMIT processing, sessions 1-3 hours long

Kinematic: TRACK processing, coordinates estimated at each epoch; one or more sites

may be moving

•High frequency multipath and sometimes atmospheric errors dominate and fail to average

•Shorter satellite tracks mean less time to separate the signatures in the data, leading to higher

correlations and thus higher uncertainties in coordinates and ambiguity parameters

•Less averaging of noise and higher geometric uncertainties make ambiguity resolution more

difficult; when it fails with short tracks, the uncertainties become much larger

A 2-hr session between 12:00 and 16:00 (left plot) would be much more

likely to resolve ambiguities than a 2-hr session between 20:00 an 24:00

(right plot)

Results may vary significantly with time of day

Continuous network in Italy used

to test the effect of session

length and network

configurationon coordinate

repeatabilities

Test site is PRAT

Firuzabadi and King (2011)

Time series for 2-hr sessions

with 4 reference sites.

Note large sigmas on day 61

and outliers on days 62 and

63; with these removed the

rms is 2 mm horizontal and 7

mm vertical

Precision vs Session Length for Network Processing

Bars show repeatability in position over 31 days of test site with respect to networks of 2 to 16 sites spanning 180-600 km.

With at least 4 reference stations, outliers were less than 5% for sessions of 2 hrs or more.

Precision vs Session Length for Single Baselines

Bars show repeatability in position over 31 days of a test site with respect to each of 7 sites 26-585 km away in single-baseline processing.

10% of the 1- and 2-hr sessions had large uncertainties and were omitted. 1-hr results degrade significantly for baselines longer than 100 km

Cerca del Cielo earthflow, Ponce, Puerto Rico

10 GPS monuments (including one

continuous) on the landslide, and 2

reference monuments outside

Steady-state flow 0.5 - 2.0 mm/d

Maximum ~ 100 mm/d

From G. Wang, 2010

Time series of bi-weekly GPS surveys Mar-Dec 2008

20-minute occupations

GPS 07 and 13 near the head scarp

GK03 and GP18 mid-

slope

From G. Wang, 2010

Time series of hourly and daily positions over 10 days

GAMIT Settings for Sessions < 3 Hours

• Consider using 15s sampling

• Run sh_gamit with the –sesinfo option specifying the start time, sampling

interval, and number of epochs

• If more than one session per day, run sh_gamit with the –netext option, using a

different letter for each session

• Don’t decimate the preliminary or final solutions

Decimation factor = 1

Quick-pre decimation factor = 1

Kinematic GPS

• The style of GPS data collection and processing suggests that one or

more GPS stations is moving (e.g., car, aircraft).

• The moving stations are kept stationary at the beginning and/or end of

the track to resolve ambiguities; then phase lock is maintained (as best

as possible) through the track

• To obtain good results for positioning as a function of time it helps if the

ambiguities can be fixed to integer values. Although with the “back

smooth” option in track this is not so critical.

• Program ‘track’ is the MIT implementation of this type of processing

• Unlike many kinematic processors,track pre-reads all data before

processing. (But there is a real-time version, trackRT.)

General aspects

•

The success of kinematic processing depends on separation of sites

• There are one or more static base stations and the moving receivers

are positioned relative to these.

• For separations < 10 km, usually easy

• 10>100 km more difficult but often successful

• >100 km very mixed results depending on quality of data collected.

(Seismological example results are from 400km baselines.)

Track features

• Track uses the Melbourne-Wubbena Wide Lane to resolve L1-L2 and

then a combination of techniques to determine L1 and L2 cycles

separately.

• “Bias flags” are added at times of cycle slips and the ambiguity

resolution tries to resolve these to integer values.

• Track uses floating point estimate with LC, MW-WL and ionospheric

delay constraints to determine the integer biases and the reliability with

which they are determined.

• Kalman filter smoothing can be used. (Non-resolved ambiguity

parameters are constant, and atmospheric delays are consistent with

process noise). When atmospheric delays are estimated, the

smoothing option should always be used.

Basic input

• Track runs using a command file

• The base inputs needed are:

• Obs_file specifies names of rinex data files. Sites can be K kinematic

or F fixed

• Nav_file orbit file either broadcast ephemeris file or sp3 file

• Mode air/short/long -- Mode command is not strictly needed but it sets

defaults for variety of situations

Some results

• Moving vehicle used for gravity measurments: 5-second sampling with

stop and go

• GPS seismology: 1 HZ tracking of earthquake surface wave arrivals

Track of Map-view track of vehicle motion over 8 km

Vehicle height vs time

Zoom of height just before power failure

Surface waves from the

December, 2000, M 6

San Simeon, Calliforna

earthquake

1 Hz sampling

Detail around arrival time.

Descriptiion and data on web site.

Summary

• Under favorable conditions and especially for short inter-site distances, both

short-session static and kinematic processing can produce excellent results

• Use of more than a single reference site improves reliability

• TRACK’s forward-backward filtering improves reliablity of non-real-time kinematic

tracking

-- BUT there is now a real-time version (trackRT) available