RKT POSITIONING IN CADASTRAL GIS UPDATING 
A. Cina?, A. M. Manzino ", M. Roggero* 
Dept. of Georesource and Territory, Politecnico di Torino, C.so Duca Degli Abruzzi 24, 10129 Torino, IT 
* alberto.cina@polito.it 
® ambrogio.manzino@polito.it 
‘ roggero@atlantic.polito.it 
KEY WORDS: GPS, GIS updating, Tracking, Terrestrial Navigation. 
ABSTRACT: 
In cadastral GIS updating, quickness and economization of surveying are important but contrasting requirement. However high 
precision is usually not required. This paper present some results, obtained processing single and double frequency observations 
with ALARIS, a self made software based on dynamic Kalman filter, and with the commercial software GPSurvey. We have 
achieved good results with low cost GPS receivers, and also over long distances from the reference station, using geodetic receivers 
and modelling the atmospheric biases. 
1. ASSUMPTIONS 
The paper present some remarks about RTK technique using 
single frequency receivers. We have processed data collected 
by professional and also low cost receivers, defining their 
precision in RTK mode, and their application field. 
Data processing simulates RTK, using a self made software 
named ALARIS. This software performs one-way estimation of 
biases and real time trajectory tracking using different Kalman 
filtering techniques. 
Then, we want to clarify the reason of studying also long range 
RTK with single frequency receivers: it’s necessary to study 
some preliminary problems in MRS or NRTK. We remember 
that in NRTK a master station estimates atmospheric biases 
over a network of permanent reference stations; then the rover 
station applies to his observations the corrections broadcasted 
by the master station. This positioning technique will be largely 
diffused in future for many applications in engineering, 
cartography, cadastre, GIS and so on. For all this applications, 
that usually don’t require very high precisions, the use of low 
cost single frequency receivers is quick and economic. 
To study On The Fly ambiguity resolution, real time tracking, 
real time data quality control and residual biases estimation, we 
want to examine the simple case of positioning a rover station, 
applying corrections estimated by a single reference station. 
Then, to appreciate atmospheric biases is necessary to process 
long baselines. 
2. EQUATIONS FOR BIASES CORRECTION 
In our work, we have decided to correct the observations in the 
rover station using the single differences equations. The reason 
of this choice is to make possible NRTK using RTCM 
standards, as is RTK today. So, it’s possible to include in 
RTCM the corrections modelled over the network area, today in 
proprietary record (message type 59), in future in dedicated 
records of the new RTCM version 3. 
Single differences equations leads to cancel satellite dependant 
errors (satellite clock, hardware delay and ephemeris error up to 
500 km baselines), but residual atmospheric biases are not 
negligible for long baselines. 
78 
It is possible to calculate the biases correction using the raw 
difference between the observation and the antenna to satellite 
range. We have called these procedure raw biases estimation. 
A more refined way to calculate the biases correction is to 
estimate every single bias: all the source of errors are modelled 
in the reference station and estimated by Klaman filter, without 
using differential techniques. This procedure is named one way 
biases estimation. 
2.1 Raw biases estimation 
We remember the equation of the observation in the reference 
station, that is named master and is identified by the subscript m: 
m m m 
Pj z pl - E «c (AT, eie 
Dr = = 0j, à T + C: (AT, - AU )- H + y T Me ho. AN], 
$, - p] - E cc (AT, - &'* )- Teg ! FANS, 
(1) 
f 
where: V= e 
f; 
E! ephemeris error 
M 7 ; multipath 
Subtracting the range p, we can calculate the correction term for 
every observation; this correction term includes also master 
clock error and ephemeris error: 
2m m m m 
8C], 2 -E) * c (AT, - A | T] MG) 
Ze +c-(aT, cédant TA 
ob ES E! *6: (AT, m — A )- I +T; + Ma FAN, 
egi Mice: -A vi AT] MI FANS, 
Q) 
In the ro 
master S 
these eq 
small to 
biases hz 
MRS or |] 
e = 7 
2.2 One 
We mak 
satellite c 
oc =| 
38. =| 
b. =| 
A s 
2m 
In these 
modelled 
round br: 
modelled 
non mod 
that are n 
The stat 
paramete 
X, = [a, 
Where: 
the numb 
par =4 
that is i.e 
In this s 
State. Ea« 
vector x, 
System n: