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Mapping without the sun
Zhang, Jixian

error data, which may used to correct the atmospheric error
effect of InSAR (Ge, L„ 2001).
It can be seen that InSAR and GPS data fusion technology can
break through the limitation of single method and improve the
resolution both in spatial and temporal. InSAR/GPS fusion
technique is chosen as an effective means for surface subsi
dence monitoring in mining area.
2.1 The processing procedure of InSAR (D-InSAR) data
used in mining area
To monitor the mining area’s surface deformation with InSAR
(D-InSAR), the following strategy could be adopted.
In the first step, a pair of short time interval (only 1 day) single
look complex (SLC) SAR imageries should be selected to
create an interferometric phase image (iph) which reflect the
DEM of the mining area’s surface, (sometimes created with existing DEM and orbital parameters).
In the second step, select another pair SLCSAR imageries that
span deformation period and in the same area to create another
phase image (cps) which includes the information of topographic
In the final step, subtracted (ph from cps, we can get the
deformation phase image (cpd) and the slant-range changing
amount (cprd) from microwave transmitter to ground pixels, cprd
needs to be decomposed into the horizontal and vertical
displacement components with the baseline parameters and the
orbit-state vector.
2.2 Approaches for Improving InSAR data based on GPS
At present, there are many approaches to improve the InSAR
data’s quality with GPS technology. Main aspects are as
follows (Diao, J., 2005):
1) Atmospheric delay error correction;
2) Baseline and orbital parameters estimation;
3) Geometric correction.
2.2.1 Atmospheric delay error correction
Atmospheric delay is one of the major error sources in InSAR
data, which affects the accuracy of mining-induced surface
subsidence monitoring. Atmospheric delay error includes the
tropospheric delay and ionospheric delay error. As for dual
frequency GPS receivers, the pseudo-range measurement
equation of a certain GPS observation station is shown in
equation (1) (Chen, J., 2004).
L\j ~ P j dtrop ^ ion (./l) "f £
L 2j = Pj ~ d trop - d ion(fl)+ £
where e = other deviation and residual term
¿¡rap = tropospheric delay error
dio n {fk) = ionospheric delay error for frequency f k
2.2.2 Baseline and orbital parameters estimation
Another error source of repeat-pass InSAR used in monitoring
the surface deformation in mining area is baseline and orbital
parameters. In general, baseline can be estimated by using the
satellites ephemeris parameters. However, the origin motivation
of sending radar satellite was not for SAR interferometry, it
caused the ephemeris parameters have lack of accuracy usually
and cannot meet the demand of SAR interferometry. In order to
gain high precision baseline vector parameter, ground control
points (GCP) with high precision can be used to obtain the radar
satellite baseline vector parameters (Volker, J., et al., 2003).
This method needs to set equipments that are called comer
reflectors on the surface of mining area. Figure 1 shows the
structure figure of comer reflector.
Comer reflectors can be seen as high bright points in InSAR
imageries, the interferometric phase differences among these
points can be exacted according to their phase information. The
geodetic coordinates and their relative coordinates could be
gained by GPS measurements. Thus baseline parameters could
be estimated by using image interferometric phase differences
and the relative coordinates of ground comer reflectors.
In order to estimate the InSAR orbital parameters, InSAR
terrain surveying equation (Shi, S., 2000) must be used. Showed
in equation (2) and equation (3).
a i
a 2
a 3
= \
b 2
r sin 9
_ c i
c 2
c 3 _
r cos 9
. Z s_
9 = arccos +a
2 \ AnB J
where X, Y,Z = geodetic coordinates of a certain GCP
a \, a 2, a 3, ■■■C3 = rotation matrix of attitude angles
X = scale factor
r = the slant distance from a certain GCP to satellite
6 = over look angle
X s , Y s , Z s = orbital position of satellite
d> =absolute phase of interferometry
The Satellite orbital attitude parameters and the baseline can be
expressed by time linear equation or polynomial. Showed in
equation (4).