Simulating IRS-P3 Navigation System using GPS Receiver

A.S. Ganeshan
asganesh@lsac.emet.in
ISRO

Abstract:
IRS-P3 is a multi-Payload remote sensing spacecraft to be placed
in a 817 km orbit. As a piggy back payload,a six channel GPS receiver
with a C/A code, is proposed to fly on-board to provide the instantaneous
state vector of the spacecraft. The on-board processor computes
the state vector from the pseudo range and pseudo delta-range measurements
obtained from the visible GPS satellites based on the minimum GDOP criteria.
The ground segment is supported through spacecraft telemetry and as a part
of it, the instantaneous position and velocity are received in three data
streams namely, the Low Bit rate Telemetry, Play back mode and in Real Time.
Additionally, the pseudo range and pseudo delta-range measurements, used for
the on-board computation of IRS-P3 position, are also made available in the
RT stream during ground station visibility of IRS-P3. A ground GPS receiver
yields the GPS position that are commonly visible to the ground and on-
board GPS receiver.  The measurement data from the RT stream together with
the GPS position from the ground receiver are used to estimate the IRS-P3
position on the ground as well, in an off-line mode.  During simulations,
the measurements of range and delta-range between the highly dynamic, IRS-P3 
and the visible GPS satellites are generated.  Subsequently, noise are added
to these measurements using the Gauss-Markov process to simulate the realistic
scenario.  The noise patterns applicable at IRS altitude are assumed to be
owing to selective availability (SA), receiver noise and constant receiver error.
Contributions stemming from ionosphere, troposphere and multipath are assumed
negligible for the IRS-P3 satellite.  However, the same are assumed to be present
for the ground GPS receiver.  In the ground processing the state vector estimates
of IRS-P3 are improved further by removing the ground receiver specific errors,
which in turn aids assessing and removing SA errors from the measurement data
received from IRS-P3. The paper discusses the simulation algorithm and the results
in detail and the estimation aspects in brief