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Vol. 118, Issue 7, July 2010, pp.144-155




Attitude Modeling Using Kalman Filter Approach for Improving the Geometric Accuracy of Cartosat-1 Data Products


1Nita H. SHAH, 2B. ISLAM

1Department of Mathematics, Gujarat University Ahmedabad 380 009, Gujarat, India

2Space Applications Centre, ISRO, Ahmedabad - 380015, India

E-mail: nitahshah@gmail.com


Received: 10 March 2010   /Accepted: 24 July 2010   /Published: 31 July 2010


Abstract: This paper deals with the rigorous photogrammetric solution to model the uncertainty in the orientation parameters of Indian Remote Sensing Satellite IRS-P5 (Cartosat-1). Cartosat-1 is a three axis stabilized spacecraft launched into polar sun-synchronous circular orbit at an altitude of 618 km. The satellite has two panchromatic (PAN) cameras with nominal resolution of ~2.5 m. The camera looking ahead is called FORE mounted with +26 deg angle and the other looking near nadir is called AFT mounted with -5 deg, in along track direction. Data Product Generation Software (DPGS) system uses the rigorous photogrammetric Collinearity model in order to utilize the full system information, together with payload geometry & control points, for estimating the uncertainty in attitude parameters. The initial orbit, attitude knowledge is obtained from GPS bound orbit measurement, star tracker and gyros. The variations in satellite attitude with time are modelled using simple linear polynomial model. Also, based on this model, Kalman filter approach is studied and applied to improve the uncertainty in the orientation of spacecraft with high quality ground control points (GCPs). The sequential estimator (Kalman filter) is used in an iterative process which corrects the parameters at each time of observation rather than at epoch time. Results are presented for three stereo data sets. The accuracy of model depends on the accuracy of the control points.


Keywords: Collinearity model, Kalman filter, Geometric Modeling, Cartosat-1, Geometric accuracy


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