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Satellite based imaging sensors are subjected to several factors that may cause the values of the calibration parameters to vary between the time of ground calibration and on-orbit operation. This paper considers the problem of satellite based imaging sensors calibration, while estimating the state of a target of opportunity. The 2D pixel based measurements (estimated location of the target’s image in the Focal Plane Array - (FPA)) generated by these sensors are used to estimate the sensors pointing angle biases. The noisy measurements provided by these sensors are assumed to be perfectly associated, i.e., they belong to the same target. The proposed algorithm leads to a maximum likelihood bias estimator. The evaluation of the corresponding Cramer- Rao Lower Bound (CRLB) on the covariance of the bias estimates, and the statistical tests on the results of simulations show that both the target trajectory and the biases are observable and this method is statistically efficient.
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Djedjiga Belfadel, Yaakov Bar-Shalom, "On-orbit calibration of satellite based imaging sensors," Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 1064605 (27 April 2018); https://doi.org/10.1117/12.2304693