Error sensitivity To test the error sensitivity of the inverse tomographic problem we take the test model from section 3.1 and impose errors in the projection/forward model/imaging process. Here the sensitivity to two sources of errors will be discussed. The first is in the sensitivity of the cameras and the second is in uncertainties concerning the directions of the lines-of-sight. The sensitivity errors are introduced by multiplying the modelled images from the stations at 50 km north and 100 km south by 1.03 and the model image from the station at 50 km south by 0.97, modelling an uncertainty of 3 % in camera sensitivity. To test the sensitivity to errors in orientation, the 1-D images are randomly shifted by one pixel for all stations simulating an angular uncertainty of $0.2$. The uncertainties are first applied separately and finally together. The imperfect 1-D images are then used to make reconstructions with both damped least square and the ART inversion. The result is that even for the perfect images the reconstructions are more coarse than the auroral model, as can be seen in the upper-left panels of Figure 3.8 and Figure 3.9. For the non-perfect projections, the noise in the images makes the damped least square reconstructions, in particular, more noisy but also the ART reconstructions show artifacts manifested mainly as streaks in the radial direction from the stations. Figure 3.8: Model test of the damped least square solution of the tomographic problem using the model aurora shown in Figure 3.3. Upper-left panel is a reconstruction from perfect projections with a 1 % noise level. Upper-right panel is a reconstruction from projections with 3 % sensitivity errors. Lower-left panel is a reconstruction from projections that have $0.5$ rotational errors. Lower-right panel is a reconstruction from projections with errors in both sensitivity and rotation. Figure 3.9: Model test of the algebraic reconstruction technique (ART) solution of the tomographic problem with the model aurora shown in Figure 3.3. Upper-left panel is a reconstruction from perfect projections with a 1 % noise level. Upper-right panel is a reconstruction from projections with 3 % sensitivity errors. Lower-left panel is a reconstruction from projections that have $0.5$ degrees rotational errors. Lower-right panel is a reconstruction from projections with errors in both sensitivity and rotation. As can be seen, the errors in the reconstruction increase already at these low levels of uncertainties in the forward model. Thus, in order to obtain reconstructions of the aurora with sufficient quality for making further analysis worthwhile, it is of vital importance to achieve the necessary accuracy of the forward model.