4 Final Report - Emits - ESA

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4 Final Report Figure 4.4-2: Structure FEM used for the BBW microvibration analysis and computed stability over 70 msec for a typical 2-day wheel rate profile The following conclusions are drawn from this analysis. First, elastomeric suspension is mandatory since it allows a reduction by a factor 100 of the high-rank harmonics perturbations. Second, the elastomeric suspension frequency shall be set to 15 Hz and the wheels velocity shall be maintained below 45 Hz (2700 rpm) thanks to adequate wheel off-loading process at AOCS level. Then, conservatively considering a linear summation of the harmonics and the worst wheel FM, the worst case performance over a typical wheel velocity profile is 0.24 µrad peak-to-peak over 70 ms. This is above the Geo-Oculus requirement (0.15-0.2 µrad peak-to-peak), but the impact on the achievable resolution would be limited, with a degradation of the nadir ground resolution from 10.5 m to 11.5 m. Of course, the level of this preliminary analysis cannot give commitment on these figures, but the order of magnitude is believed to be valid. Therefore, the use of BBW for Geo-Oculus shall not been ruled out by microvibration aspects. Furthermore, the technology is fully qualified, flying on previous programmes. 4.4.3 Post-integration Stabilité sur 70 ms (µrad) 0.25 0.2 0.15 0.1 0.05 Performance en fonction du temps FM09 FM06 Pire cas 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 Temps (jour) 4.4.3.1 Principles Post-integration consists in taking several successive images of the scene with short integration time and to add them together to obtain long-integration images, i.e. with high SNR. Keeping the integration time small is necessary for avoiding pixel saturation and for relaxing LoS stability when drift is the dominant error. Post-integration is of no use for micro-vibrations mitigation and applies only to drift mitigation, by reducing the integration time. One option is to perform this post-integration on ground, but this dramatically increases the downlink data rate since up to several tens of images are required on the most critical channels (e.g. for marine applications with high SNR requirements and low reflectance). On-board post-integration is therefore the baseline for Geo-Oculus, based on the of the experience gained on COMS satellite developed by Astrium for Korea. Page 4-46 Doc. No: GOC-ASG-RP-002 Issue: 2 Astrium GmbH Date: 13.05.2009
4 Final Report If the LoS motion during the summation of the successive images is large (typically > 1 pixel), the motion must be compensated for by shifting the pixels. The simplest correction is the so-called "nearest pixel motion compensation", where the shift is limited to an integer number of pixels, simply achieved by a shift in memory and an accumulation. The average MTF loss at the Nyquist frequency is 0.64 on the accumulated image, i.e. equivalent to a shift of one pixel over the whole accumulation. To reduce this significant degradation of the MTF, refined offset correction methods based on pixel interpolation are possible, but not retained for Geo-Oculus for their low maturity and the required large on-board computation and storage capabilities. The first step is however to measure the LoS motion between two integration phases, with an accuracy significantly better than half a pixel (0.2 pixel i.e. ~0.1 µrad). 4.4.3.2 LoS drift measurement The LoS motion information can be extracted from gyroscope measurements, provided they are mounted close to the focal plane. The following figure shows the LoS drift estimation error for two high accuracy gyros (Pleiades Astrix 200 FOG and SIRU HRG): Over the maximum image acquisition time (5 sec), the error is 0.3-0.5 µrad, well above the 0.1 µrad requirement. Gyros are therefore not adequate for LoS drift estimation. Gyro drift (µrad) 0,5 0,4 0,3 0,2 0,1 0,0 0 1 2 3 4 5 Time (secs) Figure 4.4-3: LoS drift estimation accuracy using gyroscopes ASTRIX200 In the case of GEO-observation with a staring instrument, the motion information can also be extracted from the image itself, which removes the need for additional motion sensor. The principle is to correlate in real-time on board the spacecraft the incoming image with the accumulated image, so as to determine the relative image to be corrected. Either the full image or vignettes of interest are used. In the first case, the processing load is high, but the algorithm is simple (correlation over a small moving window) and repetitive, which is well adapted to FPGA or ASIC implementation. In the latter case, the system shall identify vignettes of interest within the first image using an algorithm detecting areas with contrasted variations. Then the correlation is performed between the selected vignettes extracted from the accumulated & current image. Such techniques are actively investigated at Astrium, primarily for on-ground processing to improve image quality without relying on pre-defined landmarks. The resulting accuracy of image correlation is in the order of 10% to 20% of a pixel, that is to say below 0.03 to 0.06 µrad, well with in the 0.1 µrad requirement. Image correlation is therefore the selected approach for LoS drift measurement. Doc. No: GOC-ASG-RP-002 Page 4-47 Issue: 2 Date: 13.05.2009 Astrium GmbH SIRU
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Geo-Oculus: A Mission for Real-Time
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DL Final Distribution List Report Q
Page 11 and 12: TOC Final Table of Content Report D
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