Experience feedback from in-flight measurements is therefore very useful in order to infer what really occurs and to allow comparison between actual findings and ground tests. |
1.PIXEL DARK SIGNAL AND RADIATION EFFECTS1.1GeneralIn darkness, the active pixels generate what is known as pixel dark voltage (also called pixel dark signal). This phenomenon depends on many factors, including:
As a detector can be made up of several registers, the average pixel dark signal can be defined over the entire detector or over just one register (or a matrix row). In addition, a non-uniformity parameter, known as DSNU (Dark Signal Non Uniformity) can be defined. This parameter represents the peak-to-peak pixel dark signal along a row or a register for linear CCD, or over an area for frame transfer CCD. 1.2Radiation effectsTwo effects stand out among the various causes of permanent damage to detectors:
Figure 1 illustrates these two permanently damaging effects: 2.DEFINITION OF PARAMETERS STUDIED IN FLIGHT2.1Available dataIn-flight measurements can be used to monitor variations in pixel dark voltage in several detectors used on various missions. This chapter presents a focus on different detectors in orbit: the SPOT5 detectors (SPOT5_XS for multispectral detectors, SPOT5_PAN for panchromatic detectors and SPOT5_ST for SPOT5 Star Tracker), and the PARASOL detectors (PARASOL_Payload for the Observation CCD array and PARASOL_ST for the Star Tracker). The set of analysed data covers a period of three years for SPOT5 and one year for PARASOL. 2.2Relative drift in dark signalUsually, dark signal variation ΔV is written versus initial dark signal V0 and total dose as follows (1): where A represents dark signal slope versus total dose. In order to ease comparison between data taken with various operating conditions, the relative drift ΔVr between dark signal variation ΔV and the initial dark signal Δ0 has been preferred (2). Assuming that dark signal drift and initial dark signal are proportional to integration time and temperature, then relative drift only depends on received dose (3). Therefore, drift values on board different satellites can be compared simply by calculating the values at the same received dose (a proportionality factor is assumed: the greater the dose, the greater the drift). Relative drift is expressed as %/kRad. 2.3Study of dark signal jumpsA jump is a sudden increase in a pixel dark signal after proton-nuclear interaction. Jump amplitude can vary with proton energy and interaction properties. This study focuses only on the maximum in-flight amplitude. Jumps, expressed as the number of electrons generated, must therefore be compared at: DSNU drift is not constant. If one pixel is impacted by a proton hit and exceeds the maximum dark signal value previously observed in a register, then the DSNU significantly increases. However, many pixels can be impacted without exceeding the maximum dark signal value. This means that the DSNU increases in a random manner over time. Similarly, if one severely damaged pixel (thus imposing the DSNU in the register) shows evidence of annealing (gradual and partial decrease in darkness level after impact, see Fig. 2), then the DSNU decreases significantly. Assuming that a pixel can only be significantly impacted once, it can be assumed that DSNU increase is limited by the maximum_jump. The only way to reach the maximum DSNU increase would be for a pixel with a near-maximum initial dark voltage to undergo a jump roughly equivalent to the maximum observable jump. The study of jumps gives then an idea of DSNU increase worst case. Figure 3 illustrates the supposed drift in DSNU: 2.4Study of the number of singular pointsA cumulative approach is adopted to study variations in the number of singular points (pixel with a dark voltage beyond the average value + 3σ, whereσ is the standard deviation inside a register): any point that has become singular once, continues to be counted as such during subsequent acquisitions, regardless of its later state. Measurement frequency is seen to have an impact on the number of singular points count (see Fig. 4 and 5), as some pixels are annealed and become normal again. Consequently, the greater is the measurement frequency, the more likely we can count pixels of this type. For this reason, a measurement frequency of one measurement per month (i.e. the measurement frequency of PARASOL detectors, the lowest available) has been adopted to be able to compare the results. The number of singular points also depends on the received dose (the higher the received dose, the greater the probability of having a singular pixel) and on the pixel surface area (the larger the sensitive surface of a pixel, the greater the probability of having a singular pixel). The following conditions must therefore be fulfilled to be able to compare results:
It is important to know the variation in the number of singular points as it gives us an idea of the rate at which calibration should be carried out. 3.RESULTS3.1GeneralThe same trends are observed on all the detectors studied:
Figures 6 to 8 below illustrate these trends in the case of the PARASOL Payload, and Figures 9 to 10 show the case of SPOT5_XS. 3.2Comparison of variations observedBy considering the parameters studied under equivalent conditions (calculation of received dose by considering the orbit and equivalent aluminium shielding), it can be seen that the trends observed in flight are on a similar amplitude (factor of 1 to 3) for all the detectors studied (see following table 1). Table 1:comparison of in-flight variations
These similarities are surprising considering that the detectors concerned are very different in terms of type and use (matrix or linear array, integration time, etc…). The main similarities appear on singular points and jumps related to proton displacement effect. This shows clearly that the mechanisms involved seem to be independent on the CCD technology, and are rather intrinsic to the silicon-based material common to all the devices tested. A spread of a factor 3 is observed on mean dark signal increase. As pointed in § 1.2, mean dark signal increase is related to total dose effect and oxide ionisation. In this case, an enhanced dependency on CCD design and process fabrication might be evidenced. It should be underlined, however, that there is an uncertainty factor (even if it is less than 2) in the calculation of the in-flight dose received by the detector. This is because sectorial analysis are either missing or approximated. 3.2Comparison with on-ground measurementThe results of ground measurement are available in the table 2. Table 2:ground measurement
It is observed, compared to table 1, that even if ground predictions are quite close to in-flight values, the predictions indicate a drift value that is 16.5 times greater than that actually observed in flight in the case of the SPOT5_XS detector. 4.CONCLUSIONSConfirmation of these results by in-flight measurements on other detectors (other manufacturers, same type of orbit, etc.) would be very useful for end-of-life predictions. An empirical model would give a clear idea of actual in-flight variation before testing (variations in DSNU and pixel dark signal, calibration rate, etc.). In addition, ground predictions can prove very pessimistic compared with actual in-flight values (this is the case of TH7834B). In this case, a more realistic estimation would release some margin when adjusting certain parameters – detector temperature for example. Refined analysis of all the ground tests would be useful at a later stage to determine which come closest to these observations and possibly attempt to identify which test conditions offer the most realistic predictions. |