1.1.

Value of the PG System for JWST

Proper alignment of telescope mirrors to each other is essential to meet image quality requirements. The JWST is the largest segmented space telescope every built. With an actuated primary and SM, the system is designed to align itself on orbit. Ensuring the system has the range required was a primary goal of the OTIS cryogenic test.⁴ With a PM diameter of 6.5 m, a spacing to the SM of 8 m, an operational temperature of 40 K, and alignment tolerances approaching an absolute accuracy of 0.100 mm this is an exceptionally challenging problem. The only conceivable technology to meet those parameters was a photogrammetry system.

The requirements for the PG system were as follows.

1.2.

CPM Hardware Description

For thermal/vacuum tests of the JWST observatory, a set of four cameras on rotating windmill booms contained in pressure and thermal tight enclosures are used inside the helium shroud.⁷ As the windmills rotate, the camera system records multiple images of special photogrammetry targets placed on the OTE and throughout the chamber. Figure 1 provides an overview of the JWST OTIS flight hardware and optical GSE (OGSE) in the JSC chamber A. The OTIS photogrammetric survey was done primarily during conditions of a 30-K vacuum environment, although some testing was done at ambient temperature and during cool down/warm up.

Fig. 1

Overview of JWST OTIS flight hardware and OGSE in JSC chamber.

The successful application of photogrammetry requires support equipment that includes scale bars, coded targets to aid automated processing, and metrology target point locations that define the object of interest. The scale bars were used for the correct calculation of scale to apply to a photogrammetric bundle. This is of critical importance to the overall accuracy of a measurement survey. The code targets are used to aid in defining the position and orientation of the camera during bundle adjustment.

1.3.

Scale Bars

To scale a photogrammetric measurement, at least one known distance must be present in the imagery. For the purposes of the JWST PG system, multiple scale fixtures (i.e., scale bars) are incorporated into the object space that contain target pairs of known distances. The distances between target pairs on the bar were characterized and can be used to scale the measurement survey. Multiple distances allow a higher order of scale calculation accuracy and the redundant measurements allow for the ability to find scale errors. Thermal sensors were placed on each bar to accurately calculate scale bar length at each point in the temperature cycle where a measurement was performed.

The modeled setup for this PG application included 20 invar scale bars positioned around the PM from posts attached to the Hardpoints and Offloader Support Subsystem (HOSS) structure. In addition, as part of the gravity references located on the posts, there were five vertical scale bars for vertical ($Z$) scale. Each scale bar contains one thermal diode and a set of four target pairs for redundant scale. Figure 2 shows the distribution and an example invar scale bar.

Fig. 2

Distribution of invar scale bars around the HOSS and example invar scale bar.

Based on results from JWST pathfinder chamber tests, vertical scale bars were also added near the SM affixed to the chamber walls. The bars provided a vertical scale reading that had a lower bundle adjustment uncertainty in some pointing schemes than the vertical bars on the HOSS and thus provided a check that the scale factors were consistent throughout the bundle. Inconsistent scale would be a sign of distortion of the bundle.

1.4.

Coded Targets

Coded targets are a special type of target that the Video, Self-Calibration, Triangulation, and Resection Software (V-STARS) can recognize, automatically decode, and use to automatically calculate the position and orientation of the camera to aid bundle adjustment. Each code is made up of a unique pattern of dots. When planning a photogrammetry, project coded targets must be well-distributed throughout the object space so that each captured image contains a minimum of four coded targets. Coded targets were distributed on the chamber wall and on sleeves that went around the telescope rod supports. In addition, the telescope rod sleeves provide PG targets in what would otherwise be empty space so that there were sufficient points in each image to stitch the entire bundle together. Initially, the points on the telescope rods were planned to be used as scale bars, but measurements of expected coefficient of moisture expansion and coefficient of thermal expansion (CTE) indicated that the materials properties were too variable to ensure reliable scale bar accuracy. An illustration of the telescope rod sleeve is shown in Fig. 3.

Fig. 3

Distribution of composite sleeves on the telescope rods and example composite sleeve.

1.5.

INCA Camera System

The photogrammetric camera system selected for the JWST photogrammetric application is the third generation Intelligent Camera (INCA3) system provided by Geodetic Systems, Inc. (GSI). In addition to its robust design and vetted operational accuracy, this system was chosen because it could operate in an automated capacity. Due to the demands of the cryogenic vacuum tests at JSC, remote operation was an important capability. A compact but powerful computer accompanied the camera system to do image processing and bundle adjustment. Figure 4 shows the INCA3 photogrammetric camera system and identifies some of the advanced features. Table 1 outlines the manufacturer’s specifications for the INCA3 camera system.

Fig. 4

INCA3 camera system as provide by GSI.

Table 1

Manufacturer’s specifications for the INCA3 camera system.

1.6.

Coordinate System

The results in this paper are reported relative to a coordinate system that is defined with respect to the Aft Optics Subsystem (AOS). The origin is the center of the base of the AOS on the PM and the axis is oriented as shown in Fig. 1 where +M1 is toward the top of the chamber, and +M2/+M3 are in the plane of the PM.

4.1.

Hardware Configuration, Target Placement, and Data Flow Testing

Prior to the completion of the CPM, the modeled imagery was used to determine optimal camera pointing schemes to ensure that all objects were adequately sampled and to assess the expected accuracy of the system. Two camera pointing schemes were developed—one that samples the whole chamber (OTIS_ps) and one that provides for more accurate determination of objects at or below the PM plane by not recording images of the Auto-Collimating Flat (ACF) at the top of the chamber (LOWCH_ps). Both pointing schemes were used successfully without modification during CCT and OGSE1 testing. A small modification was made to the lower chamber pointing scheme (LOWCH_ps) during OGSE2 to provide better imaging of the SM targets.

The DIRSIG model provided the ability to assess the impact of changes made in the number of targets used and answer other configuration questions such as the utility of having vertical scale bars on the telescope rod sleeves if the deficiencies in materials properties could be overcome. For example, originally 120 targets were proposed for the PM, but that number was eventually reduced to 30 for the final OTIS design. V-STARS analysis using modeled imagery of the two cases indicated that the same level of accuracy would be expected. In the case of the vertical scale bars on the telescope rods, the model showed that they were poorly seen and would be expected to have a very large uncertainty and so would not provide reliable scale values.

The existence of a full set of DIRSIG model imagery also provided the ability to exercise the analysis software to ensure that there were no issues with the number of images required, the spacing and placement of coded targets, etc. proved quite useful prior to actual chamber testing. It allowed very quick turnaround of the initial chamber test data without having to work out logistics, fitting parameters, etc. at that time of the first data collects. The necessity of multiple coded target sizes in the chamber to accommodate the large variation in distance, and hence intensity, between the closest and furthest sets required modification to V-STARS. Using the modeled image data, the new capability was tested out prior to actual chamber measurements. Having the data available from modeled images also allowed the determination of the pros and cons of various coordinate system alignment fitting schemes in terms of number of objects used so the best accuracy could be ensured.

4.2.

Prediction of PG Accuracy

One key advantage of using a model versus a physical mockup is the ability to compare against absolute truth. There are several ways to estimate the expected accuracy of the CPM system based on the DIRSIG modeled imagery. Overall numbers can be calculated based on the image residuals or RMS of the bundle adjustment uncertainty. More detailed analysis of each object can be obtained by looking at point by point comparison of the V-STARS calculated bundle values versus the reference values. A more extensive description of all these methods can be found in Ref. 10, some key results are provided below.

To determine values and statistics for residuals, bundle adjustment uncertainty and absolute position four consecutive PG runs were obtained under both ambient and cryogenic conditions during the CCT. Comparison of model results to observed performance indicated that there was a larger value for image residuals than seen under experimental conditions. Image residuals reflect the variability in the value of PG measurement of an individual target point in all the images that contain that point. Image residuals were $\sim 0.73\mu \mathrm{m}$ for the DIRSIG modeled imagery, whereas GSI predicted their camera would be $\sim 0.25\mu \mathrm{m}$ for the bundle adjustment. Image residuals are measured with respect to the dimensions of a pixel on the sensor, which is $10\mu \mathrm{m}$ (Table 1). For ISIM testing, measured residuals were $0.2527\mu \mathrm{m}$.¹¹

For the commissioning tests, the bundle adjustment of imagery from the CPM gave an overall image residual of $0.18\mu \mathrm{m}$ which is similar in magnitude to that found for the ISIM testing and consistent with what was expected by the manufacturer. The contribution to image residuals due to model limitations of, for instance, the target center visibility at oblique angles, is the most likely cause of the over prediction.

The actual bundle adjustment uncertainties of a representative run from CCT are shown in Table 2 compared to model predictions. A few areas are similar (e.g., SM V2/V3), but in most cases, the modeled imagery bundle adjustment uncertainties were a factor of $\sim 3$ to 4 times larger than measured in the chamber. The actual imagery versus simulated imagery predicted bundle adjustment uncertainties were quite consistent with the differences in the image residuals of about 3 to 4 times (0.75 versus $0.18\mu \mathrm{m}$), so the increase in residual correlates directly with an increase in bundle adjustment uncertainty.

Table 2

Bundle adjustment uncertainties obtained from the first run of the PG commissioning testing. Predictions from simulated images are shown in parentheses.

It should be noted that bundle adjustment uncertainty does not necessarily translate to increased absolute error, as the bundle adjustment uncertainty is a measurement of variability image to image of the point measurements and a large distribution does not necessarily imply a shifted mean value. The mean value is the absolute position in space.

To provide an independent characterization of the absolute accuracy of the CPM system, laser trackers (LTs) were utilized in CCT and laser radar (LR) systems were utilized in OGSE 1 preliminary chamber tests to provide calibrated 3-D coordinates for a subset of PG target mount locations. The CPM testing consisted of four consecutive PG runs with concurrent LT or LR measurements. Prior to installation in the chamber, the LR measurements of many targets were also taken in the clean room. The run-to-run repeatability and absolute accuracy with respect to an LT- or LR-based reference position were calculated for each run and compared across runs.

LT data were taken in the chamber. LR data were obtained both in the clean room and in the chamber. Due to the constraints of where the LR could be put in the chamber and the fall off of accuracy as a function of laser angle of incidence, some targets could only be measured in the clean room where the LR could be positioned more freely. Some pieces of hardware were not installed in the cleanroom and so were only measured in the chamber. The top of the SM targets could not be measured in the chamber or the cleanroom, and so the back of the PG target was measured instead, and the PG center was calculated based on design measurements of the target mount.

The error of PG measured versus LT and radar measured values are shown in Table 3. The measured errors include both the PG and independent metrology uncertainties. The average error of the model is consistent with the actual measurements within the uncertainty. The actual measurement uncertainty with respect to model values is at a level that is consistent for individual axes with a $3\times$ change in image residuals roughly causing a $2\times$ change in overall magnitude.

Table 3

Actual error from CCT measurements versus predicted error using DIRSIG imagery (in parentheses) for selected objects. Values are 1 sigma. ACF numbers are from CCT data, SM, AOS, and PM from OGSE1 data. Data are from a single photogrammetry run.

The lack of availability of known reference points other than scale bars under cryogenic conditions prevented extensive characterization of the absolute accuracy under those conditions. The CTE of the invar used to construct the scale bars was measured experimentally and used to predict the length under cryo-conditions to provide an accurate reference.

The strut base points targets (SBT) on the HOSS do provide a reference to cross check that the scale predictions are within expected tolerances. Spatial analyzer software was used to fit measured changes in SBT positions for ambient and cryogenic runs from OGSE1 and OGSE2 preliminary chamber tests. For the SBT points, a repeatability of $50\mu \mathrm{m}$ was achieved for an object of 7-m diameter. A cross check of the change in distance from ambient to cryo-stable on a similarly sized stainless steel feature in the chamber also agreed within $50\mu \mathrm{m}$ to expected changes.

In summary, modeled performance using DIRSIG generated imagery was limited by the artificially high residuals from bundle adjustment, which did provide good guidance when that difference was taken in account as to the overall performance of the system. The use of modeled imagery also allowed for determination of camera pointing schemes that would best optimize the trade between number of images per object and the need to cover a large chamber space.

4.3.

Additional Chamber Tests for CPM Characterization

4.3.2.

SM measurement cross checks

Due to the critical need of knowledge of the SM position in both cryo-stable PM-SM alignment and AD testing and the difficulty in getting the absolute position comparison during the commissioning process, additional data was collected and analysis was performed during subsequent OGSE1, OGSE2, and TPF tests on the repeatability and stability of the SM measurements. Two general areas were assessed—the ability to accurately determine the scale and the impacts of different camera pointing schemes.

Scale factors

One large driver of possible errors in SM position is the ability to correctly assess and to repeatedly calculate scale. As a cross check on the repeatability of the scale calculation, the distance from scale bar set to scale bar set across the PM was monitored (referred to as “Big Bar,” see Fig. 6) starting in OGSE2 and continued through OTIS. Results showed that the $2\sigma$ variance was $<0.06\mathrm{mm}$ on average across the $\sim 8\text{-}\mathrm{m}$ distance from scale bar to scale bar under cryo-stable conditions for OGSE1 and $<0.08\mathrm{mm}$ for OGSE2.

Fig. 6

Examples of scale bar to scale bar distances (Big Bar) used to monitor scale calculation consistency during cryo-stable testing.

Similar results could not be obtained for the TPF test as several scale bar points became unmeasurable (Fig. 7) as discussed below.

Fig. 7

Images or scale bar points at the juncture of post 1 and post 2. Image contrast was kept at a constant range so that intensity can be compared directly image to image.

Of the scale bars remaining, the bundle adjustment uncertainty was markedly higher than during OGSE2 (Fig. 8). The increase in noise in the scale bars began during cool down. Root cause investigation traced the problem to a chamber leak causing ${\mathrm{O}}_2$ and ${\mathrm{N}}_2$ condensation on the coldest scale bar targets thus obscuring the retroreflective surface (Table 5). The sensitivity of the bundle adjustment uncertainty calculation to condensation was used during OTIS testing to monitor for signs of this kind of issue. The only occurrence found was during a brief period during warm-up that had conditions that were conducive to previously condensed gases that had started evaporating off warm parts of the chamber (a “burp”) recondensing on the much colder scale bar posts.

Fig. 8

Average bundle adjust uncertainty (2 sigma) for all eight points of each scale bar for all OTIS_ps runs in OGSE2 and TPF tests.

Table 5

Average temperature for each post for the last cryo-stable run in TPF. Posts are ranked from least noisy to most noisy based on the average of the bundle adjustment uncertainty shown in Fig. 8 for the scale bars attached to that post.

Post	T (K)
1	28.46
3	26.47
5	32.37
4	24.84
2	24.30

An experimental change during OTIS testing as compared to prior chamber tests was to add vertical scale bars attached to the chamber walls. These bars were attached about a meter below the SM level so that the bundle adjustment uncertainty was predicted to be at an acceptable level for both camera pointing schemes. Unfortunately, the position experimentally proved to give unreliable scale bar estimates in the LOWCH_ps case due to the low number of usable images, as approximated by the number of “rays” used in the PG solution, (Table 6) and so those bars were excluded for use in the pointing scheme. The OTIS_ps and use of bundles created from the combined images of both sets provided much more consistent estimates of vertical and horizontal scale because the number of rays was significantly increased.

Table 6

Number of rays per point for one of the vertical chamber-wall-mounted scale bars. Points A-D2 are located on the top part of the bar, E2-H on the bottom.

Point	Number of rays
	LOWCH_ps	OTIS_ps
SN_072_A	66	215
SN_072_B	65	208
SN_072_C	70	203
SN_072_D	73	219
SN_072_D1	89	223
SN_072_D2	82	224
SN_072_E2	156	207
SN_072_E1	158	209
SN_072_E	155	208
SN_072_F	161	211
SN_072_G	162	217
SN_072_H	152	187

Camera pointing scheme factors

The calculation of scale was very consistent run to run and between camera pointing schemes. However, testing indicated increasing discrepancy between the calculated SM position in M1 as more targets were installed near the PM. Table 7 illustrates the difference between the average calculated position of the SMA between the two pointing schemes. Although differences always existed, with the full flight hardware installed in OTIS, the difference in M1 became more pronounced than in previous tests and this prompted further analysis. Because the measurements from scale bar to scale bar (Big Bar) agreed, scale error between the pointing schemes was quickly ruled out as a cause of the discrepancy.

Table 7

Comparison of average LOWCH_ps value–OTIS_ps value for SM points in three pre-OTIS chamber tests. Each set compares a single run for each pointing scheme.

	ΔM1 (mm)	ΔM2 (mm)	ΔM3 (mm)	Delta big bar (mm)
OGSE1	−0.013	−0.275	−0.614	0.080
OGSE2	0.045	0.078	0.099	0.057
TPF	0.067	0.076	0.083	a
OTIS	0.125	0.192	0.038	0.036

^aUnable to create direct comparison due to scale bar condensation issues that prevented the same scale bar sets being used.

During pre-OTIS testing, inconsistency in calculated SM position by the CPM system was also observed during initial AD testing. The purpose of the AD test is to characterize the change in PM to SM M1 position as a function of telescope temperature. Because the variations on flight are so small ($\sim 0.2\mathrm{K}$), a large temperature delta is used for the ground test (20 K or more) so that the measured PM to SM distance changes are well above the measurement noise of the PG system. The experimental results showed large ($>0.2\mathrm{mm}$) deviation of measured results to expected values in the first change from 35 to 55 K in some but not all of the chamber tests.

Measurement of the SM was hampered by two factors. The first is that SM targets were constructed as flat targets facing up and due to the configuration of the booms and requirements of pointing angles to see other critical objects, there were significantly lower number of images of the SMA targets than at the PM level. The second issue is target visibility. The SM is the only object besides the telescope rods that provide PG targets in the 16 m of space between the PM and the ACF. Examination of the predicted bundle adjustment uncertainty at the SM level in the pretesting DIRSIG simulation data indicated that the dearth of points in the bundle at this level creates a nonuniform distribution in visibility across the object at the SM versus the PM level (Fig. 9). The predicted uneven distribution in visibility was seen in actual OTIS_ps data taken during OTIS testing (Fig. 9). The average number of SM views is also roughly half the number of PM views for both camera pointing schemes. There is a strong correlation between visibility and bundle adjustment uncertainty up to a level of about 200 rays (Fig. 10) with an empirically observed floor for this case system of 0.012 mm for all points on the JWST hardware.

Fig. 9

Comparison of distribution of point visibility of simulated versus actual data for SM and PM points. Point visibility is defined as the ratio of the number of rays of a point on an object to the mean of all points of that object. Higher values (yellow points) indicate a more visible point on the object, lower values (blue) indicate a less visible point on the object. Green/light blue points are close to the mean value. The color scales have been set to the same range for all graphs. Note: the simulated positions of the PM points are slightly different than actually installed in chamber.

Fig. 10

Bundle adjust uncertainty versus number of rays for the six SMA targets for both camera pointing schemes, a combined data set, and scaled model data. The scale factor used for the modeled data was 0.25 as per Sec. 4.2.

The LOWCH_ps case, with the increased number of rays for objects lower in the chamber, might be expected to improve the situation. Although there is a noticeable increase in the number of rays between the OTIS_ps and LOWCH_ps camera pointing schemes (Table 6) that improves the overall bundle adjustment uncertainty of the points (Fig. 10), overall the same nonuniformity is present (Fig. 11).

Fig. 11

Visibility distribution of SM points for the LOWCH_ps camera pointing scheme. For more detailed description, see Fig. 9.

In summary, chamber measurements indicated that there was a noticeable inconsistency in the solution of the position of the SM points as a function of pointing scheme, objects present in the chamber, and the presence of a thermal gradient during the start of AD testing. Investigation as to possible causes of these observations found no problems in the CPM in image collection, image quality, or bundle adjustment despite extensive cross checks. However, analysis of the modeled data indicated that there is a measurable nonuniformity of the visibility of the SM points and half the number of views, which was confirmed with test data. This nonuniform distribution and sparse point density is likely to have increased the sensitivity to how changes in uncertainty distributed in the lower chamber due to different camera pointing schemes or number of lower chamber PG targets in turn changes the optimum SM position required to give the minimum random error distribution during the photogrammetric calculation. More views of the SM were required.

The behavior during the initial phase of AD testing in OGSE 1 and OGSE 2 was also consistent with an increased sensitivity to changes in the lower chamber. Precise photogrammetry relies on the assumption that the targets are in a stable position throughout the duration of the image collection. The disagreement between the predicted and measured SM position during the AD testing in OGSE 1 and OGSE 2 occurred during a period in which the hardware temperature was increasing per the test plan. The suspended configuration as a whole expands during this change in temperature thereby resulting in motions of the scale bars with respect to each other, the flight hardware and all tie points used in the V-STARS bundle. The stable assumption was not met during these periods.

The calculated movement of horizontal scale bars was 3 to $5\mu \mathrm{m}$ per meter per hour based on the change in Big Bar lengths (total change of up to $40\mu \mathrm{m}$ of length of scale bars) during a 45-min data collection. The height of the hanging configuration changed by an estimated rate of $100\mu \mathrm{m}/\mathrm{h}$ based on the average change in height of two rail targets with respect to the AOS. Even with the larger noise of the rail points compared to the scale bars (estimated values are $2\sigma =72\mu \mathrm{m}$ for the rails versus $2\sigma =28\mu \mathrm{m}$ for Big Bar points), the change is considerably larger than the estimated horizontal expansion and so not only is the hardware changing, it is changing asymmetrically.

The team believes that this instability impacted the calculated position and variability of the SM. This could have been analyzed using the DIRSIG imaging analysis tools developed prior to hardware installation but was deemed too time-consuming. With the hypothesis that the changes in temperature were the cause, the test plan was modified to include thermal plateaus, in which the data were acquired. With this change for the flight hardware test, the agreement between measured and predicted data was within the predicted test uncertainty and the observed measurement variability was also reduced to an estimated $10\mu \mathrm{m}/\mathrm{h}$ in the vertical direction.

In an effort to mitigate the sensitivity to SM position calculations inherent in the use of a single camera pointing scheme, a “combined” bundle solution was created from all 2360 images from both camera pointing schemes for critical measurements, thus providing additional images of the SM. During active OTIS testing, because of the processing time needed to create the combined bundle, a numerical weighted average was created from a sequential OTIS_ps, LOWCH_ps, and OTIS_ps collection set. As shown in Table 8, the approximation of a combined bundle with an average gives a difference 0.059 $2\sigma$ between the results—well within the measured error in absolute position of 0.086 (Table 3).

Table 8

Difference between SM position result from averaging two combined bundles and an approximation based on the weighted average of an OTIS_ps, LOWCH_ps, and OTIS_ps set.

Conditions	Date	ΔM1 (mm)	ΔM2 (mm)	ΔM3 (mm)
Ambient	7/9	−0.069	0.017	−0.025
Warm Vac	7/13	−0.025	0.043	0.011
Warm Vac	7/19	−0.077	0.007	−0.055
Cooldown	7/29	0.003	0.036	−0.008
Cooldown	7/30	−0.044	0.051	0.012
Cryo Vac	8/26	−0.051	0.028	−0.011
Cryo Vac	9/27	−0.077	0.042	0.009
	Average	−0.044	0.030	−0.013
	$2\sigma$	0.059	0.033	0.050

There was a marked increase in number of rays for the SM points with the use of the combined data (Table 9), though the visibility nonuniformity pattern was the same as it is a feature of both camera pointing schemes. The two camera schemes also collected images from different angular positions, which are known to help in bundle adjustment uncertainty. The bundle adjustment uncertainty for the SM points in the combined set approached the empirical limit, and so presumably a lower limit of sensitivity to camera pointing scheme and chamber configuration had also been reached. The combined bundles are considered to have the highest absolute accuracy because they consist of the greatest number of images and have the lowest bundle adjustment values.

Table 9

Comparison of number of rays at the SM level for the two camera pointing schemes used for data collection.

	# Rays model	# Rays OTIS_ps	# Rays LOWCH_ps	# Rays combined
SM1	194	113	196	307
SM2	284	184	285	426
SM3	159	86	124	234
SM4	285	166	264	382
SM5	196	127	159	253
SM6	104	84	158	208

DIRSIG modeled data did correctly predict the visibility nonuniformity at the SM level, but overpredicted the actual number of rays and expected relative bundle adjustment uncertainty. A lesson learned is that in future systems more scrutiny should be paid to assessing sensitivity to camera and pointing scheme of areas with asymmetric visibility to ensure that the sensitivities are within acceptable limits and that the pointing schemes adequately sample the objects from a variety of angles.

5.1.

Repeatability

To verify that the CPM variability in object and scale was the same as observed in the previous chamber tests, Big Bar and run statistics were collected. The $2\sigma$ variability of PM-Global and SM center position for runs completed during the cryo-stable test period are given in Table 10. The average $2\sigma$ for Big Bar measurements were 0.028 mm.

Table 10

Repeatability of cryo-stable measurements over several runs for PG data using averaged coordinate positions from two different camera pointing schemes. The SMM data are used as a proxy for the SMA as the SMM points did not move during alignment, but the SMA did. Values are for the entire period of cryo-stable testing (8/21-9/27/2017) and are from 11 runs. The PM-Global data are from the period 8/26-9/9/2017 when no changes to the PM position were made and are from 6 runs.

5.2.

Alignment of PM and SM

The CPM provided reliable measurement of the position of the PM and SM during alignment, which allowed for effective predictions of adjustments needed to obtain the desired positional accuracy.

Representative runs taken from 8/5/17-8/24/17 over the period of PM phasing are shown in Table 11. Note the initial jump from unaligned to close-to-predicted on 8/6. The period from 8/6-8/24 covered various moves done to phase the mirrors based on optical information from the Center of Curvature Optical Assembly (CoCOA). Note the drift from ideal and realignment back to the model as the phasing progressed.

Table 11

Difference between measured PG position of the PM center versus expected position based on optical model used during testing. PG positions are weighted average values of two different camera pointing schemes as described in Sec. 4.3.2 under “Camera pointing scheme factors.” Units are mm for M1, M2, M3, and mrad for rM1, rM2, rM3.

Detailed investigation of the cryo-shift behavior postchamber test indicated that there was a small but statistically meaningful movement of the AOS Source Plate Assembly (ASPA) Bridge with respect to the AOS baseplate consisting of a shear of 0.05 to 0.06 mm. The reference coordinate system was revalued to account for the actual position of the AOS and ASPA Bridge points. Small updates to the optical model were also made post-test. The results of the PM aligned position with respect to tolerances compared with the optical model used in-test and the final post-test revised optical model are show in Table 12.

Since the SM is a single unit, it required much less adjustment to be brought into alignment. The position at times is shown in Table 13. The SM was placed in a nominal start position on 8/21/17, and an initial alignment move was made 8/26. Examination of the large angular mismatch uncovered a unit’s error in the move prediction software, and a correction was done on 8/31. Subsequently, additional mirror changes were done based on interferometer information. Final alignment was achieved on 9/4/17.

Table 12

Comparison of PG measurements of aligned global PM position with respect to the requirements.

Table 13

Difference between measured PG position of the SM center versus expected position based on optical model. PG positions are weighted average values of two different camera pointing schemes as described in Sec. 4.3.2 under “Camera pointing scheme factors.” Units are mm for M1, M2, M3 and mrad for rM1, rM2, rM3.

Table 14

Comparison of PG measurements of aligned SM position with respect to the pass/fail tolerances.