Small Aperture Telescope Observations of Co-located Geostationary Satellites

Transcription

1 Small Aperture Telescope Observations of Co-located Geostationary Satellites Robert (Lauchie) Scott Defence R&D Canada -Ottawa, Ottawa, Ontario, Canada, K1A 0Z4, Dr. Brad Wallace Defence R&D Canada -Ottawa, Ottawa, Ontario, Canada, K1A 0Z4, ABSTRACT Co-location is a geostationary orbit formation strategy where two or more satellites reside within one station keeping box. As geostationary orbit continues to be populated, satellite operators are increasing usage of co-location techniques. Colocation causes the participants to move in relative motion ellipses about each other with typical separations varying from 1 to 100 kilometres. This paper focuses on correlation effectiveness on co-located geostationary satellites as their close proximity to one another is a challenge for ground-based space surveillance sensors. During the course of this study we identify two unique observational events where co-located satellites close proximity causes problems for ground based sensors. The satellites sometimes appear to conjunct which makes discrimination by automated space surveillance systems difficult. During these conjunctions, if one of the satellites is more optically reflective than the other, the possibility exists that it will glint-mask the fainter satellite under small phase angle conditions, further making its detection difficult. 1. ITRODUCTIO An issue encountered with automated optical space surveillance systems is satellite identity discrimination while observing closely-spaced geostationary (GEO) satellites. These systems can unintentionally mistag the identity of the objects they are tracking due to uncertainties in the predicted locations of the satellites. A more acute case is satellite orbital co-location which is gaining popularity with satellite operators to populate more capacity in geostationary orbit. Co-location is a GEO orbit formation strategy where two or more satellites reside within one geostationary longitude box [1]. As of this writing there are 48 satellites in 22 co-located groupings in GEO. Canada currently co-locates 6 satellites as 3 co-located pairs. The Luxembourg operator, SES, once co-located six satellites [2] in one longitude slot and currently has 3 co-located clusters. The satellites are often separated by less than 0.05 degrees of longitude and this close proximity between the satellites strains the accuracy of the general perturbation orbital elements used to predict their orbits and to correlate the identities of the satellites in optical systems. In a more extreme case, co-located satellites sometimes appear to conjunct. The actual physical separation may be tens of kilometers or more (more than enough to safeguard against collision) but the apparent angular extent of the satellite separation is small when observed by a ground-based observer. Under certain conditions it can become impossible to detect two individual objects on the field of view as the two satellites appear to merge on the image plane. For large geostationary satellites, CCD (Charged Couple Device) imager saturation is a possibility as the combined visual magnitude of the objects can sometimes exceed the well depth of limit of an optical CCD sensor performing metric measurements. In another case, two co-located satellites with largely different optical cross sections can cause glint-masking effects which can effectively mask the presence of the other satellite on a CCD imager. This paper seeks to characterize correlation effectiveness of a Ground Based Optical Sensor on co-located satellites using the DRDC Ottawa Space Surveillance Observatory [3]. The following sections provide a brief overview of geostationary orbital parameters and how geostationary co-location is performed. Relative motion of co-located satellite motion is described, and an analysis of measurements taken by a small ground based telescope is then presented. A check of the effectiveness of the correlation approach used to differentiate the satellites is investigated and results presented. We show that correlation is practical with relatively current orbital element sets on these objects but changes to the existing correlation algorithm in use by DRDC is required to further enhance its accuracy. Special cases are also shown where colocated satellites perform unique space surveillance events when detected by CCD imagers. Co-located satellites result in unique observational events as well. A visual conjunction (objects appearing to merge on the CCD imager) and glintmasking event where one object overwhelms the other due to one objects high reflectivity were both detected on closeformation co-located satellites. 2. GEOSTATIOARY SATELLITES AD CO-LOCATIO The International Telecommunications Union (ITU) assigns geostationary orbital longitude slots to satellite operators to maintain frequency management of the GEO orbit resource [4]. The ITU typically assigns a station keeping box of ~0.1 degrees in longitude and latitude, with approximate dimensions being 74 x 74 x 35 km. In practice, new geostationary satellites maintain station within 0.05 degrees of longitude and latitude and limiting dead bands are used to help prevent orbital box violation.

2 Latitude (β) ~0.1 Nimiq-1 Galaxy-11 Stationkeeping box 2 (unused) Co-location DirectTV-1 Long (λ) Fig. 1 Geostationary satellite station keeping boxes with imagery showing Galaxy 11 (left on image) and the co-located imiq-1, Direct TV-1 group (center of image) Geosynchronous orbital elements are linearized [1] Keplerian elements used for describing near circular geostationary satellite orbits. The primary parameter of the geostationary orbit is the semi major axis parameter (a GEO ) which is equivalent to 42,164.5 km. The offset of the geostationary satellites orbital semi major axis size (a), above or below a GEO is expressed as equation 1. δ a a a GEO a 42,164.5 km (1) = GEO ( ) Since the orbital inclination and eccentricity are near zero, the eccentricity and inclination vectors can be expressed as projections onto Earth s equatorial plane as equations 2 and 3 respectively. e = ω, T [ e cos( ω+ω), esin( +Ω) ] = [ e e ] T x y i =, T [ i cos( Ω), i sin( Ω) ] = [ i i ] T Where e and i are the eccentricity (dimensionless) and inclination (degrees) parameters for the geostationary orbit respectively. The parameter ω is the argument of perigee and Ω is the orbit s right ascension of the ascending node. The eccentricity vector points towards the location of orbital perigee and the inclination vector is a projection of the geostationary satellite's inclination vector onto the equatorial plane. The longitude drift rate (D) of a geostationary satellite with a semimajor axis above of below that of a GEO is expressed as equation 4. x y (2)(3) D= 1.5 δa a GEO (4) The co-location of two or more satellites in the same geostationary longitude slot requires management of the risk of collision between the co-located GEO peers. This encourages a separation approach for the formation. Geostationary satellites with suspended solar panels that experience an impact with as little as 1 m/s velocity could be very destructive [1]. The separation strategy normally used for co-located satellites uses combined offsets between the pair s eccentricity and inclination vectors [1][5]. A relative motion ellipse is then formed where in-track position uncertainties of the satellites are aligned nearly perpendicular to the relative motion of the two spacecraft (fig. 2). This elegantly places the much higher precision components of radial and cross-track uncertainty in a direction that helps maintain separation between the satellites. The ellipse's shape can be estimated by determining the differences between each satellite's geostationary elements. The eccentricity and inclination vector differences, e and I are shown as equations 5 and 6 respectively. These parameters establish the geometric shape of the relative motion ellipse. e = ei e j I = ii i j The two satellites are forced to stay within close proximity to one another therefore the relative drift rate between the satellites is near zero (equation 7). In practice, real orbital operations incur maneuver errors and small drift rates are observed but the drift tends to be small between the co-located members. Hence a longitude offset between the two colocated satellites is preserved between the spacecraft. D D D 0 (7) = i j (5)(6)

3 A In-track Apparent group orbit A cross-track radial B B Apparent object motion in cluster Co-located GEO orbits with inclination and eccentricity offsets Apparent orbit and apparent relative motion inside the colocated group. Fig. 2. Colocated satellite motion. As the satellites are in near circular orbits, the size of the relative motion ellipse can be estimated by computing the following radial, in-track and crosstrack values relative to an arbitrary "primary" satellite in the co-located group. It should be noted that in normal space surveillance tasking, one object is tracked when tasked and the telescope tracks the tasked object, not both satellites in the co-located group. Therefore, the other co-located member would appear to move relative to the tasked satellite during tracking. RadialGEO = 2aGEO e IntrackGEO = 4aGEO e Crosstrack = a GEO I The in-track ellipse size is twice the radial separation size due to the eccentricity offset [6]. The size of the relative motion semi minor axis can be approximated by equation 11. (8) (9) (10) CA size = a GEO e + I (11) Crosstrack Crosstrack Intrack 2D Radial Fig. 3.Relative motion ellipse radial, in-track and crosstrack motion directions. The separation between the spacecraft is the linear distance using the separation of longitudes λ is expressed as equation (12) IS = λ (12) a GEO The satellite peer can appear to "orbit" a location not around the primary satellite if there is considerable difference between the mean longitude of the satellites. This usually takes place if the longitudes of the satellites are offset by a distance larger than the in-track size. A useful ratio to identify this is the ratio of the longitude separation to the in-track ellipse size, termed IR.

4 IR = IS λ = Intrack GEO 4 e (13) IR ratios greater than 1 indicate that the satellites undergo collocated motion where the relative motion ellipse forms externally to the primary object. IR ratios less than 1 indicate that the peer orbits about the primary satellite. 3. CAADIA GEO SATELLITE CO-LOCATIO GEOMETRY SUMMARY Canadian geostationary co-located satellite geometry is shown in Fig 4 and Fig 5. It is seen that the co-located Canadian satellites are in relatively tight formation where the relative motion ellipses are ~ km in size. The co-located motion has in-track (IR) ratios less than one hence the objects tend to normally orbit the primary satellite. Note that Direct TV-3 was repositioned in March 2009 which shows as growth in the ellipse size at that time. A 20 km separation at 40,000 km range is approximately 103 arcsecond as observed from the ground. Relative Motion Ellipse Size (km) Relative Motion Ellipse Size Co-located Canadian Satellites ( ) Anik F1, Anik F1-R Nimiq-2, DirectTV-3 Nimiq-1, DirectTV-1 0 Nov 2007 Feb 2008 Jun 2008 Sep 2008 Dec 2008 Mar 2009 Jul 2009 Fig. 4.Relative motion ellipse size for co-located Canadian satellites. Most objects maintain 20km and greater ellipse sizes. Date IR Ratio (dimensionless) Intrack Ratio Co-located Canadian Satellites ( ) Anik F1, Anik F1-R Nimiq-2, DirectTV-3 Nimiq-1, DirectTV Nov 2007 Feb 2008 Jun 2008 Sep 2008 Dec 2008 Mar 2009 Jul 2009 Fig. 5.In-track Ratio (IR) for co-located Canadian satellites. Most Canadian objects "orbit" around the other satellite in the co-located group. Date 4. GROUD BASED OPTICAL CORRELATIO ALGORITHM The Ground Based Optical Correlation algorithm was designed by DRDC Ottawa to minimize mistags on deep space objects which fall into clustered groups. When an image is processed by the image processor, a snap propagation of the entire SSN (Space Surveillance Network) elset catalog is performed over the time span of the image being processed. Each object detected in the image is assigned a coordinate (RA,DEC) pair and objects falling within a 1 degree angular radius are

5 considered as candidates for tagging. The algorithm then performs a nearest neighbour matching, where objects with the smallest angular separation between measured and predicted locations are selected. High confidence matches are normally found when the match is found within 400 arcseconds between detected and predicted object locations. Each object detected in the CCD image is tested against the predicted satellite positions independently (Fig 6.) Fig. 6.Correlation processes (not to scale) - each detected object is checked against the predicted positions (red crux) of nearby objects in the SS catalog. In this case, (imiq-1) would be tagged as it is the nearest-neighbor is not considered as it is external to the 1degree candidate radius. 5. CO-LOCATED SATELLLITES OBSERVED Data for this study was collected using the DRDC Space Surveillance Observatory [3] located in Ottawa, Ontario. Images were collected in rate-track mode where the telescope tracks the satellites at the rate which they move across the sky. Once each 4-second exposure image is acquired, it is immediately transferred to DRDC Ottawa for automated processing by the Semi Quick Intelligent Detector (SQUID) [3] image processing algorithm. The Canadian geostationary satellites observed and their co-located peers are listed in table 1. Data were collected on 24, 25 February 2008 and 17 Mar 2008 Table 1. Co-located Canadian Satellites and Peers Primary Co-located Peer Long. (deg W) Nimiq 2 (27632) Direct TV-3 (23598) 82.0 Nimiq 1 (25740) Direct TV-1 (22930) 91.2 Anik F1 (26624) Anik F1-R (28868) MEASUREMETS All datasets have data blackouts where the geostationary satellites entered eclipse. The data is displayed using Right Ascension as the primary coordinate between all measurements. Right ascension clocks proportionally with time as the GEOS orbit the Earth thus, right ascension serves as a convenient independent variable when combining brightness and position plots for co-located satellites. Examples of the data analysis are shown as Figs 7-9 and show visual magnitude of each satellite, followed by declination and SGP4 residuals. The declination plot shows the measured position of the tagged satellites. Conjunction locations are implied where the two declination curves cross each other. This location does not necessarily indicate that the two satellites are occulting each other as they may be separated by a small angle in right ascension. The last plot is the residuals between the measured J2000 satellite positions relative to the predicted topocentric SGP4 (Simplified General Perturbation) position. This information is a relative indicator of the quality of matching between the element set and its actual measured position on the sky.

6 Small insets are also shown on each figure with reference predicted positions of the observed satellites indicated by the yellow dot. The reference predicted positions are propagated using SGP4 and plotted using TheSky6 TM software. The star streaks in each frame are a relative indicator of angular size. As each exposure was 4 seconds duration, the streak length is approximately 60 arcseconds. Each plot has the true identity and position of each satellite marked as a callout to help identify which object is which on the plots and on the image insets. 7. DATA AALYSIS The percentages of correct tagging of the co-located satellites for the primary and secondary objects are shown as percentages in table 2. The colour indicators indicate the relative success of the correlation algorithm. Green is good performance (>90%) tagging, yellow (50% - 89%) moderate and red indicating datasets that were tagged with less than 50% accuracy. There is a weakness in the nearest neighbour correlation algorithm when the predicted satellite positions are offset, in-track, from the measured positions of the satellites (Fig. 10). This caused entire datasets to be mistagged during the tracks on the Nimiq-1 and Direct TV-1 group (e.g. Fig. 8). The correlation algorithm assigned the nearest object's identity (25740) to both objects as it was the nearest object to detections. In general, it was observed that the measured satellite positions are offset by ~100 arcseconds or more in-track of the predicted positions. The average age of the reference orbital elements used for correlation averaged 2.4 days. A small bias appears as the elsets for 24 and 25 February 2008 were unchanged as no new elsets were published at that time. The lowest aged elset, Anik F1- R on 17 March, had peak correlation size of 40 arcseconds showing excellent agreement with the measured positions of the satellites. A weak dependence on elset age and maximum correlation residual was observed where the difference between measured position and elset position changed by ~40 arcseconds per day of elset age. Table 2. Ground Based Optical Correlation Performance on Co-located Canadian Satellites 2008 Observations Tagging Effectiveness (Primary /secondary) Reference Elset Age(d) Peak Separation before Mistag (arcsec) CA Size (km) Intrack separation (km) imiq-2 / Direct TV-3 24 February 24% 91% February 100% 73% March 100% 100% imiq-1 / Direct TV-1 24 February 93% 8% * * February 100% 0% * * March 100% 0% * * Anik F1 / Anik F1-R** 24 February 70% 100% February 76% 100% March 99% 100% * indicates object was correlated with wrong element set ** SSN catalog has suspected embedded mistag where Anik F1 and Anik F1R have been swapped IR Correlation Effectiveness Overall the correlation algorithm performed well as the predicted positions of the satellites were relatively well matched to the measured positions for the co-located clusters. Often, it was observed however that the algorithm would begin a track well correlated, but as time progressed, it degraded as the predicted reference satellite s position lost consistency with the shape of the co-located cluster (Fig 9). The Nimiq-1 cluster (Fig 8) showed an entire dataset which blanket mislabeled Direct-TV1 as Nimiq-1. This occurred as Nimiq-1 s predicted position was closest to both satellites for the entire duration of the tracks. Similar behaviour was also observed in the datasets for Anik F1 and Anik F1R. A recurring event that was noted was that the elsets were usually offset (Fig. 10) by a lag in right ascension of ~100 arcseconds and ~100 arcseconds or more in declination. The correlation algorithm did not handle this offset very well and the nearest neighbour approach mistagged both satellites with the nearest object. It is of note that the general arrangement of the two objects was well preserved, but the offset in right ascension caused the correlation algorithm to fail. A future iteration of the correlation algorithm is already under consideration which would perform a least squares fit to the residuals to ignore this offset's effect and preserve the arrangement of the satellites when tagging them.

7 6 7 Nimiq-2, Photometry 17 Mar 2008 Data Timespan(UTC) Cluster peer(s) Conjunction separation (arcsec) 17-Mar 08 00:05 17-Mar 08 10:21 Nimiq-2 Direct TV-3 80" 8 9 Propagated linear separation 9.3 km Mv Nimiq Right Ascension Nimiq-2, Measured J2000 RA,DEC 17 Mar Declination (deg) Nimiq Nimiq-2, Measured - SGP4 Positions 17 Mar Residuals (arcsec) Nimiq Fig. 7.imiq-2, Direct TV-3 17 Mar 2009

8 6 Nimiq-1 (25740), Direct TV-1 (22930) Photometry 25 Feb 2008 Data Timespan(UTC Cluster peer(s) Conjunction separation (arcsec) 25 Feb :25 25 Feb :36 Nimiq-1 Direct TV-1 60" 7 8 Propagated linear separation 4.5 km 9 Mv Nimiq Nimiq-1 (25740), Direct TV-1 (22930) J2000 RA,DEC 25 Feb Declination (deg) Nimiq-1 Nimiq-1 (25740), Direct TV-1 (22930) - SGP4 Positions 25 Feb Residuals (arcsec) AngSep Nimiq Fig. 8.imiq-1, Direct TV-1

9 Anik F1 (26624), Anik F1R (28868) Photometry 24 Feb 2008 Data Timespan(UTC Cluster peer(s) 17-Mar :12 17-Mar :21 Anik F1-R/Anik F1 Mv Conjunction separation (arcsec) Propagated linear separation km Anik F1-R Photo acquired at RA=4.5h Anik F1 (26624), Anik F1R (28868) Measured J2000 RA,DEC 24 Feb Declination (deg) Anik F1-R Anik F1 (26624), Anik F1R (28868) Residuals Measured - SGP4 Positions 24 Feb Residuals (arcsec) AngSep AngSep Anik F1-R Fig. 9.Anik F1, Anik F1-R

10 Fig. 10. Stressing cases for the nearest neighbour matching algorithm. The algorithm would be successful on the frame on the left, however both objects would be mistagged as Direct TV-3 on the right as it is closest to both detected objects. An improved correlation approach would need to handle the offset condition that was frequently seen for the co-located satellites. Visual Conjunctions and Glint Masking Anik F1 and Anik F1R maintain a tight co-location formation within ~ 40 kilometres of each other and this resulted in unique events on 24 and 25 February Both satellites appeared to close within 20 arcseconds of each other while the satellites were at minimum phase angle while just exiting Earth s shadow. When both objects re-entered direct sunlight, the sensor recorded a merged elongated object and was ignored by the image processor as a star streak. The site seeing conditions were ~4 arcseconds causing the bright pixels to pass the image processor threshold, and merged the two objects together. Fig. 10. Visual conjunction of Anik F1 and Anik F1R. Left both satellites while they were partially illuminated in penumbra. Center objects after exiting Earth s shadow, Right Anik F1 and Anik F1R two hours later. A visual conjunction occurred near minimum phase angle where a glint was observed from Anik F1. The imagery shows that Anik F1 overwhelmed the signature of Anik F1-R while in close proximity to one antoher (Fig. 11) and again a large, saturated object was detected along with blooming streaks at ~Mv 5.6. This effectively masked the presence of Anik F1-R to the SQUID detection algorithm. The saturated object would provide unreliable metrics as centroiding would be difficult and separating the positions of the two objects is not possible with the current system. The sun s declination at the time of observation did not suggest that a specular glint condition was occurring off the main panels. It is possible that a specular reflection off another part of Anik F1 was occurring at that time. A possible prevention mechanism of this is to avoid observing these satellites when their phase angles are below 20 degrees. 7:17 39 arcsec separation 7:22:43, 35 arcsec separation Mv 6.0 7:27:55 34 arcsec separation, Mv 5.6 Mv 7.6, Mv 9.3 (measured) Fig. 11. Glint mask event where Anik F1 overwhelms the nearby signature of Anik F1-R.

11 8. COCLUSIO We find that the nearest neighbour correlation algorithm using predicted positions of the satellites against detected positions worked relatively well on co-located satellites. It was noted that there were frequently recurring offsets between predicted and observed satellite positions and this was not well handled by the correlation algorithm. Often it is seen that co-located satellites' relative geometry was relatively well matched with the detected positions of the satellite, but the 100 arcsecond offset caused the correlation algorithm to mistag both satellites with the closest predicted object s identity. Inherently, the element sets do a relatively good job predicting the arrangement of the satellites, but not their precise positions on the image plane. Visual conjunctions were observed on Anik F1 and Anik F1-R where sensor seeing conditions resulted in elongated object formation on the CCD detector and the objects were ignored by SQUID. An extreme case of a visual conjunction was observed where Anik F1 glint-masked Anik F1-R. Anik F1 began reflecting a large amount of sunlight back toward the sensor while in close proximity to Anik F1-R. The observed, merged, saturated object was also ignored by the SQUID processor due to blooming streaks and size of the merged object on the detector plane. The combined visual magnitude of the merged object was in excess of Mv 5.9 and rendered Anik F1-R undetectable by sensor. Follow-on studies should consider expanding the number of co-located satellites after adjustments to the correlation algorithm have been performed. Follow on studies should also compare the tagging effectiveness with both co-located satellites and neighbouring geostationary satellites residing within their own station keeping boxes. A more advanced detection algorithm to split adjacent satellites during visual conjunctions would also be of benefit. A useful test of this new algorithm would be to determine the effectiveness of centroiding two closely spaced, bright objects of different relative intensities to help address the glint masking issue as well. 9. FUTURE COSIDERATIOS FOR SPACE SURVEILLACE As the geostationary belt further continues to be populated it is likely that co-location will be employed more often, hence, some of the problems observed in this paper could be observed more frequently for automated optical sensors. Smaller satellites are beginning to be used in GEO (e.g. Orbital s Star-1 bus [11]) therefore colocation will not only be a problem of independently detecting two large, bright objects but smaller, fainter objects. The success of the Orbital Express rendezvous mission [12] suggests that autonomous satellite refuelling and repair may become a reality. This would create a new paradigm for optical deep space Surveillance where monitoring of geostationary client satellites and manoeuvrable servicing satellites would cause problems for tradition metric sensors as relative motion between client and servicer would come within 1 km of each other making the visual conjunction cases even more problematic. Traditional correlation techniques using two line orbital elements would face significant challenges if these services became common. 10. REFERECES 1. Soup, E.M., "Handbook of Geostationary Orbits", ESA Space Technology Library, Wauther, P., Francken P., Laroche, H.., Co-location of Six Astra Satellites: Assessment after one year of operations, European Space Agency, 1997 ESASP. 3. B. Wallace, The DRDC Ottawa Space Surveillance Observatory, AMOS Technical Conference 2007, September Burlton,B., et al., Orbital Mechanics and Space Control, [Course Notes - MECH 5105], Carleton University, September M. Eckstein, C. Rajasignh, P. Blumer., Co-location Strategy and Collision avoidance For the Geostationary Satellites at 19 Degrees West, Space Dynamics, CES, November Vallado, D., "Fundamentals of Astrodynamics and Applications, Second Edition", Space Technology Library, Scott, L., Wallace, B., "Small Aperture Optical Photometry of Canadian Geostationary Satellites", Canadian Aeronautics and Space Institute CASI, ASTRO 2008, Montreal, Quebec, April Payne, T., et al. SSA Analysis of GEOS Photometric Signature Classifications and Solar Panel Offsets, AMOS Technical Conference 2006, Maui HI. 9. Floherer, T., Krag., H., Klinkrad., H., Assessment and Categorization of TLE Orbit Errors for the US SSN Catalogue, Proceedings of the 2008 AMOS Technical Conference 2008., Maui HI. 10. Africano, L., Kervin, P., Sydney P., Lambert., J., Deep Space Optical Brightness Catalog, AMOS Technical Conference Richmond, C., "The Growth of Orbital Sciences and the Market for Small GEO Satellites", SJR, No. 55 April/May Mulder., Orbital Express Autonomous Rendezvous and Capture Flight Operations Part 1 or 2: Mission Description, AR&C Exercises 1,2 and 3, Spaceflight Mechanics Meeting 2008., Galveston TX