Radar Tracking Campaigns for ESA CO-VI. European Space Surveillance Conference 7-9 June 2011

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1 Radar Tracking Campaigns for ESA CO-VI European Space Surveillance Conference 7-9 June 2011 Jordi Fontdecaba i Baig (1), Francis Martinerie (1), Moise Sutter (1), Vincent Martinot (1), Emmet Fletcher (2) (1) Thales Alenia Space, France 26, Av. Champoillon Toulouse (France) Jordi.FontdecabaBaig@thalesaleniaspace.com, Francis.Martinerie@thalesaleniaspace.com, Moise.Sutter@thalesaleniaspace.com, Vincent.Martinot@thalesaleniaspace.com (2) ESA, European Space Astronomy Centre P.O. Box, 78 E Villanueva de la Cañada (Spain) Emmet.Fletcher@esa.int ABSTRACT Following the decision at the Ministerial Council 2008 to initiate a Preparatory Programme on Space Situational Awareness, the European Space Agency has started a series of activities with the industry, implementing both classical design approaches: bottom-up and top-down. For Space Surveillance and Tracking, the bottom-up approach translates in particular into an activity in CO-VI consisting of an assessment of the existing European assets that can be used for tracking campaigns, both in low and high altitude regions. It addresses non only the technical performances of the assets but also the identification of their current operational constraints that could be in fine parts of a Service Level Agreement for their contribution in the future European SSA System. In that context, this paper presents both aspects, addressing only the radar tracking campaigns i.e. the LEO region (a similar article is written on the high altitude region). During the campaigns, the following existing European radars EISCAT and CAMRa - were used to track several satellites selected to cover a wide range of altitude and inclination in the LEO region. Two different campaigns were done to track the satellites. Orbit restitution was performed in order to characterize the role of the different observation parameters and to point out the best way to improve the orbit estimation performance with a single assets or with a combination of the different assets. This paper describes the preparation of the campaigns as well as the results obtained, with particular focus on the first campaign. The campaigns were mainly driven by the availability of radar assets and the visibilities of the satellites. The precise orbit determination enabled the comparison of the different assets performance. INTRODUCTION The objective of the SSA programme [Ref.1] is to support Europe's independent utilisation of, and access to, space through the provision of timely and accurate information, data and services regarding the space environment, and particularly regarding hazards to infrastructure in orbit and on the ground. In general, these hazards stem from possible collisions between objects in orbit, harmful space weather and potential strikes by natural objects that cross Earth's orbit. The SSA programme will, ultimately, enable Europe to autonomously detect, predict and assess the risk to life and property due to remnant man-made space objects, re-entries, in-orbit explosions and release events, in-orbit collisions, disruption of missions and satellite-based service capabilities, potential impacts of Near Earth Objects, and the effects of space weather phenomena on space- and ground-based infrastructure. Activities in the initial SSA Preparatory Programme ( ) are addressing the consolidation of requirements and the architectural study and design of the complete SSA system. But precursor SSA services will also be established through the use of existing national facilities, when possible. In parallel, essential components of the complete SSA system are being designed, including radars, sensors, networks and data centres. The programme is active in the following three main areas: Survey and tracking of objects in Earth orbit - comprising active and inactive satellites, discarded launch stages and fragmentation debris that orbit the Earth;

2 Monitoring space weather - comprising particles and radiation coming from the Sun that can affect communications, navigation systems and other networks in space and on the ground; Watching for near-earth objects - comprising natural objects that can potentially impact Earth and cause damage and assessing their impact risk and potential mitigation measures. Under the SSA Preparatory Programme, one of the objective of the Space Survey and Tracking (SST) element is to provide an independent ability to promptly acquire and catalogue precise information on objects orbiting Earth. Using these data, a wide range of services will be provided by the future European SSA System, such as warning of potential collisions and alerting when and where debris re-enters Earth's atmosphere. These data will be stored in a catalogue and made available to SSA customers across Europe. The infrastructure required to provide these capabilities is referred to as the ' SST Segment'. It comprises surveillance and tracking sensors, which could use radar or optical technology, to acquire raw data, which are then processed to correlate (or link) each observed object with the ones already known, or to indicate a new object. Initially, the SST Segment will obtain data using existing sensors. When the full SSA programme begins, additional systems may be developed and deployed as required to achieve the objective of European autonomy in this area. In that context, tracking campaigns have been conducted in the frame of the ESA CO-VI study, on satellites for which accurate orbital information exists, in order to start investigating the possibility to integrate European Sensors and data into the SSA System. The measurements gathered during these campaigns have been processed in order to assess in particular the accuracy of the data supplied by the different European assets and in the end, their interest for the improvement of orbital parameters (e.g. needed in case of a high collision probability). This information combined with other types related to availability and operational process will contribute to the reflections for the creation of the most suitable Service Licence Agreement (SLA) for the use of European Assets in the SSA system, in the next phases of the program. CAMPAIGN ORGANISATION AND EXECUTION Satellite selection LEO tracking campaigns were required to be conducted for at least 6 different LEO satellites, with LEO candidate satellites spanning an interval in inclination from at least 51 degrees to 98 degrees and in perigee altitude from 350 km to 1400 km. In reality, the majority of LEO satellites are concentrated in sun-synchronous orbits since they present particularly interesting features from an Earth Observation point of view. Because of that, it is difficult to suggest a homogeneous sampling over the specified interval. This effect is graphically presented in Figure 1. Figure 1: Characteristics of LEO satellites At the sight of the distribution, it is clear that there is a large choice among sun-synchronous spacecraft (with inclinations close to 98 degrees in LEO), but that it is not the case for the rest of inclinations. Considering that the availability of precise orbits is a sine-qua-non criterion to provide a reference for orbit restitution, the selection has been done according to the following rules: ESA satellites have been chosen in SSO orbits, ESA and Non-ESA satellites have been added in non-sso orbits to fill the gaps, Satellites have been added in this tentative list whenever access to accurate orbit data has been granted.

3 When considering these criteria, the following short list was finally obtained: SATELLITE ALTITUDE (km) INC. (deg) Agency PROBA ESA CRYOSAT ESA ENVISAT ESA JASON CNES/NASA METOP-A Eumetsat GRACE ESA STARLETTE CNES Table 1: Characteristics of the satellites tracked during the campaign Tracking radar assets Two assets were considered in the first tracking campaign, which results are illustrated hereafter: EISCAT and Cam-Ra / STFC-Chilbolton. The EISCAT Scientific Association [Ref.2] is an international research organisation operating three incoherent scatter radar systems, at 931 MHz, 224 MHz and 500 MHz, in Northern Scandinavia. EISCAT (European Incoherent Scatter) studies the interaction between the Sun and the Earth as revealed by disturbances in the magnetosphere and the ionised parts of the atmosphere (these interactions also give rise to the spectacular aurora, or Northern Lights). One EISCAT transmitter site consisting of a UHF system and a VHF system is located close to the city of Tromsø, in Norway, and additional receiver stations are located in Sodankylä, Finland, and Kiruna, Sweden. In 1996 the EISCAT Scientific Association constructed a second incoherent scatter radar facility, the EISCAT Svalbard Radar (ESR), near Longyearbyen on the island of Spitsbergen, far to the North of the Norwegian mainland. The sensor of interest for CO- VI tracking campaign is the UHF radar located in Tromso. The Chilbolton Facility for Atmospheric and Radio Research (CFARR), is an experimental meteorological remote sensing facility [Ref.3]. Scientists use Chilbolton Observatory s sophisticated radar, lidar (Light Detection And Ranging), and radiometer instruments to characterise the atmosphere by making detailed measurements of water vapour, cloud, aerosol particles and precipitation such as rainfall. These measurements are helping to improve the prediction of climate change and severe weather conditions. The Chilbolton Advanced Meteorological Radar (CAMRa) considered for the tracking campaign is an S-band dualpolarisation Doppler radar based on a fully-steerable 25 m diameter dish antenna, a magnetron transmitter, a dualchannel superheterodyne receiver, and a hybrid analogue-digital signal processor. The radar uses a digital signal processing scheme to achieve coherent-on-receive operation. The radar transmits alternately horizontally and vertically polarised pulses and receives both co-polar and cross-polar returns. Fig 2: View of the two radars used on the campaigns. On the left, EISCAT, and on the right, CAMRa Campaign chronology The first radar tracking campaign took place in late 2010, between Nov 29th and Dec 3rd. The accurate definition of the campaign time slots has accounted for each asset constraint, not only technically speaking, but also in terms of operational and contractual limitations.

4 The process to select the satellites passes of interest for the experiment has consisted in: 1. Identifying all the visibility passes. 2. Select among all the passes the passes of interest, taking into account the following constraints: Select a balanced number and of passes for all the satellites, Select a balanced number of ascending / descending passes for each object, Favor passes common to different assets, Account for visibility masks and angular rates limitation (minimum time between two passes) 3. Checking if maneuvers were planned during the observation period was done, a few days prior to the experiment. Chronologies have been defined on a day-by-day basis, for each considered object. Table 2 summarizes the observed passes per day and per satellite. Starlette was not observed by EISCAT because of its low inclination. Grace-1 was not observed by EISCAT because the radar was not operational during the passes. 29/11 30/11 1/12 2/12 3/12 4/12 TOTAL CAMRa EISCAT CAMRa CAMRa EISCAT CAMRa EISCAT CAMRa EISCAT EISCAT CAMRa EISCAT Metop-A Envisat Proba Jason Cryosat Starlette Grace TOTAL Table 2: Synthesis of the acquired passes for the two sensing assets CAMPAIGN DATA PROCESSING The Campaign Data processing has been realized in two steps: (i) analysis of data, and (ii) orbit restitution. In the following, there is a short description of each of them. Analysis of Campaign Data The goal of the data analysis is to determine their characteristics and quality, previous to the orbit restitution analysis. One of the requirements regarding the tracked satellites was the availability of current precise orbits to have a reference against which to compare the measurements. In the following, these orbits will be called operational orbits since they are given by the satellite operators. These operational orbits have been used as a reference to assess the quality of the measurements. EISCAT measurements The characteristics of EISCAT measurements are as follows: for each pass, a list of range measurements vs time is provided, at a frequency of 10 to 20 measurements per pass. There is no information on the azimuth/elevation angles, but Doppler measurements are associated to range measurements. Figure 3 shows the comparison between the ranges measured from EISCAT and those computed from the operational orbit. It also includes the comparison on the angles. The angles correspond to the TLE predictions because the radar does not provide angle measurements. The residuals correspond to the TLE accuracy and it is not radar dependent. The comparison between the ranges measured and those computed from the operational orbit show low residuals (characteristic value around 100 m.).

5 Figure 3: Residuals for EISCAT measurements on Cryosat satellite for the pass at 01/12/2010 at 17:56 CAMRa measurements The characteristics of CAMRa measurements are the following: for each pass, there is a list of range measurements (plots) vs time, given at a frequency of about 10Hz, with the associated energy for each plot. Neither Doppler nor angle measurements are available. A preliminary view of the evolution of these range measurements during the pass shows that a majority of the data are non-consistent (false alarms), especially for smaller satellites. In order to keep only representative points, a filtering has been done on CAMRa data to keep only high energy echoes, since the echoes energy is the only discriminating parameter to sort the detected plots in absence of Doppler or angle information. After filtering, the remaining data correspond to the satellite of interest, and the measurement can be compared to their equivalent computed from the operational orbit. The effect of the filtering can be appreciated on Figure 4: while before filtering the satellite data are lost in the middle of false alarms, after filtering only satellite measurements are kept. The capability to distinguish between false alarm and satellite echoes depends on the radar cross section (RCS) of the space object. Small satellites or debris have a too low RCS and can not be tracked by CAMRa asset (as it was configured during the campaign). Figure 4: Effect of filtering on range data acquired with CAMRa for Cryosat. On the left, non-filtered measurements, on the right, filtered measurement.

6 The residuals on the range exhibit a worse behaviour than with EISCAT measurements. While there is no variation on the angle residual (they correspond to the TLE accuracy), a characteristic value of the residual range is 1 km. Figure 5 shows that there is a non-constant bias on the measurement residuals. Figure 5: Residuals for CAMRa measurements on Cryosat satellite for the pass at 29/11/2010 at 17:55 Orbit Restitution The orbit restitution has been done using a classic least squares method. The used dynamical model stands for standard perturbations (gravity field, third body effect, drag, SRP, albedo). The real values of the solar activity have been retrieved from the NOAA site. The fact of having range only or range + Doppler measurements with a small number of passes spanning on a few days with important gaps between successive passes is a key point regarding the convergence of the method. This has led to perform several iterations in order to optimise the obtained results. The analyses have focused on testing the influence of following parameters: The length of the arc, The number of passes used for the restitution, The timespan between the passes, The improvement on combining EISCAT and CAMRa passes, The impact of using ascendant passes, descendant passes, or both, The role of Doppler measurements, The biais and/or parametric estimation. For the sake of brevity, the paper focuses only on most interesting results. Restitution accuracy The restitution accuracy is measured using the difference between the restituted orbit position and the operational orbit position projected in along track, across track and radial axes. In order to provide synthetic results, the distance to reference orbit is provided in RMS (root mean square) of the along-track, cross-track, radial stand-off vector between reference and determined orbit in 1 minute time steps over a 24h arc centred on the orbit determination epoch. When the orbit determination period is smaller than 24h, the RMS is calculated over the complete OD period. Table 3 shows the restitution performance using EISCAT data on two observed satellites: Cryosat-2 and Jason-2. The restitution has been performed on a 4 days arc using all available passes. Tests have shown no influence of the arc length. The accuracy is better on radial and on cross track axes than in along track axis. The results are consistent with previous studies on EISCAT facility [Ref.4]. Cryosat-2 Jason-2 Along track RMS (m) Cross track RMS (m) Radial RMS (m) Table 3: Restitution performances using EISCAT data

7 Table 4 shows examples of orbit restitution performances using CAMRa data on two satellites of the campaign: Cryosat-2 and Jason-2. The restitution has been performed on a 4 days arc using all available passes. Again, the along track axis presents an accuracy worse than the two others. The results are worse than using EISCAT data because CAMRa data contains higher errors. Cryosat-2 Metop-A Along track RMS (m) Cross track RMS (m) Radial RMS (m) Table 4: Restitution performances using CAMRa data An example of combination of the measurements from the two assets is provided in table 5 for the Cryosat-2 satellite. The restitution has been performed on a 4 days arc using all available passes. CAMRa EISCAT EISCAT + CAMRa Along track RMS (m) Cross track RMS (m) Radial RMS (m) Table 5: Restitution performances using CAMRa data The results when combining the two assets are similar to the results obtained using only the most accurate asset (EISCAT). The quality of the measurements of the two assets is too different for improving the orbit determination by combining them. Influence of the number of passes Using EISCAT tracking campaign, the impact of the number of passes used for orbit determination has been investigated. Table 6 shows the orbit determination accuracy with 1 to 10 passes spread on 3 days. For results consistency, the orbits has been propagated in order to cover the full time span for 10 passes (e.g. 76h). Nb of passes Time span (h) Along track RMS (m) Cross track RMS (m) Radial RMS (m) Table 6: Influence of number of passes on the restitution performances There is a major step when introducing a third passage, but results are not significantly improved by introducing additional passes. CONCLUSION This paper presents the scheduling and the execution of a radar tracking campaign and the processing of the obtained data. The campaign has been defined in order to allow tracking experiments on objects spanning a wide altitude vs inclination window, covering the LEO domain. Beside the assessment of the existing radar means capability to realize tracking campaigns, the important number of passes successfully recovered from the CAMRa and EISCAT have permitted to perform a parametric investigation of orbit restitution performance, considering combinations of passes over time, and over the two assets. The results show heterogeneous performance on the asset considered. CAMRa shows lower accuracy. However, foreseen improvements should help providing enhanced performances

8 Acknowledgment The campaigns have been done in the frame of the contract No /10/D/HK of the ESA SSA Preparatory Programme. The authors thank their technical officer and all the ESA staff who have participated in this contract. The authors also thank the staff of EISCAT and CAMRa assets for their kind cooperation and their availability. Finally, the authors are very grateful to all the satellite operators that have supplied the operational orbits. REFERENCES [1] ESA SSA Program: [2] The Chilbolton Advanced Meteorological Radar: CAMRa, [3] The EISCAT Scientific Association: [4] Klaus Merz, Analysis of EISCAT tracking of Envisat in May 2009, ESA Internal Memo, Ref SSA-PRE-TN OPS-GR.