Resource Scheduling with Permutation Based Representations: Three Applications

Satellites require timely tracking, telemetry, and command (TT&C) for payload operation. The ground antenna is one of the key elements that enable satellite control and payload operations. To support the operation of a large number of satellites at various orbits, operators need a network of antennas distributed around the globe, such as the air force satellite control network (AFSCN), to contact satellites at a predetermined time and location. Currently, they use large mechanically steered parabolic dishes to provide hemispherical coverage and simultaneous transmit (Tx) and receive (Rx) capabilities in support of Department of Defense (DoD) satellite operations (SATOPS) network designers used reflector antennas because of relatively low acquisition cost. The current reflector antennas used to support satellite operations are approximately 10 m in diameter and are susceptible to single point failure and long downtime for repair and maintenance. S-Band component technology provided by the cell phone industry allows an affordable electronically scanned antenna (ESA). Current SATOPS require a more efficient and flexible antenna system. The ESA can offer superior performance, operability, adaptability and maintainability for satellite operation. This paper presents the design of a TR module that can provide one transmit (Tx) and two receive (Rx) links to a satellite. The TR module is part of a dome shaped antenna that could provide multiple simultaneous ground to satellite links. This geodome antenna provide multiples simultaneous operations with pointing and acquisition taking seconds. One dome antenna can replace the capability of three AFSCN parabolic dishes. The next generation low cost TR module developed by the AFRL/Information Grid Division (IFG) and Princeton Microwave Technology Inc. for the next generation of the AF Satellite Control Network (AFSCN). The TR module differs from previous modules in Ref S.S. Bharj et al, (2000) and P.J. Oleski et al, (2004) in that it consists of a single Tx channel capable of 33 dBm of output power and two Rx channels with a gain of 30 dB per channel In addition, beam switching and on board digital control has been implemented where the Tx and Rx channels provide four-bit phase shift. In addition to the control functions, built-in test (BIT) circuits monitors the health and status of the RF devices. This function utilizes a low-power micro-controller to output digital data for each of the power and low noise amplifiers, via A/D converters. The bandwidth of the TR module has been designed to cover both the unified S-Band (USB) and satellite ground link subsystem (SGLS). The TR functions are combined at the output via a ceramic resonator diplexer comprised of a band pass-band stop filter. The control of the TR module is conducted via a single programmable logic device (PLD) controller through a DAQ computer interface. The TR module has been designed to meet the cost objective for a dome antenna with approximately 47,000 TR modules. A Td generation 78 element triangular panel of TR modules is now planned to be developed, leveraging off lessons learned from generation one. This paper describes the layout and design of the 2nd generation TR module

The Air Force Satellite Control Network (AFSCN) is a global configuration of common user and dedicated control nodes and space/ground link resources whose mission is to support space vehicle telemetry, tracking, and control (TT&C) requirements and to receive, process and disseminate mission data for a variety of operational DoD space systems. The primary space/ground link resources include 9 remote tracking stations (RTS) supporting 16 antennas that operate at S-band using the Space-Ground Link System (SGLS). A study was performed last year [1] to evaluate the capability of the current NASA Tracking and Data Relay Satellite System (TDRSS) to provide space-ground connectivity for AFSCN-supported space vehicles. The results of this study were extended this year in support of a DoD/NASA TT&C Integrated Product Team (IPT) whose purpose was to explore options available to significantly reduce cost and improve mission effectiveness through increased DoD use of TDRSS. The purpose of this paper is to report the results of these studies, which address the various technical, regulatory, and economical considerations associated with TDRSS providing support to the AFSCN.

The Air Force Satellite Control Network (AFSCN) coordinates hundreds of satellite communication requests from various users every day. Building a conflict-free schedule from a large set of satellite communication requests is a difficult problem. Human schedulers are very adept at generating high-quality solutions, usually allowing all requests to be serviced. However, this process is time-intensive and requires highly trained, experienced individuals. That is, the teams of highly trained and experienced schedulers must manually check every schedule request received. Approximately half of all requests require adjustment to remove conflicts. The US Air Force (USAF) had an interest in further automating this process. Stottler Henke worked with the USAF to develop the Managed Intelligent Deconfliction and Scheduling (MIDAS) solution, an artificial intelligence (AI) tool for automatically scheduling satellite contacts, by incorporating the experience, insights, and expertise of human schedulers. MIDAS can now automate virtually all the scheduling of the satellite communication requests for the AFSCN, allowing schedulers to apply their expertise where it is really needed. MIDAS accomplishes this with a two-stage process that first shuffles tasks within their defined constraints before carefully applying a user-definable set of business rules that allow certain constraints to be relaxed when necessary. The system provides a familiar, user-friendly interface modeled on legacy Electronic Schedule Dissemination (ESD) systems to facilitate comparison and to allow users to switch from one interface to the other with relative ease. It runs on inexpensive consumer hardware and communicates with legacy systems via a well-defined plain-text file format: raw scheduling requests are imported to MIDAS, and scheduling results can be exported back to legacy tools. MIDAS now provides Air Force planning at a level not previously possible. A viable schedule can be assembled in a matter of minutes in order to assess the impact of possible outages, events, expansion of equipment, etc., that is, MIDAS provides the ability to perform "what-if" scenarios to assess the impact of a potential event or mission change. With only a few minutes of processing, MIDAS is able to deconflict all or virtually all communications requests for a given day. MIDAS has eliminated much of the repetitive work involved in scheduling and allows schedulers to focus on other important problems. This paper provides a history of MIDAS, an overview of its architecture and the many benefits MIDAS provides; in addition to its general applicability to non-USAF satellite communications scheduling.

Many optimization problems require the use of a local search to find a satisfying solution in a reasonable amount of time, even if the optimality is not guaranteed. Usually, local search algorithms operate in a search space which contains complete solutions (feasible or not) to the problem. In contrast, in Consistent Neighborhood Search (CNS), after each variable assignment, the conflicting variables are deleted to keep the partial solution feasible, and the search can stop when all the variables have a value. In this paper, we propose a generalized version of CNS, discuss its performance according to various criteria, and present successful adaptations of CNS to three types of satellite range scheduling problems. Such problems are motivated by applications encountered by the French National Space and Aeronautic Agencies and the US Air Force Satellite Control Network. The described numerical experiments will demonstrate that CNS is a powerful and flexible method, which can be easily combined with efficient ingredients.

The Space Ground Link Subsystem provides the telemetry, tracking, and command (TT&C) functions compatible with the Air Force Satellite Control Network (AFSCN). The ranging signal is made up of a 1 mega-chip-per-second pseudo-random code, directly modulating the carrier signal using binary phase shift keyed (BPSK) modulation. The command signal is made up of three-tone frequency shift keyed signal amplitude modulation (AM). The telemetry signal is on a subcarrier, and all the three signals together phase modulate (PM) the carrier before transmission. Modulation indices in the phase modulator determine the distribution of total power among all the component signals, and it is very important to know the actual measured modulation indices to ensure link closure for the command, telemetry, and ranging signals. There are several methods used in practice but the measurement accuracy depends on the method used to measure them. In this paper, different methods used to determine the modulation indices — more specifically range modulation index (RMI) — in practice are discussed and various methods are compared. Sensitivity analysis of RMI measurement methods is also provided in the paper.

Ground-based laser momentum transfer concept for debris collision avoidance

In this paper, peculiarities of automatic range tracking of the reentering space objects (SO) are studied. These SO are detected by chirp radar. Using linear frequency modulated (LFM) signals results in so-called range-Doppler coupling, which yields a displacement of measured position from a true range of moving SO. This effect may cause tracking failure therefore we present stability boundaries of the SO tracking. In addition, accuracy characteristics of the automatic range tracking algorithms estimating motion parameters of the reentering SO are evaluated.

A foundational aspect of space domain awareness is the ability to identify and track space objects, including space object discovery and custody. This paper demonstrates the power of combining an efficient multiple hypothesis joint probabilistic data association (MH-JPDA) algorithm with a fixed-interval smoother to simultaneously track multiple space objects. For newly discovered objects, statistical initial orbit determination (SIOD) is possible with a single short optical tracklet, but results in large initial uncertainties. Combining these uncertainties with closely spaced objects can result in highly ambiguous data associations, which can lead to poor state estimates and even filter divergence. This paper invokes MH-JPDA to probabilistically update multiple tracks with multiple simultaneous observations in a sequential filter, while avoiding assigning one-to-one associations. Once sufficient information has been collected, the space objects become uniquely distinguishable among each other. Subsequently, the smoother is applied to achieve improved association of the prior observations. MH-JPDA allows for immediate track formation (using SIOD) and sequential processing of incoming observations, providing statistically rigorous real-time state estimates, whereas smoothing produces a more-refined, higher-confidence overall track estimate at user-defined intervals. This paper demonstrates this approach within the Constrained Admissible Region, Multiple Hypothesis Filter (CAR-MHF) software by tracking a simulated break-up scenario.

We propose the diffusion-based enhanced covariance intersection cooperative space object tracking (DeCiSpOT) filter. The main advantage of the proposed DeCiSpOT algorithm is that it can balance the computational complexity and communication requirements between different sensors as well as improve track accuracy when measurements do not exist or are of low accuracy. Instead of using the standard covariance intersection in the diffusion step, the enhanced diffusion strategy integrates the 0-1 weighting covariance intersection strategy and the iterative covariance intersection strategy. The proposed DeCiSpOT algorithm also uses the global nearest neighbor and probabilistic data association for multiple space object tracking. Two typical scenarios including cooperative single and multiple space object tracking are used to demonstrate the performance of the proposed DeCiSpOT filter. Using simulated ground-based electro-optical (EO) measurements for multiple resident space objects and multiple distributed EO sensors, the DeCiSpOT archived results comparable to an optimal centralized approach. The results demonstrate that the DeCiSpOT is effective for space object tracking problem with results close to the optimal centralized cubature Kalman filter.

Collision Probability with Gaussian Mixture Orbit Uncertainty

A filter for tracking non-cooperative low-thrust satellites using surveillance radar data

The number of launches and objects in space has been growing fast in the last few years, particularly due to the growth of satellite mega-constellations. Defunct satellites and other space junk products collide and create a collisional cascade of smaller space debris. Space debris ablates and burns up in the atmosphere upon re-entry and thereby metals and rare materials are injected, some of which already exceed the natural input of exogenous material today.Quantifying the influx of these anthropogenic materials into the atmosphere is essential to address the possible environmental consequences, through constraining the physico-chemical atmospheric models. This quantification can be done using catalogs of spacecraft being launched, but not all manufacturers provide these data. Small micro-debris can be used as tracers of their larger counterparts through the collisional cascade, which would complement these existing catalogs, for the inventory of elemental compositions of human-made materials in Low EarthOrbit that will re-enter in the atmosphere.We propose in situ measurements of sub-micrometer and micrometer sized particles as tracers of the larger space debris, using in situ mass spectrometers with a velocity grid, that were originally designed for cosmic dust measurements.These instruments can measure the elemental composition (impact-speed dependent), mass distribution, surface charge, impact velocity vector, and time-resolved fluxes of dust and debris particles. Moreover, measuring the natural cosmic dust flux itself is necessary as a benchmark for the debris.In this talk we introduce in situ cosmic dust measurements in the past, the different measurement methods, and measurements of micrometer-sized space debris so far with “active” (time-resolved) and “passive” (sample return) methods. We elaborate on the particles we can expect to measure in orbit, and the science goals to be achieved through such measurements that are useful for both the assessment of the anthropogenic influx into the atmosphere and for space debris research in Low Earth Orbit. Elemental composition measurements of these micro-debris particles, combined with orbital velocity and location data, offer a new avenue for quantifying the chemical influx of anthropogenic material into Earth’s atmosphere, and for assessing more thoroughly the broader space debris populations.

This article investigates the satellite constellation scheduling problem for noncooperative space-object tracking. Different from the traditional Earth observation tasks, space-object tracking tasks require observation of fast moving targets that may have unpredictable trajectories, and estimation of the position of the targets through cooperative observation of multiple satellites. An agent-based scheduling framework is proposed to enable real-time, distributed scheduling of low Earth orbits constellation satellites for tracking noncooperative space targets. In the proposed framework, a nonlinear filtering of the targets’ trajectories is incorporated, and the observation satellites are dynamically allocated according to the status of the satellites and the states of the noncooperative targets. Specifically, event triggers of tracking space targets for activating task handover among satellites are defined and classified into five categories. The event-trigger processing and task response mechanism are embedded in the proposed scheduling framework. Thereafter, autonomously adjusting the observation-satellite sets can be achieved through distributed negotiation within only a few satellites. The effectiveness of the proposed method is validated by simulating scenarios of tracking targets without or with maneuvers.

Space Debris Mitigation

Space activities are continuously at risk due to the ever-increasing amount of uncontrolled space objects, called space debris, which can collide with operational spacecraft. Therefore, space agencies have started space situational awareness (SSA) programs, which aim to provide timely and accurate data regarding the space environment and hazards to infrastructure in orbit and on the ground. An essential need for SSA is the orbit determination of as many space objects as possible, in order to predict and prevent collisions. In this work, techniques for orbit determination of objects observed on short arcs are developed. This scenario frequently occurs with space debris, which are characterised by long observational gaps due to observability constraints. The classical least squares method, used for orbit determination, is revisited by studying the effect of nonlinearities in the mapping between observations and state. Differential algebra techniques are exploited, which enable the computation of high-order Taylor expansions of the residuals with respect to the state. Approximations of differential correction methods can then be avoided and the confidence region of the solution accurately characterized with a nonlinear approach. This uncertainty region can be reduced when more observations of the same objects are acquired. Thus, a method that both recognizes associated observations and sequentially reduces the solution uncertainty when two or more sets of observations are associated is proposed. The six dimensional ($6D$) association problem is addressed as a series of $2D$ and $4D$ problems to alleviate the computational cost. In case of successful association, part of the initial uncertainty is pruned away. The least squares solution and its uncertainty region can finally be used to initialize a sequential filter. A particle filter is implemented using differential algebra, so that system and measurement equations are substituted by polynomial evaluations and the resulting computational cost of the algorithm is alleviated. A population-based stochastic optimizer, the multiobjective particle swarm optimizer, is exploited to generate particles that best represent the probability distribution over solution orbits.