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Method of computing control signals to aim antenna based on predictive control-and-estimation algorithm that takes advantage of control inputs. Conceived for controlling antenna in tracking spacecraft and celestial objects, near-future trajectories of which are known. Also useful in enhancing aiming performances of other antennas and instruments that track objects that move along fairly well known paths.
Recent advances in spacecraft tracking, chronometry, ephemerides, and orbit and trajectory determinations are reviewed. Improvements in timekeeping are reviewed, as well as precision distance and range measurements; orbit determinations, trajectory-correction maneuvers, flight path optimization, and information provided by rotation of the tracking station with the earth's surface. Doppler and tropospheric wave propagation effects are dealt with. Nongravitational perturbations (solar radiation pressure, release of gases from the spacecraft, stochastic unmodeled accelerations and sequential estimation to cope with them), the effect of the target planet's gravitational field upon close approach, and navigation problems in the outer reaches of the solar system (TV data telemetered back for inertial navigation) are covered. By-products of the research include: refined data on the mass of planets, on planetary mass distributions, planet configurations, on physical properties of the atmospheres and ionospheres of planets, and opportunities for refined tests of gravitation and relativity theories and models.
The Level-4 Prepass Readiness Test (PRT) (the load and go countdown) provides an effective and low risk method of improving network productivity. A carefully controlled trial period preceded the full-scale application of the Level-4 PRTS to Pioneer, Helios, and Viking cruise tracking operations. Use of this load and go concept to count down a station brings about a substantial increase in the proportion of total station hours devoted to spacecraft tracking.
The National Aeronautics and Space Administration's (NASA) Marshall Space Flight Center (MSFC) in Huntsville, Alabama will launch the Gravity Probe B (GP-B) space experiment in the Fall of 2002. The GP-B spacecraft was developed to prove Einstein's theory of General Relativity. This paper will provide an overview of the GPB mission and will discuss the design, and test of the spacecraft Tracking, Telemetry and Control (TT&C) subsystem which incorporates NASA's latest generation standard transponder for use with the NASA Tracking and Data Relay Satellite System (TDRSS).
Description of an automatic phase control receiver for tracking interplanetary spacecraft
The various activities for which the Venus Station's 26 m antenna was used are described and the number of manned tracking hours devoted to each activity are given. A brief description of the goal of each activity supported is provided, and, where appropriate, the observing technique is summarized. Projects involving spacecraft tracking, advanced systems development, and radio astronomy are included.
With three complexes spread evenly across the Earth, NASA’s Deep Space Network (DSN) is the primary means of communications as well as a significant scientific instrument for dozens of active missions around the world. A rapidly rising number of spacecraft and increasingly complex scientific instruments with higher bandwidth requirements have resulted in demand that exceeds the network’s capacity across its 12 antennae. The existing DSN scheduling process operates on a rolling weekly basis and is time-consuming; for a given week, generation of the final baseline schedule of spacecraft tracking passes takes roughly 5 months from the initial requirements submission deadline, with several weeks of peer-to-peer negotiations in between. This paper proposes a deep reinforcement learning (RL) approach to generate candidate DSN schedules from mission requests and spacecraft ephemeris data with demonstrated capability to address real-world operational constraints. A deep RL agent is developed that takes mission requests for a given week as input, and interacts with a DSN scheduling environment to allocate tracks such that its reward signal is maximized. A comparison is made between an agent trained using Proximal Policy Optimization and its random, untrained counterpart. The results represent a proof-of-concept that, given a well-shaped reward signal, a deep RL agent can learn the complex heuristics used by experts to schedule the DSN. A trained agent can potentially be used to generate candidate schedules to bootstrap the scheduling process and thus reduce the turnaround cycle for DSN scheduling.
A digital signal-processing algorithm has been devised as a means of aligning (as defined below) the outputs of multiple receiving radio antennas in a large array for the purpose of receiving a desired weak signal transmitted by a single distant source in the presence of an interfering signal that (1) originates at another source lying within the antenna beam and (2) occupies a frequency band significantly wider than that of the desired signal. In the original intended application of the algorithm, the desired weak signal is a spacecraft telemetry signal, the antennas are spacecraft-tracking antennas in NASA s Deep Space Network, and the source of the wide-band interfering signal is typically a radio galaxy or a planet that lies along or near the line of sight to the spacecraft. The algorithm could also afford the ability to discriminate between desired narrow-band and nearby undesired wide-band sources in related applications that include satellite and terrestrial radio communications and radio astronomy. The development of the present algorithm involved modification of a prior algorithm called SUMPLE and a predecessor called SIMPLE. SUMPLE was described in Algorithm for Aligning an Array of Receiving Radio Antennas (NPO-40574), NASA Tech Briefs Vol. 30, No. 4 (April 2006), page 54. To recapitulate: As used here, aligning signifies adjusting the delays and phases of the outputs from the various antennas so that their relatively weak replicas of the desired signal can be added coherently to increase the signal-to-noise ratio (SNR) for improved reception, as though one had a single larger antenna. Prior to the development of SUMPLE, it was common practice to effect alignment by means of a process that involves correlation of signals in pairs. SIMPLE is an example of an algorithm that effects such a process. SUMPLE also involves correlations, but the correlations are not performed in pairs. Instead, in a partly iterative process, each signal is appropriately weighted and then correlated with a composite signal equal to the sum of the other signals.
The NASA Deep Space Network (DSN) is a world class spacecraft tracking facility with stations located in Spain, Australia and USA, serving Deep Space Missions of many space agencies.
The organization of the NASA Deep Space Network (DSN), a network of tracking station control and data handling facilities, is briefly reviewed. It has been designed, constructed, maintained, and operated by the Jet Propulsion Laboratory at California Institute of Technology in support of NASA lunar and interplanetary flight programs. Some important technological and organizational advances made by DSN since the early development of spacecraft tracking in the 1950s are considered.
Data from scientific and application satellites managed by the NASA Goddard Space Flight Center are acquired through the world-wide Spacecraft Tracking and Data Network (STDN). These data are forwarded to a central telemetry data processing facility whose primary objective is the timely provision of the data to users in a form suitable for their analysis. In a successful evolution, a satellite data processing facility must adapt to changing support requirements while operationally supporting active spacecraft. Advances in the technology of data transmission, data storage systems, and file management make it feasible to implement a third-generation system which will be able to satisfy experimenter requirements for the next ten years.
The CHAMP (Challenging Minisatellite Payload) mission's unique combination of sensors and orbit configuration will enable unprecedented improvements in modeling and understanding the Earth's static gravity field and its temporal variations. CHAMP is the first of two missions (GRACE (Gravity Recovery and Climate Experiment) to be launched in the later part of '01) that combine a new generation of GPS (Global Positioning System) receivers, a high precision three axis accelerometer, and star cameras for the precision attitude determination. In order to isolate the gravity signal for science investigations, it is necessary to perform a detailed reduction and analysis of the GPS and SLR tracking data in conjunction with the accelerometer and attitude data. Precision orbit determination based on the GPS and SLR (Satellite Laser Ranging) tracking data will isolate the orbit perturbations, while the accelerometer data will be used to distinguish the surface forces from those due to the geopotential (static, and time varying). In preparation for the CHAMP and GRACE missions, extensive modifications have been made to NASA/GSFC's GEODYN orbit determination software to enable the simultaneous reduction of spacecraft tracking (e.g. GPS and SLR), three axis accelerometer and precise attitude data. Several weeks of CHAMP tracking and accelerometer data have been analyzed and the results will be presented. Precision orbit determination analysis based on tracking data alone in addition to results based on the simultaneous reduction of tracking and accelerometer data will be discussed. Results from a calibration of the accelerometer will be presented along with the results from various orbit determination strategies. Gravity field modeling status and plans will be discussed.
The CHAMP mission's unique combination of sensors and orbit configuration will enable unprecedented improvements in modeling and understanding the Earth's static gravity field and its temporal variations. CHAMP is the first of two missions (GRACE to be launched in the early part of 02') that combine a new generation of Global Positioning System (GPS) receivers, a high precision three-axis accelerometer, and star cameras for the precision attitude determination. In order to isolate the gravity signal for science investigations, it is necessary to perform a detailed reduction and analysis of the GPS and Satellite Laser Ranging (SLR) tracking data in conjunction with the accelerometer and attitude data. Precision orbit determination based on the GPS and SLR tracking data will isolate the orbit perturbations, while the accelerometer data will be used to distinguish the non-gravitational forces from those due to the geopotential (static, and time varying). In preparation for the CHAMP and GRACE missions, extensive modifications have been made to NASA/GSFC's GEODYN orbit determination software to enable the simultaneous reduction of spacecraft tracking (e.g. GPS and SLR), three-axis accelerometer and precise attitude data. Several weeks of CHAMP tracking and accelerometer data have been analyzed and the results will be presented. Precision orbit determination analysis based on tracking data alone in addition to results based on the simultaneous reduction of tracking and accelerometer data will be discussed. Results from a calibration of the accelerometer will be presented along with the results from various orbit determination strategies.
The Earth Radiation Budget Experiment (ERBE) waqs designed to examine the thermal equilibrium between the sun, the earth, and space. The major space-based component of the experiment is the Earth Radiation Budget Satellite (ERBS) which was launched from Shuttle (Mission 41-G) on October 5, 1984. The ERBS is a three-axis momentum-biased spacecraft containing its own subsystems for attitude control, power generation, thermal control, and data handling. The satellite transmits data via the NASA Spacecraft Tracking and Data Network (STDN) and the Tracking and Data Relay Satellite System (TDRSS). The ERBS instrument package includes eight channels in two sensor packages: a nonscanning radiometer and a scanning radiometer. The combined spectral range of the two instruments is 0.2-5.0 microns and the scale of the radiometer measurements can be changed to collect regional, zonal, or global data. A series of schematic diagrams of the ERBS spacecraft and its instrument package is provided.
The current best estimates of Bennu’s gravity field will be presented, based on the independent solutions from four different teams involved on the OSIRIS-REx mission. The discovery of ejected particles about Bennu that may remain in orbit for several days or more provide a unique opportunity to probe the gravity field to higher degree and order than possible by using conventional spacecraft tracking. However, the non-gravitational forces acting on these particles must also be characterized, and their impact on solution accuracy must be assessed. This talk will present the latest results from the mission, incorporating spacecraft tracking from the lowest orbit in which the satellite will be during the mission.
Mars ranging observations are available over the past 10 years with an accuracy of a few meters. Such precise measurements of the Earth-Mars distance provide valuable constraints on the masses of the asteroids perturbing both planets. Today more than 30 asteroid masses have thus been estimated from planetary ranging data (see [1] and [2]). Obtaining unbiased mass estimations is nevertheless difficult. Various systematic errors can be introduced by imperfect reduction of spacecraft tracking observations to planetary ranging data. The large number of asteroids and the limited a priori knowledge of their masses is also an obstacle for parameter selection. Fitting in a model a mass of a negligible perturber, or on the contrary omitting a significant perturber, will induce important bias in determined asteroid masses. In this communication, we investigate a simplified version of the mass determination problem. Instead of planetary ranging observations from spacecraft or radar data, we consider synthetic ranging observations generated with the INPOP [2] ephemeris for a test model containing ~25000 asteroids. We then suggest a method for optimal parameter selection and estimation in this simplified framework.
The Deep Space Network (DSN) is a network of tracking stations, located throughout the globe, used to track spacecraft for NASA's interplanetary missions. This paper describes a computer program, DSNTRAK, which provides an optimum daily tracking schedule for the DSN given the view periods at each station for a mission set of n spacecraft, where n is between 2 and 6. The objective function is specified in terms of relative total daily tracking time requirements between the n spacecraft. Linear programming is used to maximize the total daily tracking time and determine an optimal daily tracking schedule consistent with DSN station capabilities. DSNTRAK is used as part of a procedure to provide DSN load forecasting information for proposed future NASA mission sets.
Wide beam radio interferometer system for reentry tracking of Apollo spacecraft