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Relocation of the Deep Space Network Maintenance Center

The Jet Propulsion Laboratory maintains a Deep Space Network (DSN) maintenance center (DMC), whose task is to engineer and manage the repair and calibration program for the electronic and mechanical equipment used in the tracking stations located at Madrid, Spain, and Canberra, Australia. The DMC also manages the Goldstone complex maintenance facility (GCMF), whose task is to repair and calibrate the Goldstone electronic and mechanical equipment. The rationale for moving the facility to Barstow, California, and the benefits derived from the move are discussed.

Beutler, K. F.↗

A two-year history of atomic frequency standards syntonization in the Deep Space Network

The frequency and timing system (FTS) of the Deep Space Network (DSN) consists of a collection of three sets of clocks driven by independent atomic oscillators. The synchronization of the output frequencies (syntonization) of these oscillators (reference frequency standards) is reported. There is an implied specification of a + or - 5.5 X 10 to the 12th power related to the DSN time synchronization specification of a + or - 100 microseconds. Both the syntonization within the three sets and the syntonization of the sets to the international standard (International Atomic Time) are considered.

Ward, S. C.↗

The Deep Space Network: An instrument for radio astronomy research

The NASA Deep Space Network operates and maintains the Earth-based two-way communications link for unmanned spacecraft exploring the solar system. It is NASA's policy to also make the Network's facilities available for radio astronomy observations. The Network's microwave communication systems and facilities are being continually upgraded. This revised document, first published in 1982, describes the Network's current radio astronomy capabilities and future capabilities that will be made available by the ongoing Network upgrade. The Bibliography, which includes published papers and articles resulting from radio astronomy observations conducted with Network facilities, has been updated to include papers to May 1987.

Renzetti, N. A.↗

The Deep Space Network stability analyzer

A stability analyzer for testing NASA Deep Space Network installations during flight radio science experiments is described. The stability analyzer provides realtime measurements of signal properties of general experimental interest: power, phase, and amplitude spectra; Allan deviation; and time series of amplitude, phase shift, and differential phase shift. Input ports are provided for up to four 100 MHz frequency standards and eight baseband analog (greater than 100 kHz bandwidth) signals. Test results indicate the following upper bounds to noise floors when operating on 100 MHz signals: -145 dBc/Hz for phase noise spectrum further than 200 Hz from carrier, 2.5 x 10(exp -15) (tau =1 second) and 1.5 x 10(exp -17) (tau =1000 seconds) for Allan deviation, and 1 x 10(exp -4) degrees for 1-second averages of phase deviation. Four copies of the stability analyzer have been produced, plus one transportable unit for use at non-NASA observatories.

Breidenthal, Julian C.↗

Enabling a Larger Deep Space Mission Suite: A Deep Space Network Queuing Antenna for Demand Access

The advent of deep space small spacecraft, as exemplified by the Mars Cubesat One (MarCO), Lunar Trailblazer, Janus, the Escape and Plasma Acceleration and Dynamics Explorers (EscaPADE), and the thirteen Artemis 1 missions, opens the possibility that a much larger number of deep space spacecraft may be launched over the next 10 years and beyond. While scientifically exciting, the prospect of a (much) larger mission suite raises significant challenges for the current approach to ground stations and mission operations. We have been investigating an integrated approach for ground stations and missions operations to enable new modes of operation while maintaining the capabilities of the current operational techniques. This integrated approach is built around three core capabilities: (1) A queuing antenna that enables monitoring the status of a much larger number of spacecraft, and allows spacecraft to transmit requests for telemetry with NASA’s Deep Space Network (DSN); (2) a flexible scheduling system that expands the current DSN scheduling services to enable allocating time on DSN antennas in near real-time; and (3) a cloud-based ground data system that can be spun up and down according to how tracks are assigned by the flexible scheduling system. We shall show that an 18 meter DSN queuing antenna equipped with cyrogenic receivers would enable use of the DSN Demand Access Service for small spacecraft throughout the inner Solar System, thus providing service to a large mission suite. We first discuss the architecture of the queuing antenna and its supporting systems, including, for instance, the service required to generate the schedule for the queueing antenna (which dictates how it slews to monitor multiple spacecraft in a day of operations). Next, we describe the signaling scheme used to encode a request, which is inherited from the already operational DSN Beacon Tone Service, and describe two alternative ways to detect the incoming tone at the ground station, one based on maximum likelihood estimation (MLE), and another one based on Fast-Fourier Transfer (FFT) processing. We then use these results to estimate the maximum range at which a request can be reliably detected as a function of the spacecraft and ground station communication capabilities. Finally, the last part of this part of this paper briefly describes the prototyping effort undertaken at Morehead State University (MSU) and JPL to demonstrate the viability of this new DSN demand access. In particular, we describe the suite of tests conducted using MSU’s 21 meter ground station to validate its use a queuing antenna.

Mattle, Emily↗

Evaluating the Trustworthiness of Deep Neural Networks in Deployment – A Comparative Study (Replicability Study)

As deep neural networks (DNNs) are increasingly used in safety critical applications, there is a growing concern for their trustworthiness. Even highly trained, high-performant networks are not 100% accurate. However, it is very difficult to predict their behaviour during deployment without ground truth. In this paper, we provide a comparative and replicability study on recent approaches that have been proposed to evaluate the trustworthiness of DNNs. We find that it is very difficult to run and reproduce the results for these approaches on their replication packages, and it is even more difficult to run the tools on artifacts other than their own. Further, it is difficult to compare the effectiveness of the tools, due to lack of clearly defined evaluation metrics. Our results indicate that more effort is needed in our research community to obtain sound techniques for evaluating the trustworthiness of neural networks in safety-critical domains. To this end, we contribute an evaluation framework that incorporates the considered approaches and enables evaluation on common benchmarks, using common metrics. Using this framework, we run a comparative study of the three approaches.

Trustworthy AI↗

Telecommunications technology development for the Deep Space Network

The telecommunications technology that is currently being developed for the Deep Space Network (DSN), a system providing communications and navigation support for NASA's deep space missions, is discussed. The major areas of development include Ka-band (32 GHz) technology, beam waveguide antennas, low-noise amplifiers, coding, navigation techniques, high-power transmitters, and optical technology. The expected payoffs of the new technology during the mid-1990's and later are examined.

Yuen, J. H.↗

The Impact of Traffic Prioritization on Deep Space Network Mission Traffic

A select number of missions supported by NASA's Deep Space Network (DSN) are demanding very high data rates. For example, the Kepler Mission was launched March 7, 2009 and at that time required the highest data rate of any NASA mission, with maximum rates of 4.33 Mb/s being provided via Ka band downlinks. The James Webb Space Telescope will require a maximum 28 Mb/s science downlink data rate also using Ka band links; as of this writing the launch is scheduled for a June 2014 launch. The Lunar Reconnaissance Orbiter, launched June 18, 2009, has demonstrated data rates at 100 Mb/s at lunar-Earth distances using NASA's Near Earth Network (NEN) and K-band. As further advances are made in high data rate space telecommunications, particularly with emerging optical systems, it is expected that large surges in demand on the supporting ground systems will ensue. A performance analysis of the impact of high variance in demand has been conducted using our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) simulation tool. A comparison is made regarding the incorporation of Quality of Service (QoS) mechanisms and the resulting ground-to-ground Wide Area Network (WAN) bandwidth necessary to meet latency requirements across different user missions. It is shown that substantial reduction in WAN bandwidth may be realized through QoS techniques when low data rate users with low-latency needs are mixed with high data rate users having delay-tolerant traffic.

prioritization↗

Three-Dimensional Analysis of Deep Space Network Antenna Coverage

There is a need to understand NASA s Deep Space Network (DSN) coverage gaps and any limitations to provide redundant communication coverage for future deep space missions, especially for manned missions to Moon and Mars. The DSN antennas are required to provide continuous communication coverage for deep space flights, interplanetary missions, and deep space scientific observations. The DSN consists of ground antennas located at three sites: Goldstone in USA, Canberra in Australia, and Madrid in Spain. These locations are not separated by the exactly 120 degrees and some DSN antennas are located in the bowl-shaped mountainous terrain to shield against radiofrequency interference resulting in a coverage gap in the southern hemisphere for the current DSN architecture. To analyze the extent of this gap and other coverage limitations, simulations of the DSN architecture were performed. In addition to the physical properties of the DSN assets, the simulation incorporated communication forward link calculations and azimuth/elevation masks that constrain the effects of terrain for each DSN antenna. Analysis of the simulation data was performed to create coverage profiles with the receiver settings at a deep space altitudes ranging from 2 million to 10 million km and a spherical grid resolution of 0.25 degrees with respect to longitude and latitude. With the results of these simulations, two- and three-dimensional representations of the area without communication coverage and area with coverage were developed, showing the size and shape of the communication coverage gap projected in space. Also, the significance of this communication coverage gap is analyzed from the simulation data.

Kegege, Obadiah↗

Propagation Effects of Importance to the NASA/JPL Deep Space Network (DSN)

This paper presents Propagation Effects of Importance To The NASA/JPL Deep Space Network (DSN). The topics include: 1) DSN Antennas; 2) Deep Space Telecom Link Basics; 3) DSN Propagation Region of Interest; 4) Ka-Band Weather Effects Models and Examples; 5) Existing Goldstone Ka-Band Atmosphere Attenuation Model; 6) Existing Goldstone Atmosphere Noise Temperature Model; and 7) Ka-Band delta (G/T) Relative to Vacuum Condition. This paper summarizes the topics above.

Slobin, Steve↗

The Deep Space Network

This report presents DSN progress in flight project support, tracking and data acquisition (TDA) research and technology, network engineering, hardware and software implementation, and operations. Each issue presents material in some, but not all, of the following categories in the order indicated. - Description of the DSN - Mission Support Ongoing Planetary/Interplanetary Flight Projects Advanced Flight Projects - Radio Science - Special Projects - Supporting Research and Technology Tracking and Ground-Based Navigation Communications--Spacecraft/Ground Station Control and Operations Technology Network Control and Data Processing - Network and Facility Engineering and Implementation Network Network Operations Control Center Ground Communications Deep Space Stations - Operations Network Operations Network Operations Control Center Ground Communications Deep Space Stations - Program Planning TDA Planning Quality Assurance In each issue, the part entitled "Description of the DSN" describes the functions and facilities of the DSN and may report the current configuration of one of the five DSN systems (Tracking, Telemetry, Command, Monitor & Control, and Test & Training). The work described in this report series is either performed or managed by the Tracking and Data Acquisition organization of JPL for NASA.

Tracking and Data Acquisition organization↗

NASA Deep Space Network Commitments for Human Missions to the Moon and Beyond

NASA’s Deep Space Network (DSN) serves as a critical element in the exploration of deep space, typically supporting 30-40 operational missions at any given time, each with unique characteristics and telecommunications requirements. In order to meet the needs of its diverse customer base, DSN relies on the Mission Support Definition and Commitments Office to interface with its customers and to develop, negotiate, and document the appropriate service commitments to meet each mission’s needs. Members of this office provide the needed support throughout each mission’s lifetime. While DSN’s primary focus in recent years has been supporting scientific missions by robotic spacecraft deployed across the solar system, the network is ramping-up to provide support for human spaceflight (HSF) endeavours to the moon and beyond, starting with the Artemis missions which aim to land humans on the lunar surface in the 2020’s. These HSF missions pose unique challenges for the DSN, including technical, operational, and programmatic concerns. Examples of challenges in each of these areas are provided, along with descriptions of how they are being addressed and open issues remaining.

Turcios, Ricky↗

LQG and Feedforward Controllers for the Deep Space Network Antennas

The controller development and the tracking performance evaluation for NASA's Deep Space Network antenna are presented. A trajectory preprocessor, LQG (Linear Quadratic Gaussian) controller, feedforward controller, and their combination are designed, built, analyzed, and tested.

Deep Space Network (DSN)antennas feedforward contr↗