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The NASA Deep Space Network (DSN) Array

The DSN Array Project is currently working with Senior Management at both JPL and NASA to develop strategies towards starting a major implementation project. Several studies within NASA are concluding, all of which recommend that any future DSN capability include arraying of antennas to increase performance. Support of Deep Space, Lunar, and CEV (crewed exploration vehicle) missions is possible. High data rate and TDRSS formatting is being investigated. Any future DSN capacity must include Uplink. Current studies ongoing to investigate and develop technologies for uplink arraying; provides advantages in three ways: 1) N2 effect. EIRP grows as N2(-vs-N for a downlink array); 2) Improved architectural options (can separate uplink and downlink); and 3) Potential for more cost effective transmitters for fixed EIRP.

communications

DSN Array Simulator

The DSN Array Simulator (wherein 'DSN' signifies NASA's Deep Space Network) is an updated version of software previously denoted the DSN Receive Array Technology Assessment Simulation. This software (see figure) is used for computational modeling of a proposed DSN facility comprising user-defined arrays of antennas and transmitting and receiving equipment for microwave communication with spacecraft on interplanetary missions. The simulation includes variations in spacecraft tracked and communication demand changes for up to several decades of future operation. Such modeling is performed to estimate facility performance, evaluate requirements that govern facility design, and evaluate proposed improvements in hardware and/or software. The updated version of this software affords enhanced capability for characterizing facility performance against user-defined mission sets. The software includes a Monte Carlo simulation component that enables rapid generation of key mission-set metrics (e.g., numbers of links, data rates, and date volumes), and statistical distributions thereof as functions of time. The updated version also offers expanded capability for mixed-asset network modeling--for example, for running scenarios that involve user-definable mixtures of antennas having different diameters (in contradistinction to a fixed number of antennas having the same fixed diameter). The improved version also affords greater simulation fidelity, sufficient for validation by comparison with actual DSN operations and analytically predictable performance metrics.

Tikidjian, Raffi

Weak-signal Phase Calibration Strategies for Large DSN Arrays

The NASA Deep Space Network (DSN) is studying arrays of large numbers of small, mass-produced radio antennas as a cost-effective way to increase downlink sensitivity and data rates for future missions. An important issue for the operation of large arrays is the accuracy with which signals from hundreds of small antennas can be combined. This is particularly true at Ka band (32 GHz) where atmospheric phase variations can be large and rapidly changing. A number of algorithms exist to correct the phases of signals from individual antennas in the case where a spacecraft signal provides a useful signal-to-noise ratio (SNR) on time scales shorter than the atmospheric coherence time. However, for very weak spacecraft signals it will be necessary to rely on background natural radio sources to maintain array phasing. Very weak signals could result from a spacecraft emergency or by design, such as direct-to-Earth data transmissions from distant planetary atmospheric or surface probes using only low gain antennas. This paper considers the parameter space where external real-time phase calibration will be necessary, and what this requires in terms of array configuration and signal processing. The inherent limitations of this technique are also discussed.

interferometry

The effects of correlated noise in intra-complex DSN arrays for S-band Galileo telemetry reception

A number of the proposals for supporting a Galileo S-band (2.3-GHz) mission involve arraying several antennas to maximize the signal-to-noise ratio (and bit rate) obtainable from a given set of antennas. Arraying is no longer a new idea, having been used successfully during the Voyager encounters with Uranus and Neptune. However, arraying for Galileo's tour of Jupiter is complicated by Jupiter's strong radio emission, which produces correlated noise effects. This article discusses the general problem of correlated noise due to a planet, or other radio source, and applies the results to the specific case of an array of antennas at the DSN's Tidbinbilla, Australia, complex (DSS 42, DSS 43, DSS 45, and the yet-to-be-built DSS 34). The effects of correlated noise are highly dependent on the specific geometry of the array and on the spacecraft-planet configuration; in some cases, correlated noise effects produce an enhancement, rather than a degradation, of the signal-to-noise ratio. For the case considered here--an array of the DSN's Australian antennas observing Galileo and Jupiter--there are three regimes of interest. If the spacecraft-planet separation is approximately less than 75 arcsec, the average effect of correlated noise is a loss of signal to noise (approximately 0.2 dB as the spacecraft-planet separation approaches zero). For spacecraft-planet separations approximately greater than 75 arcsec, but approximately less than 400 arcsec, the effects of correlated noise cause signal-to-noise variations as large as several tenths of a decibel over time scales of hours or changes in spacecraft-planet separation of tens of arcseconds; however, on average its effects are small (less than 0.01 dB). When the spacecraft is more than 400 arcsec from Jupiter (as is the case for about half of Galileo's tour), correlated noise is a less than 0.05-dB effect.

Dewey, R. J.

Breadboard Signal Processor for Arraying DSN Antennas

A recently developed breadboard version of an advanced signal processor for arraying many antennas in NASA s Deep Space Network (DSN) can accept inputs in a 500-MHz-wide frequency band from six antennas. The next breadboard version is expected to accept inputs from 16 antennas, and a following developed version is expected to be designed according to an architecture that will be scalable to accept inputs from as many as 400 antennas. These and similar signal processors could also be used for combining multiple wide-band signals in non-DSN applications, including very-long-baseline interferometry and telecommunications. This signal processor performs functions of a wide-band FX correlator and a beam-forming signal combiner. [The term "FX" signifies that the digital samples of two given signals are fast Fourier transformed (F), then the fast Fourier transforms of the two signals are multiplied (X) prior to accumulation.] In this processor, the signals from the various antennas are broken up into channels in the frequency domain (see figure). In each frequency channel, the data from each antenna are correlated against the data from each other antenna; this is done for all antenna baselines (that is, for all antenna pairs). The results of the correlations are used to obtain calibration data to align the antenna signals in both phase and delay. Data from the various antenna frequency channels are also combined and calibration corrections are applied. The frequency-domain data thus combined are then synthesized back to the time domain for passing on to a telemetry receiver

Jongeling, Andre

Greatly enhanced deep space mission data return using verv large DSN arrays

The purposes of the Array System are: To fulfill the mission needs for higher data rates in the post-2010 era - Reduce the cost per data bit by two orders of magnitude. Specific Goal: Achieve a factor of 10 increase in DSN reception capability per decade from 2012 through 2027 (an average of 1 dB per year).

array

A compact presentation of DSN array telemetry performance

The telemetry performance of an arrayed receiver system, including radio losses, is often given by a family of curves giving bit error rate vs bit SNR, with tracking loop SNR at one receiver held constant along each curve. This study shows how to process this information into a more compact, useful format in which the minimal total signal power and optimal carrier suppression, for a given fixed bit error rate, are plotted vs data rate. Examples for baseband-only combining are given. When appropriate dimensionless variables are used for plotting, receiver arrays with different numbers of antennas and different threshold tracking loop bandwidths look much alike, and a universal curve for optimal carrier suppression emerges.

Greenhall, C. A.

Operation's Concept for Array-Based Deep Space Network

The Array-based Deep Space Network (DSNArray) will be a part of more than 10(exp 3) times increase in the downlink/telemetry capability of the Deep space Network (DSN). The key function of the DSN-Array is to provide cost-effective, robust Telemetry, Tracking and Command (TT&C) services to the space missions of NASA and its international partners. It provides an expanded approach to the use of an array-based system. Instead of using the array as an element in the existing DSN, relying to a large extent on the DSN infrastructure, we explore a broader departure from the current DSN, using fewer elements of the existing DSN, and establishing a more modern Concept of Operations. This paper gives architecture of DSN-Array and its operation's philosophy. It also describes customer's view of operations, operations management and logistics - including maintenance philosophy, anomaly analysis and reporting.

operations concept

DSN Antenna Array Architectures Based on Future NASA Mission Needs

A flexible method of parametric, full life-cycle cost analysis has been combined with data on NASA's future communication needs to estimate the required number and operational dates of new antennas for the Deep Space Network (DSN). The requirements were derived from a subset of missions in the Integrated Mission Set database of NASA's Space Communications Architecture Working Group. Assuming that no new antennas are 'constructed', the simulation shows that the DSN is unlikely to meet more than 20% of mission requirements by 2030. Minimum full life-cycle costs result when antennas in the diameter range, 18m-34m, are constructed. Architectures using a mixture of antenna diameters produce a slightly lower full life-cycle cost.

array

Planning for VLA/DSN arrayed support to the Voyager at Neptune

Preplanning for the use of the National Radio Astronomy Observatory's Very Large Array (VLA) in support of Voyager at Neptune has been underway since early 1982. When arrayed with the Deep Space Network (DSN) antennas at Goldstone, CA, the VLA more than doubles the potential data return over the American longitude for the 1989 Voyager encounter. The background, rationale and current status of planning for VLA-DSN Arrayed Support to the Voyager at Neptune are discussed.

Layland, J. W.