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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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FPGA-Based Filterbank Implementation for Parallel Digital Signal Processing

One approach to parallel digital signal processing decomposes a high bandwidth signal into multiple lower bandwidth (rate) signals by an analysis bank. After processing, the subband signals are recombined into a fullband output signal by a synthesis bank. This paper describes an implementation of the analysis and synthesis banks using (Field Programmable Gate Arrays) FPGAs.

Berner, Stephan↗

An infrared search for extraterrestrial laser signals

The focus of project SETI is on microwave frequencies, where receivers fundamentally have the best sensitivity for the detection of narrow band signals. Such receivers, when coupled to existing radio telescopes, form an optimum system for broad area searches over the sky. Detection of narrow band infrared signals is best done with a laser heterodyne reciever similar in function to a microwave spectral line receiver. A receiver was built for astrophysical observations at 30 THz (10 microns) and the spectrometer is being adapted for SETI work. The receiver uses a small CO2 laser as the local oscillator, a HgCdTe diode as the photomixer, and a multichannel intermediate frequency (IF) filterbank. An advanced multichannel IF processor is now being built to detect infrared line radiation in 1000 spectral channels each 1 MHz wide. When completed this processor will be used with a ground based telescope next year for a survey of several hundred selected stars for narrow band CO2 laser signals at 30 THz.

Betz, A.↗

RDBE Development and Progress

A digital backend based on the ROACH board has been developed jointly by the National Radio Astronomy Observatory and MIT Haystack Observatory. The RDBE will have both Polyphase Filterbank and Digital Downconverter personalities. The initial configuration outputs sixteen 32-MHz channels, comprised of half the channels from the PFB processing of the two IF inputs, for use in the VLBI2010 geodetic system and in the VLBA sensitivity upgrade project. The output rate is 2x109 bits/second (1x10(exp 9) bits/sec = 1 Gbps) over a 10 GigE connection to the Mark 5C with the data written in Mark 5B format on disk.

Niell, A.↗

DSN Radio Astronomy Spectrometer

The Deep Space Network (DSN) enables NASA to communicate with its deep space spacecraft. By virtue of its large antennas, the DSN can be used as a powerful instrument for radio astronomy. In particular, Deep Space Station (DSS) 43, the 70 m antenna at the Canberra Deep Space Communications Complex (CDSCC) has a K-band radio astronomy system covering a 10 GHz bandwidth at 17 to 27 GHz. This spectral range covers a number of atomic and molecular lines, produced in a rich variety of interstellar gas conditions. A new high-resolution spectrometer was deployed at CDSCC in November 2019 and connected to the K-band downconverter. The system has two different firmware modes: 1) Using a 65k-pt FFT to provide 32,768 spectral channels at ~30.5 kHz (0.45 km/s velocity resolution) and 2) Using a 16k-pt polyphase filterbank (PFB) to provide 8,192 spectral channels with ~122 kHz resolution (1.8 km/s velocity resolution). Previous work extensively described the spectrometer system. In this paper we present added functionality and updates to the commissioned spectrometer. The changes include developments in system timing, metadata, firmware and data products.

Bradford, Brian↗

Implementation of an Antenna Array Signal Processing Breadboard for the Deep Space Network

The Deep Space Network Large Array will replace/augment 34 and 70 meter antenna assets. The array will mainly be used to support NASA's deep space telemetry, radio science, and navigation requirements. The array project will deploy three complexes in the western U.S., Australia, and European longitude each with 400 12m downlink antennas and a DSN central facility at JPL. THis facility will remotely conduct all real-time monitor and control for the network. Signal processing objectives include: provide a means to evaluate the performance of the Breadboard Array's antenna subsystem; design and build prototype hardware; demonstrate and evaluate proposed signal processing techniques; and gain experience with various technologies that may be used in the Large Array. Results are summarized..

array↗

Frequency Domain Beamforming for a Deep Space Network Downlink Array

This paper describes a frequency domain beamformer to array up to 8 antennas of NASA's Deep Space Network currently in development. The objective of this array is to replace and enhance the capability of the DSN 70m antennas with multiple 34m antennas for telemetry, navigation and radio science use. The array will coherently combine the entire 500 MHz of usable bandwidth available to DSN receivers. A frequency domain beamforming architecture was chosen over a time domain based architecture to handle the large signal bandwidth and efficiently perform delay and phase calibration. The antennas of the DSN are spaced far enough apart that random atmospheric and phase variations between antennas need to be calibrated out on an ongoing basis in real-time. The calibration is done using measurements obtained from a correlator. This DSN Downlink Array expands upon a proof of concept breadboard array built previously to develop the technology and will become an operational asset of the Deep Space Network. Design parameters for frequency channelization, array calibration and delay corrections will be presented as well a method to efficiently calibrate the array for both wide and narrow bandwidth telemetry.

Filterbank↗

Big Data Challenges for Large Radio Arrays

Future large radio astronomy arrays, particularly the Square Kilometre Array (SKA), will be able to generate data at rates far higher than can be analyzed or stored affordably with current practices. This is, by definition, a "big data" problem, and requires an end-to-end solution if future radio arrays are to reach their full scientific potential. Similar data processing, transport, storage, and management challenges face next-generation facilities in many other fields.

Combining↗