Hardware description

My current hardware for low frequency, wideband interferometry is as follows:

Antennas

I am currently working with a three element system designed to receive signals from 10 to 88 MHz. Inverted V antennas built along the lines of those used by the LOFAR and MWA groups are in use. Each inverted V is coupled to 1:1 baluns at their feed point, support on a PVC pipe frame with a 3x3 meter ground screen underneath them. Details for these antennas are provided in the project update section.

LNA

AntennaCraft 10G212 mast mounted television preamplifiers are used to achieve sky noise limited performance from 40 to 88 MHz and push the signal through ~250 meters of RG-6/U coax. Low pass filtering just past the baluns are used to exclude strong, out of band signals from the system. This system will only work in a rural location, there is simply too much RFI in an urban/suburban environment.

Some info elsewhere on this site is stale (Channel Master preamps/MiniCircuits amps). Here is the most up-to-date antenna/LNA chain:

Broad element Inverted V antenna (resonant at 65 MHz) -> 1:1 coaxial balun -> Macom Pico 54 MHz high pass filter -> 10G212 Preamp (mast mounted) -> 250 meters RG-6/U coax -> MiniCircuits 70 MHz LPF -> 10G212 Preamp -> ZEM-4300 Mixer (inverted IF and RF ports) -> BladeRF SDR

Upconversion

MiniCircuits ZEM-4300 mixers (with inverted R and I channels) are used to upconvert ~40 to 88 MHz signals up to ~1040 to 1088 MHz. A Valon 5007 signal generator is used to provide a LO that can be referenced to a GPSDO 10 MHz signal for future VLBI work.

Software defined radios

Three BladeRF SDRs are used and connected via their MIMO ports to synchronize their clocks. A Valon 5007/5008 38.4 MHz clock can be provided for future VLBI work.

Computer

An i7 Core 4790K with 16 Gb of RAM, and four 1 Tb solid state drives is used. One SSD is used for running the Ubuntu 14.10 OS with minimal latency and three additional SSDs are used to capture data from each BladeRF running at 15 MSPS. This allows for ~1.5 hours of continuous data recording.

Experiments are underway with a GTX 770 videocard to do GPU based computing that might allow for on-the-fly correlation in the future using pyCUDA based routines.

Software

A Python based FX correlator is used to generate baseline solutions that are saved as FITs files using pyFITS. These baseline data files are then processed using AIPY to generate images of the sky (work still in progress). See the following link for access to the AIPY code:

https://github.com/AaronParsons/aipy

Considerably more detail is provided in the data updates section.

Check out the file called "3 element inteferometer.pdf" in the files section for a more up-to-date description of my system.