Over the last few weeks I have been helping the Allen Telescope Array by calibrating the pointing of some of the recently upgraded antennas using the GNU Radio backend, which consists of two USRP N32x devices that are connected to the IF output of the RFCB downconverter. For this calibration, GPS satellites are used, since they are very bright, cover most of the sky, and have precise ephemerides.
The calibration procedure is described in this memo. Essentially, it involves pointing at a few points that describe a cross in elevation and cross-elevation coordinates and which is centred at the position of the GPS satellite. Power measurements are taken at each of these points and a Gaussian is fitted to compute the pointing error.
The script I am using is based on this script for the CASPER SNAP boards, with a few modifications to use my GNU Radio polarimetric correlator, which uses the USRPs and a software FX correlator that computes the crosscorrelations and autocorrelations of the two polarizations of two antennas. For the pointing calibration, only the autocorrelations are used to measure Stokes I, but all the correlations are saved to disk, which allows later analysis.
In this post I analyse the single-dish polarimetric spectra of the GPS satellites we have observed during some of these calibrations.
This post belongs to a series about the activities of the GNU Radio community at Allen Telescope Array. For more information about these activities, see my first post.
The feeds in the ATA dishes are dual polarization linear feeds, giving two orthogonal linear polarizations that are called X and Y and (corresponding to the horizontal and vertical polarizations). In the setup we currently have, the two RF signals from a single dish are downconverted to an IF around 512 MHz using common LOs and then sampled by the two channels of a USRP N32x. Since we have two USRPs, we are able to receive dual polarization signals from two dishes simultaneously.
The two USRPs are synchronized with the 10MHz and PPS signals from the observatory, but even in these conditions there will be random phase offsets between the different channels. These offsets are caused by fractional-N PLL states and other factors, and change with every device reset. To solve this problem, it is possible to distribute the LO from the first channel of a USRP N321 into its second channel and both channels of a second USRP N320. In fact, it is possible to daisy chain several USRPs to achieve a massive MIMO configuration. By sharing the LO between all the channels, we achieve repeatable phase offsets in every run.
During the first weekends of experiments at ATA we didn’t use LO sharing, and we finally set it up and tested it last weekend. After verifying that phase offsets were in fact repeatable between all the channels, I did some polarimetric observations of GNSS satellites to calibrate the phase offsets. The results are summarised in this post. The data has been published in Zenodo as “Allen Telescope Array polarimetric observation of GNSS satellites“.
Back in July, I wrote about how the Galileo E24 differential code biases were abnormally large in comparison to other satellites from the constellation. This was initially noticed by Bert Hubert from galmon.eu in the large size of the BGDs of this satellite. In that post I did a study of the DCB products from the Chinese Academy of Science and the broadcast ephemeris BGDs, and explained the relation between them.
At the end of September, Bert tweeted that after some maintenance the BGDs of E24 had stopped being so large. That is not so surprising, since the payload on-board the satellite can adjust the relative delays between each of the navigation signals, in order to correct these kinds of problems.
After letting a few weeks go by so that the MGEX products get uploaded, I have now redone some of the plots in that study with the data surrounding the change.
Since the beginning of October, together with a group of people from the GNU Radio community, we are doing some experiments and tests remotely at Allen Telescope Array (ATA). This amazing opportunity forms part of the recent collaboration agreement between SETI Institute and GNU Radio. We are taking advantage of the fact that the ATA hardware is relatively unused on weekends, and putting it to good use for our experiments. One of the goal of these activities is to put in contact GNU Radio people and radio astronomy people, to learn from each other and discover what features of GNU Radio could benefit radio astronomy and SETI, particularly at the ATA.
I’m very grateful to Wael Farah, Alex Pollak, Steve Croft and Ellie White from ATA and SETI Institute for their support of this project and the very interesting conversations we’ve had, to Derek Kozel, who is Principal Investigator for GNU Radio at SETI, for organizing and supporting all this, and to the rest of my GNU Radio teammates for what’s being an excellent collaboration of ideas and sharing of resources.
From the work I’ve been doing at ATA, I already have several recordings and data, and also some studies and material that I’ll be publishing in the near future. Hopefully this post will be the first in a series of many.
Here I will speak about one of the first experiments I did at ATA, which is a recording of one Galileo GNSS satellite using two of the dishes from the array. This kind of recording can be used to perform interferometry. GNSS satellites are good test targets because they have strong wideband signals and their location is known precisely. The IQ recording described in this post is published as the dataset “Allen Telescope Array Galileo E31 RF recording with 2 antennas and 2 polarizations” in Zenodo.
Back on January, I did a post with a simulation about the DOP distribution for the Galileo and GPS constellations. In there, I computed the DOP for a grid of points on the surface of the Earth and then plotted maps with the average and worst DOP. I used three different kinds of constellation definitions, both for Galileo and for GPS: the base constellation, which has 24 satellites in both cases; an expanded constellation, which in the case of Galileo adds 6 spares and in the case of GPS has 27 satellites as defined in the 2008 SPS performance standard; and a real life constellation taken from the almanac at the beginning of January.
Since I wrote that post, the 2020 SPS performance standard came out in April. This defines a new expandable reference constellation of 30 satellites. Besides the three expandable slots on planes B, D and F, three new expandable slots are added on planes A, C and E, so that now there is one expandable slot per plane. All the RAANs and mean anomalies corresponding to the slots have also been updated, since the constellation is now referenced to an epoch on 2016 (the previous one had an epoch on 1993).
I have now run again my simulations using the 30 satellite expandable constellation, which provides a closer model to the real life constellation. Here I show briefly the results.
In my previous post I looked at the BGDs and related topics for the Galileo satellites. We saw that satellite E24 has atypically large BGDs, but everything else seems fine and consistent with that satellite. However, Bert Hubert from galmon.eu shows that several RTCM sources broadcast a clock correction of around -5ns for E24. Here we look at the possible causes for that correction, and discuss whether it might be problematic.
A few days ago, Bert Hubert, from galmon.eu noticed that Galileo satellite E24 was somewhat special because it had unusually large BGDs. This raised a number of questions, such as what is the physical interpretation of BGDs, what they have to do with broadcast clock models, and so on.
In this post I will explain a few basic facts about BGDs and related topics, following an approach that is perhaps different to that of the usual GNSS literature, and also study the current values for the Galileo constellation. People who know all the details about the BGDs or who just want to see a few pretty plots can skip all the first section of the post.
One of the things I’ve always wanted to do since Es’hail 2 was launched is to perform two-way ranging by transmitting a signal through the Amateur transponder and measuring the round trip time. Stefan Biereigel DK3SB first did this about a year ago. His ranging implementation uses a waveform with a chip rate of only 10kHz, as it is thought for Amateur transponders having bandwidths of a few tens of kHz. With this relatively slow chiprate, he achieved a ranging resolution of approximately 1km.
The QO-100 WB transponder allows much wider signals that can be used to achieve a ranging resolution of one metre or less. This weekend I have been doing my first experiments about ranging through the QO-100 WB transponder.
In GNSS, when considering the propagation of signals from the satellites to a receiver, it is easier to work in an ECI reference frame, since (ignoring the gravitational potential of Earth), light travels in straight lines in ECI coordinates. However, it is often common to do all the calculations in an ECEF frame, as the final goal is to obtain the receiver’s position in ECEF coordinates, and the ephemerides also use ECEF coordinates to describe the satellite positions. Therefore, a non-relativistic correction needs to be applied to account for the fact that light no longer travels in straight lines when one considers ECEF coordinates. Often, the correction is done as some kind of approximation. These types of corrections are known in the GNSS literature as the Sagnac effect.
The goal of this post is to discuss where the corrections arise from, the typical approximations that can be made, and how these corrections affects the calculation of range and range-rate. I didn’t find a good source in the literature where this is described in detail and in a self-contained way, so I decided to write it myself.
I have been wondering about how the DOP for the different GNSS constellation varies geographically, owing to the different number of satellites and constellation geometries. There are many DOP maps, such as this Galileo HDOP map by the Galileo System Simulation facility, but after a quick search in the literature I couldn’t find any survey paper that made a comprehensive comparison. The closest thing I found to what I was looking for was Consellation design optimization with a DOP based criterion, by Dufour etl. This was published in 1995, so it compares the GPS and GLONASS constellations with prototypical constellations such as the Walker delta using different parameters, but it doesn’t mention Galileo, which wasn’t even planned back then.
Therefore, I have decided to do my own simulations and compare the DOP for the Galileo and GPS constellations. Since the actual distribution of the satellites can differ substantially from the slots designated in the constellation, I am considering both the theoretical reference constellations and the real world constellations, as taken from the almanacs at the beginning of 2020. This post is a detailed account of my methodology and results.