The DSN Telecommunications Link Design Handbook is a large document describing many aspects pertaining deep space communications and how they are implemented by the NASA Deep Space Network. One of the many things it contains is a description of a Reed-Solomon encoder for the CCSDS code using the Berlekamp bit-serial architecture. While following this description to implement an encoder, I have found an error. In this post, I explain the error and where I think it comes from.

# Category: Maths

Mathematics

## Voyager 1 and Reed-Solomon

In one of my previous posts about Voyager 1, I stated that the Voyager probes used as forward error correction only the k=7, r=1/2 CCSDS convolutional code, and that Reed-Solomon wasn’t used. However, some days ago, Brett Gottula asked about this, citing several sources that stated that the Voyager probes used Reed-Solomon coding after their encounter with Saturn.

My source for stating that Reed-Solomon wasn’t used was some private communication with DSN operators. Since the XML files describing the configuration of the DSN receivers for Voyager 1 didn’t mention Reed-Solomon either, I had no reason to question this. However, the DSN only processes the spacecraft data up to some point (which usually includes all FEC decoding), and then passes the spacecraft frames to the mission project team without really looking at their contents. Therefore, it might be the case that it’s the project team the one who handles the Reed-Solomon code for the Voyagers. This would make sense specially if the code was something custom, rather than the CCSDS code (recall that Voyager predates the CCSDS standards). If this were true, the DSN wouldn’t really care if there is Reed-Solomon or not, and they might have just forgotten about it.

After looking at the frames I had decoded from Voyager 1 in more detail, I remarked that Brett might be right. Doing some more analysis, I have managed to check that in fact the Voyager 1 frames used Reed-Solomon as described in the references that Brett mentioned. In this post I give a detailed look at the Reed-Solomon code used by the Voyager probes, compare it with the CCSDS code, and show how to perform Reed-Solomon decoding in the frames I decoded in the last post. The middle section of this post is rather math heavy, so readers might want to skip it and go directly to the section where Reed-Solomon codewords in the Voyager 1 frames are decoded.

## Computing the symbol error rate of m-FSK

How to compute the symbol error rate rate of an m-FSK modulation is something that comes up in a variety of situations, since the math is the same in any setting in which the symbols are orthogonal (so it also applies to some spread spectrum modulations). I guess this must appear somewhere in the literature, but I can never find this result when I need it, so I have decided to write this post explaining the math.

Here I show an approach that I first learned from Wei Mingchuan BG2BHC two years ago during the Longjiang-2 lunar orbiter mission. While writing our paper about the mission, we wanted to compute a closed expression for the BER of the LRTC modulation used in the uplink (which is related to \(m\)-FSK). Using a clever idea, Wei was able to find a formula that involved an integral of CDFs and PDFs of chi-squared distributions. Even though this wasn’t really a closed formula, evaluating the integral numerically was much faster than doing simulations, specially for high \(E_b/N_0\).

Recently, I came again to the same idea independently. I was trying to compute the symbol error rate of \(m\)-FSK and even though I remembered that the problem about LRTC was related, I had forgotten about Wei’s formula and the trick used to obtain it. So I thought of something on my own. Later, digging through my emails I found the messages Wei and I exchanged about this and saw that I had arrived to the same idea and formula. Maybe the trick was in the back of my mind all the time.

Due to space constraints, the BER formula for LRTC and its mathematical derivation didn’t make it into the Longjiang-2 paper. Therefore, I include a small section below with the details.

## ESA NEOCC riddle 1

A few weeks ago, the ESA Nearth Earth Object Coordination Center started a series of NEOCC riddles about Near Earth Object orbits and related topics. The first riddle was about orbits with a peculiar characteristic: they spend 50% of the time inside some fixed radius from the Sun (1.3au in the riddle), and the remaining 50% of the time outside this radius. It was published on June 4. Shortly after that I submitted my solution. The deadline for sending solutions ended yesterday, so today NEOCC has published their solution together with the list of people that solved the riddle correctly. In this post I publish my solution and make some additional comments.

## Reverse-engineering the DSCS-III convolutional encoder

One thing I left open in my post yesterday was the convolutional encoder used for FEC in the DSCS-III X-band beacon data. I haven’t seen that the details of the convolutional encoder are described in Coppola’s Master’s thesis, but in a situation such as this one, it is quite easy to use some linear algebra to find the convolutional encoder specification. Here I explain how it is done.

## Earth rotation corrections for range and range-rate in GNSS

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.

## Simulating the TED gain for a polyphase matched filter

Trying to improve the performance of the demodulators in gr-satellites, I am switching to the Symbol Sync GNU Radio block, which was introduced by Andy Walls in GRCon17. This block covers the functionality of all the other clock synchronization blocks, such as Polyphase Clock Sync and Clock Recovery MM, while fixing many bugs.

One of the new features of the Symbol Sync block is the ability to specify the gain of the timing error detector (TED) used in the clock recovery feedback loop. All the other blocks assumed unity gain, which simply causes the loop filter taps to be wrong. However, the TED gain needs to be calculated beforehand either by analysis or simulation, as it depends on the choice of TED, samples per symbol, pulse shaping, SNR and other.

While Andy shows how to use the Symbol Sync block as a direct replacement for the Polyphase Clock Sync block in his slides, he leaves the TED gain as one, since that is what the Polyphase Clock Sync block uses. In replacing the Polyphase Clock Sync block by Symbol Sync in gr-satellites, I wanted to use the correct TED gain, but I didn’t found anyone having computed it before. This post shows my approach at simulating the TED gain for polyphase matched filter with maximum likelyhood detector.

## Measuring the gain of a dish

Here I want to show a technique for measuring the gain of a dish that I first learned from an article by Christian Monstein about the Moon’s temperature at a wavelength of 2.77cm. The technique only uses power measurements from an observation of a radio source, at different angles from the boresight. Ideally, the radio source should be strong and point-like. It is also important that the angles at which the power measurements are made are known with good accuracy. This can be achieved either with a good rotator or by letting an astronomical object drift by on a dish that is left stationary.

## Projection of a sphere onto the unit sphere in spherical coordinates

The title of this post is quite a mouthful (I couldn’t come up with anything better), so let me start by describing the particular problem that got me thinking into this sort of things.

## DSLWP-B Moonbounce

If you have been following my latest posts, you will know that a series of observations with the DSLWP-B Inory eye camera have been scheduled over the last few days to try to take and download images of the Moon and Earth (see my last post). In a future post I will do a chronicle of these observations.

On October 6 an image of the Moon was taken to calibrate the exposure of the camera. This image was downlinked on the UTC morning of October 7. The download was commanded by Reinhard Kuehn DK5LA and received by the Dwingeloo radiotelescope.

Cees Bassa observed that in the waterfalls of the recordings made in Dwingeloo a weak Doppler-shifted signal of the DSLWP-B GMSK signal could be seen. This signal was a reflection off the Moon.

As far as I know, this is the first reported case of satellite-Moon-Earth (or SME) propagation, at least in Amateur radio. Here I do a Doppler analysis confirming that the signal is indeed reflected on the Moon surface and do some general remarks about the possibility of receiving the SME signal from DSLWP-B. Further analysis will be done in future posts.