WSJT-X and linear satellites: part II

This is a follow-up to the part I post about using WSJT-X modes through a linear transponder on a LEO satellite. In part I, we considered the tolerance of several WSJT-X modes to the residual Doppler produced by a temporal offset in the Doppler computation used for computer Doppler correction. There, we introduced a parameter \delta which represents the time shift between the real Doppler curve and the computed Doppler curve. The main idea was that a decoder could try to correct the residual Doppler by trying several values of \delta until a decode is produced.

Here we examine the effect of TLE age on the accuracy of the Doppler computation. The problem is that, when a satellite pass occurs, TLEs have been calculated at an epoch in the past, so there is an error between the actual Doppler curve and the Doppler curve predicted by the TLEs. We show that the actual Doppler curve is very well approximated by applying a time shift to the Doppler curve predicted by the TLEs, justifying the study in part I.

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Acquisition and wipeoff for JT9A

Lately, I have been playing around with the concept of doing acquisition and wipeoff of JT9A signals, using a locally generated replica when the transmitted message is known. These are concepts and terminologies that come from GNSS signal processing, but they can applied to many other cases.

In GNSS, most of the systems transmit a known spreading sequence using BPSK. When the signal arrives to the receiver, the frequency offset (given by Doppler and clock error) and delay are unknown. The receiver runs a search correlating against a locally generated replica signal which uses the same spreading sequence. The correlation will peak for the correct values of frequency offset and delay. The receiver then mixes the incoming signal with the replica to remove the DSSS modulation, so that only the data bits that carry the navigation message remain. This process can be understood as a matched filter that removes a lot of noise bandwidth. The procedure is called code wipeoff.

The same ideas can be applied to almost any kind of signal. A JT9A signal is a 9-FSK signal, so when trying to do an FFT to visually detect the signal in a spectrum display, the energy of the signal spreads over several bins and we lose SNR. We can generate a replica JT9A signal carrying the same message and at the same temporal delay than the signal we want to detect. Then we mix the signal with the complex conjugate of the replica. The result is a CW tone at the difference of frequencies of both signals, which we call wiped signal. This is much easier to detect in an FFT, because all the energy is concentrated in a single bin. Here I look at the procedure in detail and show an application with real world signals. Recordings and a Python script are included.

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WSJT-X and linear satellites: part I

Several weeks ago, in an AMSAT EA informal meeting, Eduardo EA3GHS wondered about the possibility of using WSJT-X modes through linear transponder satellites in low Earth orbit. Of course, computer Doppler correction is a must, but even under the best circumstances we cannot assume a perfect Doppler correction. First, there are errors in the Doppler computation because the TLEs used are always measured at an earlier time and do not reflect exactly the current state of the satellite. This was the aspect that Eduardo was studying. Second, there are also errors because the computer clock is not perfect. Even a 10ms error in the computer clock can produce a noticeable error in the Doppler computation. Also, usually there is a delay between the time that the RF signal reaches the antenna and the time that the Doppler correction is computed for and applied to the signal, especially if using SDR hardware, which can have large buffers for the signal. This delay can be measured and compensated in the Doppler calculation, but this is usually not done.

Here we look at errors of the second kind. We denote by D(t) the function describing the Doppler frequency, where t is the time when the signal arrives at the antenna. We assume that the correction is not done using D(t), but rather D(t - \delta), where \delta is a small constant. Thus, a residual Doppler D(t)-D(t-\delta) is still present in the received signal. We will study this residual Doppler and how tolerant to it are several WSJT-X modes, depending on the value of \delta.

The dependence of Doppler on the age of the TLEs will be studied in a later post, but it is worthy to note that the largest error made by using old TLEs is in the along-track position of the satellite, and that this effect is well modelled by offsetting the Doppler curve in time. This justifies the study of the residual Doppler D(t)-D(t-\delta).

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A first look at DSLWP SSDV downlink

The Chang'e 4 is a Chinese lunar mission that will land a rover on the far side of the Moon by the end of 2018. To support this mission, the Chang'e 4 relay satellite will be launched six months before and put into a halo orbit around the Earth-Moon Lagrange L2 point. The relay will provide four 256Kbps links with the rover and lander on X-band and a 2Mbps link with Earth on S-band using a 4.2m dish. Two CE-4 microsatellites will be launched together with the relay satellite. They will be put in a 200km x 9000km lunar elliptical orbit. The main mission of the CE-4 microsatellites is to perform HF interferometry of celestial bodies, using the Moon as a shield from the radiation of the Sun and Earth. The satellites also carry an Amateur radio system called DSLWP, which will provide telecommand, telemetry and image downlink.

A team at Harbin Institute of Technology is currently designing the Amateur radio payload. As it is the case with previous HIT satellites such as BY70-1 and LilacSat-1, the payload will have a camera which can be telecommanded by radio Amateurs, which can use it to take and download pictures. Yesterday, Wei BG2BHC has released some work in progress of the image downlink. Many important parts of the downlink will still change, but releasing the work in progress at this early stage is a very good idea. Probably it is not too late in the development process so that the Amateur community can contribute with ideas and improvements.

The release consists of an IQ recording of the signal containing a full image and a decoder in gr-lilacsat. The IQ recording is at 2ksamp/s, since the signal is FSK at 250baud. Note that the recording is almost 32 minutes long. It takes a while to transmit an image at such a low rate. However, a low baudrate and a good amount of FEC are needed for an effective downlink from the Moon, given the huge path loss of around 197dB in the 70cm band.

The good news about this work in progress is that SSDV is now used to transmit the image. SSDV is a packetised protocol based on JPEG, but which is tolerant to packet loss. In contrast, BY70-1 and LilacSat-1 send JPEG images in 64byte chunks, and a single lost chunk can destroy the image completely. SSDV was originally developed to transmit images from Amateur high altitude ballons, so it is a good idea to use it also for DSLWP.

The bad news is that the way that SSDV has been included into the downlink protocol is not very optimal. In the rest of this post I do an in-depth look at the protocol, point out the main problems and suggest some solutions. Hopefully the protocol can still be modified and improved.

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LilacSat-1 downlink usage

In my previous post, I examined a recording of LilacSat-1 transmitting an image. I did some calculations regarding the time it would take to transmit that image and the time that it actually took to transmit, given that the image was interleaved with telemetry packets. I wondered if the downlink KISS stream capacity was being used completely.

You can find more information about the downlink protocol of LilacSat-1 in this post. The important information to know here is that it consists of two interleaved channels: a channel that contains Codec2 frames for the FM/Codec2 repeater and a channel that contains a KISS stream. The KISS stream is sent at 3400bps. At any moment in time, the KISS stream can be either idling, by sending c0 bytes, or transmitting a CSP packet. The CSP packets can be camera packets (which are sent to CSP destination 6) or telemetry packets (and perhaps also other kinds of packets).

I have extracted the KISS stream from the recording and examined its usage to determine if it is being used at its full capacity or if it spends time idling. The image below represents the usage of each byte in the KISS stream, as time progresses. Bytes belonging to image packets are shown in blue, bytes belonging to other packets are shown in red and idle bytes are shown in white. (Remember that you can click the images to view them in full size).

The first 3 or 4 seconds of the graph are garbage, since the signal wasn't strong enough. Then we see some telemetry packets and the image transmission starts. We observe that most image packets are transmitted leaving an idle gap between them. The size of the gap is similar to the size of the image packet. Every 10 seconds, a bunch of telemetry packets are transmitted, in a somewhat different order each time. Some telemetry packets are sent back to back, and others are interleaved with image packets. Image packets are only sent back to back just after a telemetry transmission.

The next graph shows the usage of the KISS stream averaged over periods of 5 secons. The y-axis means fraction of capacity of the link, so a 1 means that the full 3400bps are used. The capacity spent for image packets is shown in blue and the capacity used for telemetry is shown in red. The green curve is the sum of the blue and red, so it means the fraction of time that the link is not idle. We see that the link is never used completely. The total usage ranges between 60% and 90%, but never reaches 100%.

As expected, the capacity used for telemetry spikes up every 10 seconds. The blue curve is more interesting. It is roughly around 55%, but whenever telemetry is sent, it decreases a little. Just after each telemetry burst, the blue curve increases a little. This matches the behaviour we have seen in the previous graph. Every 10 seconds a telemetry burst is sent, using up some capacity that would normally be spent for image. After the telemetry burst, some image packets are sent back to back in a burst, peaking up to 60% capacity, but soon the packets continue being sent with idle gaps between them, and the capacity goes down to 55%.

It is a bit strange that the link is not fully utilised. One would expect that image packets are sent as fast as possible, stopping only to send telemetry. However, we have seen that there are many idle gaps. It seems that the image can't be read very fast or that there is some other throttling mechanism. This would explain why a burst of image packets is sent after each telemetry burst: the image packets buffer up, because the link is sending telemetry. When the link is no longer busy with telemetry, it sends all the buffered image packets in a row, but soon enough image packets can't be produced as fast as the link sends them, so idle gaps appear. This seems quite an important performance issue, as it appears that image transmission speed is capped at about 1870bps.

The Python code that generated these graphs can be seen below. The KISS file is also in the same gist.

Waterfalls from the EAPSK63 contest

Last weekend, I recorded the full EAPSK63 contest in the 40m band with the goal of monitoring IMD levels. I made a 48kHz IQ recording spanning the full 24 contest hours (from 16:00 UTC on Saturday to 16:00 UTC on Sunday). This week I've been playing with making waterfall plots from the recording. These are very interesting, showing patterns in propagation and contest activity. Here I show some of the waterfalls I've obtained, together with the Python code used to compute them.

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Monitoring IMD levels in the EAPSK63 contest

This weekend I have recorded the full EAPSK63 Spanish PSK63 contest in the 40m band with the goal of playing back the recording later and reporting the stations showing excessively high IMD levels. In PSK contests, it is usual to see terribly distorted signals, which are the result of reckless operating techniques and stations which are setup inadequately. Contest rules don't help much, as they are usually too weak to prevent distorted signals from interfering other participants. Amateurs should take care and strive to produce a signal as clean as possible. For instance, in the US, Part 97 101 a) states that "each amateur station must be operated in accordance with good engineering and good amateur practice". Here I describe the signal processing done in this study and list a "hall of shame" of the worst stations I have spotted in my recording. I will notify by email the contest manager and all the stations in this list with the hope that the situation improves in the future.

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GNU Radio decoder for AO-73

During the last few days, I have been talking with Edson PY2SDR about using GNU Radio to decode digital telemetry from AO-73 (FUNcube-1) and other FUNcube satellites. I hear that in Virginia Tech Groundstation they have a working GNU Radio decoder, but it seems they never published it.

The modulation that the FUNcube satellites use is DBPSK at 1200baud. The coding is based on a CCSDS concatenated code with a convolutional code and Reed-Solomon, but it makes extensive use of interleaving to combat the fading caused by the spin of the spacecraft. This system was originally designed by Phil Karn KA9Q for AO-40. Phil has a description of the AO-40 FEC system in his web and there is another nice description by James Miller G3RUH.

I took a glance at this documents and noted that it would be a nice and easy exercise to implement a decoder in GNU Radio, as I have most of the building blocks that are needed already working as part of gr-satellites. Today, I have implemented an out-of-tree module with a decoder for the AO-40 FEC in gr-ao40. There is another gr-ao40 project out there, but it seems incomplete. For instance, it doesn't have any code to search for the syncword. I have also added decoders for AO-73 and UKube-1 to gr-satellites.

The signal processing in gr-ao40 is as described in the following diagram taken from G3RUH's paper.

AO-40 FEC decoding (borrowed from G3RUH's paper)

First, the distributed syncword is searched using a C++ custom block. It is possible to set a threshold in this block to account for several bit errors in the syncword. De-interleaving is done using another C++ custom block. For Viterbi decoding, I have used the "FEC Async Decoder" block from GNU Radio, since I like to use stock blocks when possible. Then, CCSDS descrambling is done with a hierarchical block from gr-satellites. Finally, the interleaved Reed-Solomon decoders are implemented in a C++ custom blocks that uses Phil Karn's libfec.

The complete FEC decoder is implemented as a hierarchical block as show in the figure below.

GNU Radio AO-40 FEC decoder

Open telecommand for BY70-1

Recently, Wei BG2BHC has published instructions for the use of BY70-1's camera by Amateurs. Essentially, there are three commands that can be used: 0x00 to take a picture and send it, 0x55 to take a picture and store it in memory, and 0xaa to send the picture stored in memory. He also gives the modulation and coding details for the commands. They use AX.25 with 1000baud FM-AFSK with tones at 1000Hz and 1833.33Hz. The AX.25 frames are UI frames containing a single byte with the command (0x00, 0x55 or 0xaa as described above). For ease of use, he also gives WAV recordings of the three commands, so they can be played back easily into an FM transmitter by any Amateur. Here I look at the contents of these WAV files and how to process and create this kind of packets.

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KS-1Q decoded

In a previous post, I talked about my attempts to decode KS-1Q. Lately, WarMonkey, who is part of the satellite team, has been giving me some extra information and finally I have been able to decode the packets from the satellite. The decoder is in gr-ks1q, together with a sample recording contributed by Scott K4KDR. I've also added support for KS-1Q in gr-satellites. Here I look at the coding of the packets in more detail.

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