## Detecting the Sprites from KickSat-2

The Sprites chipsats are tiny satellites built on a 3.5×3.5cm PCB with the bare minimum electronics to do something useful: a CC430 microcontroller with integrated FSK transceiver, an IMU, and solar cells.

The Sprites have been developed as part of the KickSat project, led by Zac Manchester, from Stanford University. The idea is to carry up to 128 Sprites in a cubesat and deploy them in a swarm once the cubesat is in orbit. The first test of this concept was done by the KickSat 3U cubesat in 2014. The test was a failure, since the Sprites couldn’t be deployed before KickSat reentered.

The second test was made this year with the KickSat-2 3U cubesat, a reflight of the KickSat mission carrying 104 Sprites. KickSat-2 was launched to the ISS onboard Cygnus NG-10 in November 2018 and deployed into orbit in February 2019.

On March 19, the Sprites were successfully deployed from KickSat-2, as Zac announced in Twitter, requesting help from the Amateur radio community to receive the signals from the Sprites at 437.240MHz. On March 22, Cees Bassa and Tammo Jan Dijkema tried to detect the Sprites by doing a planar scan with the Dwingeloo 25m radiotelescope. They were successful, detecting several transmissions from the Sprites in the waterfall. At that moment, the Sprites were up to 5 minutes ahead KickSat-2, due to their much higher drag to mass ratio. They all probably reentered a few days after this.

All the Sprites transmit in the same frequency using CDMA, so further analysis is required to identify which Sprites were observed by Dwingeloo. Zac said he was working on decoding the recording, however, I haven’t seen any results published yet. Here I show my analysis of the recording made at Dwingeloo. I manage to detect 4 different Sprites.

## Recovering an image transmitted by DSLWP-B

The image accompanying this post has a nice story to it. It was taken by the Amateur camera in DSLWP-B, the Chinese microsatellite in lunar orbit. On February 27, a download of this image was attempted by transmitting the image in SSDV format in the 70cm band and receiving it in the Dwingeloo radiotelescope, in the Netherlands.

The download was attempted twice, but due to errors in the transmission, a small piece of the image was still missing. Today, the Amateur payload of DSLWP-B was active again, and the plan was to download the missing piece, as well as other images. However, after the payload turned on and transmitted its first telemetry beacons, we discovered that the image had been overwritten.

The camera on-board DSLWP-B has a buffer that stores the last 16 images taken. Any of these images can be selected to be transmitted (completely or partially) while the Amateur payload is active. An image can be taken manually by issuing a command from ground. Besides this, every time the Amateur payload powers on, an image is taken. Of course, taking new images overwrites the older ones.

This is what happened today. The image we wanted to download was the oldest one in the buffer and got overwritten as soon as the payload turned on. This is a pity, especially because there was another activation of the payload last Friday, but a large storm in Germany prevented Reinhard Kuehn DK5LA’ from moving his antennas safely, so the satellite couldn’t be commanded to start the download.

After seeing that the image had been overwritten, Tammo Jan Dijkema suggested that I try to recover manually the missing chunk in the recording made on February 27. As you can see, I was successful. This is a report of how I proceeded.

## Batch processing of DSLWP-B Moonbounce: part I

In previous posts I’ve talked about how the DSLWP-B 70cm signal can sometimes be received in the Dwingeloo 25m radiotelescope via a reflection off the Moon’s surface. I’ve studied the geometry of this reflection, the cross-correlation against the direct signal, and even decoded some reflected JT4G.

However, so far the reflection has been detected by hand by looking at the recording waterfalls. We don’t have any statistics about how often it happens or which conditions favour it. I want to make some scripts to process all the Dwingeloo recordings in batch and try to extract some useful conclusions from the data.

Here I show my first script, which computes the power of the direct and reflected signals (if any). The analysis of the results will be done in a future post.

## Decoding TANUSHA-3

On August 15, during a Russian EVA on the ISS, a total of four Russian nanosatellites were deployed by hand. Although different online sources give incomplete and contradictory information about which satellites were released, it seems that they were SiriusSat 1 and 2, from the Sirius educational centre in Sochi, and Tanusha 3 and 4 from the Southwest State University in Kursk (see also Jonathan McDowell’s space report).

The SiriusSats are using 4k8 FSK AX.25 packet radio at 435.570MHz and 435.670MHz respectively, using callsigns RS13S and RS14S. The Tanushas transmit at 437.050MHz. Tanusha-3 normally transmits 1k2 AFSK AX.25 packet radio using the callsign RS8S, but Mike Rupprecht sent me the other day a recording of a transmission from Tanusha-3 that he could not decode.

It turns out that the packet in this recording uses a very peculiar modulation. The modulation is FM, but the data is carried in audio frequency phase modulation with a deviation of approximately 1 radian. The baudrate is 1200baud and the frequency for the phase modulation carrier is 2400Hz. The coding is AX.25 packet radio.

Why this peculiar mode is used in addition to the standard 1k2 packet radio is a mystery. Mike believes that the satellite is somehow faulty, since the pre-recorded audio messages that it transmits are also garbled (see this recording). If this is the case, it would be very interesting to know which particular failure can turn an AFSK transmitter into a phase modulation transmitter.

I have added support to gr-satellites for decoding the Tanusha-3 phase modulation telemetry. To decode the standard 1k2 AFSK telemetry direwolf can be used. The decoder flowgraph can be seen in the figure below.

The FM demodulated signal comes in from the UDP source. It is first converted down to baseband and then a PLL is used to recover the carrier. The Complex to Arg block recovers the phase, yielding an NRZ signal. This signal is lowpass filtered, and then clock recovery, bit slicing and AX.25 deframing is done. Note that it is also possible to decode this kind of signal differentially, without doing carrier recovery, since the NRZI encoding used by AX.25 is differential. However, the carrier recovery works really well, because there is a lot of residual carrier and this is an audio frequency carrier, so it should be very stable in frequency.

The recording that Mike sent me is in tanusha3_pm.wav. It contains a single AX.25 packet that when analyzed in direwolf yields the following.

RS8S>ALL:This is SWSU satellite TANUSHA-3 from Russia, Kursk<0x0d>
------
U frame UI: p/f=0, No layer 3 protocol implemented., length = 68
dest    ALL     0 c/r=1 res=3 last=0
source  RS8S    0 c/r=0 res=3 last=1
000:  82 98 98 40 40 40 e0 a4 a6 70 a6 40 40 61 03 f0  ...@@@...p.@@a..
010:  54 68 69 73 20 69 73 20 53 57 53 55 20 73 61 74  This is SWSU sat
020:  65 6c 6c 69 74 65 20 54 41 4e 55 53 48 41 2d 33  ellite TANUSHA-3
030:  20 66 72 6f 6d 20 52 75 73 73 69 61 2c 20 4b 75   from Russia, Ku
040:  72 73 6b 0d                                      rsk.
------


The contents of the packet are a message in ASCII. The message is of the same kind as those transmitted in AFSK.

## Detecting meteor scatter pings from GRAVES during the Perseids

GRAVES is a French space surveillance radar that transmits with very high power at 143.050MHz. It is easy to receive it from neighbouring countries via meteor scatter. During this year’s Perseids meteor shower I did a recording of GRAVES and the 2m Amateur band for later analysis. The recording was done at 08:56 UTC of Saturday 12th August and it is about 1 hour and 34 minutes long. Here I present an algorithm to detect and extract the meteor scatter pings from GRAVES.

## Trying to make the DSLWP-B GMSK decoder more robust

If you’ve being following my latest posts, probably you’ve seen that I’m taking great care to decode as much as possible from the SSDV transmissions by DSLWP-B using the recordings made at the Dwingeloo radiotelescope. Since Dwingeloo sees a very high SNR, the reception should be error free, even without any bit error before Turbo decoding.

However, there are some occasional glitches that corrupt a packet, thus losing an SSDV frame. Some of these glitches have been attributed to a frequency jump in the DSLWP-B transmitter. This jump has to do with the onboard TCXO, which compensates frequency digitally, in discrete steps. When the frequency jump happens, the decoder’s PLL loses lock and this corrupts the packet that is being received (note that a carrier phase slip will render the packet undecodable unless it happens very near the end of the packet).

There are other glitches where the gr-dslwp decoder is at fault. The ones that I’ve identify deal in one way or another with the detection of the ASM (attached sync marker). Here I describe some of these problems and my proposed solutions.

## Report for today’s DSLWP-B SSDV session

Today an SSDV transmission session from DSLWP-B was programmed between 7:00 and 9:00 UTC. The main receiving groundstation was the Dwingeloo radiotelescope. Cees Bassa retransmitted the reception progress live on Twitter. Since the start of the recording, it seemed that some of the SSDV packets were being lost. As Dwingeloo gets a very high SNR and essentially no bit errors, any lost packets indicate a problem either with the transmitter at DSLWP-B or with the receiving software at Dwingeloo.

My analysis of last week’s SSDV transmissions spotted some problems in the transmitter. Namely, some packets were being cut short. Therefore, I have been closely watching out the live reports from Cees Bassa and Wei Mingchuan BG2BHC and then spent most of the day analysing in detail the recordings done at Dwingeloo, which have been already published here. This is my report.

## DSLWP-B corrupted SSDV frames

In my previous post I looked at the first SSDV transmission made by DSLWP-B from lunar orbit. There I used the recording made at the Dwingeloo radiotelescope and showed how to decode the SSDV frames and produce a JPEG image.

Only four SSDV frames where transmitted by DSLWP-B, and out of those four, only two could be decoded correctly. I wondered why the decoding of the other two frames failed, since the SNR of the signal as recorded at Dwingeloo was very good, yielding essentially no bit errors (even before FEC decoding).

Now I have looked at the signal more in detail and have found the cause of the corrupted SSDV frames. I have demodulated the signal in Python and have looked at the position where an ASM (attached sync marker) is transmitted. As explained in this post, the ASM marks the beginning of each Turbo codeword. The Turbo codewords are 3576 symbols long and contain a single SSDV frame.

A total of four ASMs are found in the GMSK transmission that contains the SSDV frames, which matches the four SSDV transmitted. However, the distance between some of the ASMs doesn’t agree with the expected length of the Turbo codeword. Two of the Turbo codewords where cut short and not transmitted completely. This explains why the decoding of the corresponding SSDV frames fails.

The detailed analysis can be seen in this Jupyter notebook.

This is rather interesting, as it seems that DSLWP-B had some problem when transmitting the SSDV frames. I have no idea about the cause of the problem, however. It would be convenient to monitor carefully future SSDV transmissions to see if any similar problem happens again.

## DSLWP-B GMSK detector

Following the success of my JT4G detector, which I used to detect very weak signals from DSWLP-B and was also tested by other people, I have made a similar detector for the 250baud GMSK telemetry transmissions.

The coding used by the DSLWP-B GMSK telemetry follows the CCSDS standards for turbo-encoded GMSK/OQPSK. The relevant documentation can be found in the TM Synchronization and Channel Coding and Radio Frequency and Modulation Systems–Part 1: Earth Stations and Spacecraft blue books.

The CCSDS standards specify that a 64bit ASM shall be attached to each $$r=1/2$$ turbo codeword. The idea of this algorithm is to correlate against the ASM (adequately precoded and modulated in GMSK). The ASM spans 256ms and the correlation is done as a single coherent integration. As a rule of thumb, this should achieve a reliable detection of signals down to around 12dB C/N0, which is equivalent to -12dB Eb/N0 or -22dB SNR in 2500Hz. Note that the decoding threshold for the $$r=1/2$$ turbo code is around 1.5dB Eb/N0, so it is much easier to detect the GMSK beacon using this algorithm than to decode it. The difficulty of GMSK detection is comparable to the difficulty of JT4G decoding, which has a decoding threshold of around -23dB SNR in 2500Hz.

Here I explain the details of this GMSK ASM detector. The Python script for the detector is dslwp_gmsk.py.

## DSLWP-B detected with 7 element yagi

Yesterday I tried to detect DSLWP-B using my 7 element Arrow satellite yagi. The test schedule for DSLWP-B was as follows: active between 21:00 and 23:00 UTC on 2018-06-22. GMSK telemetry transmitted both on 435.4MHz and 436.4MHz. JT4G only on 435.4MHz every 10 minutes starting at 21:10. The idea was to record the tests with my equipment and the run my JT4G detector, which should be able to detect very weak signals. Today I have processed the recorded data and I have obtained a clear detection of one of the JT4G transmissions (albeit with a small SNR margin). This shows that it is possible to detect DSLWP-B with very modest equipment.