Tianwen-1 post–TCM-1 state vectors

Yesterday I reported about Tianwen-1’s first trajectory correction manoeuvre, TCM-1. In that post I commented the possibility that the updated state vectors that we saw on the telemetry after TCM-1 might come from a prediction or planning rather than take into account the actual performance of the burn.

The figure below shows the error between the state vectors collected after TCM-1 over the last two days, and a trajectory propagated in GMAT, using the following state vector, which is one of the first received after TCM-1.

[0151059eb9ea] 2020-08-02 00:17:06.711400 100230220.21360767 -106145016.11787066 -45441035.07405791 25.581827920522485 18.240707152437626 8.567874276424218

We see that on the UTC night between August 1 and 2 the state vectors deviate very little from the GMAT trajectory. However, on the UTC night between August 2 and 3 we see a slightly different trajectory in the state vectors. We have no data in between, as the spacecraft is not visible in Europe, so we don’t know the precise moment of change. The gap in telemetry around 2020-08-03 00:45 UTC is due to a transmission of high-speed data.

It seems reasonable to think that after TCM-1 the Chinese DSN performed precise ranging of the spacecraft to determine the new orbit accurately and then uploaded a correction to the state vectors on-board Tianwen-1.

The state vectors from last night all describe the same trajectory, as shown in the plot below which uses

[0151322e67d0] 2020-08-02 21:03:08.078400 102132184.96868199 -104770375.00352533 -44795830.46284772 25.29849580646669 18.532513218789806 8.692135086385246

to propagate a trajectory in GMAT. There is a small jump of a few hundred meters at some point. We usually see one or two these jumps per day, but we don’t understand well why they happen.

The trajectory according to the state vectors from 00:17:06 and from 21:03:08 are very similar. For example, at the closest approach to Mars they only differ in 1197km. For comparison, the difference between the new trajectory and the pre–TCM-1 trajectory is 126529km (again, at the closest approach to Mars).

I have generated a new table of right-ascension, declination and distance coordinates based on the updated state vectors. Note that this table doesn’t include light-time delay to the spacecraft.

Thanks to AMSAT-DL‘s Bochum observatory team and to Paul Marsh M0EYT for their continuous effort in tracking Tianwen-1. The data used in this post has come from their observations.

Tianwen-1 TCM-1

On 2020-08-01 23:00 UTC, Tianwen-1 made its first correction manoeuvre, called TCM-1. The manoeuvre was observed by Amateur trackers, such as Edgar Kaiser DF2MZ, Paul Marsh M0EYT, and the 20m antenna at Bochum observatory, operated by AMSAT-DL. The news of the successful manoeuvre appeared in Chinese media, and in the German Wikipedia article for Tianwen-1 (thanks to Achim Vollhardt DH2VA for sharing this information).

Since Tianwen-1 transmits its own real time orbit state vectors in the telemetry, by comparing the vectors transmitted before and after TCM-1, and also by studying the Doppler observed by groundstations on Earth, we can learn more about the manoeuvre.

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Tianwen-1 manoeuvre and high-speed data

On the Beijing time morning of 2020-07-30, Tianwen-1 did something. Paul Marsh M0EYT reports that the probe first switched from the high gain antenna to the low gain antenna, then returned to the high gain antenna, and then switched to a high-speed data mode, finally coming back to the usual 16384baud telemetry.

r00t.cz has already analysed the telemetry data collected during this event. He reports that the high speed data was a replay of the telemetry produced during the period when the low gain antenna was used. He shows some interesting behaviour on APIDs 1280, 1281 and 1282 (see my previous post for a description of these during nominal operation). These seem to contain ADCS data.

This event was followed with some expectation by the Amateur deep space tracking community, since according to this paper Tianwen-1 would make the first correction manoeuvre (TCM-1) early on in the mission (day 9 is stated in the paper). However, by now it is clear that a true correction manoeuvre didn’t happen, since no significant change has been seen in the trajectory described by the state vectors transmitted in the spacecraft’s telemetry. However, this event might have been a very small thruster firing, in order to test the propulsion in preparation for the true TCM-1.

In this post, I look at the data during the high speed replay, following the same approach as in the previous post. With this data, I reach a definite conclusion of what happened during this event (I won’t spoil the mystery by stating it in advance). The description of the modulation and coding used by the high speed data will come in a later post.

The Jupyter notebook for the calculations in this post can be found here.

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Tracking Tianwen-1’s orbit to Mars: part II

Yesterday I published a post explaining how Tianwen-1 is transmitting real time state vectors for its own orbit in its telemetry and how we’ve used those to propagate its orbit and track the spacecraft with the Bochum observatory 20m dish. However, there seemed to be some problem in the way we were interpreting the state vectors, since the ephemerides derived from these had a pointing error of a few degrees when compared with observations from Bochum and other smaller Amateur stations.

As of writing that post, I believe I have found the problem. It has to do with the way that the timestamps from the state vectors are interpreted. After correcting this problem I am getting an orbit that matches the observations well. Here I explain this problem and show some more details about the corrected ephemerides.

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Tracking Tianwen-1’s orbit to Mars

Last Thursday 2020-07-23 at 04:41 UTC, Tianwen-1, a Chinese mission to Mars consisting of an orbiter, a lander and a rover, launched from Wenchang. Usually, I would be posting an analysis of a recording of the telemetry signal, made by Paul Marsh M0EYT or another of my Amateur DSN contributors, as I did a few days ago for the Emirates Mars Mission. However, something amazing has happened that has kept me quite busy. Rest assured that the analysis of the signal will come in a future post, but here I’m going to tell a story about Tianwen-1’s orbit.

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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.

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Advances with delta-range and delta-range rate observations in GMAT

A month ago I started modifying the GMAT EstimationPlugin to support delta-range observations. This work is needed in order to perform orbit determination with the VLBI observations that we did with DSLWP-B (Longjiang-2) during its mission. Now I have a version which is able to use both delta-range and delta-range rate observations in simulation and estimation. This is pretty much all that’s needed for the DSLWP-B VLBI observations.

The modified GMAT version and accompanying GMAT scripts for this project can be found in the gmat-dslwp Github repository. This post is an account of the work I’ve made.

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Simulating delta-range observations in GMAT

During the DSLWP-B (Longjiang-2) mission, we made a number of VLBI observations of the spacecraft’s UHF signal by performing GPS-synchronized recordings at Dwingeloo (The Netherlands), Shahe and Harbin (China), and Wakayama (Japan). The basic measurement for these observations is the time difference of arrival (TDOA), which measures the differences between the time that it takes the spacecraft’s signal to arrive to each of the groundstations. This can be interpreted in terms of the difference of distances between the spacecraft and each groundstation, so this measurement is also called delta-range.

One very interesting practical application of the VLBI observations is to perform orbit determination. The delta-range measurements can be used to constrain and determine the state vector of the spacecraft. This would give us an autonomous means of tracking Amateur deep-space satellites, without relying on ranging by a professional deep-space network. Even though the measurements we made showed good agreement with the ephemerides computed by the Chinese deep-space network, during the mission we never ran orbit determination with the VLBI observations, mainly due to the lack of appropriate software.

While GMAT has good support for orbit determination, it doesn’t support delta-range measurements. Its basic orbit determination data type is two-way round-trip time between a groundstation (or two) and the satellite, as shown in the orbit determination tutorial.

I have started to modify GMAT in the gmat-dswlp Github repository to implement the support for this kind of VLBI observations. As a first step, I am now able to create and simulate delta-range observations.

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DOP geographical distribution for the Galileo and GPS constellations

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.

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Trying to find the DSLWP-B crash site

As you may well know, DSLWP-B, the Chinese lunar orbiting Amateur satellite crashed with the Moon on July 31 as a way to end its mission without leaving debris in orbit. I made a post with my prediction, which showed the impact point southeast of Mare Moscoviense, in the far side of the Moon. Phil Stooke was more precise and located the impact point near the Van Gent crater.

Our plan is to get in contact with the LRO team and try to find the crash site in future LRO images. We are confident that this can be done, since they were able to locate the Beresheet impact site a few months ago. However, to help in the search we need to compute the location of the impact point as accurately as possible, and also come up with some estimate of the error to define a search area where we are likely to find the crash. This post is a detailed account of my calculations.

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