STRF Mean Anomaly value

Hello, I’m a students with a undergrade thesis with a topic about STRF. I am observing three satellites (Cubesat XI-IV, Saudisat 1C, and LAPAN-A2) to estimate their orbit using Doppler observation and strf.

With LAPAN-A2, I get a TLE with very close number with that of reference TLE. But with Cubesat XI-IV and Saudisat 1C, I get mean anomaly number that is very different with the reference number (and get error when I checked with TLE validator.

Here one of the sample that I took from an observation on 25th April 2026:

TLE generated from strf:
1 27607U 02058C 26115.38765514 .00001017 00000-0 13739-3 0 9991
2 27607 64.5516 290.8647 0075584 272.1087 266.7100 14.82926048256607

Reference TLE:
1 27607U 02058C 26115.21880762 .00001017 00000-0 13739-3 0 9991
2 27607 64.5516 292.8529 0075584 272.1087 87.1365 14.82926048256607

You can see the mean anomaly is very different from the reference (TLE from Celestrak) and when I checked on TLE validator, its showing error.

Is there any explanation for that or a step that I missed on strf? It only happened after I updated the epoch on strf but not when I didn’t update it. The Cubesat XI-IV also has similar issue but not with LAPAN-A2.

Any help or input would be appreciated.
Thank you!

2 Likes

Oh I forgot, here’s a screenshot from the strf.

2 Likes

im also working with STRF too, maybe this should get more attention to
thanks namiken for sharing

1 Like

you should clean the dot, remove unnecesarry dot.

image

1 Like

Thanks for the input, I have cleaned the dot

Here is after fitting the Ascending Node and Mean Anomaly without fitting the epoch at all:

And here is after fitting the epoch, then the data (Ascending Node and Mean Anomaly):

You can see the Mean Anomaly value differs very much from the reference. If I fit the data first then the epoch, then the Ascending Node value will differ very much.

If I may, what is the correct step to fit the data, I may miss something as different step resulting with different value.

Thanks!

1 Like

can you inform the max elevation of sat when obs?

if check from screenshot seen low elevation

i recommend you to use another obs that have higher elevation. for the best result i recommend above 45 degree. more higher more accurate

2 Likes

The mean anomaly represents the position of the satellite in the orbit at epoch. So if you change the epoch you should expect mean anomaly to change. Quick calculation:

  • your epochs are 26115.3876 - 26115.2188 = ~0.169d apart
  • with a mean motion of ~14.829 rev/day, that means (assuming a circular orbit) you have moved 14.829 * 0.169 * 360° = 902°
  • 87° + 902° = 989°
  • that wraps to 989° - 2 * 360° = 269°

So a mean anomaly of 266.71° is pretty close to what I would expect.

Regarding RAAN I can’t tell you why there is a difference. But I don’t think you can reliably fit RAAN with measurements from only a single pass.

3 Likes

i test your tle on my observation around that date , and the result is better than before remove unnecessary dot

before:

1 27607U 02058C   26115.38765514  .00001017  00000-0  13739-3 0  9991
2 27607  64.5516 290.8647 0075584 272.1087  266.7100 14.82926048256607

after:

1 27607U 02058C   26115.38765722  .00000000  00000-0  13739-3 0    01
2 27607  64.5516 291.6288 0075584 272.1087 268.8242 14.82926048    09

so as @jazzpi post , the mean anomaly value is still ok, and not always close with the reference. mean anomaly between 0-360 degree is valid.

i use this tool

1 Like

Thank you for the calculation, that’s really make sense. After I plot the orbital parameter on python and orbitron, it looks more clear. I think its normal for a different epoch time to generate different mean anomaly value.

Thank you for your input, I didn’t think that step can really make that difference on the end TLE value. I thought more dots/measurement will result a better data.

Wow, this tools is really usefull. It helped to visually reassure that the TLE is “correct” compared to observations on satnogs station.

Sorry for late reply , but thank you very much for all the explanations. For now its clear but I’ll probably ask again in the future :slight_smile:

2 Likes

I know you recommended this tools a while ago but it was just now I’ve using it and I use it quite a bit :sweat_smile:

1 Like