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I use CNN for time series prediction (1D), not for image works (2D or 3D).

Learning Materials

  • How to Develop 1D Convolutional Neural Network Models for Human Activity Recognition
    • time series classification
    • two 1D CNN layers, followed by a dropout layer for regularization, then a pooling layer. 为什么这样?
      • It is common to define CNN layers in groups of two in order to give the model a good chance of learning features from the input data. 为什么这样?
      • CNNs learn very quickly, so the dropout layer is intended to help slow down the learning process
      • The pooling layer … consolidating them to only the most essential elements.
    • After the CNN and pooling, the learned features are flattened to one long vector
    • a standard configuration of 64 parallel feature maps and a kernel size of 3 (Where comes this “standard” configuration?)
    • a multi-headed model, where each head of the model reads the input time steps using a different sized kernel.
Read more »

I ran across this document page of pytransform3d, and it claims:

There are two different quaternion conventions: Hamilton’s convention defines ijk = -1 and the JPL convention (from NASA’s Jet Propulsion Laboratory, JPL) defines ijk = 1. We use Hamilton’s convention.

It’s not new to know about different definitions (mostly the sequency differs), but what is this ijk=1 definition? First time to hear about.

Then I continue diving into the reference source it provided.

Only after this, I found that the problem is not only about the sequence of the components, but about something more fundamental.
So I put down this summary for my future reference.

(q0,q1,q2,q3)(q_0, q_1, q_2, q_3) or (q1,q2,q3,q4)(q_1, q_2, q_3, q_4) ?

The answer is it doesn’t matter that much.
This is not a mathematical or fundamental difference.

Equations can be easily converted.
Codes can be easily modified.

ij=kij=k or ij=kij=-k

This is about math!

  1. Harold L. Hallock, Gary Welter, David G. Simpson, and Christopher Rouff, ACS without an attitude, London: Springer, 2017.
  • (p.16) Alternatively, one could follow a different convention with quaternion multiplication. Many authors prefer a convention that, although not expressed as such, essentially redefines Hamilton’s hyper-complex commutation relations (Eq. 1.5b above) into ij=k,kj=i,ki=ji j = -k, k j = -i, ki = -j

The quaternion representation is one of
the best characterizations, and this chapter will focus on this representation. The
presentation in this chapter follows the style of [99, 205, 219].

Which one is used in references?

Will keep updating as I read more references…

Using ij=kij=k and (q0,q1,q2,q3)(q_0, q_1, q_2, q_3)

  1. Yaguang Yang, Spacecraft Modeling, Attitude Determination, and Control Quaternion-based Approach, Boca Raton, FL : CRC Press, 2019. | “A science publishers book.”: CRC Press, 2019. [Link].

Using ij=kij=k and (q1,q2,q3,q4)(q_1, q_2, q_3, q_4)

  1. Harold L. Hallock, Gary Welter, David G. Simpson, and Christopher Rouff, ACS without an attitude, London: Springer, 2017.

Using ij=kij=-k and (q1,q2,q3,q4)(q_1, q_2, q_3, q_4)

还是没有搞明白为什么这就相当于重新定义了 ij=kij=-k

  1. F. Landis Markley, and John L. Crassidis, Fundamentals of Spacecraft Attitude Determination and Control, New York, NY: Springer New York, 2014.

  2. Malcolm D. Shuster, “The nature of the quaternion”, The Journal of the Astronautical Sciences, vol. 56, Sep. 2008, pp. 359–373.

  3. Hanspeter Schaub, and John L. Junkins, Analytical Mechanics of Space Systems (Second Edition), Reston, VA: American Institute of Aeronautics and Astronautics, 2009.
    (p.107) 似乎是默认了与 Rotation matrix 顺序一致的一种,即 ij=kij=-k

Official documents

Book:

Probabilistic Programming & Bayesian Methods for Hackers (Version 0.1)

PyMC3 is a Python library for programming Bayesian analysis [3]. It is a fast, well-maintained library. The only unfortunate part is that its documentation is lacking in certain areas, especially those that bridge the gap between beginner and hacker. One of this book’s main goals is to solve that problem, and also to demonstrate why PyMC3 is so cool.

We assign them to PyMC3’s stochastic variables, so-called because they are treated by the back end as random number generators.

Change Content root at Project Structure, so that I have the same pwd when run and execute selection in console.

  • 不然的话,两者的pwd有可能不同

USNavalResearchLaboratory/TrackerComponentLibrary at GitHub

The Tracker Component Library is a collection of Matlab routines for simulating and tracking targets in various scenarios. Due to the complexity of the target tracking problem, a great many routines can find use in other areas including combinatorics, astronomy, and statistics.

Recently, I ran into a very comprehensive MATLAB repository, which is very rare to my knowledge.
Usually people find comprehensive packages in other languages, like Orekit in Java, GMAT in C++, many others in Python, and even one in Julia.
So, I decide to have a look at it and take nots here.

碎片组成

In the centimeter range, the dominant source is fragments followed by slag particles from solid rocket motors.


[1]: Horstmann, A., Kebschull, C., Müller, S., Gamper, E., Hesselbach, S., Soggeberg, K., Ben Larbi, M. K., Becker, M., Lorenz, J., Wiedemann, C., and Stoll, E., “Survey of the Current Activities in the Field of Modeling the Space Debris Environment at TU Braunschweig,” Aerospace, vol. 5, Apr. 2018, p. 37.

The third largest contribution is
sodium-potassium droplets (NaK droplets) that have been released from orbital nuclear reactors and
are highlighted here as an example. These droplets are found today mainly in orbits near 900km
altitude and are treated as a historical source due to their early generation but relatively late discovery.

An estimated 250 g have been released per event [23];
however, since these droplets were observed during radar measurements [25], they are considered in
the model for the sake of completeness. In total, there are now about 20,000 droplets in space, mostly in
orbits near 900km altitude [26].

The contribution of droplets in the entire centimeter population at 800km altitude today
is about 10% [23].


TLE


[1]: Horstmann, A., Kebschull, C., Müller, S., Gamper, E., Hesselbach, S., Soggeberg, K., Ben Larbi, M. K., Becker, M., Lorenz, J., Wiedemann, C., and Stoll, E., “Survey of the Current Activities in the Field of Modeling the Space Debris Environment at TU Braunschweig,” Aerospace, vol. 5, Apr. 2018, p. 37.

Two Line Elements that are provided by the Joint Space Operations Center (JSpoC) have a
low precision due to the analytic SGP4-propagation theory, which can amount to several hundred
meters [41,42], whereas precise orbit data is not accessible to publicity.