John L. Crassidis, and John L. Junkins, Optimal Estimation of Dynamic Systems, CRC Press, 2011.
Corrections to the book can be found at here.
John L. Crassidis, and John L. Junkins, Optimal Estimation of Dynamic Systems, CRC Press, 2011.
Corrections to the book can be found at here.
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) definesijk = 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.
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.
This is about math!
- Harold L. Hallock, Gary Welter, David G. Simpson, and Christopher Rouff, ACS without an attitude, London: Springer, 2017.
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].
Will keep updating as I read more references…
还是没有搞明白为什么这就相当于重新定义了 $ij=-k$
F. Landis Markley, and John L. Crassidis, Fundamentals of Spacecraft Attitude Determination and Control, New York, NY: Springer New York, 2014.
Malcolm D. Shuster, “The nature of the quaternion”, The Journal of the Astronautical Sciences, vol. 56, Sep. 2008, pp. 359–373.
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 $ij=-k$
TF blog: Regression with Probabilistic Layers in TensorFlow Probability
RG: Is it possible to get confidence intervals in LSTM forecasting?
Gaussian process 的重要组成部分——关于那个被广泛应用的Kernel的林林总总
An Introduction to Latent Variable Models
Gaussian Process Regression using Spectral Mixture Kernel in GPflow
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.
I use CNN for time series prediction, not for image works.
Keras.layers.Conv1D
的所有要点an effective approach might be to combine CNNs and RNNs in this way: first we use convolution and pooling layers to reduce the dimensionality of the input. This would give us a rather compressed representation of the original input with higher-level features. (from here)
像Fourier analysis这种，用一组完备的基函数，去表示任意一个函数，这种研究，wavelet analysis, taylor expansion，这些感觉都是一个思路，只是不同的基函数。
那么，有没有研究用 非正交的、非完备的、冗余很大的 一组基函数，去展开任意一个函数的数学分支？
感觉这个和现在的各种机器学习的骚操作很像啊……
Excerpt some information about the attitude subsystem of CubeSats.
Learned something about the attitude estimation EKF used in several books and papers. Try to note something here to clarify their relationships.
The only thing I’m sure about is:
The quaternion attitude
+ gyro bias
estimator is widely used in practice.
Hanspeter Schaub, and John L. Junkins, Analytical Mechanics of Space Systems (Second Edition), Reston, VA: American Institute of Aeronautics and Astronautics, 2009.
I just roughly read section 3, mainly about the attitude basics and kinematics.
Change Content root
at Project Structure
, so that I have the same pwd
when run
and execute selection in console
.
pwd
有可能不同