From 9dbda02b41786ddd1755c3b73e236825c4f3183d Mon Sep 17 00:00:00 2001 From: Noah Smith Date: Fri, 17 May 2024 14:04:19 +0200 Subject: [PATCH] starid77 --- _drafts/graphite.md | 6 ------ _drafts/lost-in-space.md | 38 ----------------------------------- _drafts/starid77.md | 24 ++++++++++++++++++++++ _posts/2024-05-17-starid77.md | 24 ++++++++++++++++++++++ 4 files changed, 48 insertions(+), 44 deletions(-) delete mode 100644 _drafts/graphite.md delete mode 100644 _drafts/lost-in-space.md create mode 100644 _drafts/starid77.md create mode 100644 _posts/2024-05-17-starid77.md diff --git a/_drafts/graphite.md b/_drafts/graphite.md deleted file mode 100644 index 2e9f34a..0000000 --- a/_drafts/graphite.md +++ /dev/null @@ -1,6 +0,0 @@ ---- -layout: post -title: "graphite" -categories: aerospace materials ---- -[photos](https://photos.app.goo.gl/rL5NTL2iFomFjedM6){:target="_blank" rel="noopener"} diff --git a/_drafts/lost-in-space.md b/_drafts/lost-in-space.md deleted file mode 100644 index 68cadf0..0000000 --- a/_drafts/lost-in-space.md +++ /dev/null @@ -1,38 +0,0 @@ ---- -layout: post -title: "lost in space problem" -categories: aerospace starid ---- -the core of the lost in space problem is the lack of star tracker pointing knowledge. often there's at least some knowledge of the star tracker's attitude, but the lost in space problem is the extreme opposite case, with infinite attitude uncertainty. - -the terms 'pointing' and 'attitude' are used interchangeably here. yaw around the pointing unit-vector is always included, and pointing is a rotation matrix, rotation vector, euler vector, quaternion, etc. the yaw is a challenge for image recognition algorithms, which often assume a stable image orientation. for lost in space, there's no 'gravity' and no 'upwards and downwards' stabilizing the images. - - low-resolution 'lo-fi' star tracker images force recognition algorithms to be more robust and coarsely tuned. there's a bare minimum of information in the images, with only crude, global features, and little opportunity for over-fitting and fine-tuning. with randomly oriented lo-fi images of 'naked-eye visual' stars, recognition generally won't be too different than what the human brain does, using broad patterns and relationships between the individual stars. - -the 'foundational' nature of lo-fi star tracker image recognition is reflected in using the 28 x 28 pixel format of the [mnist database](https://en.wikipedia.org/wiki/MNIST_database). all incoming information is encoded in 28 x 28 pixels, and successful star identification algorithms are necessarily robust and fundamental. - -here's a collection of earlier comments around the lost in space problem from this project. - -...snip... - -a vehicle in deep space accidentally tumbles out of control, loses power, and goes into a 'safety mode'. later, emergency systems regain power and stop the tumbling. the vehicle's star tracker snaps an image. what an onboard computer needs to do is match the stars in the image with entries in a star catalog. it's then straightforward to determine the vehicle's orientation in space. - -it turns out that the essence of the problem doesn't focus on two dimensional images. instead, the focus is on three dimensional unit vectors. true, for unit vectors one of the three coordinates is redundant. given the other two, the unit constraint determines the third. but each star is essentially 'purely a direction' in the star tracker's reference frame. purely a pointing vector. the image encodes a set of unit vectors pointing out of an origin in various directions. with appropriate knowledge of the star tracker's characteristics, a set of three dimensional unit vectors are immediately extracted from the image. - -this parallels the nature of star catalogs. star catalogs are collections of three dimensional unit vectors in an agreed on celestial reference frame. these days, the celestial frame is tied to the pointing directions to quasars, astronomical objects distant enough to be effectively 'fixed in space'. fixed landmarks as it were. star catalogs also provide names, brightnesses, etc, but here the core information is 'purely pointing direction'. - -so the lost in space problem is about matching a set of unit vectors in a sensor reference frame with a set of unit vectors in a star catalog reference frame. the unit vectors can point towards any patch of directions 'on the sky'. it's really about the whole sphere of the night sky, that's one of the core elements here. - -...snip... - -the answer was, no. there wasn’t an easy or obvious solution, and helping to figure out a practical method of identifying those particular stars on those particular plates was ultimately the real job. not that an undergrad had any chance of finding a real solution. but just becoming aware of and recognizing the magnitude of the problem was a huge step forward. how are stars recognized? humans could do it, but could an eighties computer system? - -surprisingly, though, it soon became clear that there was still no publicly-available software for the lost-in-space star identification problem. apparently, each time star identification software had been developed, it’s been within classified or industry projects. a serious interest in star identification was probably tied to selling star trackers, and that’s become a fairly mature industry. - -...snip... - -cultural differences between aerospace and computer science quickly became apparent. basically, networks want to be about two dimensional images, while aerospace wants to be about physical three dimensional unit vectors. what happened in practice was that a kind of image 'api' grew up organically over the unit vector geometry. this happened over a period of a few months, and a curious sequence of coincidences took place. - -low resolution makes the star identification problem more challenging and interesting. it forces use of global structures and patterns within an image, rather than localized features and heuristics. there’s simply less information available and more has to be done with less. it even suggests questions about how the human brain recognizes stars. for example, a typical high-resolution aerospace algorithm might focus on the exact separation between a pair of stars, along with the angle to a third star. that’s clearly not how the brain works. so, what's the brain in fact doing? - -focusing on lo-fi mnist-like images led to a discovery. to recognize a particular star in an image, it's helpful to shift the star to the image-center and make its presence implicit. there’s no point in including it in the image, it's effectivly redundant. what’s significant is the relative-geometry of the other stars. the target star becomes the origin of the coordinate system, and if there’s another star nearby, as often happens in a low resolution image, there’s no confusion. in practice, the effects are even nicer since, in a way, there's a 'free' extra star, and there's also less need for coordinate transformations. diff --git a/_drafts/starid77.md b/_drafts/starid77.md new file mode 100644 index 0000000..fd8643f --- /dev/null +++ b/_drafts/starid77.md @@ -0,0 +1,24 @@ +--- +layout: post +title: "starid77" +categories: aerospace starid +--- +[paper 1977](https://statespace.dev/docs/papers/1977%20junkins.pdf){:target="_blank" rel="noopener"} + +this paper is a time-capsule from the seventies, capturing the era when integrated-circuit 'chips' were fully coming on-line, at least for state of the art aerospace hardware, in two separate domains - microprocessors or 'systems on a chip', and charge-coupled device imagers or 'digital cameras'. + +the original was published in 77, and this is a pdf of an extended version from 78. 77 is a reminder of fortran77. fortran was born in 57, the same year as sputnik, and this paper is a window into the twentieth year of the space age and the fortran era. + +the star recognition algorithm is limited by the first-generation hardware, and nowhere near tackling the lost in space problem. it assumes an attitude estimate is available and sufficient to limit the pattern match to a 'sub-catalog' of stars, in other words a small region of the sky. it's an excellent historical review of the types of work done from the fifties thru the seventies. + +the discussion of the [fairchild semiconductor](https://en.wikipedia.org/wiki/Charge-coupled_device#History) ccd camera is of special interest. fairchild played an important role in the research and development phase of digital imaging. + +_Several companies, including Fairchild Semiconductor, RCA and Texas Instruments, picked up on the invention and began development programs. Fairchild's effort, led by ex-Bell researcher Gil Amelio, was the first with commercial devices, and by 1974 had a linear 500-element device and a 2D 100 × 100 pixel device._ + +the paper describes a 488 x 380 pixel device, so possibly fairchild's second generation ccd imager. the larger story around the transistor, shockley, fairchild, chips, and the birth of intel is too far afield for project starid, at least for now. + +beyond the purely technical history, this paper also captures a certain 'spirit of the times'. one element of the fortran era was the cold war sense of urgency around engineering and science. some of that legacy survives today in enclaves like the national science foundation, the [berkeley physics course](https://en.wikipedia.org/wiki/Berkeley_Physics_Course), the [feynman lectures on physics](https://en.wikipedia.org/wiki/The_Feynman_Lectures_on_Physics), and the remaining engineers and scientists from that generation. + +by the eighties and nineties, the fortran generation were becoming the teachers and role models. this paper captures a part of what that was like. it was created on a manual typewriter, and then poorly xeroxed multiple times. at the same time, it was discussing dramatic digital advances. it's on the divide between the analog and digital worlds. + +john junkins became a leading professor at texas a&m university and interacted directly with byron tapley, bob schutz, george born, the university of texas at austin center for space research, and the university of colorado at boulder laboratory for atmospheric and space physics. parts of that enter the project starid story, and the intention is to explore that over time. diff --git a/_posts/2024-05-17-starid77.md b/_posts/2024-05-17-starid77.md new file mode 100644 index 0000000..fd8643f --- /dev/null +++ b/_posts/2024-05-17-starid77.md @@ -0,0 +1,24 @@ +--- +layout: post +title: "starid77" +categories: aerospace starid +--- +[paper 1977](https://statespace.dev/docs/papers/1977%20junkins.pdf){:target="_blank" rel="noopener"} + +this paper is a time-capsule from the seventies, capturing the era when integrated-circuit 'chips' were fully coming on-line, at least for state of the art aerospace hardware, in two separate domains - microprocessors or 'systems on a chip', and charge-coupled device imagers or 'digital cameras'. + +the original was published in 77, and this is a pdf of an extended version from 78. 77 is a reminder of fortran77. fortran was born in 57, the same year as sputnik, and this paper is a window into the twentieth year of the space age and the fortran era. + +the star recognition algorithm is limited by the first-generation hardware, and nowhere near tackling the lost in space problem. it assumes an attitude estimate is available and sufficient to limit the pattern match to a 'sub-catalog' of stars, in other words a small region of the sky. it's an excellent historical review of the types of work done from the fifties thru the seventies. + +the discussion of the [fairchild semiconductor](https://en.wikipedia.org/wiki/Charge-coupled_device#History) ccd camera is of special interest. fairchild played an important role in the research and development phase of digital imaging. + +_Several companies, including Fairchild Semiconductor, RCA and Texas Instruments, picked up on the invention and began development programs. Fairchild's effort, led by ex-Bell researcher Gil Amelio, was the first with commercial devices, and by 1974 had a linear 500-element device and a 2D 100 × 100 pixel device._ + +the paper describes a 488 x 380 pixel device, so possibly fairchild's second generation ccd imager. the larger story around the transistor, shockley, fairchild, chips, and the birth of intel is too far afield for project starid, at least for now. + +beyond the purely technical history, this paper also captures a certain 'spirit of the times'. one element of the fortran era was the cold war sense of urgency around engineering and science. some of that legacy survives today in enclaves like the national science foundation, the [berkeley physics course](https://en.wikipedia.org/wiki/Berkeley_Physics_Course), the [feynman lectures on physics](https://en.wikipedia.org/wiki/The_Feynman_Lectures_on_Physics), and the remaining engineers and scientists from that generation. + +by the eighties and nineties, the fortran generation were becoming the teachers and role models. this paper captures a part of what that was like. it was created on a manual typewriter, and then poorly xeroxed multiple times. at the same time, it was discussing dramatic digital advances. it's on the divide between the analog and digital worlds. + +john junkins became a leading professor at texas a&m university and interacted directly with byron tapley, bob schutz, george born, the university of texas at austin center for space research, and the university of colorado at boulder laboratory for atmospheric and space physics. parts of that enter the project starid story, and the intention is to explore that over time.