Meeting Agenda
1. Call to Order
2. Approval of Agenda
3. Approval of Minutes of previous mtg
4. IEEE Patent Policy
5. Discussion of Draft Standard
6. Other Business
7. Future Meetings
8. Adjourn
Minutes of SAR Metadata Std Working Group Meeting
September 24, 2020
1. Call to order
attendees:
Leland Pierce
Wade Schwartzkopf
Marc Trachy
Chuck Heazel
Mike Stewart
Nathan Bombaci
Alexander Awuviri
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2. Approval of agenda
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Marc moved, Mike seconded, no discussion, no opposition
approved.
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3. Approval of minutes of previous meeting
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Marc moved, Mike seconded, no discussion, no opposition
approved.
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4. IEEE Patent and Copyright Policy
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1. slides 1-4 were shown and discussed by the chair
2. Chair provided an opportunity for participants to identify patent
claim(s)/patent application claim(s) and/or the holder of patent
claim(s)/patent application claim(s) of which the participant is
personally aware and that may be essential for the use of that
standard.
Wade has a version of the letter that his lawyers are going to send to
IEEE for approval.
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5. Discussion of current draft standard
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Wade presented his views on the polynomial vs. grid issue, and
the group had a discussion.
In either case, the region of validity needs to be specified.
So that the “fit” is not used where it is not valid.
JPL Study of spaceborne orbits:
state vectors with a suggested polynomial was sufficient for sub-mm
accuracy.
airborne: to track actual flight path polynomials would provide
insufficent accuracy. But generally once we have SLC, we don’t need to
know the actual flight-path, but the “virtual” one used with
motion-compensation applied.
Everything we have in every SAR dataset so far does not “need” the
abilities of the grid/spline approach as they are all well-behaved
functions.
Marc mentioned that basically it came down to what the user does with
the data. Even with a polynomial or grid, they could do a simple
constant, or linear fit, and not need or care about differentiability,
etc.
Mike brouhgt up the idea of the sampling used for a grid: is it
regularly sampled, or irregular? How would this be used with splines?
Marc said he thought that irregularly-sampled data does not work well
with splines.
Wade is curious why anybody would care about accurate models for
badly-behaved antenna patterns, since this has already been applied ot
the data.
Mike brought up the idea that sure, current systems have parameterrs
that can be modeled accuately with polynomials. But do we want to
preclude the use of our standard with some future system whose
parameters need the grid/spline approach?
Marc mentioned that users could still fit polynomials to grid
data. It’s up to them how they use. We just provide the suggestion as
to what to use, and what accuracy is provided by that choice.
Overall, I think we agreed that the representation of the data with
grids/splines is the most general, and so best to use it to allow for
flexibility for future systems.
…and that we must add some things to such a representation:
1. an explicit range of validity,
2. some kind of error measures, like worst-case, rms, etc…
when using the suggested fitting procedure: cubic splines.
Now, someone needs to come up with a metadata representation for this.
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6. Other business?
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none
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7. Next meeting
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the group wanted to have the next meeting in 2 weeks, at 11am.
Our next meeting will be on :
Thursday, OCT 8, 11AM Eastern time
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8. Adjourn
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Marc motioned, Wade seconded. no opposition. passed