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    Re: How good is St. Hilaire?
    From: Andrés Ruiz
    Date: 2010 Mar 3, 10:30 +0100

    About DeWit, USNO Nautical Almanac, and Compac Data, Least squares algorithm for n LOPs SR:

     

    "This rings a bell. Checking my copy of AstroNavPC, from 2001, I find that I had penciled "A = C and B = 0" into the margin of p. 68. Is that it? "

    Yes, an example:

     

    DeWit/USNO Nautical Almanac/Compac Data, Least squares algorithm for n LOPs

     

    GHA

     DEC

     HO

     BO

     LO

     LHA

     HC

     Z

     p

    85.0000

    0.0000

    60.7917

    15.6178

    -60.0000

    25.0000

    60.7911

    240.0004

    0.0006

    35.0000

    0.0000

    60.7917

    15.6178

    -60.0000

    335.0000

    60.7911

    119.9996

    0.0006

    60.0000

    44.8267

    60.7917

    15.6178

    -60.0000

    0.0000

    60.7911

    360.0000

    0.0006

     

     

    Estimate position at time of fix:

    Befix [deg] = 15.6178

    Lefix [deg] = -60.0000

     

    Least Squares information:

    nObservations = 3

    AA = 1.5000

    BB = -0.0000

    CC = 1.5000

    DD = 0.0000

    EE = 0.0000

    FF = 0.0000

    G = 2.2500

     

    Error:

    S = 0.0000

    sigma = 0.0601 nm

    sigmaB = 0.0490

    sigmaL = 0.0490

     

    Ellipse:

    Prob = 0.9500

    k = 2.4477

    theta = 0.6585

    a = 0.1201

    b = 0.1201

     

    Improved position at time of fix:

    dB [deg] = 0.0000

    dL [deg] = 0.0000

    DO [deg] = 0.0000 nm

    BI [deg] = 15.6178

    LI [deg] = -60.0000

     

    iteraciones = 7

     

    The text then says- "statistical theory shows that the estimated position has a probability P of lying within" such a confidence ellipse.

    As I see it, the confidence ellipse is intended to be plotted around that estimated position, so the estimated position will therefore ALWAYS be placed at the exact centre of such a confidence ellipse!

    What would be nice to have, if it was possible, is the probability that such a confidence-ellipse will contain the TRUE position, not the estimated position.

     

    This is the example in the “Compact Data 2001-2005”. The ellipse is centered in the fix not in the DR or initial position.

    If we choose as an initial position one far from the fix, the ellipse axis, a,b,  tends to infinite.

    The solution for 4 iterations and a 50% ellipse is:

    I think the problem is the original text, the book uses the words: estimated position, (DR or initial for the iterative process), and improved estimated position.

     

    Confidende ellipse is not new in AstronavPC & Compac Data, widely used in statistics:

    http://en.wikipedia.org/wiki/Confidence_region

    http://pierremarie.gagey.perso.sfr.fr/EllipseConfiance-a.htm

     

    The confidende ellipse is a statistical technique that plots the region where the real position, not the calculated fix, could it be under certain probability, based under the observed phenomena. Historically the bisector of the azimuths determined the most probable position in a cocked-hat, and can result a cocked-hat. Other technique is to obtain the symmedian point also called Lemoine point or Grebe point,

    http://en.wikipedia.org/wiki/Symmedian

    With a two-body fix, we can draw a confidence ellipse again based on the standard deviation of observations as an input. It's an ellipse about the same size as the "overlap box" for the error bands around each LOP. And with a three-body fix, this answers your concern about a confidence ellipse being drawn too small when the LOPs just happen by chance to coincide in a small triangle. That small triangle should not imply a small confidence ellipse, and it doesn't if the s.d. is an input rather than calculated from the observations themselves.

    An ellipse has 3 dof, degrees of freedom, thus without any assumption is not possible to plot it.

    An example of a rapid fix, the algorithm is very robust.

     

    See [NavList 5168] Series of Sun sights in relatively rapid succession

     

    ---

    Andrés Ruiz

    Navigational Algorithms

    https://sites.google.com/site/navigationalalgorithms/

     

     

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