NavList:
A Community Devoted to the Preservation and Practice of Celestial Navigation and Other Methods of Traditional Wayfinding
Re: Cocked hats, again.
From: Dave Walden
Date: 2007 Mar 16, 22:03 -0700
From: Dave Walden
Date: 2007 Mar 16, 22:03 -0700
Below is a short FORTRAN program to do Monte Carlo simulations of a
three point LOP. It is rough and uncommented. I provide it as is
since there seems to be quite some interest at the moment. I have
found it, and other versions and modifications, very helpful as others
have said recently such a program might be. It's late, and I apolgize
in advance if I mis-speak below.
It assumes, without loss of generality, the true location is at x=0,
y=0. sd is the standard deviation of altitude uncertainty. For each
Monte Carlo run, for each LOP it finds the altitude error based on a
random selection from a distribution of errors. h45 for example.
(NORRAN is the subroutine. The choice of random number generators can
require some attention, as many may realize.) It checks if the true
location is inside the cocked hat, itest=3. It finds the center of
the cocked hat, the a,b,c,d,e,g calculation from the Nautical
Almanac. It calculates the distance from the true location to the
center of the cocked hat, dist. It accumulates some variables to
provide statistics on this distance as well as x and y distance from
the true location. It calculates the length of the side of this cocked
hat, len, via CALL CHECK. It calculates the number of times the point
is with a cirle of radius of .5887*len of the true location. It
writes out dist, len, and itest. By analyzing this file, one can
calculate probabilites of such things as small cocked hats that do not
contain the true location, how often large cocked hats do contain
cocked hats, how often cocked hats of various sizes occur, etc.
These quantities can be calculated analytically and I have found the
Monte Carlo results to tend towards these results as the number of
runs increases. (A million only takes a minute on an old, slow PC.)
In the sample output, next, one sees that of the 100,000 runs for
25,230 cases, the true location was inside the cocked hat.
Approaching 25%. The average x and y errors are -.0012 and .0008
respectively. Approaching zero as expected.
ii 100000
number less than 0.37134999 *len away ratio= 26119
in, inside cocked hat= 25230
ii,sumsq,sum 100000 0.331236064 0.510192156
sd 0.26634568
sum, sumsq,sqrt( sumsq- sum**2) 0.510192156 0.331236064
0.26634568
xsum,xsumsq,sqrt(xsumsq-xsum**2) -0.00127442868 0.16588138
0.407283396
ysum,ysumsq,sqrt(ysumsq-ysum**2) 0.0008370672 0.165351331
0.406633288
sh-3.00#
The first few lines from the output file,
0.057159 1.233867 3
0.724052 0.217705 1
0.387911 0.322774 1
0.608533 0.352897 1
0.635789 0.097189 1
1.136409 1.546760 1
0.175892 0.142276 1
show for example, a case where the distance from the center of the
cocked hat to the true location is .057 min (or naut miles) and length
of the sides of the cocked hat is 1.233 min and the true location is
inside the cocked hat, itest=3.
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