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total of 10 pages only may be xeroxed - Memorial University's Digital ...

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the tangentid component. For -pie, the adar data used here were processed to I<br />

yield a current resolution <strong>of</strong> 8pprmdmately 7 mjs. while the mean m ent owr the<br />

experimental zone k on the order <strong>of</strong> 20 -1s. Therefore, it <strong>may</strong> <strong>be</strong> difficult to mea-<br />

sure the change in the radial current from adjacent <strong>be</strong>-, aod hence the tangential<br />

current component, if the &age rn lea thao the nominal error <strong>of</strong> the radial current<br />

messurement. An alternative in this ease is to in- the slmuthal extent <strong>of</strong> the<br />

region and proceed with the essmnption <strong>of</strong> current uniformity<br />

In summary, from the above discurnion there is a elear trade<strong>of</strong>f <strong>be</strong>tMen the radar<br />

parameters <strong>of</strong> <strong>be</strong>amwidth aod current resoittian, an well an the selection <strong>of</strong> the opt&<br />

ma1 region size to <strong>be</strong> used for wetor current estimation based on these parameters.<br />

This vdl aLso depend on the variability <strong>of</strong> the current regimes <strong>be</strong>ing monitored and<br />

the magnitudes <strong>of</strong> the currents. For example the technique <strong>may</strong> provide <strong>be</strong>tter ec<br />

timates when cur-& are large, relative to the current resolution <strong>of</strong> the system. it<br />

<strong>may</strong> &o provide reliable mean current etimates in the event <strong>of</strong> extreme -nt<br />

variability in the estimation region if the size chasen is large enough to 'force' a mean<br />

estimate from the region. AU in dl, m y <strong>of</strong> t<strong>be</strong> paints noted here wiU have to <strong>be</strong> in-<br />

vestigated further to determine their etfeets on the reliability <strong>of</strong> the estimate provided<br />

by the aigorithmn.<br />

4.6.4 Simplifications<br />

At t h stage in the algorithm development, it is unclear how the mam algorithmn<br />

parameters, AR and AB, sect the solution. It <strong>may</strong> vltimately require some 'good-<br />

ness <strong>of</strong> fit' testing while varying the algorithmn parameters to minimize the solution<br />

in a least squares sense with same optimal set. Since this <strong>may</strong> detract from the fun-<br />

damental issue <strong>of</strong> establishing the potential <strong>of</strong> the algorithm for current estimation,<br />

optimal parameter selection will not <strong>be</strong> dealt with. Hence, for the 6 <strong>of</strong> simplicity,<br />

key issues related to the algorithmn fundament& will <strong>be</strong> a ddrd here. These will<br />

50

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