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We must also consider the case where the above model does not
apply: when
is too small for the large limits
approximations to be valid.
In that case, we may use the
Taylor series approximation for an exponential signal with a small
argument, namely:
where the Taylor series error introduced is
, as the argument of the exponential will be at most
.
Hence, the model loses accuracy as the argument value strays from
zero, though we can ensure that our model introduces less than
2.1% error, for example, if we require that
. The accuracy of the model versus
will be
apparent in section 4.
Applying the Taylor series approximation allows us to write the
DFT of the windowed chirp signal as
where
is an arbitrary zero-phase symmetric windowing
function whose DFT is
.
Applying Fourier theory and approximating frequency domain
differentiation with DFT domain differencing (with large
), we
may write
where the number of
superscripts indicates the order of
differencing applied.
Though the result in equation 12 may suggest an estimator
in itself, it is not tolerant of phase offset in
. An
estimator robust to this may be found by analyzing the phase
curvature of
at
. Specifically, it may be shown that,
for zero-phase symmetric
where the subscript 0 indicates
.
By substituting equations 12 and 13 into the above
expression, we obtain that
For future convenience, we will denote the observed value of phase
curvature at zero as
.
The expression in equation 15 may be solved for
to obtain an estimator for small
.
Next: MODEL APPLICATION: ESTIMATORS
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Aaron S. Master
2003-02-12