GMAP Step Description
Step 2: Determine the Noise
Power
In general, the spectrum noise power is known from periodic noise power
measurements. Since the receiver is linear and requires no STC or AGC, the
noise power is well-behaved at all ranges. The only time that the spectrum
noise power diers from the measured noise power is for very strong clutter
targets. In this case, the clutter contributes power to all frequencies,
essentially increasing the spectrum noise level. This occurs for two reasons:
in the presence of very strong clutter, even a small amount of phase noise
causes the spectrum noise level to increase, and there is significant power
that occurs in the window side-lobes. For a Hamming window, the window
side lobes are down by 40 dB from the peak at zero velocity. 50 dB clutter
targets have spectrum noise that is dominated by the window sidelobes in
the Hamming case. The more aggressive Blackman window has
approximately 55 dB window sidelobes at the expense of having a wider
impulse response and larger negative
eect on the variance of the
estimates.
When the noise power is not known, it is optionally computed using a
dynamic approach similar to that of Hildebrand and Sekhon (1974). The
Doppler spectrum components are first sorted in order of their power. As
shown in the figure, the sorting places the weakest component on the left
and the strongest component on the right. The vertical axis is the power of
the component. The horizontal axis is the percentage of components that
have power less than the y- axis power value. Plotted on a dB scale, Poisson
distributed noise has a distinct shape, as shown by the curved line in the
figure. This shape shows a strong singularity at the left associated with
taking the log of numbers near zero, and a strong maximum at the right
where there is always a
finite probability that a few components have
extremely large values.
There are generally two regions: a noise region on the left (weaker power)
and a signal/clutter region on the right (stronger power). The noise level and
the transition between these two regions is determined by
first summing
the power in the range 5% to 40%. This sum is used to determine the noise
level by comparing with the sum value corresponding to the theoretical
curve. Next, the power is summed beyond the 40% point for both the actual
and theoretical rank spectra. The point where the actual power sum exceeds
the theoretical value by 2 dB determines the boundary between the noise
region and the signal/clutter region.
Finally there are two outputs from this step: a spectrum noise level and a list
of components that are either signal or clutter
Chapter 7 – Processing Algorithms
195
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