hi my name is Rick Gentile I'm the
phased array system toolbox product
manager I'd like to show you how easy it
is to process a radar data cube with
MATLAB in the phased array system
toolbox as we saw in part 1 of the
recording the radar data cube is a
collection of radar returns received by
a phased array radar it's organized into
a three-dimensional matrix the vertical
axis of the queue is composed of the
received time samples representing each
individual radar pulse the horizontal
axis contains the time samples collected
in each the array elements for the depth
axis there's a collection of consecutive
pulses focus on a particular direction
or object this is sometimes called the
dwell time in this presentation will
talk about the three array processing
algorithm starting with beam forming a
beamforming is a process of combining
the individual receive channels into a
single receive signal you can think of
beam forming as a spatial filter that
applies different complex weights to the
channels and that sums the results to
effectively steer a beam in a specific
direction a beam forming works across
the horizontal axis of the radar data
cube and it gives you information about
the bearing elevation of the object
you're trying to track the second
algorithm is matched filtering or pulse
compression which enhances the radar
return by correlating the receive time
samples with a sampled version of the
source waveform match filtering is
performed on the data that makes up the
vertical axis of the radar data cube the
range bin where the peak amplitude
occurs can be used to determine the
distance of an object you are trying to
track the radar returns from moving
objects will have a Doppler shift that's
proportional to the radial velocity of
the object so if we take the FFT of the
radar returns along the depth dimension
of the radar data cube we can extract
information about the speed of the
moving object now let's take a look at
some matlab code that can be used to
process the radar data cube will use
some code from a previous recording
called building the radar data cube to
quickly generate our radar data cube for
a target located at 20 kilometers away
from the radar with a radial velocity of
150 meters per second so you can see the
data cube variable in my matlab
workspace it's built up as a thousand
time sample by eight receive element x
32 pulse variable
it's complex data type because there are
complex inq samples that have been
received here after the array now we'll
start with beamforming which can give us
information about the bearing of the
moving object we're tracking you can use
the phased array system toolbox to
create a phase shift beamformer and set
the properties that we would like to use
now once we've created this object we
can use the step method as a way of
executing the beamformer now for
illustration purposes we're going to
steer the beam both 20 degrees azmuth
and to a 30-degree azmuth where the
moving object is actually located so go
ahead and execute this cell on the
resulting plot we can see three
different things the first is the plot
response this is the response of the
uniform linear array object we can see
with no beam forming the peak of the
response is at zero degrees azmuth
there's a deep null at 30 degrees where
our targets located if we just some the
receive elements we can't see any
indication that the targets present this
is because we have the beam steered to
the zero Degree azmuth location if we
use some phased array weights in the
beam former to steer the array to a 30
degree azmuth where the target is we now
see an enhanced target return or we can
really see the target return for the
noise now when you're processing the
radar data cube you have to do
beamforming for all the pulses along the
depth dimension and that's the
processing you see here the figure we
see shows the improved target returns
for the entire sequence of 3G pulses
when we use beamforming we can now use
pulse compression to determine the
distance to the target and you'll see
here we can use the get matched filter
method to return the match filter for
the transmitted wave form we use this
filter object to process the time
samples for the radar pulse return now
you can see here the result is a sharp
peak at the range bin of the moving
object this is one of the advantages of
using a modulated pulse like the linear
FM waveform we see here on the Left
there's a very strong correlation
property and therefore produces a strong
narrow peak at the target return once
we've detected this peak we can
calculate the distance the
moving object the index of the time
sample where the peak exists tells us
the distance of the object in this case
we have to use the time deranged
function and subtract the length of
match filter to convert the time to
distance when we execute this it gives
us a distance of 19.9 4 kilometers which
is within the range resolution of the
waveform that we selected and last of
all we can determine the speed of the
target using the Doppler shift observed
in the target returns in this case the
FFT across the range bin where the
moving object has been detected yields a
plot where we can see the peak here and
it's at a frequency 150 Hertz which
corresponds to a radial velocity 150
meters per second now this Doppler
resolution is a function of the number
of pulses in the dwell time so if we
wanted to improve the accuracy of the
speed measurement we can send out more
pulses at this particular object a
phased array system toolbox also has a
range Doppler response system object
this object essentially computes the f
of T across the range bins in the data
cube so when you look at this plot you
can see the strong return at a distance
of twenty kilometers and a speed of 150
meters per second now this example is
meant to show how to process a radar
data cube to determine the range speed
and bearing of a moving object the
phased array system toolbox has other
very processing techniques like do a
algorithms and stab space-time adaptive
processing or you can extract even more
information about the target returns
contained in the rdc you can find more
information at the product page and if
you're interested in this code you can
find it in matlab central with the title
processing the rdc thank you again for
your time