*A* Radar station has transmitted the sinusoidal pulse as described above. The reflected signal received has been corrupted by AWGN and recorded into the RangeDetection.mat file. Extract your allocated data from RangeDetection.mat using:

*load RangeDetection.mat*

*mysignal = RangeDetection(n,:);*

Detect the presence of the object with the matched filter you designed in section 2.1. Provide a plot of the output of the matched filter and hence calculate the distance of the object relative to the transmitter

Since the matched filter can be implemented as correlation operation between the received signal and the transmitted signal, you can implement the receiver using correlation instead of convolution. (ie: Implement the matched filtering as a correlation receiver ). Correlation can be done when we use the xcorr function in matlab. Note that when the xcorr function is used, there will be zero padding done to the arguments before correlation. Processing will need to be done to obtain the solution. You might want to read the help files concerning the xcorr function.

In Radar applications, it is often necessary to be able to detect the presence multiple objects. You will investigate the use of matched filter in this section to study the task of multiple object detection.

Load the file MultipleObjectDetection.mat and extract your data

Detect the presence of the multiple objects using the optimal receiver. Provide a plot at the output of the matched filter and hence calculate the spatial separation of the objects.

We now consider the effect of closely situated targets to study how well the particular transmitted signal and matched filter reception is able to resolve the position of the targets ie: the range resolution characteristics of the system.

Load the file MultipleObjectDetection1.mat and calculate the distance between the objects using the optimal receiver. Comment on your findings

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