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@@ -129,10 +129,49 @@ sample_rate = 30.72e6;
 start_time = 2.722209;
 burst_duration = 0.00080729;
 
-start_time_samples = int(start_time * sample_rate);
-burst_duration_samples = int(burst_duration * sample_rate);
+start_time_samples = round(start_time * sample_rate);
+burst_duration_samples = round(burst_duration * sample_rate);
+
+fprintf(1, 'Start sample offset: %d, sample duration: %d\n', start_time_samples, burst_duration_samples);
 ```
 
+Running this script you should get the following output:
+```
+Start sample offset: 83626260, sample duration: 24800
+```
+
+Next the samples need to be read from the file they were recorded to.  Using the function in [5] that looks like this:
+```
+file_path = '/path/to/your/file.fc32';
+sample_rate = 30.72e6;
+
+start_time = 2.722209;
+burst_duration = 0.00080729;
+
+start_time_samples = round(start_time * sample_rate);
+burst_duration_samples = round(burst_duration * sample_rate);
+
+samples = read_complex_floats(file_path, start_time_samples, burst_duration_samples);
+
+length(samples)
+```
+
+The output of which should look like:
+```
+ans =  24800
+```
+Which means that `samples` now contains 24,800 complex samples.
+
+Now that you have the samples, it's a good idea to plot them to make sure that you really got a full burst.  An easy way to do this is to plot the magnitude squared (`abs(samples).^2`).  Add the following to the script above:
+
+```
+figure(1);
+plot(10 * log10(abs(samples).^2));
+```
+
+In my case the plot looks like this
+![image](https://user-images.githubusercontent.com/4240543/163081765-bdb3debf-0363-465d-8b1e-92d645d0ddd0.png)
+
 
 [4] https://github.com/gnuradio/gnuradio/blob/main/gr-utils/octave/read_complex_binary.m
 [5] https://github.com/proto17/dji_droneid/blob/main/matlab/read_complex_floats.m