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1. zengqw2021
   

   Member
   Joined: Jun '21
   Posts: 26

   Dear all,
   I'm try to understand 2D Time Reversal Reconstruction For A Line Sensor Example. If I define a binary line sensor by:

   sensor.mask = zeros(Nx, Ny);
   sensor.mask(60:200, 60) = 1; %1 for receiver, 0 for no receiver?

   we find the received sensor_data is a array 141×Ny. Does that mean there are 141 receivers?
   If so, can I sum up several receiver signals and reconstruct the image again?
   For example:
   NewSensor_data(1,:)= sensor_data(1,:)+sensor_data(2,:)+sensor_data(3,:);
   NewSensor_data(2,:)= sensor_data(6,:)+sensor_data(7,:)+sensor_data(8,:);
   ...
   The new detection point is the sum of the received signals of the original three detection points, and the distance between the new detection point is about the distance of the original three detection points.
   Is the above idea correct?
   Thanks
   Zeng

   Posted 3 years ago #

2. Bradley Treeby
   

   Developer
   Joined: Mar '10
   Posts: 1,643

   Hi Zeng,

   The size of sensor_data will be (number_sensor_points, number_time_points). In your case, yes, there are 141 grid points that form part of the sensor mask, so there will be 141 time series in the returned sensor data.

   Yes, you could sum them up in the way you mention. Then depending on what you're trying to achieve in the reconstruction, either use a smaller grid, or use the same grid/mask but assign the summed value to all of the grid points that form part of that detecting element.

   Brad.

   Posted 3 years ago #

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