I hope following link will be helpful, best wishes

https://uk.mathworks.com/matlabcentral/answers/450692-delay-and-sum-beamforming

Irfan Qaisar Here is a possible implementation of the Delay and Sum algorithm for image reconstruction in microwave imaging using MATLAB:

% Initialize the image matrix with zeros

img = zeros(m, n);

% Define the frequencies and time delays

frequencies = [f1, f2, ..., fm];

delays = [t1, t2, ..., tm];

% Loop over the frequencies and time delays

for i = 1:length(frequencies)

for j = 1:length(delays)

% Compute the current weight

weight = exp(-1j*2*pi*frequencies(i)*delays(j));

% Accumulate the weighted measurements in the image matrix

img = img + weight * measurements(i, j);

end

end

% Normalize the image

img = img / sum(abs(img(:)));

In this code, m and n are the dimensions of the image matrix, f1, f2, ..., fm are the frequencies of the microwaves used in the imaging system, t1, t2, ..., tm are the corresponding time delays, and measurements is a matrix containing the measured responses of the system at each frequency and time delay. The Delay and Sum algorithm is implemented by looping over the frequencies and time delays, computing the weights for each pair based on the formula exp(-1j*2*pi*frequencies(i)*delays(j)), and accumulating the weighted measurements in the image matrix. Finally, the image is normalized by dividing by the sum of its absolute values.

Hi I am also working on delay and sum algorithm, if you got lucky then let me know please