  Computational time reversal imaging can be used to locate the position of
multiple scatterers in a known background medium. The current methods for
computational time reversal imaging are based on the null subspace projection
operator, obtained through the singular value decomposition of the frequency
response matrix. Here, we discuss the image recovery problem from a small
number of random and noisy measurements, and we show that this problem is
equivalent to a randomized approximation of the null subspace of the frequency
response matrix.
