Super-resolution Processing of Multi-static Data Using Time Reversal and MUSIC

The problem of estimating the location of one or more coherent point scatterers from the time-reversal matrix as computed from backscattered narrow or broadband multi-static data is investigated. For the case of homogeneous backgrounds it is shown that under very weak conditions and as long as the number of sensor elements exceeds the number of scatterers the time reversal matrix has a rank equal to the number of scatterers so that the well-known vector subspace methods underlying the MUSIC algorithm can be applied to this matrix. A MUSIC type of algorithm is presented which computes a “pseudo-spectrum” of the location of M coherent point targets from multistatic data obtained using an N (N > M) element sensor array. The algorithm is tested in computer simulations and shown to yield excellent results, especially in the case of very sparse arrays where conventional time-reversal imaging breaks down.