Sparse Objects Location Using Compressive Sensing

This work suggests a method to solve the inverse problem of scattering using compressive sensing in order to locate and characterize targets in space. We consider the case of point scatters located on a small fraction of an overall region of interest. The measurement of the response of the scalar wave scattering from the objects is collected using a remote random sensor array. The proposed method achieves two significant improvements over conventional techniques: (i) increases the number of recoverable objectives depending on the number of transmitters and receivers, and (ii) determines both the position and the reflectivity of the objectives in a single solution. In addition, an indicator of the performance of the model based on the calculation of a so-called global error and a threshold parameter to improve the detection of targets are proposed. Results are obtained using computer simulations.