A compressive sensing algorithm using truncated SVD for three-dimensional laser imaging of space-continuous targets

For traditional array 3-D laser radars, the resolution of the intensity image and range profile is limited by the number and accuracy of sensors. Moreover, for a space-continuous target, peak detection in the pulsed time of flight is no longer suitable for super-resolution reconstruction algorithms. Hence, a compressive sensing algorithm for 3-D laser imaging is proposed. A range observation matrix composed of time interval basis vectors is constructed to acquire the range information regarding a target. However, the range observation matrix is generally ill-posed owing to the spatial continuity of the target. To address this shortage, truncated singular value decomposition is utilized to extract the peak values of echo pulses for image reconstruction. Simulation results demonstrate the effectiveness and performance of the proposed algorithm.