  The newly emerging theory of compressed sensing (CS) enables restoring a
sparse signal from inadequate number of linear projections. Based on compressed
sensing theory, a new algorithm of high-resolution range profiling for
stepped-frequency (SF) radar suffering from missing pulses is proposed. The new
algorithm recovers target range profile over multiple coarse-range-bins,
providing a wide range profiling capability. MATLAB simulation results are
presented to verify the proposed method. Furthermore, we use collected data
from real SF radar to generate extended target high-resolution range (HRR)
profile. Results are compared with `stretch' based least square method to prove
its applicability.
