  Compressed sensing (CS) schemes are proposed for monostatic as well as
synthetic aperture radar (SAR) imaging with chirped signals and
Ultra-Narrowband (UNB) continuous waveforms. In particular, a simple,
perturbation method is developed to reduce the gridding error for off-grid
targets. A coherence bound is obtained for the resulting measurement matrix. A
greedy pursuit algorithm, Support-Constrained Orthogonal Matching Pursuit
(SCOMP), is proposed to take advantage of the support constraint in the
perturbation formulation and proved to have the capacity of determining the
off-grid targets to the grid accuracy under favorable conditions.
Alternatively, the Locally Optimized Thresholding (LOT) is proposed to enhance
the performance of the CS method, Basis Pursuit (BP). For the advantages of
higher signal-to-noise ratio and signal-to-interference ratio, it is proposed
that Spotlight SAR imaging be implemented with CS techniques and
multi-frequency UNB waveforms. Numerical simulations show promising results of
the proposed approach and algorithms.
