Multiple-input multiple-output (MIMO) radar is an enabling technique for high-resolution imaging, which is especially useful for near-field electromagnetic scattering diagnosis of complex targets. Among others, high sidelobes and radar cross section (RCS) calibration uncertainty are the major challenges for such applications, due to array nonuniformity, imperfect channels, and antenna pattern tapering. These shortcomings prevent a MIMO radar from obtaining high-quality images with enough dynamic range and RCS accuracy. In this paper, we develop a complete solution for these problems. A novel adaptive weighting technique is proposed, where the complex weights are optimized for exact amplitude and phase error calibration of a MIMO array and for azimuth sidelobe reduction. A MIMO filtered backprojection algorithm is developed for image formation with improved RCS calibration accuracy, where propagation path-loss, antenna pattern tapering, and phase distortion due to the near-field spherical wave front are compensated. Both indoor and outdoor field test results are presented to show the high-quality images obtained using the proposed techniques, demonstrating the applicability of a MIMO radar for diagnostic RCS imaging of complex targets.

It is known that the challenge for detection of small targets on the sea surface is the low signal-to-clutter ratio (SCR). In particular, for low grazing angles and high sea states, wave shading and sea spikes make the small target detection even more difficult. This letter proposed a novel phase-feature detector of small targets in sea clutter. Three phase features, which correspond to different radar scattering mechanisms between the target and sea surface, are extracted in the phase domain of radar echoes, namely, the number of phase crossing zero points, the maximum value of the phase difference probability density function, and the decorrelation time of the phase difference. A detector with a controllable false alarm rate (FAR) based on phase features is constructed using the fast convex hull learning algorithm. Experimental results on measured databases demonstrate that the proposed phase-feature detector attains better performance than the existing tri-feature detectors.

Resolution enhancement techniques in radar imaging have attracted considerable interest in recent years. In this work, we develop an iterative sidelobe apodization technique and investigate its applications to synthetic aperture radar (SAR) and inverse SAR (ISAR) image processing. A modified noninteger Nyquist spatially variant apodization (SVA) formulation is proposed, which is applicable to direct iterative image sidelobe apodization without using computationally intensive upsampling interpolation. A refined iterative sidelobe apodization procedure is then developed for image-resolution enhancement. Examples using this technique demonstrate enhanced image resolution in various applications, including airborne SAR imaging, image processing for three-dimensional interferometric ISAR imaging, and foliage-penetration ultrawideband SAR image processing.

Compressed sensing (CS) based imaging technique is considered to be an effective solution for high-resolution radar imaging due to the sparse distribution of the scatterers. Nevertheless, the unoptimized CS based synthetic aperture radar (SAR) or inverse SAR (ISAR) imaging approach may suffer from the computationally intensive problem when apply it to wideband radar signatures of electrical large-scale targets. In this paper, a two-dimensional (2-D) superresolution imaging technique based on peak search and compressed sensing (PS-CS) is presented. A peak search strategy is first developed to solve the problem of high computational complexity of CS based method in scattering parameter estimation. Superresolution imaging result is then achieved by extrapolating the estimated parameters of scattering along with the observing angle dimension and frequency dimension. The numerical and measurement data acquired from different man-made targets are presented to demonstrate the feasibility and usefulness of the proposed technique for supperresolution radar imaging.

Currently, a set of scaled squat circular cylinders have been widely used for co-polarimetric radar cross section (RCS) calibration in various test ranges where low RCS metal pylons are used. The major drawback of a circular cylinder is its high sensitivity to elevation angle, as well as the frequency-dispersive theoretical RCS. In this work, we propose a new RCS calibrator, the metal ellipsoidal cylinder, whose RCS characteristics are similar to a metal sphere, while it can be mounted on a metal pylon with little electromagnetic (EM) interactions as a circular cylinder does. A high-frequency RCS expression is derived using geometrical optics (GO) for the new calibrator. The scattering mechanisms are analyzed to establish the accurate parametric representation of the theoretical RCS. Based on surface current analysis and numerical calculation, the calibrator-pylon interaction (CPI), the angular sensitivity, and the bistatic RCS characteristics are discussed, enabling the calibration uncertainty evaluation for applying the proposed calibrator in ground-plane range (GPR). Numerical and experimental results of a manufactured squat ellipsoidal cylinder (SEC) are presented to demonstrate the excellent performance of the proposed ellipsoidal cylinder calibrator for co-polarimetric RCS calibration.