Xiaojian Xu

Three-dimensional interferometric ISAR imaging for target scattering diagnosis and modeling

Two-dimensional (2-D) inverse synthetic aperture radar (ISAR) imaging has been widely used in target scattering diagnosis, modeling and target identification. A major shortcoming is that a 2-D ISAR image cannot provide information on the relative altitude of each scattering center on the target. In this paper, we present an interferometric inverse synthetic aperture radar (IF-ISAR) image processing technique for three-dimensional (3-D) target altitude image formation. The 2-D ISAR images are obtained from the signature data acquired as a function of frequency and azimuthal angle. A 3-D IF-ISAR altitude image can then be derived from two 2-D images reconstructed from the measurements by antennas at different altitudes. 3-D altitude image formation examples from both indoor and outdoor test range data are demonstrated on complex radar targets.

FOPEN SAR imaging using UWB step-frequency and random noise waveforms

The detection and identification of targets obscured by foliage have been topics of great interest. Several synthetic aperture radar (SAR) experiments have demonstrated promising images of terrain and man-made objects obscured by dense foliage, by using either linear frequency modulation (LFM) or step-frequency waveforms. We present here the methodology and results of a comparative study on foliage penetration (FOPEN) SAR imaging using ultrawideband (UWB) step-frequency and random noise waveforms. A statistical-physical foliage transmission model is developed for simulation applications. The foliage obscuring pattern is analyzed by means of the technique of paired echoes. The results of the comparative study demonstrates the ability of a UHF band UWB random noise radar to be used as a FOPEN SAR. Advantages of the random noise radar system include covert detection and immunity to radio frequency interference (RFI).

Polarimetric processing of coherent random noise radar data for buried object detection

Random noise polarimetry is a new radar technique for high-resolution probing of subsurface objects and interfaces. The University of Nebraska has developed a polarimetric random noise radar system based on the heterodyne correlation technique. Simulation studies and performance tests on the system confirm its ability to respond to phase differences in the received signals. In addition to polarimetric processing capability and the simplified system design, random noise radar also possesses other desirable features, such as immunity from radio frequency interference. The paper discusses the theoretical foundations of random noise polarimetry, and presents examples out of the entire data set collected that demonstrate the usefulness of the image processing and Stokes matrix presentation to enhance target detection using the coherent random noise radar.

Range sidelobe suppression technique for coherent ultra wide-band random noise radar imaging

When applied in airborne imaging surveillance, ultra wide-band (UWB) random noise radars have their special merits. Because of the randomness and the ultrawide bandwidth of the transmit and receive signals, such radars can be used for covert detection and identification, and are immune from hostile detection and jamming while preserving very high range resolution. However, the images are plagued with artifacts caused by high range sidelobes. In this paper, a new technique for the range sidelobe suppression of UWB random noise radar, which combines median and apodization filtering, is proposed. Computational and experimental results show the effectiveness of this image enhancement procedure.

Enhanced resolution in SAR/ISAR imaging using iterative sidelobe apodization

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.

Principles and applications of coherent random noise radar technology

Random noise radar is rapidly emerging as a promising technique for high-resolution probing and imaging of obscured objects and interfaces. The University of Nebraska-Lincoln has developed and field-tested coherent ultra wideband polarimetric random noise radar systems that show great promise in their ability to estimate Doppler and image target and terrain features. Theoretical studies and extensive field tests using these systems confirm their ability to respond to and utilize phase information from the received signals. This paper summarizes our recent developments in coherent random noise radar imaging and discusses future research directions in this area.

Impact of different correlation receiving techniques on the imaging performance of UWB random noise radar

Cross correlation receiver is one of the most important parts in a random noise radar system. In this paper, the impact of different correlation receiving techniques on the imaging performance of ultra wideband (UWB) random noise radar is studied. Three types of correlation receivers, namely, the ideal analog correlation receiver, the digital-analog correlation receiver, and the fully digital correlation receiver, are discussed.

Enhanced resolution in 3-D interferometric ISAR imaging using an iterative SVA procedure

Multi-dimensional high resolution is one of the most important factors in automatic target recognition (ATR) using the synthetic aperture radar (SAR) or inverse SAR (ISAR) images. In this work, we propose a resolution enhancement technique in three-dimensional (3-D) interferometric SAR/ISAR (IF SAR/ISAR) imaging using an iterative sidelobe apodization procedure.

SAR image enhancement using noninteger Nyquist SVA technique

In SAR and inverse SAR (ISAR) imaging, conventional Fourier transform (FT) based image reconstruction techniques result in images with limited resolution. The down-range and cross-range resolutions of these algorithms are inversely proportional to the radar signal waveform bandwidth and to the synthetic aperture size, respectively. On the other hand, when modem spectral estimation methods are applied to radar imaging, these nonlinear techniques, usually called super resolution algorithms, offer improved resolution, better contrast, and reduced speckle. Spatially variant apodization (SVA) is a nonlinear filtering operation which significantly reduces the sidelobe levels without degrading mainlobe resolution of the sinc impulse response. In this work, we propose a modified version of noninteger Nyquist SVA and develop an iterative super SVA procedure for SAR and ISAR image enhancement. The proposed technique was successfully applied to various SAR/ISAR images.

An airborne low-cost SAR for remote sensing: hardware design and development

An airborne low-cost synthetic aperture radar (SAR) is under development at the University of Nebraska-Lincoln. The SAR system is an X-band, stepped-chirp frequency modulation (SCFM) radar system. One of its unique features is that the waveform generation consists of a timing-controlled D/A converter and VCO arrangement to synthesize the SCFM signal, whereby allowing for less design complexity and a much lower overall system cost. In this paper, we present a brief description of the system and some computer simulation results.