Radar Image Formation Research Articles

Efficient technique for two‐dimensional scattering center extraction and ISAR image formation

AbstractThis article presents efficient technique of two‐dimensional (2D) scattering center extraction and inverse synthetic aperture radar (ISAR) image formation of a target. The proposed technique uses a sparse scanning order conception and modified spatial smoothing preprocessing (MSSP). The MSSP is used to construct autocorrelation matrix. In general, 2D IFFT (inverse fast Fourier transform) is widely used to obtain 2D scattering center and ISAR image. This method is computationally efficient, but has drawbacks that are poor in terms of resolution. To overcome these shortcomings with the IFFT‐based method, various high‐resolution techniques were developed. The proposed algorithm enables us to provide exact scattering centers and ISAR image of a target. In order to show the performances of the proposed technique, we use backscattered field data of the ideal point scatterers and the F‐18 aircraft to estimate 2D scattering centers and obtain 2D ISAR image. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 2173–2178, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23619

Through-wall radar imaging using UWB noise waveforms

This paper examines the results of our research on the use of ultrawideband noise waveforms for imaging objects behind walls. The advantages of using thermally generated noise as a probing signal are introduced. The technique of heterodyne correlation used to inject coherence in the random noise probing signal and to collapse the wideband reflected signal into a single frequency are presented. Central to successful imaging through building walls is the characterization of the wideband propagation properties of wall materials and these are discussed. The basic concepts of synthetic aperture radar image formation using noise waveforms and the unique problems associated with the random nature of the transmit waveform are analyzed. We also address issues related to locating, detection, and tracking humans behind walls, using new tools for human activity characterization, namely the Hilbert-Huang Transform approach. The results indicate that noise radar technology combined with modern signal processing approaches is indeed a viable technique for covert high-resolution imaging of obscured stationary and moving targets.

Motion Analysis in SAR Images of Unfocused Objects Using Time–Frequency Methods

Synthetic aperture radar (SAR) image formation processing assumes that the scene is stationary, and to focus an object, one coherently sums a large number of independent returns. Any target motion introduces phases that distort and/or translate the target's image. Target motion produces a smear primarily in the azimuth direction of the SAR image. Time-frequency (TF) modeling is used to analyze and correct the residual phase distortions. An interactive focusing algorithm based on TF modeling demonstrates how to correct the phase and to rapidly focus the mover. This is demonstrated on two watercraft observed in a SAR image. Then, two time-frequency representations (TFRs) are applied to estimate the motion parameters of the movers or refocus them or both. The first is the short-time Fourier transform, from which a velocity profile is constructed based on the length of the smear. The second TFR is the time-frequency distribution series, which is a robust derivative of the Wigner-Ville distribution that works well in this SAR environment. The smear is a modulated chirp, from which a velocity profile is plotted and the phase corrections are integrated to focus the movers. The relationship between these two methods is discussed. Both methods show good agreement on the example.

PRF-ambiguity resolution for SAR by contrast minimization in range-Doppler domain

An algorithm was developed to accurately estimate the Doppler centroid, which is needed for high-quality synthetic aperture radar (SAR) image formation by resolving the SAR pulse repetition frequency (PRF) ambiguity. The algorithm uses the SAR range migration to resolve the PRF-ambiguity by searching for a PRF-ambiguity number that minimizes the intensity contrast in the range-Doppler domain. Experimental results show that the approach, compared with traditional methods for resolving the SAR PRF ambiguity, is more suitable for both high contrast scenes such as urban areas and low contrast scenes such as mountains. Moreover, the approach is more computationally efficient for there are no time-consuming correlations or fast Fourier transform (FFT) operations needed in the range-Doppler domain and only part of the range cells are used in the calculation.

Range Resampling in the Polar Format Algorithm for Spotlight SAR Image Formation Using the Chirp $z$-Transform

Besides an inverse two-dimensional (2-D) Fourier transform, the polar format algorithm (PFA) for the spotlight synthetic aperture radar (SAR) image formation can be normally divided into two cascaded processing stages, which are called the range and azimuth resampling, respectively. This paper focuses on a new implementation of the first stage, i.e., the range resampling, using the chirp z-transform (CZT). The presented algorithm requires no interpolation. It works for the SAR system directly digitizing the echo signal, as well as that employing the dechirp-on-receive approach. The parameters of the CZT, including the frequency spacing and the start frequency, are derived to accommodate the PFA in both cases. Related filtering and compensation procedures are developed for the chirp z-transformed range signal with and without dechirp, respectively, in order to achieve a signal format entirely suitable for the azimuth resampling. Furthermore, incorporating the new algorithm with the existing CZT-based azimuth resampling and focusing algorithm, we can achieve a PFA totally free of interpolation. The presented approach has been validated by point target simulation, and the test is carried out with a very critical relative bandwidth of 30%

A Keystone Transform Without Interpolation for SAR Ground Moving-Target Imaging

Synthetic aperture radar (SAR) image formation for a ground moving target necessitates the compensation of the unknown target trajectory. The keystone transform has been employed to remove the linear component of the range migration for the moving target, where interpolation is required. In this letter, a realization of the keystone transform avoiding interpolation is presented. The kernel of this transform, i.e., the range-frequency-dependent azimuth time rescaling, is implemented using only complex multiplications and fast Fourier transforms based on the scaling principle, which has been successfully applied in the equalization of the space-variant range cell migration in SAR processing. In addition, the moving target is coarsely focused according to the SAR geometry and the platform velocity while exploiting the scaling principle. This preliminary focusing is helpful in the isolation of the moving target from ground clutter, so as to facilitate a more refined processing with respect to each mover. SAR raw data combined with simulated echoes of moving targets are utilized to validate the presented approach

A developing approach of the space-based SIFP using rectangular algorithm

The developing approach of synthetic aperture radar image formation processor (SIFP) is to depict the image formation algorithm, to evaluate the fractional errors, to establish the software and hardware (HW) mapping, and to provide the HW selection criteria. The purpose of this paper is to provide whole works related to the space-based SIFP during design stage. This technique can be used to reduce errors and risks of design before implementation. Thus, this method can be applied for developing the space-based SIFP using rectangular algorithm.

Ultra-wideband synthetic aperture radar time-frequency representation image formation

In ultra-wideband synthetic aperture radar (UWB SAR) imaging, scatterers often perform the frequency- and aspect angle-dependent reflectivity characteristic, which is usually neglected in traditional imaging processing. A novel UWB SAR time-frequency representation image formation (TFRIF) is proposed to retrieve the frequency- and aspect angle-dependent information, which is valuable in target detection. Based on the TFRIF, two fusion schemes are studied: pixel level fusion (PLF) and decision level fusion (DLF). Based on the analytical expressions, it is concluded that TFRIF can extract the reflectivity pattern information with high precision and little sacrifice of the spatial resolutions. Quantitative analyses of spatial resolutions and detectability improvement of the proposed fusion schemes are tested on airborne UWB SAR data. The real data results validate the proposed TFRIF and its associated PLF and DLF schemes.

Physics-Based Predictions for Coherent Change Detection Using X-Band Synthetic Aperture Radar

A theoretical model is developed to describe the interferometric coherency between pairs of SAR images of rough soil surfaces. The model is derived using a dyadic form for surface reflectivity in the Kirchhoff approximation. This permits the combination of Kirchhoff theory and spotlight synthetic aperture radar (SAR) image formation theory. The resulting model is used to describe the interferometric coherency between pairs of SAR images of rough soil surfaces. The theoretical model is applied to SAR images formed before and after surface changes observed by a repeat-pass SAR system. The change in surface associated with a tyre track following vehicle passage is modelled and SAR coherency estimates are obtained. Predicted coherency distributions for both the change and no-change scenarios are used to estimate receiver operator curves for the detection of the changes using a high-resolution, X-band SAR system.

Polar format algorithm for bistatic SAR

Matched filtering (MF) of phase history data is a mathematically ideal but computationally expensive approach to bistatic synthetic aperture radar (SAR) image formation. Fast backprojection algorithms (BPAs) for image formation have recently been shown to give improved O(N/sup 2/ log/sub 2/N) performance. An O(N/sup 2/ log/sub 2/N) bistatic polar format algorithm (PFA) based on a bistatic far-field assumption is derived. This algorithm is a generalization of the popular PFA for monostatic SAR image formation and is highly amenable to implementation with existing monostatic image formation processors. Limits on the size of an imaged scene, analogous to those in monostatic systems, are derived for the bistatic PFA.

Radar penetration imaging using ultra-wideband (UWB) random noise waveforms

Ultra-wideband (UWB) radar has been proven to be a very powerful tool for high-resolution penetration imaging of obscured objects. The authors discuss a radar penetration imaging technique using UWB random noise waveforms. The theoretical foundations for random noise radar, the random noise radar imaging model, and the synthetic aperture radar (SAR) image formation algorithm are presented. Typical field test results using an experimental random noise radar system are demonstrated.

Polarimetric SAR target feature extraction and image formation via semi-parametric methods

We present a semi-parametric spectral estimation algorithm for fully polarimetric synthetic aperture radar (SAR) target feature extraction and image formation, referred to as POLarimetric semi-parametric (POL-SPAR) algorithm. The algorithm is based on a flexible data model that models each target scatterer in each polarization channel as a two-dimensional complex sinusoid with arbitrary amplitude and constant phase in cross-range and with constant amplitude and phase in range. The polarization scattering matrix is assumed to be an arbitrary unknown for each scatterer. We also develope an improved POL-SPAR algorithm by adding a smoothness constraint on the target radar-cross-section (RCS) as a function of the cross-range. Both numerical and experimental examples are presented to demonstrate the performance of the proposed algorithms. Traditional approaches like the fast Fourier transform (FFT) and polarimetric whitening filter (PWF) methods are also applied to experimentally measured data for comparison purposes.

Estimation of wavefield power distribution in the remotely sensed environment: Bayesian maximum entropy approach

The problem of estimating, from one random realization of the remotely sensed signal, the spatial spectrum pattern (SSP) of the wavefield sources distributed in the environment is cast in the framework of Bayesian estimation theory. The kernel spectral estimation method that is familiar, for the classical SSP estimation problem, with the Fourier transform operator and white noise in the observations is extended to incorporate spatial correlation in the data, the system-oriented model of the signal formation operator, and the maximum entropy (ME) statistical a priori information about the SSP. To derive the estimate of the SSP, we applied the Bayesian strategy for maximization of the a posteriori probability density function of the randomized ME model of the SSP. The estimator was obtained as a nonlinear adaptive algorithm that also permits a concise robust implementation. The optimal algorithm implies formation of the second-order sufficient statistics of the data and their smoothing by applying the window operator. The new formalism of the sufficient statistics and windows, explaining their adjustment to the metrics in a solution space, a priori nonparametric model and assumed correlation properties of the desired SSP, is developed. Simulation results are included to illustrate the overall performance of the proposed method in an example of application to radar image formation.

Extended Chirp Scaling Algorithm for Spotlight SAR

Among Synthetic Aperture Radar (SAR) image formation algorithms, the chirp scaling algorithm (CSA) is computationally highly efficient and has been practically used. In this paper, how to implement the subaperture extended CSA in a high resolution spotlight mode SAR is studied in detail. The procedures such as subaperture processing and azimuth processing are discussed. According to the problems presented when using the method (A. Moreira, et al, 1996) to process spotlight SAR data, full formula expressions suitable for high squinted angles is presented. While point target simulation is analyzed, the method is validated by E-SAR raw data. The results can be directly implemented in the design of SAR processors.

Prescreening during image formation for ultrawideband radar

Standard radar image formation techniques waste computational resources by full resolving all areas of the scene, even regions of benign clutter. We introduce a multiscale prescreener algorithm that runs as part of the image formation processing step for ultrawideband (UWB) synthetic aperture radar (SAR) systems. The prescreener processes intermediate radar data generated by a quadtree backprojection image former. As the quadtree algorithm iterates, it is resolving increasingly finer subpatches of the scene. After each quadtree stage, the prescreener makes an estimate of the signal-to-background ratio of each subpatch and applies a constant false alarm rate (CFAR) detector to decide which ones might contain a target of interest. Whenever the prescreener determines that a subpatch is not near a detection, it cues the image former to terminate further processing of that subpatch. Using a small database of UWB radar field data, we demonstrate that the prescreener is able to decrease the overall computational load of the image formation process. We also show that the new multiscale prescreener method produces fewer false alarms than the conventional two-parameter CFAR prescreener applied to the completely formed image.

Synthetic aperture radar image of agricultural fields with surface drainage network: simulation and spatial information retrieval

We develop a 3-D model to simulate the synthetic aperture radar (SAR) image formation process of an undulated vegetation canopy such as corn grown in fields with large periodic drainage reliefs. We explain how the simulated SAR image of undulated vegetation medium is obtained by the convolution of a 2-D slice of the 3-D simulated SAR system point spread function [(PSF), emulating the SAR beam modeled by a cosine modulated Gaussian], with the 2-D projection of the observed undulated vegetation canopy (modeled with scatterers randomly distributed in 3-D undulated space) followed by the extraction of each look envelope, the summation of looks, and sampling in azimuthal and range directions. Our model is useful to study the parameters involved in the formation and the analysis of SAR images of undulated vegetation medium. Validation of simulations made with actual SAR images shows that undulated corn crop canopies are well characterized by the mean contrast of the backscattered amplitude, the shape parameter ? of the K distribution, the coefficient of variation, and the autocorrelation function of the backscattered amplitude. These experiments also show that the discrimination of corn parcels with or without subsurface drainage and the monitoring of the corn plant height differential across the drainage ridge during the growing season are possible.

Feature-enhanced synthetic aperture radar image formation based on nonquadratic regularization

We develop a method for the formation of spotlight-mode synthetic aperture radar (SAR) images with enhanced features. The approach is based on a regularized reconstruction of the scattering field which combines a tomographic model of the SAR observation process with prior information regarding the nature of the features of interest. Compared to conventional SAR techniques, the method we propose produces images with increased resolution, reduced sidelobes, reduced speckle and easier-to-segment regions. Our technique effectively deals with the complex-valued, random-phase nature of the underlying SAR reflectivities. An efficient and robust numerical solution is achieved through extensions of half-quadratic regularization methods to the complex-valued SAR problem. We demonstrate the performance of the method on synthetic and real SAR scenes.

Autofocus and super-resolution synthetic aperture radar image formation

An FFT (fast Fourier transform) based parametric algorithm, referred to as MCCLEAN, is devised for cross-range phase error compensation in SAR (synthetic aperture radar) imaging. It can be used as an independent autofocus approach for the SAR imaging of a large scene. The authors also present a similarly structured algorithm for simultaneous autofocus and super-resolution SAR image formation of a small scene or small region of interest (ROI) in a large scene. Examples are provided to illustrate the performance of the proposed algorithms.

Analysis and Evaluation of the DEM derived from TOPSAR Airborne Interferometric SAR System

The aim of this paper is to assess the quality of Digital Elevation Models (DEMs) derived from Airborne Synthetic Aperture Radar (SAR) interferometry. An evaluation is made of the accuracy of the DEMs generated by the JPL/NASA TOPSAR interferometric SAR system, by comparing them with an accurate reference DEM derived from the digital photogrammetric processing of 1: 25000 aerial stereo photographs. The terrain in the test site location was relatively flat, with a variation in elevation ranging from 29 m to 115 m. DEMs generated from the acquired radar data were rotated and translated to overlay the reference DEM, allowing an analysis of the achieved height accuracy. The errors measured over 4.5 km x 2.5 km were 3.9 m rms for C-band interferometry DEM and 12.9 m rms for L-band interferometry DEM. The background on radar and SAR image formation, the principles and applications of SAR interferometry as well as the key factors that presently limit this technology are also presented.

Analysis and evaluation of the DEM derived from TOPSAR airborne interferometric SAR system

The aim of this paper is to assess the quality of Digital Elevation Models (DEMs) derived from Airborne Synthetic Aperture Radar (SAR) interferometry. An evaluation is made of the accuracy of the DEMs generated by the JPL/NASA TOPSAR interferometric SAR system, by comparing them with an accurate reference DEM derived from the digital photogrammetric processing of 1: 25000 aerial stereo photographs. The terrain in the test site location was relatively flat, with a variation in elevation ranging from 29 m to 115 m. DEMs generated from the acquired radar data were rotated and translated to overlay the reference DEM, allowing an analysis of the achieved height accuracy. The errors measured over 4.5 km x 2.5 km were 3.9 m rms for C-band interferometry DEM and 12.9 m rms for L-band interferometry DEM. The background on radar and SAR image formation, the principles and applications of SAR interferometry as well as the key factors that presently limit this technology are also presented.