A new algorithm for the formation of ISAR images

A new technique for implementing the enhanced image processing (EIP) algorithm for the formation of inverse synthetic aperture radar (ISAR) images is presented. The EIP algorithm is required when, during the formation of an image, scattering centers on a target move out of range and/or Doppler resolution cells. This phenomenon is common for high resolution imagery of practical-sized targets. The method presented is based entirely on the fast Fourier transform (FFT) and therefore does not require the interpolation schemes that are prevalent in the standard EIP implementation. A brief review of the theory of radar imaging is presented to establish the notation for the work. Following the presentation of the new algorithm, a simple example is given to demonstrate the effectiveness of the new technique. In addition work is presented that demonstrates the processing required to reduce the sidelobes in imagery generated by the EIP technique     

Joint time-frequency transform for radar range-Doppler imaging

Conventional radar imaging uses the Fourier transform to retrieve Doppler information. However, due to the complex motion of a target, the Doppler frequency shifts are actually time-varying. By using the Fourier transform, the Doppler spectrum becomes smeared and the image is blurred. Without resorting to sophisticated motion compensation algorithms, the image blurring problem can be resolved with the joint time-frequency transform. High-resolution time-frequency transforms are investigated, and examples of applications to radar imaging of single and multiple targets with complex motion are given     

An extended chirp scaling algorithm for spaceborne sliding spotlight synthetic aperture radar imaging

A system impulse response with low sidelobes is critical in synthetic aperture radar（SAR） images because sidelobes contribute to noise and interfere with nearby scatterers. However,the conventional tricks of sidelobe suppression are unable to be exactly applied to the case of spaceborne sliding spotlight SAR due to great azimuth shifts in both time and frequency domains. In this paper, an extended chirp scaling algorithm is presented for spaceborne sliding spotlight SAR data imaging. The proposed algorithm firstly uses the spectral analysis（SPECAN） technique to avoid the azimuth spectrum folding effect and then employs the chirp scaling（CS） algorithm to achieve data focusing, i.e., the so-called two-step approach. To suppress the sidelobe level, an efficient strategy for the azimuth spectral weighting which only involves matrix multiplications and short fast Fourier transformations（FFTs） is proposed, which is a post-process executed on the focused SAR image and particularly simple to be implemented. The SAR image processed by the proposed extended CS algorithm is very precise and perfectly phase-preserving. In the end, computer simulation results verify the analysis and confirm the validity of the proposed algorithm.     

High resolution 3D “snapshot” ISAR imaging and featureextraction

We have developed a new formulation for three dimensional (3D) radar imaging of inverse synthetic aperture radar (ISAR) data based on recent developments in high resolution spectral estimation theory. Typically for non real-time applications, image formation is a two step process consisting of motion determination and image generation. The technique presented focuses on this latter process, and assumes the motion of the target is known. The new technique offers several advantages over conventional techniques which are based on the correlation imaging function. In particular, the technique provides for a direct 3D estimate (versus back projection to a 3D target grid matrix) of the locations of the dominant scattering centers using only a minimum set of independent 2D range-Doppler ISAR “snapshots” of the target. Because of the snapshot nature of the technique, it is particularly applicable to 3D imaging of sectors of sparse-angle data, for which the sidelobes of the correlation imaging integral become high. Furthermore, the technique provides for an estimate of amplitude and phase of each scattering center as a function of aspect angle to the target, for those aspect angles which encompass the set of 2D range-Doppler snapshots. Results illustrating the technique developed are presented for both simulated and static range data     

A Generalized Approach to Multiresolution Complex SAR Signal Processing

Multiresolution synthetic aperture radar (SAR) image formation has been proven to be beneficial in a variety of applications such as improved imaging and target detection as well as speckle reduction. SAR signal processing traditionally carried out in the Fourier domain has inherent limitations in the context of image formation at hierarchical scales. We present a generalized approach to the formation of multiresolution SAR images using biorthogonal shift-invariant discrete wavelet transform (SIDWT) in both range and azimuth directions. Particularly in azimuth, the inherent subband decomposition property of wavelet packet transform is introduced to produce multiscale complex matched filtering without involving any approximations. This generalized approach also includes the formulation of multilook processing within the discrete wavelet transform (DWT) paradigm. The efficiency of the algorithm in parallel form of execution to generate hierarchical scale SAR images is shown. Analytical results and sample imagery of diffuse backscatter are presented to validate the method.     

Adaptive nulling of SAR sidelobe discretes

By using adaptive subarrays for crossrange imaging we have developed a computationally simple method that removes any image degradation caused by strong, discrete clutter located in the crossrange sidelobes of a synthetic aperture radar (SAR) image. The procedure is based on the minimization of the mean interference power with the constraint that the image of a desired scatterer is undistorted. The applicability of the approach has been illustrated by simulation     

An efficient 3-D near-field ISAR algorithm

This paper presents a new three-dimensional (3-D) near-field inverse synthetic aperture radar (ISAR) imaging technique. A 3-D ISAR image can be obtained by processing coherently the backscattered fields as a function of the frequency and two rotation angles about axes which are mutually orthogonal. Most of the existing ISAR algorithms are based on the Fourier transform and as such can tolerate only small amounts of wavefront curvature. Wavefront curvature must be taken into account when imaging an object in the near-field. Near-field ISAR imaging of large objects using a direct Fourier inversion may result in images which are increasingly unfocused at points which are more distant from the center of rotation. An algorithm based on an azimuth convolution between a near-field focusing function and the frequency domain backscattered fields is discussed. This convolution is efficiently implemented by using fast Fourier transform (FFT) techniques. Furthermore, in order to further alleviate the computational load of the algorithm, the discrete Fourier transform (DFT) of the focusing function is evaluated by means of the stationary phase method. Experimental results show that this technique is precise and virtually impulse invariant     

Range-Doppler Imaging of Rotating Objects

During the integration time required to obtain fine Dopplerfrequency resolution in a range-Doppler imaging radar, a point on a rotating object may move through several range and Doppler resolution cells and produce a smeared image. This motion can be compensated by storing the appropriately processed return pulse, and the angular coordinates are determined by the angular coordinates of the radar antenna. The resulting stored data represents the three-dimensional Fourier transform of the object reflectivity density, and hence can be processed by an inverse Fourier transformation. Also included is an analysis of the three-dimensional radar/object geometry with separate source and receiver locations. The effects of various system aberrations are investigated and experimental results from a microwave test range which demonstrate the image improvement are presented.     

Robust SVA method for every sampling rate condition

Linear apodization, or data weighting, is the traditional procedure to improve sidelobe levels in a finite sampled signal at the expense of resolution. New apodization methods, such as spatially variant apodization (SVA), apply nonlinear filtering to the signal in order to completely remove sidelobes without any loss of resolution. However, the results are strongly influenced by signal sampling rate. Some variations which improve results have been previously published, but sidelobe cancellation gets worse since sampling frequency is not settled at Nyquist (or a multiple). This paper presents a new and efficient technique based on SVA that drastically reduces sidelobe levels for every sampling rate condition. The algorithm is, essentially, a parameter optimization of a variant filter for each pixel of the image. A one-dimensional case and a two-dimensional generalization are presented, as well as some applications to target detection capability in a synthetic aperture radar (SAR) system.     

Novel Approach for ISAR Image Cross-Range Scaling

Inverse synthetic aperture radar (ISAR) imaging systems produce electromagnetic images of targets in the range-Doppler domain. In order to rescale the image in a homogeneous range-cross range domain (meters by meters), the modulus of the target effective rotation vector must be known. Although in some cases it can be retrieved by means of ancillary data, in most cases the modulus of the target effective rotation vector must be estimated. A blind technique is proposed for estimating the modulus of the target effective rotation vector that exploits information carried by the chirp rate of scattering centres. A technique based on image segmentation, local polynomial Fourier transform (LPFT), and image contrast (IC) maximisation is used in order to extract the scattering centres and estimate their chirp rate. Simulated and real data analyses are provided to confirm the effectiveness of the proposed algorithm.     

Doppler Compensation & Single Pulse Imaging using Adaptive Pulse Compression

The effects of target Doppler are addressed in relation to adaptive receive processing for radar pulse compression. To correct for Doppler-induced filter mismatch over a single pulse, the Doppler-compensated adaptive pulse compression (DC-APC) algorithm is presented whereby the respective Doppler shifts for large target returns are jointly estimated with the illuminated range profile and subsequently incorporated into the original APC adaptive receive filter formulation. As a result, the Doppler-mismatch-induced range sidelobes can be suppressed thereby regaining a significant portion of the sensitivity improvement that is possible when applying adaptive pulse compression (APC) without the existence of significant Doppler mismatch. In contrast, instead of compensating for Doppler mismatch, the single pulse imaging (SPI) algorithm generalizes the APC formulation for a bank of Doppler-shifted matched filters thereby producing a sidelobe-suppressed range-Doppler image from the return signal of a single radar pulse which is applicable for targets with substantial variation in Doppler. Both techniques are based on the recently proposed APC algorithm and its generalization, the multistatic adaptive pulse compression (MAPC) algorithm, which have been shown to be effective for the suppression of pulse compression range sidelobes thus dramatically increasing the sensitivity of pulse compression radar.     

Advances in non-linear apodization

Selected new methods and applications of non-linear apodization for irregularly-shaped and parse coherent apertures and arrays are presented. The benefits include unproved impulse response performance, i.e., reduced peak sidelobes and integrated sidelobe power, along with improved mainlobe resolution, compared to classic windowing techniques. Nonlinear apodization (NLA) techniques can also serve as powerful engines for effective superresolution and bandwidth extrapolation of coherent data for filling sparse apertures. The sparse aperture filling property of superresolution algorithms for radar data forms the basis for a new concept which is introduced here: synthetic multiple aperture radar technology (SMART). Increased swath and/or reduced antenna size are some of the benefits postulated for SMART applied to synthetic aperture radar (SAR) systems. The benefits of these new methods and applications for nonlinear apodization are then demonstrated for two specific applications: 1) sidelobe control for Y-type synthetic aperture radiometers, such as the European Soil Moisture and Ocean Salinity (SMOS) system (Kerr et al.) and JPL's proposed GeoSTAR (Lambrigsten) concept; and, 2) filling of sparse synthetic aperture radar data by exploiting the bandwidth extrapolation properties of nonlinear apodization based superresolution techniques. The methods that have been developed and demonstrated herein have potential application to a wide range of passive and active microwave remote sensing and radar systems.     

Frequency Domain Error Correction for Monopulse Radar Signals

Angle-measurement error of a coherent monopulse radar signalresulting from imbalances between in-phase and quadraturecomponents, as well as between sigma and delta channels, arecorrected in a simple procedure. No correction is needed for I,Qimbalances in the time domain [1]. Instead, a postintegrationcorrection is performed. This reduces the number of calibrationoperations of the monopulse signal by a factor X, 2 ? X ? N (N isthe number of DFT samples), depending on the degree of filtering.It also reduces the number of numerical operations necessary forthe production of the correction term by a factor of three. A firstorderrder estimation is made of the residual error after correction, dueto bias and image sidelobes.     

两种自适应方向图峰值副瓣控制方法比较

自适应阵列（或称自适应波束形成）目前已广泛应用到雷达、声纳和通信领域中用来抑制各种干扰（有意的干扰，杂波干扰和多用户干扰等）。在雷达应用中，为了减轻脉冲欺骗式干扰或旁瓣目标并利用单脉冲雷达来准确测量目标波达方向．要求自适应方向图具有低副瓣和稳定的主瓣形状。在实际应用中，各种失配误差将降低自适应阵列的性能．这些误差包括由于目标的波达方向不精确引起的信号指向误差，由通道失配和位置扰动引起的阵列校准误差和由小样本教引起的协方差矩阵估计误差。在此情况下，自适应波束形成的性能大大下降（干扰抑制性能变差。主瓣失真和高的副瓣）。已提出了一种基于二次约束的集成峰值副瓣控制（integrated peak sidelobe control，简称IPSC）方法。该方法可以精确地控制峰值副瓣电平并产生具有稳定的主瓣形状的自适应方向图。研究IPSC中目标信号的影响和信号消除方案以进一步提高IPSC的性能。并将IPSC方法和最新提出的基于二阶锥规划（second-order cone programming，简称SOCP）的分布式峰值副瓣控制（distfibuted peak sidelobe control，简称为DPSC）新方法在性能上进行了比较。仿真结果表明。在干扰抑制性能和方向图控制质量方面IPSC比DPSC性能优越。此外IPSC比DPSC计算高效。     

Quantitative SNR analysis for ISAR imaging using jointtime-frequency analysis-Short time Fourier transform

V.C. Chen recently presented an inverse synthetic aperture radar (ISAR) imaging technique using the joint time-frequency analysis (JTFA), which has been shown having a better performance for maneuvering targets over the conventional Fourier transform method. The main reason is because the frequencies of the radar returns of the maneuvering targets are time varying and a JTFA is a technique that is suitable for such signals, in particular a JTFA may concentrate a wideband signal, such as a chirp, while it spreads noise. We quantitatively study the signal-to-noise ratio (SNR) in the ISAR imaging using one of the typical JTFA techniques, namely the short time Fourier transform (STFT). We show that the SNR increases in the joint time-frequency (TF) domain over the one in the time or the frequency domain alone both theoretically and numerically. This quantitatively shows the advantage of the JTFA technique for the ISAR imaging     

Removing autocorrelation sidelobes by overlaying orthogonal coding on any train of identical pulses

A coherent train of identical linear FM (LFM) pulses is used extensively in radar because of its good range and Doppler resolution. Its relatively high autocorrelation function (ACF) sidelobes are sometimes reduced through spectrum shaping (e.g., nonlinear FM, or intrapulse weighting on receive). We show how to completely remove most of the ACF sidelobes about the mainlobe peak, without any increase to the mainlobe width, by diversifying the pulses through overlaying them with orthonormal coding. A helpful byproduct of this design is reduced ACF recurrent lobes. The overlaid signal also results in reduced Doppler tolerance, which can be considered as a drawback for some applications. The method is applied to several trains of identical pulses (LFM and others) using several orthonormal codes. The effect on the three important properties of the radar signal: ACF, ambiguity function (AY), and frequency spectrum is presented. The effect on Doppler tolerance is studied, and implementation issues are discussed. The new design is also compared with complementary and sub-complementary pulse trains and is shown to be superior in many aspects.     

Nonlinear apodization for sidelobe control in SAR imagery

Synthetic aperture radar (SAR) imagery often requires sidelobe control, or apodization, via weighting of the frequency domain aperture. This is of particular importance when imaging scenes containing objects such as ships or buildings having very large radar cross sections. Sidelobe improvement using spectral weighting is invariably at the expense of mainlobe resolution presented here is a class of nonlinear operators which significantly reduce sidelobe levels without degrading mainlobe resolution implementation is via sequential nonlinear operations applied to complex-valued (undetected) SAR imagery. SAR imaging is used to motivate the concepts developed in this work. However, these nonlinear apodization techniques have potentially broad and far-ranging applications in antenna design, sonar, digital filtering etc., i.e., whenever data can be represented as the Fourier transform of a finite-aperture signal     

激光微粒影象的粒径判读准则

1.引言 在许多工程及科学领域中,微粒尺寸及分布的测量是很重要的。在诸类测粒方法中,摄影测粒技术尤受重视。因为摄影方法可将结果长期保存,记录信息量大,测量结果直观易于分析。当以脉冲激光照明进行摄影时,还能将高速运动的微粒“冻结”下来,完全可视作静态处理。激光摄影测粒技术有激光显微摄影和激光全息摄影,二者最后都转化为从     

Improved imaging for X-ray inspection systems

A number of advancements for X-ray inspection systems have recently been implemented in the image presented to the operator. Advances in the use of color and image fusion techniques have been developed to maximize the information available in the initial view shown on the monitor. Different techniques are appropriate depending upon the size of the inspection item. Inspection of checked and carry-on baggage requires imaging methods that would not be appropriate for use on larger, more complex objects such as cargo containers or whole trucks. Color-coded presentation of CT images of baggage imposes yet other demands. Comparative images and analyses are presented to support choices for imaging on L-3 Communications systems in terms of the conflicting requirements of cost, sensitivity, resolution, and penetration. A number of enhancements are available to the operator and their influence on system performance is explored. Some experimental enhancements are demonstrated and their trade-offs discussed. The imaging system is ultimately based on hardware, and the choice of detectors, amplifiers, and sampling methods plays an important role in overall performance. Image degradation can be caused by deficiencies in the imaging hardware. Effects such as detector cross-talk and afterglow will negatively impact system performance. Recognition of these factors and steps to mitigate them are discussed. The effect of X-ray source choices such as beam voltage, milliamps, and sampling rate has a direct influence on the image quality and bag dose. Results of theoretical modeling as well as results on actual systems are presented. For a given bag dose, the trade-off between sensitivity, resolution, and penetration are considered. Possibilities for future advancements in imaging for X-ray inspection systems are explored.     

Accurate 3D Target Positioning in Close Range Photogrammetry with Implicit Image Correction

Accurate three-dimensional (3D) target positioning is of great importance in many industrial applications. Although various methods for reconstructing 3D information from a set of images have been available in the literature, few of them pay enough attention to the indispensable procedures, such as target extraction from images and image correction having strong influences upon the 3D positioning accuracy. This article puts forward a high-precision ellipse center (target point) extraction method and a new image correction approach which has been integrated into the 3D reconstruction pipeline with a concise implicit model to accurately compensates for the image distortion. The methods are applied to a copyright-reserved close range photogrammetric system. Real measuring experiments and industrial applications have evidenced the proposed methods, which can significantly improve the 3D positioning accuracy.