An effective focusing approach for azimuth invariant bistatic SAR processing

This paper proposes a processing method to extend monostatic imaging algorithms for the azimuth invariant bistatic SAR (BISAR) data where the transmitter and the receiver move on parallel tracks with equal velocities. The bistatic range history is approached by a polynomial of the azimuth time. Based on this model, an analytic 2-D signal spectrum derived by the method of series reversion is utilized and a simple one-to-one mapping between the transmitter and the receiver closest ranges is established. In this way, efficient monostatic imaging algorithms which operate in the 2-D frequency domain or the range-Doppler domain are easily modified to handle the BISAR data. In this paper, a chirp scaling algorithm for the BISAR is developed as an application of the new method. By implementing two key operations, range cell migration correction by a chirp scaling, and azimuth compression by a curve fitting technique, this algorithm is able to process the azimuth invariant BISAR data. Simulation results are presented to demonstrate the validity and the efficiency of the proposed algorithm.     

Three-dimensional focusing with multipass SAR data

Deals with the use of multipass synthetic aperture radar (SAR) data in order to achieve three-dimensional tomography reconstruction in presence of volumetric scattering. Starting from azimuth- and range-focused SAR data relative to the same area, neglecting any mutual interaction between the targets, and assuming the propagation in homogeneous media, we investigate the possibility to focus the data also in the elevation direction. The problem is formulated in the framework of linear inverse problem and the solution makes use of the singular value decomposition of the relevant operator. This allows us to properly take into account nonuniform orbit separation and to exploit a priori knowledge regarding the size of the volume interested by the scattering mechanism, thus leading to superresolution in the elevation direction. Results obtained on simulated data demonstrate the feasibility of the proposed processing technique.     

Airborne SAR processing of highly squinted data using a chirpscaling approach with integrated motion compensation

Proposes a new approach for high-resolution airborne SAR data processing, which uses a modified chirp scaling algorithm to accommodate the correction of motion errors, as well as the variations of the Doppler centroid in range and azimuth. By introducing a cubic phase term in the chirp scaling phase, data acquired with a squint angle up to 30° can be processed with no degradation of the impulse response function. The proposed approach is computationally very efficient, since it accommodates the variations of Doppler centroid without using block processing. Furthermore, a motion error extraction algorithm can be incorporated into the proposed approach by means of subaperture processing in azimuth. The new approach, denoted as extended chirp scaling, is considered to be a generalized algorithm suitable for the high-resolution processing of most airborne SAR systems     

A new Doppler ambiguity resolution technique for SAR data based on SPECAN processing

In this paper, we describe an approach for Doppler ambiguity resolution. This approach adopts the fact that unwrapped Doppler centroid is a linear function of range frequency for a given antenna squint angle. On this basis, an alternative azimuth compression method is addressed and performed in range frequency domain to accumulate target energy in the azimuth direction. The resulting trajectories behave as some straight lines with the average slope proportional to absolute Doppler centroid. This slope can be well estimated by image-contrast methods. Theoretical analysis and real measured SAR data show that the proposed approach works well in high- and relatively low-contrast scenes.     

基于Wigner-Hough的合成孔径雷达信号处理

交叉项问题是合成孔径雷达信号处理的主要难题,为了解决常规的合成孔径雷达信号处理中的交叉项问题,从 Wigner-Ville引出 Wigner-Hough变换的原理,及Wigner-Hough变换处理这一问题的方法。通过 Matlab软件仿真实验,比较常规方法与Wigner-Hough变换处理后的合成孔径回波信号效果,经过Wigner-Hough变换处理后的回波信号解决了交叉项问题,凸显Wigner-Hough变换在处理合成孔径信号中的优势。     

Compression of SAR data through range focusing and variable-ratevector quantization

In spaceborne SAR systems, some form of data compression is required to reduce the bandwidth of the downlink channel. Compressing the raw data is very inefficient because such data exhibit little or no correlation. Data focusing would restore the original dependencies of the image, but it is too complex to be implemented onboard. In this paper we propose to carry out a partial, low-complexity focusing onboard, and then compress the resulting data by means of a suitable algorithm based on variable-rate adaptive vector quantization. Experiments show a performance improvement of 0.5-0.7 dB over compression techniques proposed in the literature     

New approaches in interferometric SAR data processing

It is known that interferometric synthetic-aperture radar (SAR) images can be inverted to perform surface elevation mapping. Among the factors critical to the mapping accuracy are registration of the interfering SAR images and phase unwrapping. A registration algorithm is presented that determines the registration parameters through optimization. A figure of merit is proposed that evaluates the registration result during the optimization. The phase unwrapping problem is approached through a new method involving fringe line detection. The algorithms are tested with two SEASAT SAR images of terrain near Yellowstone National Park. These images were collected on SEASAT orbits 1334 and 1420, which were very close together in space, i.e. less than 100 m     

Three-dimensional multipass SAR focusing: experiments with long-term spaceborne data

Synthetic aperture radar (SAR) interferometry is a modern efficient technique that allows reconstructing the height profile of the observed scene. However, apart for the presence of critical nonlinear inversion steps, particularly crucial in abrupt topography scenarios, it does not allow one to separate different scattering mechanisms in the elevation (height) direction within the ground pixel. Overlay of scattering at different elevations in the same azimuth-range resolution cell can be due either to the penetration of the radiation below the surface or to perspective ambiguities caused by the side-looking geometry. Multibaseline three-dimensional (3-D) SAR focusing allows overcoming such a limitation and has thus raised great interest in the recent research. First results with real data have been only obtained in the laboratory and with airborne systems, or with limited time-span and spatial-coverage spaceborne data. This work presents a novel approach for the tomographic processing of European Remote Sensing satellite (ERS) real data for extended scenes and long time span. Besides facing problems common to the airborne case, such as the nonuniformly spaced passes, this processing requires tackling additional difficulties specific to the spaceborne case, in particular a space-varying phase calibration of the data due to atmospheric variations and possible scene deformations occurring for years-long temporal spans. First results are presented that confirm the capability of ERS multipass tomography to resolve multiple targets within the same azimuth-range cell and to map the 3-D scattering properties of the illuminated scene.     

Compression of SAR raw data through range focusing andvariable-rate trellis-coded quantization

There is an ever-growing interest in the compression of SAR data because of the huge resources required for storage and transmission. This is especially true for spaceborne sensors, given the limited capacity of the downlink channel. Unfortunately, SAR data lack the useful properties on which compression algorithms rely; indeed, these are present in the focused images, but focusing is too complex for on-board implementation at this time. Poggi et al. (2000) proposed to perform on the satellite only the low-complexity range focusing, which increases the data correlation and better concentrates their energy. These properties were then exploited by adopting a variable-rate vector quantizer, with a clear performance improvement with respect to reference techniques. However, vector quantization (VQ) is too complex for actual on-board implementation, and therefore, here we replace VQ with trellis-coded VQ. To limit complexity, only small vectors are used, which reduces VQ's ability to exploit data dependencies; on the other hand, trellis coding allows one to encode large blocks of data at once, and to obtain a better partition of the input space. Experiments on real SAR data show that the overall performance is comparable to that of Poggi et al., but the complexity is much lower, making on-board implementation possible.     

Real-time synthetic aperture radar (SAR) processing with a newsubaperture approach

A time-domain subaperture approach that is suitable for real-time synthetic aperture radar (SAR) processing and that produces high-quality, full-resolution images is presented. The real-time subaperture algorithm is based on an approximation of the phase history correction in each subaperture with a simple linear correction, which can be carried out by an up/down-conversion of the received signal followed by a moving average operation. The characteristics of the impulse response function are improved considerably by means of a frequency overlap of the subapertures and become comparable to a conventional matched filter response. Special algorithms for high-quality SAR processing, such as autofocus, Doppler centroid estimation, and range migration correction, can be efficiently implemented. High flexibility is achieved for multilook processing and no secondary range compression is needed, even for high squint angles     

A new subaperture approach to high squint SAR processing

A high squint subaperture (HSS) algorithm was developed from the perspective of a strip map synthetic aperture radar (SAR) system and has the ability to focus SAR data at extremely high squint angle of 55° with less than 1.27% mainlobe expansion or even higher squint angles if larger mainlobe expansion can be tolerated. The unique characteristic of this algorithm is that the subapertures are formed by multiplying the received signal with a set of overlapped complex conjugated reference signals where the chirp rate varies in the azimuth direction. This is done to solve the range focus problem that arises after the azimuth input signal undergoes the range walk removal procedure. As the IISS algorithm only involves short fast Fourier transforms (FFTs) and avoids interpolation, it is computationally efficient and allows for small data buffers and facilitates hardware real-time implementation. The distinct feature of this algorithm is its simplicity of implementation, which is vital in real time processing and motion compensation when the squint angle may be changing continuously     

New applications of nonlinear chirp scaling in SAR data processing

New applications of nonlinear chirp scaling (NLCS) have been found in processing monostatic and bistatic SAR data acquired in the strip-map mode. When the effects in impulse response broadenings due to quadratic range migration are negligible for short radar wavelengths, a time domain range cell migration correction (RCMC) can be applied. After the correction, the FM rates of targets confined in a range gate will differ from each other. A nonlinear chirp perturbation function can be applied to each range gate to equalize the targets' FM rates before azimuth compression. This algorithm is analyzed in the paper and is supported by point target simulation experiments     

Sub-aperture algorithm for motion compensation improvement inwide-beam SAR data processing

The effects of strong motion errors in wide-beam azimuth synthetic aperture radar (SAR) processing are analysed and discussed, using simulated data, as well as data collected by the airborne experimental SAR system of the Deutsches Zentrum fur Luft- und Raumfahrt e.V. (DLR) (E-SAR). A new sub-aperture approach for residual motion error compensation in wide-beam azimuth processing is proposed     

基于DSP的导航计算机数据处理

研究了以数字信号处理芯片作为数字硬件平台,实现捷联式惯性导航系统(SINS)数据处理的软件设计。分析了捷联式惯性导航系统的动力学方程,模拟了陀螺仪漂移的数据,并用系统辨识中的时间序列分析法对漂移数据建模,之后进行了卡尔曼滤波。最后,在CC环境下,运用C语言和汇编语言混合编程的方式,将位移解算和卡尔曼滤波程序移植到开发板上,利用CC环境自带的优化编译器,对所编写的数据处理程序进行优化,使运行速度达到最快。     

Fuzzy data fusion approach for image processing

The use of fuzzy set theory to combine the results of different image processing techniques is discussed, and it is shown how classical decision theory can be used to guide the choice of fuzzy methods to take account of observation inter-dependencies and risk in a meaningful way     

Speckle filtering in polarimetric SAR data based on the subspace decomposition

In this paper, a new approach to speckle filtering of synthetic aperture radar (SAR) data is presented. We define a parameter space consisting of two orthogonal subspaces-the signal subspace and the noise subspace. Then, the full polarimetric information from the signal subspace is obtained after speckle filtering. In this way, edges of different kinds of targets are preserved. The effectiveness of this method is demonstrated using the National Aeronautics and Space Administration Jet Propulsion Laboratory airborne L-band polarimetric SAR data.     

一种基于STAP的多通道SAR噪声干扰抑制方法

随着合成孔径雷达(SAR)的广泛应用,针对SAR的干扰技术也不断发展.首先分析了SAR噪声干扰技术的特点,提出了一种基于空时自适应处理(STAP)的多通道SAR噪声干扰抑制方法,原理是通过对总干扰协方差矩阵的特征子空间分析,将多通道SAR回波数据投影到杂波子空间以及干扰子空间的垂直子空间,以实现噪声干扰信号的抑制,与通常的自适应波束形成方法相比,子空间方法对存在主波束内的噪声干扰具有更好的抑制效果,数据处理的结果验证了该方法的有效性.     

基于LabVIEW的火箭试验数据处理方法

针对常规火箭试验的手动数据处理方法过于繁琐的问题,利用虚拟仪器LabVIEW对采集到的试验数据进行自动分析处理,以单根管装药火箭发动机推力曲线为例,提出了一种近似方法来代替常规的燃烧终止点的寻找方法,并解决了在计算机上进行自动处理的问题,然后对该方法进行论证,推广到一般曲线。经过实践证明,该处理方法与常规的手动寻找特征点的方法相比,误差不超过0.1%,且运行稳定。     

基于VBScript的遥测数据处理技术研究

飞行器的遥测数据帧格式随型号、批次而不同,给遥测数据处理带来很大不便。利用Active X Scripting技术能实现VBScript引擎嵌入到遥测处理程序中,使得遥测处理程序在不修改程序的情况下能够通过VBScript脚本灵活处理多变的数据帧格式。经应用证明,该技术具有配置灵活、可扩展性强等特点,能够满足不同格式遥测数据解析的需要。     

基于大数据背景下的计算机信息处理技术研究

大数据时代已经到来,必将给社会带来翻天覆地的变化,大数据顾名思义就是“大的”、“海量的”数据,它涉及五个领域,包括数据挖掘、数据分析、机器学习、人工智能和业务分析,巨量的数据在收集、存储、分析方面必然是巨大的工作量,即便依据最先进的计算机信息处理技术,都无法对所有数据进行精细化的处理,不过随着5G通讯技术的发展和大规模商用,必然有促进作用,可以说发展至今,大数据时代才刚刚开始。