Noise radar using random phase and frequency modulation

Pulse compression radar is used in a great number of applications. Excellent range resolution and high electronic counter-countermeasures performance is achieved by wideband long pulses, which spread out the transmitted energy in frequency and time. By using a random noise waveform, the range ambiguity is suppressed as well. In most applications, the random signal is transmitted directly from a noise-generating microwave source. A sine wave, which is phase or frequency modulated by random noise, is an alternative, and in this paper, the ambiguity function and the statistical characteristics of the correlation output for the latter configuration are further analyzed. Range resolution is then improved because the noise bandwidth of the modulated carrier is wider than that of the modulating signal, and the range sidelobes are also further suppressed. Random biphase modulation gives a 4-dB (/spl pi//sup 2//4) improvement, but much higher sidelobe suppression could be achieved using continuous phase/frequency modulation. Due to the randomness of the waveform, the output correlation integral is accompanied by a noise floor, which limits the possible sidelobe suppression as determined by the time-bandwidth product. In synthetic aperture radar (SAR) applications with distributed targets, this product should be large compared with the number of resolution elements inside the antenna main beam. The advantages of low range sidelobes and enhanced range resolution make frequency/phase-modulated noise radar attractive for many applications, including SAR mapping, surveillance, altimetry, and scatterometry. Computer algorithms for reference signal delay and compression are discussed as replacements for the classical delay line implementation.     

基于自适应加权方法的复值SAR图像的频域压缩改进算法

该文提出了一种基于自适应加权方法的复值SAR图像的频域压缩改进算法。该算法在原有频域压缩算法的基础上采用了自适应的加权方法,在低压缩比(20:1)的情况下能够很好地保留原始数据图像的特征,是一种有效的复值SAR图像的压缩算法。复值空域相关系数指标评估,以及原始数据、重建数据的幅度图对比和两幅数据图像之间的相关系数图都验证了算法的有效性。     

基于二维查找表结构的SAR原始数据自适应频域压缩算法

该文针对实际SAR多普勒中心偏移及多普勒谱分裂问题,提出基于一维查找表的自适应多普勒非均匀压缩比分配方法,该方法结合一维量化编码查找表构成二维查找表结构的SAR原始数据自适应频域压缩算法。该文推导了SAR距离向回波频谱解析式,给出距离向非均匀压缩比分配通用方案。实际数据处理结果表明,该方法比传统频域类压缩算法具有更好的信噪比及鲁棒性。理论分析结果表明,其运算量提高很小,易于工程实现。     

合成孔径雷达数据压缩算法性能分析

随着合成孔径雷达(SAR)向高分辨率、宽测绘带和多模式方向发展,星载SAR系统存在高数据率下传和处理的问题.原始数据压缩成为减小数据率的重要手段.文中在详细分析SAR原始数据压缩算法性能的影响因素的基础上,从工程应用的角度结合高分辨率SAR实际数据.从原始数据域和图像域等方面对目前存在的BAQ、AP和WT-AP等6种SAR原始数据压缩算法的性能做了深入的比较分析,为星载合成孔径雷达系统设计提供有益的参考.     

A rate distortion optimal ECG coding algorithm

Signal compression is an important problem encountered in many applications. Various techniques have been proposed over the years for addressing the problem. In this paper, we present a time domain algorithm based on the coding of line segments which are used to approximate the signal. These segments are fit in a way that is optimal in the rate distortion sense. Although the approach is applicable to any type of signal, we focus, in this paper, on the compression of electrocardiogram (ECG) signals. ECG signal compression has traditionally been tackled by heuristic approaches. However, it has been demonstrated [1] that exact optimization algorithms outperform these heuristic approaches by a wide margin with respect to reconstruction error. By formulating the compression problem as a graph theory problem, known optimization theory can be applied in order to yield optimal compression. In this paper, we present an algorithm that will guarantee the smallest possible distortion among all methods applying linear interpolation given an upper bound on the available number of bits. Using a varied signal test set, extensive coding experiments are presented. We compare the results from our coding method to traditional time domain ECG compression methods, as well as, to more recently developed frequency domain methods. Evaluation is based both on percentage root-mean-square difference (PRD) performance measure and visual inspection of the reconstructed signals. The results demonstrate that the exact optimization methods have superior performance compared to both traditional ECG compression methods and the frequency domain methods.     

星载SAR原始数据BAQ压缩算法性能评估

对星载合成孔径雷达(SAR)原始数据压缩算法的压缩性能评估是全面了解算法性能、合理选择算法方案的有效手段。该文模拟了以真实SAR图像为背景,引入点目标阵列的SAR回波数据;定义了综合评估指标;对分块自适应量化(BAQ)算法进行了不同分块方案、不同压缩比下的压缩实验;得到了一系列评估指标的计算结果。研究结果表明:BAQ算法对图像域的空间分辨率没有影响;不会引起图像的几何失真;对辐射分辨率影响很小;压缩引起的图像主瓣峰值失真不能够用统一的因子校正。同时该综合评价指标也可以推广到其他压缩算法评估中。     

基于Tetrolet Packet变换的SAR图像稀疏表示

Tetrolet变换作为多尺度几何分析的一种,能够对平滑的自然图像进行有效的稀疏表示。SAR图像具有丰富的细节纹理信息,因此经过Tetrolet变换后的高频系数依然具有较大的幅值,从而严重影响了稀疏表示SAR图像的性能。该文针对此问题提出了一种新的变换方法Tetrolet Packet,该算法将高频子带系数进行重新排序后,使用熵作为代价函数对不同的高频子带进行不同层次的Tetrolet分解得到Tetrolet最优分解树,从而使系数能量更加集中同时尽量减少方向信息,以便于后续SAR图像压缩。实验比较了Tetrolet和Tetrolet Packet两种算法,用相同个数的变换系数来进行图像重建,无论是主观视觉质量还是客观参数PSNR评价,Tetrolet Packet稀疏表示SAR图像的性能都优于Tetrolet。最后针对两种算法的变换系数均具有类似零树结构的特性,提出分别使用SPIHT和Modified-SPIHT算法对Tetrolet和Tetrolet Packet变换系数进行编码,并探讨了该两种算法对SAR图像的压缩性能。     

使用变换域编码技术压缩SAR原始数据

首先分析了在合成孔径雷达（SAR）原始数据中通常使用的块自适应量化（BAQ）算法,然后在此基础上详细讨论了两种基于块自适应量化的变换域编码算法,即基于快速傅里叶变换块自适应量化（FFT-BAQ）和基于小波变换块自适应量化（WT-BAQ）,并对这两种算法压缩得到数据解压缩获得图像与块自适应量化得到的图像进行分析比较,结果显示变换域编码技术能改善SAR原始数据压缩性能。     

一种新的高分辨率宽波束机载SAR成像算法

目前的频域成像算法在应用于高分辨率宽波束机载合成孔径雷达(SAR)时不能精确补偿运动误差,而可以精确成像的时域算法存在计算效率低下的问题。针对上述问题,该文提出一种新的成像算法。该算法通过对信号2维频谱进行扰动操作,将频域与时域算法结合互补,在提高运补精度的同时,也提高了后向投影的计算效率,从而在应用于高分辨率宽波束机载SAR时得到成像精度与效率的平衡。通过仿真和实际数据分析,验证了该算法应用于高分辨率宽波束系统的有效性。     

A comparison of range-Doppler and wavenumber domain SAR focusingalgorithms

Focusing of SAR data requires a space-variant two-dimensional correlation. Different algorithms are compared with each other in terms of their focusing quality and their ability to handle the space-variance of the correlation kernel: the range-Doppler approach with and without secondary range compression, modified range-Doppler algorithms, and four versions of the wavenumber domain processor. The phase aberrations of the different algorithms are given in analytic form. Numerical examples are presented for Seasat and ERS-1. A novel systems theoretical derivation of the wavenumber domain algorithm is presented     

Motion compensation for wide beam SAR based on frequency division

Aperture-dependent motion compensation is important for wide beam Synthetic Aperture Radar （SAR） data processing. This paper studies a wide beam motion compensation algorithm based on frequency division. It takes blocks along azimuth dimension in frequency domain and applies angle-variant motion compensation in time domain. With this frequency division based motion compensation approach, the effects of aperture-dependent residual phase errors are corrected precisely. The rationale and procedure of this algorithm are introduced in detail. Point targets and images of a P-band airborne SAR with motion errors are simulated to validate this algorithm. Compared with the wide beam motion compensation algorithms based on time division, the proposed algorithm has better performance, especially in terms of high-frequency motion errors.     

合成孔径雷达成像中频带分割与子带处理技术研究

采用多收多发孔径的合成孔径雷达(SAR)可以获得较常规SAR更宽的测绘带和更高的空间分辨率。该文将频带分割技术应用到多收多发孔径SAR成像中,在实现方位向高分辨率的同时获得距离向高分辨率。针对同步收发的子带脉冲信号,提出了一种时域先合成再脉冲压缩的方法,并对频域子带先脉冲压缩再合成的方法进行了扩展,提出了非零中频子带脉冲压缩合成的方法,仿真结果证明了方法的有效性。文中研究了子带载频差对压缩结果及成像的影响,并通过计算机仿真分别对两种相位差的影响进行了说明。     

Chirp Scaling算法中的相位补偿因子研究

该文从SAR回波的二维频谱表达式入手,研究了适合高波段SAR的CS(Chirp Scaling)类算法和一种适合超宽带(Ultra Wideband,UWB)SAR成像的非线性CS算法,通过对算法推导中的近似性分析,重新刻画了SAR成像,即SAR成像是利用回波频谱特性构造频域或时域相位补偿因子的过程,尤其是对UWB SAR回波,相位补偿因子的精确性直接影响着目标聚焦性能。仿真实验表明,补偿三阶以上二维相位耦合的非线性CS算法能够在一定的测绘带内满足UWB SAR点目标的理想聚焦;同时,该算法在UWB SAR实测数据处理中也已得到成功应用。     

Image representation using block compressive sensing for compression applications

The emerging compressive sensing (CS) theory has pointed us a promising way of developing novel efficient data compression techniques, although it is proposed with original intention to achieve dimension-reduced sampling for saving data sampling cost. However, the non-adaptive projection representation for the natural images by conventional CS (CCS) framework may lead to an inefficient compression performance when comparing to the classical image compression standards such as JPEG and JPEG 2000. In this paper, two simple methods are investigated for the block CS (BCS) with discrete cosine transform (DCT) based image representation for compression applications. One is called coefficient random permutation (CRP), and the other is termed adaptive sampling (AS). The CRP method can be effective in balancing the sparsity of sampled vectors in DCT domain of image, and then in improving the CS sampling efficiency. The AS is achieved by designing an adaptive measurement matrix used in CS based on the energy distribution characteristics of image in DCT domain, which has a good effect in enhancing the CS performance. Experimental results demonstrate that our proposed methods are efficacious in reducing the dimension of the BCS-based image representation and/or improving the recovered image quality. The proposed BCS based image representation scheme could be an efficient alternative for applications of encrypted image compression and/or robust image compression.     

GST时频滤波SAR射频干扰抑制算法

空间中存在的射频干扰(Radio Frequency Interference,RFI)会污染合成孔径雷达(Synthetic Aperture Radar,SAR)的回波数据,进而影响成像质量以及基于图像的应用.本文针对RFI的特点,提出了一种基于广义S变换(Generalized S Transform,GST)时...     

基于压缩感知的双基SAR二维高分辨成像算法

双基地合成孔径雷达(SAR)由于收发分置,具有广阔的应用前景,但常规的频域算法不仅面临距离史双根号问题,而且数据采集受Nyquist理论限制,数据量大。近年来提出的压缩感知(CS)理论指出,在一定条件下可以从很少的采样点中以很大的概率重建原始未知稀疏信号。本文将CS理论与双基地SAR模型相结合,提出一种基于CS的双基地SAR二维高分辨成像算法。该算法将二维随机降采样回波数据作为测量值,根据发射信号构造距离向测量矩阵,通过方位向多普勒相位因子构建方位向测量矩阵,利用CS恢复算法对目标进行了分维重建。仿真结果与性能分析表明,该算法在严重欠采样情况下仍能完好的重建原始目标,而且对噪声具有一定的鲁棒性和免疫性。与传统双基SAR成像算法相比,该算法具有更高的分辨率,成像结果峰值更加尖锐,峰值旁瓣比(PLSR)和积分旁瓣比(ILSR)都较低,而且采样率低、数据量少,具有一定的有效性和实用性。      

Spatial compression of Seasat SAR imagery

The results of a study of the techniques for spatial compression of synthetic-aperture-radar (SAR) imagery are summarized. Emphasis is on image-data volume reduction for archive and online storage applications while preserving the image resolution and radiometric fidelity. A quantitative analysis of various techniques, including vector quantization (VQ) and adaptive discrete cosine transform (ADCT), is presented. Various factors such as compression ratio, algorithm complexity, and image quality are considered in determining the optimal algorithm. The compression system requirements are established for electronic access of an online archive system based on the results of a survey of the science community. The various algorithms are presented and their results evaluated considering the effects of speckle noise and the wide dynamic range inherent in SAR imagery     

基于分形和小波变换的自适应混合图像编码

待编码图像经过金字塔型离散小波变换后的系数在小波域内可以组成分层树状数据结构一个小波树，这些跨越不同分辨率的小波树之间存在一定的相似性，可以通过分形变换来描述，本文正是构造小波树的基础邮基于分形和小波变换的自适应混合图像压缩算法，实验证明，我们提出的图像压缩方法与ＪＰＥＧ相比，能够在相近的压缩比的情况下（６０：１～７０：１）使得重建图像的ＰＳＮＲ（〉２９．５ｄＢ）增加约５．４ｄＢ并且图像的主观视觉     

基于改进CS算法的侧斜视SAR成像

针对SAR的斜视工作模式,该文建立了雷达信号的回波模型,详细分析了回波信号的瞬时方位频率和瞬时多普勒频率及距离Chirp斜视对方位频率的影响,结合经典的 CS算法,提出了一种基于斜视的改进CS算法,并利用该方法进行了仿真试验,理论分析和仿真结果表明,该方法更符合斜视SAR的几何关系,能有效的进行距离压缩、距离徙动校正和方位聚焦,改善成像质量。     

小波变换的SAR原始数据网格编码量化压缩算法

介绍了小波变换和网格编码量化的优点,针对SAR原始数据的基本特点,提出了基于小波变换的8状态网格编码量化压缩算法。对小波变换后的数据进行网格编码量化,利用卷集编码和信号空间扩展来增大量化信号间的欧氏距离,获得了更好的量化效果。利用实际数据进行的实验结果表明,文中提出的算法在量化性能上优于已有的各种压缩算法。