基于模糊物元分析法的雷达网抗干扰能力评价模型

结合现代防空作战特点,分析了影响雷达网抗电子干扰能力的因素,在模糊物元分析的基础上,结合欧氏贴近度的概念,提出了基于欧氏（欧几里得）贴近度的模糊物元分析法。在对雷达网抗干扰能力进行评价时,以雷达网的各项评价指标及其相应的模糊量值构造复合模糊物元。通过计算与标准模糊物元之间的欧氏贴近度,实现了对雷达网抗干扰能力的评价,为雷达网抗干扰能力评价提供了一个新的方法。     

OFDM系统中基于零子载波检测的频偏估计模糊度校正算法

OFDM系统的性能对频率偏移非常敏感。该文针对频偏估计中所产生的模糊度问题提出了一种基于零子载波检测的频偏估计模糊度校正算法。它利用OFDM符号中不传输信息的子载波进行频偏估计模糊度校正。文中分析了定时误差对算法性能的影响并分析比较了算法的复杂度。仿真结果表明,在性能相近的前提下,该文提出的频偏估计模糊度校正算法与传统的算法相比具有运算量小的优点。     

OFDM系统中基于符号间相位差分调制的频偏估计模糊度校正算法

OFDM系统的性能对频率偏移非常敏感。该文针对OFDM系统频偏估计中所产生的模糊度问题提出了一种基于符号间相位差分调制的频偏估计模糊度校正算法。它通过在相邻OFDM符号中相同子载波间进行相位差分调制来校正频偏估计模糊度。文中从理论上给出并证明了算法具有唯 可辨识性的充分条件,并分析比较了算法的复杂度和定时误差对算法性能的影响。理论分析和仿真结果表明,在性能相近的前提下,该文提出的频偏估计模糊度校正算法具有运算量小和对定时误差不敏感的优点。     

基于宽巷组合模型求解整周模糊度的研究

传统的最小二乘降相关法(LAMBDA)在求解模糊度时,通常会因观测历元较少而出现法方程秩亏的现象,导致无法成功求解模糊度。针对此问题,提出利用双频宽巷的线性组合观测模型解算模糊度。同时,研究了观测量误差均方差值和OVT检验历元个数对模糊度解算的影响。结果表明,整周模糊度解算成功率受伪距双差观测误差均方差值的变化影响较大,模糊度解算成功率随着检验历元个数增加而增大。     

基于GNSS系统的整周模糊度解算算法仿真

利用载波相位观测值可以大大提高导航定位精度,但整周模糊度的存在会严重影响结果的准确性。为了解决整周模糊度对载波相位观测值的影响,对LAMBDA算法求解整周模糊度的过程进行分析和设计,提出利用协方差分解来降低模糊度组数之间相关性的算法,设计相应的Matlab仿真验证系统并进行仿真。比较分析不同分解算法下的搜索域的大小以及修正解的准确性。结果表明,下三角分解算法的整周模糊度解算算法在搜索域大小上比上三角分解算法大,且解算速度较快,能运用于后续的姿态解算。     

伪码判距离模糊方法及其概率计算

简述了利用伪随机码判别距离模糊度的方法，给出伪码判模糊正确概率的理论推导过程，分析发现概率、虚警概率、信噪比等相关因素对正确概率的影响，并对该种判模糊方法的实现提出改进。     

改进的模糊事故树分析方法

针对传统模糊事故树分析中语言值转换途径和模糊重要度计算方法的不足,进行了相应的改进。新的语言值转换途径使语言值所对应的概率数量级合理化,避免了专家评价语言值的单一化。新的模糊重要度计算方法解决了中值法中最小割集所含基本事件模糊重要度相同的问题,考虑了基本事件发生概率的不同对系统顶事件的影响。最后,引用了简单的实例,证明了改进的可行性,为模糊事故树分析方法的改进提供了一种有益的思路。     

灰色关联度和模糊熵相结合的图像分割算法

提出了一种结合灰色关联度和模糊熵的分割算法.传统模糊熵分割算法的隶属度函数只利用了图像灰度值的统计信息,因此算法容易受噪声或光照不均的影响.在隶属度函数的计算中,引入灰色关联度来表示像素的空间信息,能够更加准确地反映像素属于目标或背景的影响.由理想目标或背景点组成参考序列,待处理像素及其邻域组成比较序列,计算比较序列与参考序列之间的灰色关联度,并修正隶属度函数.对实际图像的测试实验表明,结合灰色关联分析的最大模糊熵分割算法比传统模糊熵分割算法具有更强的噪声抑制能力和更准确的分割结果.     

地球同步轨道SAR方位模糊度研究

与低轨合成孔径雷达(SAR)相比较,地球同步轨道合成孔径雷达（GEO SAR）具有重访周期短,观测范围广等优点,在军用及民用领域具有广泛应用。针对地球同步轨道合成孔径雷达多普勒中心频率时变及类滑动聚束工作模式造成常规方位模糊度计算不精确的问题,提出了一种新的方位模糊度计算方法。该方法基于精确的星地几何模型,考虑了地球自转、速度时变、多普勒中心频率时变以及类滑动聚束工作过程中天线指向变化对方位模糊度影响,通过对不模糊区域天线方位角及模糊区域天线方位角的精确求解得到了对应的天线增益值,进而得到方位模糊度的精确值。基于空间坐标系转换及矢量表示法推导了GEOSAR 方位模糊度的表达式。最后结合地球同步轨道SAR轨道参数进行了仿真,验证了该方法的有效性。      

粗糙归整映射与整周模糊度解算

在分析传统的基于GNSS载波相位测量模型对整周模糊度解算的一般规律后,得出一般归整映射的性质,进而提出粗糙归整映射理论,用来解决整周模糊度浮点解归整问题,提高了整周模糊度的搜索效率,一定程度上解决了载波相位实时测量的技术难题。     

星载ScanSAR工作模式研究与设计

该文系统地阐述了星载ScanSAR系统的基本工作原理,由ScanSAR系统的空间几何模型,确定了ScanSAR系统各子条带的空间位置,研究了ScanSAR系统的方位分辨率问题,确定了ScanSAR系统工作的时间关系,各子条带的脉冲重复频率的选择及每个burst的样本数,为系统设计提供了依据。重点研究了 ScanSAR系统的信噪比及距离模糊问题,提出了一种新的 ScanSAR系统特有的模糊概念ARASR,并提出新的分析方法,对其影响做了定量的计算,最后对 ScanSAR系统的数据下载格式提出了建议。     

LAMBDA算法在卫星导航定位中的应用研究

卫星导航定位中,基于载波相位观测值的RTK定位技术能够在达到厘米级的定位精度,其核心技术是整周模糊度的快速解算。采用LAMBDA方法能快速解算整周模糊度完成初始化,实时周跳检测,搜索并固定新的模糊度。利用2个NovAtel接收机采集数据,对采集到的数据进行仿真验证。仿真结果显示,该方法缩短了搜索的时间,定位结果达到了精度要求。     

Blind MIMO System Estimation Based on PARAFAC Decomposition of Higher Order Output Tensors

We present a novel framework for the identification of a multiple-input multiple-output (MIMO) system driven by white, mutually independent unobservable inputs. Samples of the system frequency response are obtained based on parallel factorization (PARAFAC) of three- or four-way tensors constructed based on, respectively, third- or fourth-order cross spectra of the system outputs. The main difficulties in frequency-domain methods are frequency-dependent permutation and filtering ambiguities. We show that the information available in the higher order spectra allows for the ambiguities to be resolved up to a constant scaling and permutation ambiguities and a linear phase ambiguity. Important features of the proposed approach are that it does not require channel length information, needs no phase unwrapping, and unlike the majority of existing methods, needs no prewhitening of the system outputs.     

MIMO-SAR大测绘带成像

该文提出利用MIMO-SAR系统实现大测绘带成像的方法。在该系统中,利用离散频率编码信号实现高距离分辨;同时采用低脉冲重复频率(Pulse Repetition Frequency, PRF)来获得不模糊的大测绘带,然而PRF降低会导致多普勒模糊。文中利用MIMO-SAR系统提供更多自由度进行空域滤波,成功地解决了多普勒模糊次数大于通道个数条件下的解模糊问题。仿真试验验证了该方法的有效性。     

Suppressing the azimuth ambiguities in synthetic aperture radarimages

A method for removing the azimuth ambiguities from synthetic aperture radar (SAR) images is proposed. The basic idea is to generate a two-dimensional reference function for SAR processing which provides, in addition to the matched filtering for the unaliased part of the received signal, the deconvolution of the azimuth ambiguities. This approach corresponds to an ideal filter concept, where an ideal impulse response function is obtained even in the presence of several phase and amplitude errors. Modeling the sampled azimuth signal shows that the absolute phase value of the ambiguities cannot easily be determined due to their undersampling. The concept of the ideal filter is then extended to accommodate the undefined phase of the ambiguities and also the fading of the azimuth signal. Raw data from the E-SAR system have been used to verify the improvement in image quality obtained by the new method. It has a substantial advantage in enabling the pulse-repetition frequency (PRF) constraints in the SAR system design to be relaxed and also for improving SAR image quality and interpretation     

Ambiguity resolution for permanent scatterer interferometry

In the permanent scatterer technique of synthetic aperture radar interferometry, there is a need for an efficient and reliable nonlinear parameter inversion algorithm that includes estimation of the phase cycle ambiguities. Present techniques make use of a direct search of the solution space, treating the observations as deterministic and equally weighted, and which do not yield an exact solution. Moreover, they do not describe the quality of the estimated parameters. Here, we use the integer least squares estimator, which has the highest probability of correct integer estimation for problems with a multivariate normal distribution. With this estimator, the propagated variance-covariance matrix of the estimated parameters can be obtained. We have adapted the LAMBDA method, part of an integer least squares estimator developed for the ambiguity resolution of carrier phase observations in global positioning systems, to the problem of permanent scatterers. Key elements of the proposed method are the introduction of pseudo-observations to regularize the system of equations, decorrelation of the ambiguities for an efficient estimation, and the combination of a bootstrap estimator with an integer least squares search to obtain the final integer estimates. The performance of the proposed algorithm is demonstrated using simulated and real data.     

TerraSAR-X System Performance Characterization and Verification

This paper presents results from the synthetic aperture radar (SAR) system performance characterization, optimization, and verification as carried out during the TerraSAR-X commissioning phase. Starting from the acquisition geometry and instrument performance, fundamental acquisition parameters such as elevation beam definition, range timing, receiving gain, and block adaptive quantization setting are presented. The verification of the key performance parameters—ambiguities, impulse-response function, noise, and radiometric resolution—is discussed. ScanSAR and Spotlight particularities are described.      

一种新的随机PRI脉冲多普勒雷达无模糊MTD算法

传统的脉冲多普勒雷达存在严重的测距测速模糊和盲区效应。该文结合压缩感知理论,考虑在正常脉冲重复间隔(Pulse Repetition Interval, PRI)上叠加一个随机扰动,并把PRI的随机变化巧妙转化为稀疏观测矩阵的受限等距性质(Restricted Isometry Property, RIP),提出了一种新的全相参动目标检测(Moving Target Detection, MTD)技术。并重点研究了距离速度模糊消除技术,给出了不模糊测距测速的参数设计充分条件。仿真实验结果表明,该方案检测性能高、无模糊、无盲区,并且相比传统的多脉冲串参差重频方法而言,只需一个脉冲串,大大缩短了相参处理周期。      

Explicit Ziv–Zakai bound for analysis of DOA estimation performance of sparse linear arrays

Sparse linear arrays (SLAs) provide similar direction-of-arrival estimation performance to filled linear arrays in terms of angular accuracy and resolution with reduced size, weight, power consumption, and cost. However, they are subject to significant ambiguities due to high sidelobes in the array beampattern, which give rise to large estimation errors. In this paper, we develop an explicit closed-form expression for the Ziv–Zakai bound on the mean square estimation error in order to quantify the degradation in estimation performance due to the sidelobe ambiguities. The bound consists of three terms which correspond to the three types of estimation errors: small mainlobe errors, errors due to sidelobe ambiguities, and random errors. The bound is used to analyze the performance of different SLA configurations. Maximum likelihood estimation simulations confirm the contribution of the different types of estimation errors predicted by the bound. The analysis shows that much of the performance degradation due to ambiguities are from random errors that cannot be controlled by array design, while additional degradation due to sidelobe errors depends strongly on the array configuration. Isolating the contributions of the three types of errors provides greater understanding of the behavior of sparse arrays, allowing for more effective system design and analysis.