贝塞尔级数展开的机载前视阵雷达杂波谱补偿方法

提出了基于级数展开的杂波谱补偿方法,首先采用贝塞尔函数对每个距离环实现方位和俯仰角的分离;接着将训练单元的俯仰矢量向待检单元进行投影,得到一个变换矩阵.再使用变换矩阵对给定的多普勒门的数据进行处理,减轻杂波谱对距离的依赖性;最后,从变换后的数据中估计杂波协方差矩阵,再利用空时自适应算法对补偿后的数据进行杂波抑制.仿真结果表明,该方法能有效改善杂波的非平稳性,提高了系统抑制杂波的性能.     

一种改进的机载双基雷达多普勒频移算法

机载双基雷达由于载机之间的相对运动,造成其杂波分布随距离变化而变化,直接导致杂波协方差矩阵估计不准确,进而使得空时自适应处理技术的杂波抑制和动目标检测性能下降.提出一种杂波非均匀补偿技术,该方法先采用多普勒频移预处理,使得主波束方向上的杂波谱重合,然后通过对多个空间角方向上的归一化多普勒频率进行补偿,使各距离单元的杂波谱保持一致.仿真结果表明该方法能有效改善机载双基雷达的杂波非均匀情况,性能明显优于原有算法.     

互耦效应下端射阵机载雷达空时内插STAP方法

针对端射阵天线由于阵元间距较小,容易造成能量耦合引起互耦效应,进而影响天线增益和空域导向矢量等参数以及后续的杂波抑制性能这一问题,首先利用互阻抗法和等距离环地面散射单元积分法,建立了互耦条件下的端射阵机载雷达信号模型;然后分析了互耦效应对杂波特征谱和空域导向矢量等参数的影响;最后提出了一种基于空时内插的空时自适应处理方法,对杂波的非平稳性和空域导向矢量进行了补偿.理论分析和仿真结果证明了该方法的有效性.     

机载雷达非正侧面阵近程杂波抑制新方法

根据机载雷达非正侧面阵的近程杂波随距离快变的特性,提出了俯仰向空域滤波子阵合成的算法．该算法利用平面阵列天线在俯仰向的自由度,先对近程杂波进行滤除,然后再在方位空域和时域做空时自适应处理．这样就增强了远程杂波的距离平稳性,很容易准确地估计协方差矩阵,从而提高了空时自适应处理抑制非正侧面阵杂波的性能．仿真结果证明了无误差时改善因子可以提高约30dB．     

一种新的无人机载雷达非均匀杂波抑制方法

无人机载雷达可以对感兴趣的重点区域和目标进行持续跟踪,在军用和民用领域都有广泛应用前景.然而载机平台的运动会带来地杂波谱的展宽,致使潜在的低速微弱目标淹没在强地杂波中.为了解决无人机机载雷达非均匀环境下的地面杂波抑制问题,提出一种基于恒虚警样本选择策略的非均匀下视杂波抑制方法.通过距离分块策略解决距离空变带来的非均匀样本的差异,通过低门限恒虚警(constant false alarm rate,CFAR)策略剔除孤立的强杂波散射点和疑似运动目标对训练样本的影响,降低非均匀样本单元对协方差矩阵估计的干扰,从而提高非均匀环境下对杂波的抑制性能.结合一组实测挂飞数据,对比了不同杂波抑制方法对运动目标检测的影响.实测数据验证所提方法有效.     

使用极化知识的非均匀杂波数据选择器

为了解决雷达自适应处理中由于杂波的非均匀所带来的性能恶化问题,提出了一种基于极化特征知识的非均匀复合高斯杂波训练数据选择方法．该方法对训练数据单元进行极化散射矩阵的最大似然估计,然后计算每个估计值与先验极化知识的误差,以此作为区分野值的特征,从非均匀杂波中去除野值得到均匀的训练数据．仿真结果表明,该方法在野值杂波比较低时仍能够有效地去除野值,改善了杂波协方差矩阵的估计性能．     

特征矢量约束的近程杂波抑制鲁棒自适应波束形成算法

针对机载非正侧视阵在距离模糊条件下的近程杂波抑制问题,提出了一种俯仰滤波算法.利用杂波协方差矩阵特征分解形式,建立了一种特征矢量选择方法.用该方法挑选出对应于近程和远程的特征矢量作为波束形成算法的约束.相对于传统算法,这种特征矢量约束的波束形成算法指向误差和导向矢量失配更具鲁棒性,并克服了主瓣畸变的问题.仿真结果验证了该算法的有效性.     

基于空时自适应处理的机载机控阵雷达子阵结构研究

由于实际的杂波谱随距离呈现一定的非均匀性,相应地要求ＳＴＡＰ处理器在俯仰上也应具有可控自由度．文中以６４×１２ 正侧面矩形阵为例,比较了在总的空域自由度一定的条件下,３ 种子阵结构ＳＴＡＰ的性能．研究结果表明,当空域自由度在阵面的水平和垂直方向上（与距离对应）合理分配时,ＳＴＡＰ处理器能够自适应抑制与距离有关的强杂波,使整体剩余杂波加噪声功率下降２～３ ｄＢ,从而可使ＳＴＡＰ的潜能得到进一步的发挥     

基于ＭＴＩ滤波器特性的改进直接数据域算法的研究

传统的空时自适应处理方法属于统计方法,一般假设其它相邻距离单元的训练样本满足独立同分布的条件,利用这些训练样本来估计待检测单元中杂波的协方差矩阵．对机载雷达来说,严重非均匀环境很难满足样本独立同分布的要求．直接数据域方法只利用待检测距离单元本身的数据来获取训练样本,因此得到广泛应用．提出一种改进直接数据域算法,在利用空时窗滑动对消目标信号时,基于滤波原理,对空时窗的权系数进行优化,这样有利于在对消目标的同时保留更多杂波信息,进而求解的自适应权值对杂波的抑制性能更佳．仿真结果表明了改进算法的有效性,相比原始直接数据域算法,具有更窄的改善因子凹口,提高了对慢速目标的检测性能,且计算量没有增加．     

机载双基雷达杂波分析及其距离模糊杂波的抑制

分析了各种机载双基雷达构型的几何关系,采用以方位角和双基距离为变量的杂波建模方法,推导出了在任意双基构型下接收杂波多普勒频率的计算公式．为分析双基杂波特性,提供了有效工具．然后针对具有距离模糊的杂波,提出了对各次模糊距离的主杂波分别做角度多普勒补偿的空时自适应处理(STAP)方法,有效地解决了双基雷达各次距离模糊杂波的抑制问题．     

Novel angle Doppler compensation method

In a non-side looking airborne radar system, the clutter of different range cells is not independently and identically distributed, which is caused by the severe clutter range-dependence. The clutter range-dependence can be compensated by the angle Doppler compensation (ADC) method simply and quickly. Although the ADC is widely applied, the compensation performance of the ADC is affected by the system error significantly because of the mismatch between Doppler frequency and spatial frequency. In this paper, a novel method to compensate the clutter range-dependence, namely ADC using sparse recovery (SR-ADC), is proposed. Firstly, the clutter spectral distribution estimation of the test cell and training cells are obtained by using sparse recovery. Then, the spatial frequencies and Doppler frequencies of the clutter spectrum center are determined. Finally, transform matrixes of different training cells are designed so that the clutter of training cells could be nearly stationary with respect to that of the test cell. Compared with the traditional angle Doppler compensation method, the proposed method improves greatly the compensation performance, especially that of main-lobe clutter. In addition, this method can also achieve good performance when the system error exists.     

Extended fractal properties of the AR spectrum and its application in weak target detection in sea clutter background

This paper mainly studies the extended fractal properties of the power spectrum of the sea clutter. To overcome the deficiencies of Fourier transform analysis, the power spectrum of the sea clutter is obtained by autoregressive(AR) spectrum estimation. The AR model is a linear predictive model, which estimates the power spectrum of the sea clutter from its autocorrelation matrix and has a higher frequency resolution than Fourier analysis. This paper concentrates on analyzing the extended fractal property of the power spectrum based on AR spectral estimation and its application to weak target detection. Firstly, fractional Brownian motion (FBM) is taken as an example to prove the self-similar property of the power spectrum. Then, the real measured X-band data is used to analyze the multi-scale Hurst exponent of the AR spectrum of the sea clutter and its optimized scale interval. Finally, a novel detection method based on the multi-scale Hurst exponent of the AR spectrum is proposed. The results show that the proposed method is effective for weak target detection in sea clutter background. Compared to the existing extended fractal method and the traditional CFAR method, the proposed method has a better detection performance in the low SCR condition.     

一种稳健的机载前视阵雷达杂波谱补偿方法

针对空间角频移前视阵杂波谱补偿方法将参考距离单元的杂波谱旁瓣抬高,导致旁瓣区动目标检测性能下降的缺点,提出了一种改进的空间角频移方法．先对各个距离单元回波进行多普勒频率补偿,然后再进行空间角频移．仿真实验结果表明,本方法在旁瓣区比空间角频移方法有3~5dB的性能改善,并且在雷达回波存在误差的情况下仍然能够保持好的性能．     

Registration based compensation method based on adaptive subspace tracking

The registration based compensation (RBC) method is an effective method to compensate the range-dependence of the main-lobe clutter and side-lobe clutter in the same time. However, the compensation performance of the RBC degrades because of the mismatch of prior information and the loss of degree of system freedom. Moreover, the RBC is not very suited for real-time implementation because of the enormous computational complexity and memory usage of eigenvalue decomposition. In this paper, a novel clutter range-dependence compensation method using the modified maximum likelihood adaptive subspace estimation algorithm, which is named the MRBC method for short, is proposed. The eigenvectors matrix and eigenvalues matrix of the clutter covariance matrix are estimated by iterative tracking instead of temporal and spatial smoothing, spectrum calculation and eigenvalue decomposition. Compared with the traditional RBC method, the proposed method can reduce the computational complexity significantly and maintain the performance of clutter range-dependence compensation. In addition, the proposed method can also achieve good performance when the system error exists because of no use of prior information. Experimental simulations demonstrate the validity of this method.     

机载PD雷达杂波功率谱快速重构方法

分析了机载脉冲多普勒雷达杂波功率谱理论模型,根据杂波生成机理,利用距离折叠和多普勒折叠的效应,提出了一种快速重构多脉冲重复频率下雷达杂波功率谱的方法;利用一个预先计算的基准杂波功率分布图,通过距离域和多普勒域的两次级联重构,完成多重频下杂波功率谱的计算和仿真;分析了载机与雷达参数对功率谱重构的影响,减少了运算量,为功率...     

临近空间慢速平台SAR地面动目标检测与成像

临近空间慢速平台SAR具有生存能力强、持续工作时间长、机动性能好等特点。该文提出了一种临近空间慢速平台SAR地面动目标检测与成像方法。由于平台运动速度较慢,地面静止杂波多普勒展宽较窄,有利于将地面杂波与动目标回波进行分离。首先利用多普勒滤波器实现地面动目标回波与静止杂波的分离,提取出动目标回波;然后将一阶Keystone变换与变分辨多普勒调频率估计方法相结合,在动目标速度未知的情况下完成距离走动校正和距离弯曲校正,解决了动目标回波距离徙动校正难的问题。利用估计出的多普勒调频率设计出方位压缩函数进行方位聚焦,从而完成动目标的检测与成像。该方法不仅适用于地面慢速运动目标,同时也适用于快速运动目标。计算机仿真验证了该方法的有效性。     

Intermittent Clutter Removal Approach for Wind Profiler Data Based on Fractional Fourier Transform

Through the analysis of the target characteristics and according to the intermittent clutter bursting and short duration characteristics, a new method for the clutter recognition based on the fractional Fourier transform (FRFT) is proposed. This method is predicated on the fact that the FRFT perfectly localizes a chirp signal as an impulse when the angle parameter of the transform matches the chirp rate of the chirp signal. The method involves detecting the presence of the intermittent clutter and correctly estimating its orientation in the time-frequency plane, removing the intermittent clutter in the fractional domain, and completing wind estimation by the power spectrum. By testing the artificial WPR-like signal and data measured from the field, we verify that the FRFT-based method is very effective.     

Intermittent Clutter Removal Approac for wind Profiler Data Based on Fractional Fourier Transform

Through the analysis of the target characteristics and according to the intermittent clutter bursting and short duration characteristics, a new method for the clutter recognition based on the fractional Fourier transform (FRFT) is proposed. This method is predicated on the fact that the FRFT perfectly localizes a chirp signal as an impulse when the angle parameter of the transform matches the chirp rate of the chirp signal. The method involves detecting the presence of the intermittent clutter and correctly estimating its orientation in the time-frequency plane, removing the intermittent clutter in the fractional domain, and completing wind estimation by the power spectrum. By testing the artificial WPR-like signal and data measured from the field, we verify that the FRFT-based method is very effective.     

Robust registration based compensation method based on sparse recovery

The loss of the degree of system freedom and mismatch of prior information based on the registration based compensation (RBC) method will result in a decline in computational performance. In order to solve above problems, a robust method named SRBC is proposed where the sparse recovery method is applied instead of the sub-aperture smoothing operation. First, the SRBC utilizes the sparse recovery to get the super resolution clutter space-time spectrum. Then the transition covariance matrix is calculated. Finally, the clutter covariance matrix is reconstructed by the Capon spectrum. Compared with the traditional RBC method, the SRBC proposed does not depend on sub-aperture smoothing operation and prior information and maintains the performance of clutter range-dependence. In addition, it is also steadier when the sensor error exists. Experimental simulation demonstrates the correctness and feasibility of this method.