降维STAP中稀疏恢复的角度多普勒通道选择方法

在机载雷达信号处理中,高强度的地杂波严重影响信号检测性能,而空时自适应处理(STAP)是一种有效抑制杂波的技术。实际处理中,由于杂波的非均匀性,空时自适应处理往往面临着可用有效样本数较少的问题,同时机载雷达处理的信号维度极为庞大。为了解决这些问题,提出了一种基于稀疏恢复的降维STAP通道选择方法。利用少量样本通过稀疏恢复的方法估计出全维度的杂波协方差矩阵(CCM),并以此为依据评估各个通道的重要性,选择合适的通道构造出降维后的杂波协方差矩阵并进行STAP处理,解决了有效样本较少的问题,同时保证了降维算法的性能。数值仿真验证了算法有效且比典型的稀疏STAP算法效果更好,讨论了在不同样本数下,输出性能与通道数的关系,结论具有工程应用意义。     

机载前向阵雷达近程杂波频移补偿

基于机载前向阵雷达在近距离地面目标检测时,杂波在距离上将呈现严重的非平稳性,提出了一种向量相似度准则,从杂波样本数据中计算补偿量的多普勒频移补偿方法。利用该方法对不同距离的杂波数据进行相应的频移变换预处理后,能有效改善近程地杂波的非平稳性。该算法在脉冲域和多普勒域中等效,适合并行运算,具有实现简单的优点。仿真结果表明经此方法预处理后的空时自适应滤波,能显著提高系统的性能改善因子。     

双基机载雷达的杂波谱补偿方法

双基机载雷达结构中杂波多普勒频率是随距离和双基结构发生变化的,使杂波谱在距离上呈现严重的非平稳性,导致杂波协方差矩阵估计困难．针对此问题提出一种基于最小二乘的空域导向矢量拟合的杂波谱补偿方法,先将训练单元上的空域导向矢量向待检单元的空域导向矢量投影得到一个变换矩阵,用这个矩阵对训练单元上的数据进行预处理,消除杂波谱的非平稳性,得到足够的统计数据,从而构造新的杂波协方差矩阵,最后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够有效地抑制地杂波的非平稳性,提高雷达杂波抑制的性能．     

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.     

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．     

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.     

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.     

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．     

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.     

Clutter pre-filtered method applied in bistatic airborne radar

In order to solving the problem of ineffective clutter suppression and target detection of space-time adaptive processing(STAP) in bistatic airborne radar, a clutter pre-filtering method applied in the bistatic airborne radar that takes advantage of radar operating parameters, platform velocity and so on is proposed. The velocity error of the airborne platform is also considered. Most of the clutter can be filtered so that the residual clutter can be completely suppressed by the well-developed STAP algorithm. Computer simulation results show that this method is effectively workable to several classical geometric configurations of bistatic airborne radar. The moving target detectability of the following STAP algorithm is also enhanced after this pre-filter.     

非均匀环境下利用雷达参数信息的STAP方法

针对非均匀杂波环境下空时自适应处理杂波抑制性能下降的问题,基于扁平椭球波函数的时限带限特性,给出一种利用雷达参数信息构造子空间的杂波抑制方法,降低了计算量与均匀样本数需求,提高了对非均匀杂波的抑制性能。其次,针对存在阵面偏航角误差时杂波秩无法准确估计造成基于扁平椭球波函数构造杂波子空间方法杂波抑制性能下降的问题,结合雷达参数信息及探测环境的几何构型提出一种杂波预处理方法以消除偏航角影响,从而提升其非均匀环境下的杂波抑制性能。仿真结果验证了算法的有效性。     

基于Bayes准则的STAP协方差矩阵估计算法

针对杂波功率随距离缓变的非均匀环境,提出了一种新的基于Bayes准则的加权最大似然估计(WMLE)算法,以改善空时自适应处理(STAP)中的协方差矩阵估计．通过对训练数据进行事件定义,利用Bayes准则给出了加权系数的准确计算方法,解决了WMLE中加权系数的求解难题．仿真分析验证了所提出算法的正确性和有效性．     

强空时杂波背景下自适应处理的稳健方法

对于机载雷达在强杂波背景中的自适应信号处理问题,提出了改进的静态方向图控制方法。新方法在原有架构上加入了二次波束方向图约束,并利用Taylor级数近似来估计其解。把自适应处理限制于变换域中的一个局域处理区域得到改进的降秩波束空间空时自适应处理架构。该架构中信号阻塞矩阵由围绕感兴趣单元的少量角度多普勒单元组成。把上述两种方法相结合得到一种稳健空时自适应处理方法。该方法能有效抑制杂波而同时保持低旁瓣,对采样要求低,大大减少了运算量。数值实验结果证明了所提方法的有效性。     

Inshore ambiguity clutter suppression method aided by clutter classification

To address the problem that the clutter suppression performance is reduced for the multichannel synthetic aperture radar(SAR) because of the ambiguous component of the land clutter in the inshore area,we propose an inshore ambiguity clutter suppression method aided by on clutter classification.First,a multi-look interference feature covariance matrix(MIFCM) for each range-Doppler unit is constructed,which includes multi-look interference magnitude/phase and multi-look interference magnitude gradient information.Next,with the affine invariant riemannian(AIR) distance measure of MIFCMs,the clutter classification result can be acquired.Finally,with the clutter classification result,we select independent and identically distributed(IID) training samples to estimate the clutter covariance matrix in the ambiguous clutter region,with clutter suppression performed in the multichannel SAR image domain.Simulation result shows that the proposed method can accurately classify and suppress the azimuth ambiguous clutter in the inshore area.     

DOA estimation method based on the covariance matrix sparse representation

The performance of the L₁-norm-based sparse representation of array covariance vectors(L₁-SRACV) algorithm significantly degrades with the number of samples decreasing. This paper analyzes the essential cause of this performance degradation and proposes a new direction of arrival(DOA) estimation method based on the fast maximum likelihood(FML) algorithm. Firstly, the FML algorithm is employed to estimate the covariance matrix, which attenuates the instability of the small eigenvalues of the covariance matrix. Then the sparse representation model based on the FML is formulated for DOA estimation and finally, optimized by removing the diagonal elements of the covariance matrix to obtain better performance. Simulation results indicate that our method outperforms the L₁-SRACV with a higher accuracy and detection possibility, particularly under small samples support.     

Effective Sea Clutter Spectrum Extraction Method for HFSWR in Adverse Conditions

An effective approach in solving the sea clutter spectrum extraction problem is studied in the paper. Different from the conventional signal to noise ratio (SNR) method based on Doppler frequency or range domain information, a method is developed to characterize the differences between the sea echo and those interferences are by signal to interference plus noise ratio (SINR) which jointly utilizing the range, Doppler frequency and azimuth domain information. Furthermore, these differences can be adaptable to adverse conditions by forming the necessary boundaries and constraints in searching of the maximum SINR, which greatly promotes the extraction of sea clutter spectrum. The real high frequency surface wave radar (HFSWR) data demonstrate that the proposed method is less influenced by those interferences and can effectively extract the sea clutter spectrum even under the adverse conditions. Furthermore, it has been shown as an effective method for ship detection and sea state remote sensing of HFSWR.     

MIMO雷达空时编码和接收权联合稳健设计

针对基于多进多出雷达的空时自适应处理方法的检测性能对目标参数估计误差敏感从而导致系统检测概率稳健性较差的问题,提出一种改善多进多出空时自适应检测性能的发射波形和接收权联合稳健设计方法。首先推导了多进多出空时自适应输出信干噪比的数学表达,而后构建了目标空时频导向矢量估计误差模型。在此误差模型、波形恒模特性、旁瓣以及杂波抑制等约束下,基于最大化最差情况下输出信干噪比准则,提出了改善多进多出空时自适应检测性能的发射波形相关阵和接收权联合稳健优化问题。为求解所得复杂非线性优化问题,提出一种迭代方法,其中每一步都可转化为半定规划问题,因而可获得高效求解。仿真结果表明,与现存主要的稳健方法、非稳健方法及不相关波形相比,所提方法可显著改善多进多出空时自适应检测概率的稳健性能。     

一种多普勒后处理的STAP方法研究

针对现有多普勒后处理的空时自适应处理(STAP)方法在不加权时多普勒通道相互正交,甚至在加权时相关性也不高的问题,提出了一种新的多普勒后处理的STAP方法．通过缩小主、辅多普勒通道中心频率的间距来提高相关性,降低杂波的自由度,减轻空域自适应处理的负担,使其性能提高．对机载双通道雷达实测数据的处理验证了该方法对杂波具有良好的抑制能力,能使3DT方法的改善因子提高0.5dB,且在阵元幅相误差高达10％时,仍具有较高的稳健性．     

基于频域相对样本熵的海面小目标特征检测

海面小目标是海洋雷达探测的重难点对象.针对传统检测器检测概率低的问题,本文提出一种基于相对样本熵的特征检测器(Feature Detector via Relative Sample Entropy, FD-RSE).首先,定义白化频谱,实现对主杂波带的抑制,从而增大了海杂波序列的不规则性.其次,通过引入样本熵描述序列的复杂度,提取白化频谱的相对样本熵,并将之作为特征.在检测时,该特征能够充分利用海杂波和含目标回波在频谱上的几何差异性.最后,IPIX实测数据验证表明：与传统检测器相比,FD-RSE检测器能有效改善检测性能.