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多假目标干扰是与目标信号强相关的欺骗干扰信号,其对准雷达天线主瓣方向,会严重影响雷达的性能,通常的旁瓣抗干扰技术和一些主瓣抗压制干扰技术难以奏效.针对目标和干扰信号的相对独立性以及在空域上的差异性,提出利用盲源分离(Blind Source Separation,BSS)算法抗脉冲压缩雷达多假目标干扰的方法.首先给出了假目标干扰原理和主瓣干扰信号模型;其次利用经典的BSS算法分离接收到的主瓣干扰混合信号,并脉压找出目标信号达到抗干扰的目的;最后分析了目标与多假目标干扰混合信号的可分离性.仿真实验表明,该方法对多假目标干扰有良好的抗干扰性能. 相似文献
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在水声制导技术中,提出了一种高效分离算法,实现了对多目标源信号的分离,为系统后端对多目标定位提供了技术支持。窄带信号条件下,把盲分离与阵列信号处理结合起来.借助阵列模型把接收的混合信号变成解析信号,然后利用瞬时复值盲分离算法进行分离获得源信号的解析信号,取实部后便是实源信号。从而将实数的卷积混合转化为复数的瞬时混合,在盲分离阵列模型的基础上,通过复数盲分离的手段完成盲解卷积。解卷积恢复的多目标源信号十分有利于多目标特征识别与定位。通过构建正弦信号盲解卷积仿真实验,对文中提出的盲解卷积方法进行了验证。结果表明了该方法的正确性。 相似文献
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相控阵雷达采用多个阵元进行信号的接收处理,其多通道信号处理可以采用盲信号处理的方法进行目标源信号分离.由于阵元间距导致信号在阵元间产生相位延迟,在进行盲分离的时候一般只能采用卷积混合模型,盲分离过程是较为复杂的多通道反卷积问题.文中对阵列接收信号进行波束域预处理,通过确定的空间波束相位补偿,将阵元域的多时延混合信号变换为瞬时混合信号,从而采用简单的实数分离算法即可完成信号分离,分离信号可用于后置处理.所提方法简单有效,相比常规阵列信号处理方法,可直接适用于宽带信号.仿真实验验证了其有效性. 相似文献
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针对大功率干扰下的分布式多站雷达探测能力下降的问题,本文提出了一种新的基于盲源分离的干扰抑制方法。该方法对多部雷达接收信号进行信号级和数据级的联合处理,包括干扰相对时延估计及补偿-盲源分离-多组合配对定位三个步骤。首先分别以不同接收回波信号为参考,采用相关法估计各站点干扰信号相对时延,并进行补偿使干扰成分得到校准。然后针对校准后的信号,采用盲源分离算法,实现干扰信号和目标回波信号分离。最后,利用多组合配对定位方法,剔除由于盲源分离得到的虚假目标定位点,从而得到真实目标位置信息。最后本文通过仿真实验证明了该算法的有效性。 相似文献
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针对抗波门拖引干扰现有理论研究的不足,结合现代欺骗式干扰机的结构特点和干扰信号的产生机理及对具体雷达接收机的作用机理,分析干扰信号进入雷达系统后雷达接收回波信号的特征变化;提取接收信号统计特征及细微特征检测有无干扰;并根据干扰过程中回波信号与干扰信号相互作用的规律及时变特征,研究了干扰信号识别的理论模型,形成了基于过程的波门拖引干扰子类型的识别方法,为进一步提高雷达系统抗干扰能力提供理论基础。仿真实验证明该方法有较高的识别率。 相似文献
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基于子空间分解的多通道盲解卷积算法 总被引:3,自引:0,他引:3
针对卷积混合信号,提出了一种新的多通道盲解卷积算法,该算法首先利用子空间分解方法,将信号卷积混合模型变换成线性混合模型,然后利用线性混合盲分离算法分离出源信号.该算法相对频域盲解卷积算法来说无需解决线性混合盲分离中存在的幅度和排列顺序的模糊性问题,而且该算法不要求信号独立同分布,只要求各源信号统计独立即可.因此,该算法可以直接在中频对观察信号进行处理.计算机仿真结果表明,该算法不仅能对不同频不同调制方式的通信信号进行盲解卷积,而且对同频同调制的通信信号,该算法同样有效. 相似文献
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空间电子探测信号盲分离研究 总被引:1,自引:1,他引:0
给出了盲信号分离中的瞬时混合,时延混合和卷积混合三种混合模型,介绍了两种具体的盲分离算法,等变自适应盲分离算法和非高斯性最大化的快速定点算法.其中对于窄带源信号,对时延混合模型进行了扩展,提出了用复数域瞬时盲信号分离算法分离时延混合信号的新思路.最后给出了相应的仿真和实验结论,实验结果表明用基于复数的盲分离算法确实能够有效地分离阵列接收的时延混合信号. 相似文献
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Adriana Dapena Daniel Iglesia Carlos J. Escudero 《Circuits, Systems, and Signal Processing》2010,29(3):403-417
This paper presents a novel technique for separating convolutive mixtures of statistically independent non-Gaussian signals
without resorting to an a priori knowledge of the sources or the mixing system. This problem is solved in the frequency domain by transforming the convolutive
mixture into several instantaneous mixtures which are independently separated using blind source separation (BSS) algorithms.
First, the instantaneous mixture at one frequency is solved using the joint approximate diagonalization of eigenmatrices (JADE)
technique, and the other mixtures are then separated using the mean squared error (MSE) criterion. As a special case of this
method, we consider the separation of non-Gaussian temporally white signals transmitted in blocks with zero padding between
them. 相似文献
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脉冲宽度鉴别作为雷达工程中的一种抗干扰技术,是利用雷达信号脉冲宽度与干扰信号脉冲宽度之间的差异来抑制不同脉冲宽度的干扰脉冲信号。提出了一种新颖的脉宽鉴别方式,可以根据信号功率大小自动调节比较门限,实现对雷达信号的准确鉴别。 相似文献
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An important problem in the field of blind source separation (BSS) of real convolutive mixtures is the determination of the role of the demixing filter structure and the criterion/optimization method in limiting separation performance. This issue requires the knowledge of the optimal performance for a given structure, which is unknown for real mixtures. Herein, the authors introduce an experimental upper bound on the separation performance for a class of convolutive blind source separation structures, which can be used to approximate the optimal performance. As opposed to a theoretical upper bound, the experimental upper bound produces an estimate of the optimal separating parameters for each dataset in addition to specifying an upper bound on separation performance. Estimation of the upper bound involves the application of a supervised learning method to the set of observations found by recording the sources one at a time. Using the upper bound, it is demonstrated that structures other than the finite-impulse-response (FIR) structure should be considered for real (convolutive) mixtures, there is still much room for improvement in current convolutive BSS algorithms, and the separation performance of these algorithms is not necessarily limited by local minima. 相似文献
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抗干扰性能是决定雷达作战效能发挥的重要因素,传统的雷达抗干扰性能评估仿真体系不健全,技术方法单一,智能化程度低,可视性差。基于现代雷达智能抗干扰工作体系,设计实现了基于干扰信号感知的雷达智能抗干扰评估仿真系统。系统分为干扰信号识别、主动/被动干扰拟制、抗干扰性能评估三大模块,应用支持向量机(SVM)提取干扰信号时频特征进行智能识别,对不同干扰采用旁瓣对消、旁瓣匿影、发射波束优化等抗干扰策略,给出抗干扰前后雷达抗干扰性能的提升情况,做到了雷达智能抗干扰的全过程评估。系统可为雷达抗干扰技术的分析验证提供了良好的验证平台,具有一定的应用前景。 相似文献
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The problem of blind source separation (BSS) and system identification for multiple-input multiple-output (MIMO) auto-regressive (AR) mixtures is addressed in this paper. Two new time-domain algorithms for system identification and BSS are proposed based on the Gaussian mixture model (GMM) for sources distribution. Both algorithms are based on the generalized expectation-maximization (GEM) method for joint estimation of the MIMO-AR model parameters and the GMM parameters of the sources. The first algorithm is derived under the assumption of unstructured input signal statistics, while the second algorithm incorporates the prior knowledge about the structure of the input signal statistics due to the statistically independent source assumption. These methods are tested via simulations using synthetic and audio signals. The system identification performances are tested by comparison between the state transition matrix estimation using the proposed algorithms and the well-known multidimensional Yule-Walker solution followed by an instantaneous BSS method. The results show that the proposed algorithms outperform the Yule-Walker based approach. The BSS performances were compared to other convolutive BSS methods. The results show that the proposed algorithms achieve higher signal-to-interference ratio (SIR) compared to the other tested methods. 相似文献