共查询到18条相似文献,搜索用时 312 毫秒
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复杂电磁环境下,雷达、通信等信号在时域、频域、时频域存在复杂混叠,且各类型信号带宽差异大、调制样式多样,常规信号分离方法难以应用。文中提出了一种基于信号重构的非参数化混叠信号分离方法。基于瞬时幅度的傅里叶分解,建立非参数化稀疏信号模型,将混叠信号分离转化为瞬时幅度和瞬时频率的联合估计问题,基于交替迭代思路,分别进行估计和更新。对于瞬时幅度项,基于广义近似消息传递方法进行估计;对于瞬时频率项,利用瞬时频率变化平缓性特征,建立瞬时频率更新模型,实现对瞬时频率的更新。进一步,基于瞬时幅度和瞬时频率估计结果进行各信号重构,实现混叠信号分离。仿真结果表明:文中所提方法能有效分离时频域复杂混叠信号。 相似文献
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在进行欠定盲分离时,特别是对于源信号数目及混合矩阵动态变化的情况,常规的欠定盲分离及源数估计方法不能对源信号数目的变化时刻做出判断,因此很难实现动态变化的源信号数目实时和准确的估计。针对这个问题,提出了一种动态变化混叠模型下欠定盲源分离中的源数估计方法。首先,建立动态变化混叠情形下盲源分离的数学模型及动态标识矩阵。其次,基于构建的动态标识矩阵统计和判断动态源信号数目的变化情况。最后,通过分段时间内多维观测矢量采样点聚类区间局部峰值统计,实现动态变化混叠模型下盲源分离中的源信号数目的有效估计。仿真结果表明,该方法能有效实现动态变化混叠模型下欠定盲源分离中的源数估计,并且信号估计效果良好。 相似文献
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为了解决高混响环境下欠定卷积混叠信号的分离问题,提出一种新的欠定卷积盲源分离算法。针对高混响环境的影响,设计全局脉冲响应网络削弱混响回声,提高信号质量。基于全局脉冲响应网络建立新的时频域混叠信号数学模型,采用全局脉冲响应矩阵缩短了传统脉冲响应的长度,降低了高混响带来的模型变换近似误差。基于非负矩阵分解理论设计模型参数的实时更新学习规则,将源信号分离问题转换为模型参数优化问题,实现混叠信号的盲源分离。实验结果表明,所提算法可以有效地实现中英文语音、音乐混叠信号的盲源分离,与现有比较流行的盲源分离算法的对比验证了所提算法的优越性。 相似文献
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噪声环境下的病态混叠信号具有较强的空间复共线性,因此基于聚类的稀疏分量分析(SCA)方法难以在欠定条件下对其进行有效的分离。针对这一问题,该文首先建立了噪声环境下病态混叠信号欠定盲源分离问题的数学模型,分析了基于线性聚类的SCA方法在解决该问题时的局限性,提出了一种基于SCA和非正交联合对角化(NJD)的分离算法,该方法利用NJD不要求混叠矩阵为酉矩阵的特性,较好地解决了欠定盲源分离中的病态混叠问题。仿真实验表明,该方法在信号分离效果、噪声鲁棒性以及病态混叠鲁棒性上都明显优于基于启发式聚类粒子群优化的(CGPSO)的SCA方法。 相似文献
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This paper deals with direction of arrival (DOA) estimation and blind signal separation (BSS) based on independent component
analysis (ICA) with robust capabilities. An efficient demixing procedure of complex-valued ICA is presented here, which combines
the signal-subspace demixing procedure exploiting individual signal-subspace projection and Newton’s iteration algorithm based
on maximization of the approximate negentropy of non-Gaussian signal for array signal processing. It resolves the problems
of order ambiguity and identifiability of traditional ICA for time-domain BSS. The proposed method could be directly applied
to radar, sonar, radio surveillance, and communications systems for separating signals and estimating relative DOAs of signals.
Several computer simulation examples for perturbations to the array manifold, unknown noise environments, and Rayleigh fading
channel are provided to illustrate the effectiveness of the proposed method. 相似文献
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无线电监测频谱数据中包含有大量的信号,准确提取这些信号有利于掌握全频段的频谱使用情况。实际信号的频谱由于受噪声干扰,会出现信号频带内个别频点能量值低于检测门限的情况,此时传统的门限检测算法会将该信号错估为多个信号,产生多个虚假的相邻信号间隔,导致频谱信号提取的准确率下降。对此,根据虚假相邻信号间隔特点,提出一种自适应估计信号个数的频谱信号提取算法,该算法可自动、准确估计频谱监测数据中电磁信号的个数,并将对应的信号及频谱信息提取出来。实验结果表明,该方法具有自适应性、强鲁棒性和高准确性,有效提高了频谱信号提取的准确率,为军、民电磁环境的识别与掌握提供基础的电磁信号数据支撑。 相似文献
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Direct-sequence spread-spectrum (DSSS)/code division multiple access (CDMA) transmissions are now widely used for secure communications
and multiple access. They can be transmitted at a low signal-to-noise ratio, and have a low probability of interception and
capture. How to obtain the original users' signal in a noncooperative context or estimate the spreading sequence in blind
conditions is a very difficult problem. Most of the signal sources are assumed to be instantaneous mixtures. In fact, the
received CDMA signals are linearly convoluted. A more complicated blind source separation (BSS) algorithm is required to achieve
better source separation. In this paper, a new BSS algorithm is proposed for separating linearly convolved signals in CDMA
systems when the mixture coefficients of the signal and channel response are totally unknown, but some knowledge about the
temporal model does exist. This algorithm is based on minimizing the squared cross-output-channel-correlation criterion. The
simulation results show the effectiveness of the algorithm in the blind detection of DS-CDMA signals. 相似文献