共查询到17条相似文献,搜索用时 62 毫秒
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针对非协作通信中成对载波多址(Paired Carrier Multiple Acess,PCMA)信号的盲分离问题,提出了一种基于独立分量分析(Independent component analysis,ICA)的单通道盲分离算法。首先对接收到的单路PCMA信号进行参数估计得到其残余载波频率,再对其处理得到两路基带混合信号,最后利用ICA算法分离出源基带信号。该算法在未知两个卫星地面站发送信号的情况下,从接收到的PCMA信号中恢复出两路源基带信号。仿真实验表明,本文算法在信噪比为-10dB时仍具有良好的分离效果,两路基带信号的波形相似系数可分别达到0.94与0.86以上。 相似文献
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提出了一种成对载波多址系统中信息序列和信道联合估计的算法。该算法在不具备任一协作通信方发送的信息序列的先验知识前提下从混合信号中解调出两路信息序列。该算法结合了逐幸存路径处理法无延迟的信道参数估计特性和Kalman滤波良好的估计性能。仿真实验表明,该算法具有良好的信道捕获与跟踪能力,且实现较好的符号序列估计性能。 相似文献
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针对非协作通信下数字信号解调的问题,提出一种基于粒子滤波和Viterbi序列检测的盲解调算法。粒子滤波使用一组具有相应权值的粒子来表示未知参数的后验分布,再利用Viterbi算法对信号符号作进一步估计,最终实现对数字信号的盲解调。经仿真实验验证,该方法可以有效完成对BPSK、QPSK、UQPSK、OQPSK、8 PSK等常用PSK数字信号类型的盲解调,且较传统方法实现起来更为方便。 相似文献
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针对卫星信道中高功率放大器产生非线性失真的问题,本文提出了一种基于粒子滤波技术的盲均衡法。该算法优势在于不需要对非线性信道线性化处理,而是利用带权值的离散随机样本点来对期望分布进行近似,通过将非线性模型建模成状态空间模型,对信道参数进行跟踪和符号序列估计。仿真结果表明,算法实现了对放大器非线性幅度和相位特性的粒子滤波估计,并对符号序列进行了盲恢复,在误比特率为 较截断Volterra均衡有1.5 dB左右的性能增益;通过增加粒子数目和平滑长度能一定程度上提高算法性能,但在复杂度与性能折中考虑下,不能无限增加粒子数目。 相似文献
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On the basis of a blind separation structure with low complexity,an efficient blind separation algorithm based on soft information joint correction was proposed for asymmetric PCMA to improve the demodulation performance of strong and weak signals.By utilizing the demodulation mutual influence between the strong and weak signals,this algorithm tried to correct the receiving symbols of strong signal with high error probability.Comparing the symbol constellation quality (soft information) of signals before and after correction,it can be decided whether the hard decision values of strong and weak signals need to be modified,which efficiently reduce the demodulation error rate of strong and weak signals.The simulation results show that,the demodulation error rate of strong and weak signals can be reduced by nearly two orders of magnitude after joint correction especially when the signal to noise ratio of strong signal is higher than 17 dB,and the computational complexity of this algorithm is lower than that of the conventional reconstruction cancellation algorithm. 相似文献
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A blind separation algorithm was proposed for PCMA signals with different symbol rates based on double grid per-survivor processing (DG-PSP).The channel states and two input signal components were treated as two dynamic grids,receiving mixed-signal reconstructed by respectively iterative updating the two groups of grid status,thus achieving blind signal separation.The joint iterative decoding separation structure was focused,and a detailed analysis and comparison under different error estimation of parameters was shown.The complexity of the algorithm is similar to the traditional PSP algorithm.Simulation results show that,a gain of about 2 dB in signal-noise ratio can be obtained after the first iteration at a bit error rate of 10?2,and a gain of nearly 3 dB in signal-noise ratio can be obtained after the second iteration. 相似文献
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基于FastICA的混合音频信号盲分离 总被引:2,自引:0,他引:2
独立成分分析(ICA)作为一种有效的盲源分离技术已成为信号处理领域的热点,它以非高斯源信号为研究对象,在统计独立的假设下,对多路观测到的混合信号进行盲信号分离。为了提高算法的收敛速度和稳态精度,介绍了独立成分分析的基本原理,以及利用FastICA算法进行信号分离的理论依据,引入了改进的非线性函数,运用Matlab进行仿真比较3种非线性函数下的分离性能和改进的非线性函数在不同θ下的分离性能,结果表明在综合因素的考虑下,该改进函数在实现混合音频信号盲分离方面比改进前更有效。 相似文献
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Yu Xiao Hu Guangrui 《电子科学学刊(英文版)》1999,16(2):165-171
There are two major approaches for Blind Signal Separation (BSS) problem: Maximum Entropy (ME) and Minimum Mutual Information (MMI) algorithms. Based on the recursive architecture and the relationship between the ME and MMI algorithms, an Extended ME(EME) algorithm is proposed by using probability density function (pdf) estimation of the outputs to deduce the corresponding iterative formulas in BSS. Based on the simulation results, it can be concluded that the proposed algorithm has better performances than the traditional ME algorithm in convolute mixture BSS problems. 相似文献
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一种自适应算法的语音信号盲分离 总被引:1,自引:0,他引:1
盲信号处理算法主要有批处理算法和自适应算法两类,本文导出了一种批处理和自适应相结合的快速独立分量分析(Fast Independent Component Analysis, Fast ICA)算法,将该算法应用于语音信号盲分离处理,通过综合实验,从分离前后的波形、频谱图和主要评价参数说明该算法具有良好的信号分离效果。与扩展联合对角化(The Joint Approximative Diagonalization ofEigenmatrix,JADE)算法和自然梯度(Natural Gradient,NG)算法比较, fast ICA算法具有更好的分离效果。 相似文献
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The paper proposes an improved high-speed parallel particle filter algorithm for the blind separation of PCMA-signals by utilizing particle filter’s characteristics of parallelism with the help of a cluster computer system built by using the Matlab distributed computing server and Matlab parallel computing toolbox. The simulation results show that the parallel algorithm can perform the PCMA-signal blind separation quickly and effectively. Further, it can greatly decrease the time of the separation, without reducing the performance of the algorithm, and improve the real-time application of system. 相似文献