共查询到19条相似文献,搜索用时 156 毫秒
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压缩感知技术可以用来实现对非合作宽带信号的欠采样快速处理。宽带脉冲压缩雷达能够有效解决雷达探测距离和距离分辨力的矛盾,在探测领域得到了广泛应用,为实现对非合作宽带脉冲压缩雷达信号的快速欠采样接收处理,本文首先开展了信号稀疏分解与重构算法研究,通过对贪婪算法、凸松弛类算法、组合类算法三大算法进行对比分析,选用了运行速度快且重构精度高的正交匹配追踪(OMP)算法针对非合作宽带脉冲压缩雷达信号进行压缩感知仿真分析。仿真结果表明:在一定信噪比条件下,OMP算法完全能够实现对非合作宽带脉冲压缩雷达信号的欠采样和信号重构,从而实现了对非合作宽带雷达信号的欠采样处理,为处理非合作超宽带雷达信号提供了很好的理论指导。 相似文献
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为改善采样自相关矩阵求逆(SMI)算法中期望信号存在于接收信号所引起的性能下降,提出一种修正干扰噪声自相关矩阵重构(CMR)算法。该算法首先选取采样自相关矩阵特征分解的最小特征值对应的特征向量构造空间分布系数,再对其在非期望信号波达方向上进行累加实现矩阵的重构。当存在相干信号时,可采取先利用特征向量元素对协方差矩阵进行托普利兹化处理实现解相干,再进行矩阵重构的托普利兹矩阵重构(TCMR)算法。计算机仿真与实验结果证明适用于非相干信号条件下的CMR算法与适用于相干信号条件下的TCMR算法具有更好的输出性能。 相似文献
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《信息技术》2015,(2):85-88
压缩传感理论是一种充分利用信号稀疏性或者可压缩性的全新的信号采样理论。该理论表明,通过采集少量的信号值就可实现信号的精确重构。文中在研究和总结已有经典重构算法的基础上,提出了结合图像分块思想和正则化过程的分块正则化正交匹配追踪算法(Block Regularized Orthogonal Matching Pursuit,B_ROMP)用于压缩传感信号的重构。该算法以块结构获取图像,利用正则化过程实现支撑集的二次筛选,最终实现图像信号的精确重构。实验结果表明,在相同测试条件下,该算法的重建效果无论从主观视觉上还是客观数据上都有不同程度的提高。 相似文献
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基于压缩感知理论我们可以直接处理少量的压缩采样数据从而完成感兴趣目标信号的检测任务。目前经典的压缩感知信号检测算法中,作为判决依据的特征值仅利用稀疏系数的幅值信息,而且这种算法的阈值选择通常需要消耗大量的时间。针对这个问题,提出一种基于稀疏系数特征信息的检测算法,算法充分利用稀疏系数的幅值信息和位置信息,根据部分重构得到的稀疏系数特征信息相关性完成目标信号的检测。实验结果表明,与原算法相比,该算法在保证检测性能的同时大大缩减了检测时间。 相似文献
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传统的奈奎斯特采样定理规定采样率必须是频率带宽两倍,浪费大量采样资源。如果信号可以稀疏表示,那么可以采用压缩传感技术重构原始信号,压缩传感能在采样的同时对数据进行适当压缩,节省系统资源。现存的压缩传感重构算法对图像边缘和纹理的重构效果都不太理想,提出一种基于全变差的图像重构算法,该算法能稳定有效地重构图像的边缘和纹理。 相似文献
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基于压缩感知观测序列倒谱距离的语音端点检测算法 总被引:2,自引:0,他引:2
本文基于语音信号在离散余弦基上的近似稀疏性,采用稀疏随机观测矩阵和线性规划重构算法对语音信号进行压缩感知与重构。研究了语音信号的压缩感知观测序列特性,根据语音帧和非语音帧压缩感知观测序列频谱幅度分布分散且差异较大的特性,提出基于压缩感知观测序列倒谱距离的语音端点检测算法,并对4dB-20dB下的带噪语音进行端点检测仿真实验。仿真结果显示,基于压缩感知观测序列倒谱距离的语音端点检测算法与奈奎斯特采样下语音的倒谱距离端点检测算法一样具有良好的抗噪性能,但由于采用压缩采样,减少了端点检测算法的运算数据量。 相似文献
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提出一种基于压缩感知(CS)技术在机会雷达系统中进行恒虚警率(CFAR)目标检测的算法,根据目标回波在距离单元上的稀疏性,采用压缩感知技术对目标回波进行压缩采样;设计了一种新的建立在压缩域上的CA-CFAR检测器,它能在不恢复原始信号的条件下,快速完成目标回波的检测;进行了检测门限理论分析,设计出一种适用于压缩域检测的门限选定方法;给出系统检测结果与接收机的性能曲线。仿真结果表明,本算法可以实现低信噪比下雷达信号的直接检测,无需信号重构,节省了运算量。 相似文献
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传统的信号检测算法基于奈奎斯特采样定理来实现,这对于带宽极宽的超宽带(ultra-wideband,UWB)信号而言由于要求采样速率过高而很难用硬件去实现。为此,本文研究了基于压缩感知(compressive sensing,CS)的脉冲超宽带(impulse radio UWB, IR-UWB)信号检测问题,利用IR鄄UWB 信号在时域上的稀疏特性,设计了一种基于压缩感知的IR鄄UWB 信号检测框架,在此基础上提出了一种自适应加权正交匹配追踪检测算法。仿真结果表明,新算法不仅能够通过远少于奈奎斯特定理所要求的采样速率检测出IR-UWB 信号,而且与基于匹配追踪的压缩感知检测算法相比,新算法在低信噪比的情况下对IR-UWB 信号的检测效果更佳。 相似文献
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Yijiu Zhao Xiaoyan Zhuang Houjun Wang Zhijian Dai 《Circuits, Systems, and Signal Processing》2012,31(4):1475-1486
The emerging compressive sampling (CS) theory makes processing ultra-wide-band (UWB) signal at a low sampling rate possible if the underlying signal has a sparse representation in a certain basis. The feasibility of model based compressive sampling for ultra-wide-band (UWB) signal is investigated. In this paper, a multichannel compressive sampling architecture is developed to capture UWB signal at a rate much lower than Nyquist rate. The proposed framework considers sub-Nyquist sampling stream of delayed and weighted versions of a known signal with finite support in time domain. A basis function is constructed to realize sparse signal representation. To reduce the hardware cost, a segmented architecture is suggested. In addition, a joint signal recovery algorithm is presented. Experimental results indicate that, with this system, a UWB signal sampled at about 4% of Nyquist rate still can be recovered with overwhelming probability. 相似文献
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To realize high‐speed communication, broadband transmission has become an indispensable technique in the next‐generation wireless communication systems. Broadband channel is often characterized by the sparse multipath channel model, and significant taps are widely separated in time, and thereby, a large delay spread exists. Accurate channel state information is required for coherent detection. Traditionally, accurate channel estimation can be achieved by sampling the received signal with large delay spread by analog‐to‐digital converter (ADC) at Nyquist rate and then estimate all of channel taps. However, as the transmission bandwidth increases, the demands of the Nyquist sampling rate already exceed the capabilities of current ADC. In addition, the high‐speed ADC is very expensive for ordinary wireless communication. In this paper, we present a novel receiver, which utilizes a sub‐Nyquist ADC that samples at much lower rate than the Nyquist one. On the basis of the sampling scheme, we propose a compressive channel estimation method using Dantzig selector algorithm. By comparing with the traditional least square channel estimation, our proposed method not only achieves robust channel estimation but also reduces the cost because low‐speed ADC is much cheaper than high‐speed one. Computer simulations confirm the effectiveness of our proposed method. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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为了在非协作情况下,对跳频信号的频率跳变时刻进行精确快速估计,提出一种基于压缩采样值的跳频信号跳变时刻快速估计算法。该算法首先通过压缩感知技术以远低于奈奎斯特采样定理要求的速率对跳频信号进行整周期滑动采样,然后根据不同时刻相邻两跳信号窗函数的特点,重构信号在傅里叶正交基上的2个权值最大的稀疏系数,并由此对前后两跳持续时间进行判断,从而对跳频信号的跳变时刻进行参数估计。仿真结果显示,该算法能有效地估计跳频信号的跳频转换时刻,且实时性优于现有时频估计类算法。 相似文献
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High‐resolution compressive channel estimation for broadband wireless communication systems 下载免费PDF全文
Guan Gui Wei Peng Fumiyuki Adachi 《International Journal of Communication Systems》2014,27(10):2396-2407
Broadband channel is often characterized by a sparse multipath channel where dominant multipath taps are widely separated in time, thereby resulting in a large delay spread. Accurate channel estimation can be done by sampling received signal with analog‐to‐digital converter (ADC) at Nyquist rate and then estimating all channel taps with high resolution. However, these Nyquist sampling‐based methods have two main disadvantages: (i) demand of the high‐speed ADC, which already exceeds the capability of current ADC, and (ii) low spectral efficiency. To solve these challenges, compressive channel estimation methods have been proposed. Unfortunately, those channel estimators are vulnerable to low resolution in low‐speed ADC sampling systems. In this paper, we propose a high‐resolution compressive channel estimation method, which is based on sampling by using multiple low‐speed ADCs. Unlike the traditional methods on compressive channel estimation, our proposed method can approximately achieve the performance of lower bound. At the same time, the proposed method can reduce communication cost and improve spectral efficiency. Numerical simulations confirm our proposed method by using low‐speed ADC sampling. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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由于在同步Nyquist折叠接收机结构中使用了多分量本振及对应的数字信号处理算法,单个双通道模数转换器所接收的信号频率范围可超过其Nyquist采样带宽。针对同步Nyquist折叠接收机结构,提出了基于Wigner-Hough变换的参数估计算法。对算法的理论分析表明,对不同本振周期信号的Wigner-Hough变换进行积累,能有效提高Nyquist区域检测性能。最后,仿真结果证实了提出的算法在输入信噪比优于-15 dB后,能获得准确的频率估计结果。 相似文献
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压缩感知理论指出,稀疏信号可以通过以低于奈奎斯特采样的测量数据重建出原始信号。针对高分辨率SAR成像在奈奎斯特理论下所面临的高速A/D采样、大数据量存储、传输等问题挑战。本文提出了一种基于压缩感知理论的多发多收高分辨率SAR二维成像算法。该算法减轻了高分辨率SAR成像的压力,采用压缩感知处理降低了A/D采样速率、数据量... 相似文献