共查询到18条相似文献,搜索用时 248 毫秒
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突发信号盲检测在非合作通信中至关重要。待检测信号特征量的构造与突发信号段起止点的精确捕获是突发信号盲检测技术的关键。文中提出了一种基于循环谱的突发信号盲检测算法,算法首先以循环谱循环频率截面的相对方差作为待检测信号的特征量,该特征量具有优良的抑制突发强噪声干扰性能;然后利用特征量的方差进行信号存在性判决;最后采用基于特征量峰值的突发信号段起止点搜索算法,避免了设置检测门限带来的信噪比估计、噪声功率估计等问题,同时可在一定的检测正确率条件下保证起止点的捕获精度。仿真结果表明,该算法能有效抑制突发强噪声干扰,信号存在性判决准确率高,而且在误差控制要求较严格条件下的检测精度优于双窗能量法。 相似文献
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基于循环谱能量的自适应频谱检测算法 总被引:1,自引:0,他引:1
根据信号循环平稳谱的特征,研究在低信噪比环境下的频谱检测问题,提出一种基于循环谱能量的自适应判决门限频谱检测算法。该算法融合能量检测与循环平稳特征检测的机理,以信号的循环谱能量为检测统计量,加权合并虚警率与检测率,准确估计循环谱特征值,构建了具有噪声自适应能力的频谱检测判决门限。仿真结果表明,该算法可以在低信噪比环境下有效地完成频谱检测,克服了噪声波动对频谱检测性能的影响,对不同调制主信号的感知具有稳健性。与最大—最小特征值算法和盲检测算法相比,该算法分别改善了信噪比4dB和8dB。 相似文献
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基于循环前缀频域自相关的OFDM信号频谱感知 总被引:1,自引:0,他引:1
针对无线通信频谱资源有限并且利用率非常低的问题,研究了认知无线电系统中基于信号典型特征的频谱感知策略,并进行动态频谱检测.提出了一种基于循环前缀频域自相关的频谱感知算法,利用正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)信号的循环前缀具有循环平稳特性,在信号频域进行自相关运算,设定判决门限,完成对信号频谱的检测,同时具备较好的抑制平稳噪声和干扰的能力.在低信噪比或者噪声不确定度大的应用场景下,能够获得比能量检测方法更优、更稳定的频谱感知效果,增强了噪声鲁棒性.在算法中采用双门限检测,进一步减弱了噪声不确定度对检测性能的影响,提高了频谱感知性能. 相似文献
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针对超宽带循环平稳检测存在的门限难以设定、低信噪比下检测延迟较大的问题,提出了基于累积和的改进超宽带循环平稳检测算法。首先将信号整个三维循环谱归一化为二维灰度图,与噪声对应的灰度图比较差异,再将两类图像放入卷积神经网络(Convolutional Neural Network,CNN)自行训练提取特征,解决门限难以确定的问题。若分析三维循环谱的时间块长过短,将导致信号灰度图特征在有无噪声情况下区别不大;若块长过长会导致检测延迟较大。为此,采用累积和算法提取网络全连接层输出的信号概率作为累积和的观测统计量,自适应检测所需采样时间长度。将所提算法与传统循环平稳检测以及结合了CNN的循环平稳检测进行对比,仿真表明所提算法在低信噪比下性能最优。 相似文献
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基于循环谱对称性的新型频谱判决算法 总被引:1,自引:1,他引:0
采用循环平稳信号特性检测法能够更好地分辨出不同的调制信号,其对噪声具有很好的抑制,但在循环频谱工程上使用存在数据截断效应,它会降低频谱感知的检测概率,结合频谱已有的频谱搜索策略,提出了一种新的频谱判决算法,利用相对偏差、双门限和权重来对抗传统算法上方差的差值抖动问题。在使用FPGA搭建的硬件测试系统下,证明与传统算法相比,提出的算法大大提高了单节点的检测概率。 相似文献
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Xiao-Wei Zhang Dong-Dong Yang Wen-Zhun Huang Jian-Xin Guo Yan Hou 《International Journal of Electronics》2018,105(8):1388-1398
The wideband radar transmitting the linear frequency modulation signal often processes its echoes by the stretched processing. This paper deals with the range-spread target detection in white complex Gaussian noise. Here, we propose a new detection method for the range-spread target based on sparse representation, which selects the time-frequency feature to realise the target detection. It can be simply described as follows: first, the sketched signal is reconstructed from its noisy measurements by basis pursuit de-noising (BPDN); scatterers on the target are determined by its reconstruction and used to calculate the Wigner distribution; for the target embedded in noise, the time-frequency feature in its power-density spectrum is compared with the decision threshold. Meanwhile, the median absolute deviation (MAD) is adopted to estimate the noise variance. The mainly novelties can be concluded as follows: the Fourier matrix is selected to sparsely represent the sketched signal; the sparsity is used to improve the SNR of the received echoes; the Wigner transform is utilised to acquire the time-frequency feature of the range-spread target. Both the optimisation theory and time-frequency representation are introduced to solve the target detection problem. Experimental results on the raw data show that the proposed detector outperforms the conventional methods. 相似文献
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Shibing Zhang Xiaodai Dong Zhihua Bao Haoye Zhang 《Wireless Personal Communications》2013,68(3):789-810
Energy detection is a simple spectrum sensing technique that compares the energy in the received signal with a threshold to determine whether a primary user signal is present or not. Setting the threshold is very important to the performance of the spectrum sensing. This paper proposes an adaptive spectrum sensing algorithm where an optimal decision threshold of energy detection is derived based on minimizing the weighted sum of probabilities of detection and false alarm. Since the optimal decision threshold is dependent on the noise power and signal power, a simple, practical frequency domain approach is devised to estimate both. The algorithm can be used for the detection of various kinds of signals without any prior knowledge of the signal, channel or noise power, and is able to adapt to noise fluctuation. Simulations for detecting narrow-band and wideband signals (phase shift keying signal, frequency shift keying signal, orthogonal frequency division multiplexing signal) and ultra-wideband (UWB) signals (direct sequence spread spectrum signals) in an IEEE 802.15.3a UWB band are presented. The results show that the proposed algorithm has excellent robustness to noise uncertainty and outperforms the existing spectrum sensing algorithms in the literature. 相似文献
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为了提高α稳定分布噪声下非线性信道均衡器的性能,本文利用核方法处理非线性问题,结合最小平均p范数算法的核心思想,构造了α稳定分布噪声下基于核方法的非线性均衡器,提出并推导了α稳定分布噪声下核最小平均p范数均衡算法。首先,通过核函数将接收信号映射到高维特征空间;然后,在高维特征空间中利用LMP算法对信号进行均衡;最后,将均衡器的输出信号表示为内积形式并利用核函数将其转化到输入空间进行计算。理论分析和仿真实验结果表明,与核最小均方算法和最小平均p范数算法相比,新算法在保证收敛速度的前提下降低了稳态误差,能够更好地对α稳定分布噪声下的非线性信道失真进行补偿。 相似文献
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Jean-Gabriel Gander 《Signal processing》1979,1(1):65-81
A pattern recognition approach is proposed for tone detection. Three basic tone features are extracted from the signal in the form of power, mean frequency, and spectral concentration. These three features are calculated for each signal sample taken during the decision interval and are represented by points in a three dimensional space.The actual tone detection function is then performed by partitioning the feature space in two decision volumes corresponding to the two alternatives (tone present and absent respectively) and by identifying the presence of associated clusters. A reject option is available when the decision volumes are not complementary, and allows the system to be insensitive to very noisy samples (e.g. impulsive noise).A non-linear classification method is presented which provides adaptive and robust detection in presence of non gaussian noise. Moreover global performance may be optimized on-line for unknown or time varying environments.Hardware and Software simulation results are presented and show good performance in presence of impulsive and interference noise. 相似文献
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本文提出了一种利用光纤光栅(Fiber Bragg Grating, FBG)检测脉搏波的信号处理及特征提取算法。将光纤光栅采集脉搏波与光电容积(Photoplethysmography, PPG)脉搏波进行对比,分析出光纤光栅脉搏波的特点。提出了小波阈值消噪与改进的数学形态学滤波相结合的光纤光栅脉搏波消噪算法,并根据脉搏周期对形态学结构元素长度进行自适应选择,从而改善了去除基线漂移的效果。研究了脉搏特征提取方法,提高了脉搏波峰值点和起点检测的准确性。实验结果表明,经消噪处理后,输出脉搏波的信噪比是输入脉搏波信噪比的2倍,脉搏波峰值点和起点提取准确率分别达到了97.2%和97.6%。该算法结构简单,易于实现,对光纤光栅脉搏波检测智能服装的研发和脉搏特征的有效提取具有重要的意义。 相似文献
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偏振成像目标检测对于人造目标检测有着重要意义。像元耦合是以四个方向的偏振强度数据作为一个超像元的偏振成像方法。对超像元进行偏振参量解析,会使图像的分辨率变为原始图像的四分之一,不利于小目标的检测。像元耦合图像的偏振参量解析会产生噪声,对小目标的检测造成干扰。本文提出了一个以YOLOv5s为网络基础,添加偏振信息解析模块(Covcat)的目标检测算法。该算法实现了端到端进行像元耦合偏振成像的目标检测,用网络实现偏振解析,利用多卷积信息融合提高特征提取能力,提高目标的平均检测精度(mAP)。使用对空无人机数据集对算法进行验证,实验表明,相比于使用偏振参量解析出的强度图、偏振度图和偏振角图,该算法的平均检测精度分别提升了4个百分点、5个百分点和12个百分点。 相似文献
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在心脏病诊断过程中,心电信号的检测是重要的环节,然而心电信号的噪声很强,为了能够较好地滤除信号中的噪声,对信号的特点进行准确标定,利用基于小波变换的阈值去噪算法和基于小波的模极大值-极小值的算法进行心电信号的处理.采用MIT/BIH中的数据进行仿真调试验证,实验结果表明,被引入的几种噪声能被很好地去除,而且心电信号能较完整地保留下来,特征点能被准确地检测到,从而提高了诊断心脏等疾病的诊断效率. 相似文献
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针对复杂环境下跳频信号的检测问题,提出一种基于能量特征提取的检测算法.该算法可以准确判断信道内跳频信号的存在性.首先将接收数据投影到能量域内进行白化,抑制接收信号中存在的色噪声;然后通过能量分布特征提取信道内存在的时域连续信号,去除接收信号中存在的短时突发信号;最后利用信道化处理将接收信号分解到各个子信道,通过短时能量对消的方法来检测跳频信号的存在性.对该算法的统计特性,虚警概率和检测概率进行理论推导,并对检测流程进行了实验仿真,验证了算法有效性. 相似文献