电力载波通信中强背景噪声下弱信号的混沌振子检测方法

为了检测在强干扰背景下的载波信号,提出了将Duffing混沌振子应用到三态脉冲位置调制信号检测中.检测过程首先调节系统的策动力f,确定系统的策动力阈值f_d.当三态脉冲信号加入系统后,系统从混沌态转变为大尺度周期状态,则检测出信号中包含有周期信号;如果系统继续处于混沌状态,则说明输入信号为纯噪声.仿真结果表明当信噪比大于-23 dB时所提方法能有效地检测微弱载波信号.     

Duffing振子微弱信号检测方法的统计特性研究

利用混沌振子可以检测极其微弱的信号，并且具有很多优点，本文根据随机微分方程理论，通过对噪声经过Ｄｕｆｉｉｎｇ系统后统计特性的分析，确定了采用此方法检测的信噪改善比，从而为该方法的实际应用提供了指导，并且，本文针对周期系数线性微分方程的特点，提出了其输出统计特性的求法。     

基于Duffing振子检测PSK信号方法的研究

基于混沌微弱信号检测的原理,提出一种利用Duffing振子实现PSK信号解调的新方法.介绍了该方法的原理和具体实现过程.仿真结果证明了文中所提方法的可行性和有效性,并将该方法和传统的PSK信号解调方法进行了比较.     

湮没在色噪声背景下 微弱方波信号的混沌检测方法

 建立一个其动力学行为对微弱方波信号极其敏感的混沌系统,根据该系统相轨迹的变化实现了任意色噪声背景下的微弱方波信号的测量.文中论证了方波信号的检测方法;分析了噪声对混沌检测的影响,仿真实验表明该混沌检测系统对方波信号非常敏感,对任何零均值色噪声均具有极强的抑制能力.     

基于混沌振子的电话网信号检测

首先介绍了混沌检测原理和基于相关的双频信号检测方法,然后给出了检测信号模型,介绍了结合自相关和滤波预处理利用混沌振子对双频信号进行检测的新方法,分析了其检测原理。最后进行计算机仿真实验,仿真实验说明了该方法对微弱信号非常敏感,检测性能优于单纯混沌系统检测性能,同时进一步验证了所提方法具有强抗干扰等性能,有一定的实用价值。     

一种基于混沌振子的DSSS信号盲检测方法

直接序列扩频通信是一种具有强保密性和抗干扰性的先进通信体制,对DSSS信号的检测具有重要作用。将非线性科学中的混沌理论应用于DSSS信号的盲检测,结合DSSS信号特征研究了一种利用混沌振子进行检测的方法。首先分析了洛伦兹混沌振子检测周期信号的原理和DSSS信号模型,然后构造出了一个基于混沌振子阵列的盲检测系统,可实现对低信噪比条件下对DSSS信号的盲检测。最后,通过计算机仿真结果表明了该方法的有效性,且性能优于过去的一些算法。     

基于Duffing振子的微弱信号混沌检测

分析了Duffing振子的混沌特性,给出了确定系统混沌阈值的Melnikov方法.在阐述了基于相平面变化进行微弱信号检测原理后,在混沌检测中噪声对系统状态的影响也进行了研究.仿真结果表明,Duffing振子对与参考信号频率差较小的周期信号敏感,对白噪声和频差较大的周期干扰信号具有免疫力,该振子应用于实际微弱信号的检测具有可行性.     

强混沌噪声背景下弱信号检测

提出了一种强混沌噪声中检测微弱正弦信号的新方法。该方法主要利用了数据平滑处理和自适应处理,故在硬件设计上容易实现。计算机仿真实验结果表明：能够比较精确地检测到强混沌噪声中的微弱信号,检测到微弱信号的信噪比可达到-80dB。     

二进制调制信号Duffing振子检测方法及其抗噪声机理分析

根据二进制调制信号的特点及Duffing振子微弱信号检测技术,研究了二进制调制信号的Duffing振子检测原理,给出了2ASK、2FSK及BPSK调制信号的Duffing振子检测的方法和流程.从Dufiing振子与匹配滤波器处理待测信号的不同原理出发,研究了Duffing振子输入前端信号信噪比提升的现象.指出二元通信信...     

基于Duffing混沌振子的微弱信号检测研究

传统的微弱信号检测方法在检测信噪比很低的信号时效果很差,而Duffing振子混沌系统由于具备对初值敏感、对噪声具有较好的抵抗力等优点,因此在检测微弱信号能够表现出良好的检测效果。分析了Duffing方程的基本形式和动力学演化过程,阐述了基于相平面变化进行微弱信号检测的工作原理。提出了一种准确确定相变阈值的方法,讨论了高斯白噪声对阈值的影响。按照提出的检测步骤,应用MATLAB软件进行仿真,仿真结果表明可以检测出的微弱信号的信噪比能达到-130 dB。     

THE CHAOTIC DETECTION OF PERIODIC SHORT—IMPULSE SIGNALS UNDER STRONG NOISE BACKGROUND

The periodic short-impulse signals under strong noise background are successfully detected with a special chaotic system invented by the authors.Simulation experiments show that the chaotic system is very sensitive to periodic shor-impulse signals submerged by strong noise background,and it can effectively restrain any zero-mean nose.The system has a stable working-detection limit of -83dB.     

一种强噪声背景下微弱信号检测方法研究

针对常规单混沌振子微弱信号检测方法存在检测过程不稳定的现象,将混沌吸引子与双振子差分检测技术相结合,提出一种通过调整系统稳定混沌态来检测微弱信号的改进方法,同时利用双差分振子来判别系统混沌态向周期状态转变的临界值。通过仿真分析,该方法可有效防止误判且实时性较好,有利于在强噪声背景下的微弱信号检测,为工程实际应用提供了一种可借鉴的方法。     

基于稀疏分解和混沌理论的微弱信号检测

针对数字锁定放大器中稀疏分解算法检测精度受限的缺点,结合非线性方法进行补偿,采用混沌检测联合稀疏分解的算法设计了数字锁定放大器。数字锁定放大器借助稀疏分解算法估计信号参数,根据估计得到的参数设计对应混沌系统;利用混沌系统检测信号的过程中产生间歇性混沌状态,并通过测量间歇性混沌状态的周期,精确检测信号。最终,在信号的信噪比低至-20 dB时可以成功检测信号,频率精度达到0.05 Hz,提供了一种非线性微弱信号检测方法。     

强混响背景下LFM信号回波检测

混响是主动声纳检测的主要背景干扰,由于它是一种非平稳的有色噪声,使得工作在白噪声条件下的检测器性能受到极大限制.在混响背景下实现目标回波检测,常采用自回归(AR)模型对宽带回波预白化处理,但在强混响背景条件下,白化后直接进行匹配滤波检测的结果不甚理想.针对此问题,在AR模型预白化基础上,提出一种改进方法,对白化后信号先进行二分奇异值分解(SVD)处理,有效去除大部分混响干扰,然后再作匹配检测.仿真实验分析表明,相比于仅白化后的匹配滤波检测,该方法可提高信混比约3 dB,匹配检测效果得到了明显改善.     

强噪声背景下的信号检测方法研究

提出了一种利用高阶统计量对强噪声背景下的弱信号进行检测的方法。这种检测方法对加性噪声中的确定性信号以及非高斯信号均有效 ,且可以弥补似然比检测的不足。     

Nonlinear algorithms for measuring the noise signal power against the background of interferences

Algorithms for measuring the power of mixture components of the noise signal and interferences by using functional transformations of the input mixture in the section of postdetection processing have been considered. The cases of narrowband and pulse interferences were investigated. The performance analysis of the algorithms was performed at different values of interference-to-signal ratio. The results of numerical experiments made it possible to find out the performance peculiarities of algorithms under different conditions.     

Multipath effects and adaptive transmission in presence of indoor power line background noise

The paper studies the background noise characteristics of a typical indoor power line (PL) in India. The noise decreases rapidly with frequency and can be considered as white beyond 5 MHz. The time variation of the background noise at every frequency in the non‐white region is modeled and compared in different environments which include laboratory and factory setups. In all cases, the background noise can be modeled by density functions related to multipath fading i.e. Nakagami‐m, Rayleigh and Rician. Fading is worse than the Rayleigh fading when the PL network has more connected loads and impedance discontinuities. Single frequency noise shows Rician fading when the background noise is narrowband Gaussian. The results are compared with those obtained in other countries in an attempt to check the validity of the model worldwide. A PL channel noise simulator is developed using the density functions to simulate the background noise. A technique is proposed that adapts the carrier frequency according to the channel property at a particular instant. The performance of such a system is tested in a simulated environment and shows that the method enables transmission of signals at very low transmission power compared with that in the AWGN channel. Copyright © 2009 John Wiley & Sons, Ltd.     

Weak harmonic signal detection method in chaotic interference based on extended Kalman filter

The traditional methods of weak harmonic signal detection under strong chaotic interference often suffer from high computational complexity and poor performance. In this paper, an Extended Kalman Filter (EKF) based detection method is proposed for the detection of weak harmonic signal. The EKF method avoids matrix inversion by iterating measurement equation and state equation, which simultaneously improves the robustness and reduces the complexity. Compared with the existing detection methods, the proposed method has the following advantages: 1) it has better performance than the neural network method; 2) it has similar performance with the optimal filtering method, but with lower computational complexity; 3) it is more robust compared with the optimal filtering method.