非高斯alpha稳定分布环境中自适应滤波及研究进展

讨论了非高斯alpha稳定分布噪声环境中的自适应滤波及其近十几年来的研究进展。以alpha稳定分布的线性理论和参数的最大似然估计理论为基础,发展形成了线性滤波和非线性滤波两大类算法。相对于高斯环境下的滤波,新滤波算法在脉冲噪声中的韧性得到显著提高。最后分别给出了两类算法在谐波恢复中的应用实例。     

变遗忘因子相关函数自适应滤波算法

相关函数递推最小二乘(CRLS)算法在回波消除中双方对讲情况下是有效的,但其计算复杂度较高。把相关函数最小二乘准则中的遗忘因子视为时变的遗忘因子,应用最速下降法使当前时刻的方向矢量正交于前一时刻的方向矢量,从而获得时变的遗忘因子的表达式,得到一种新的相关函数自适应滤波算法。该算法的计算复杂度比相关函数递推最小二乘算法的要低。计算机数值仿真结果表明,新算法的收敛性能和相关函数递推最小二乘算法的收敛性能相当。     

干扰极化捷变下的空域自适应滤波

雷达空域自适应滤波在应对极化捷变干扰时性能恶化, 因此研究了干扰极化捷变情况下, 雷达空域自适应滤波的性能。首先, 建立了极化捷变干扰的雷达阵列接收信号模型。其次, 对阵列接收数据构成的协方差矩阵进行研究, 得出一个干扰源在极化捷变时, 等价于两个不同方向的干扰源, 需消耗的雷达空域自由度为2的结论。进一步, 提出干扰极化捷变下的空域自适应滤波算法。最后, 试验验证了理论研究的合理性。     

基于最大熵方法的鲁棒自适应滤波及其应用

针对过程噪声和量测噪声受到脉冲噪声影响而呈现非高斯分布,且噪声统计特性不精确从而导致估计精度下降的问题,提出一种基于最大熵方法的变分贝叶斯自适应卡尔曼滤波(maximum correntropy variational Bayes adaptive Kalman filter, MCVBAKF)算法,并将其应用于捷联惯导系统(strapdown inertial navigation system, SINS)/全球卫星定位系统(global positioning system, GPS)组合导航系统。首先,使用最大熵鲁棒滤波方法对由脉冲噪声产生的野值问题进行处理;然后,通过改进的变分贝叶斯自适应方法进行后验更新,估计噪声,收敛所估参数的估计值;最后,进行了仿真对比。结果表明, MCVBAKF在复杂环境下可以有效提升滤波精度和稳定性。     

Scheme of adaptive polarization filtering based on Kalman model

1.INTRODUCTIONIn modern high technology war,the electroniccounter measures(ECM)and precise guidance tech-nology are rapidly developed and becoming the re-search hotspot of militarysciencefor all the countries.The guidance missiles are the main weapons andhigher anti-jamming ability and guidance precision arerequired for guidance radar.For the active mono-pulse guidance radar,the angle information of thetarget is obtained by usingthe angle measured methodof amplitude sum/difference or pha…     

区间小波变换域的新拟牛顿LMS自适应消噪

将小波变换、自适应算法和新拟牛顿算法相结合,得出一种区间离散正交小波变换域新拟牛顿LMS消噪算法。该算法具有较好的环境适应性,有效克服了传统步长因子选取和输入信号自相关函数估计误差对算法收敛速度和稳态误差的影响。计算机仿真结果表明,在新拟牛顿条件下,该算法具有较快的收敛速度和较强的消噪能力,可以很好地应用于自适应消噪系统中。     

On UWB system performance under impulsive noise environment

In this paper, the performance of UWB (ultrawide bandwidth) radio systems under impulsive noise environment (INE) is investigated. At first, the Middleton's class a model is used as a model of impulsive noise (IN), we investigate the statistical characteristics of in-phase and quadrature components of IN, and it is proved that unlike Gaussian noise (GN), they are dependent especially to IN with small impulsive indices, Then, making use of this dependence between in-phase and quadrature components, an ovel UWB radio receiver designed for IN is proposed. The exact expression for the average BER (bit error rate) of this receiver, which is a function of SNR (signal to noise power ratio) and threshold value, is derived. Thirdly, we'll discuss the optimum threshold value. We'll also estimate the performance of UWB radio systems with the proposed receiver designed for IN and with the conventional receiver designed for GN in INE. Numerical results show that the performance achieved by the proposed UWB radio receiver is much etter than that of the conventional UWB radio receiver. Meanwhile, it is shown that both impulsive index and threshold value have much effect on the performance of UWB radio system s under the condition of INE     

Receiver design of UWB radio systems for an impulsive noise environment

1 .INTRODUCTIONUltrawidebandwidth (UWB )radiosystemshavedrawnalotofattentionduringthelastfew years[1,2 ] .Suchsystems ,basedontimehoppingspread spec trum (THSS)impulseradio (IR ) ,are plannedtoworkinco existencewithotherdigitalsystemsoverabandwidthranging…     

干扰条件下自适应滤波定位精度分析

在干扰条件下,单纯采用自适应滤波(adaptive Kalman filter, AKF) 或扩展卡尔曼滤波器(extensive Kalman filter, EKF) 在全球导航卫星系统/惯性测量单元(global navigation satellite systems/inertial measurement units, GNSS/IMU)组合导航的运用中都无法达到系统精度最优。为了指导组合导航系统的数据融合滤波器设计,获取AKF和EKF定位性能的经验数值是十分必要的。首先推导出EKF和一种AKF算法--新息序列自适应估计(innovation based adaptive estimation, IAE)的数学模型和计算公式。然后提出了一种实际数据结合仿真的验证方法。针对不同的干扰程度造成的精度降低的测量值,比较AKF算法跟普通EKF在GNSS/IMU组合导航数据融合中的定位精度性能。试验和仿真得到了在实验所采用的IMU精度条件下,自适应滤波在组合导航方面的定位性能的经验曲线以及IAE与EKF定位精度存在的临界点。     

基于后推技术的直接鲁棒自适应模糊控制

针对一类带摄动的严格反馈非线性系统,基于后推设计方法,利用第一类模糊系统的逼近能力,提出了一种新的直接自适应控制方案。该方案中引入连续鲁棒项对系统的摄动部分进行抑制,并在自适应律中利用了leakage项以防止参数漂移。通过理论分析,证明了闭环系统是半全局一致终结有界的,跟踪误差收敛到一个小的残差集内。仿真结果表明了该方法的有效性。     

FM interference suppression for PRC-CW radar based on adaptive STFT and time-varying filtering

The influence of frequency modulation (FM) interference on correlation detection performance of the pseudo random code continuous wave (PRC-CW) radar is analyzed.It is found that the correlation output deteriorates greatly when the FM interference power exceeds the anti-jamming limit of the radar.According to the fact that the PRC-CW radar echo is a wideband pseudo random signal occupying the whole TF plane,while the FM interference only concentrates in a small portion,a new method is proposed based on adaptive short-time Fourier transform (STFT) and time-varying filtering for FM interference suppression.This method filters the received signal by using a binary mask to excise only the portion of the TF plane corrupted by the interference.Two types of interference,linear FM (LFM) and sinusoidal FM (SFM),under different signal-to-jamming ratio (SJR) are studied.It is shown that the proposed method can effectively suppress the FM interference and improve the performance of target detection.     

Adaptive IIR filtering based on balanced-realization

Due to low parameter sensitivity for balanced realizations, balanced structure becomes a good candidate for an statespace adaptive infinite impluse response (IIR) filter. Here, using coefficients of the transfer function as the adaptive filtering parameters, a balanced adaptive IIR filtering algorithm is proposed for output-error minimization. The algorithm in the internally balanced realization guarantees that the adaptive IIR filter always minimizes the ratio of maximum-to-minimum eigenvalue of the Grammianmatrices at the each iteration. Simulation results are provided to corroborate the proposed algorithm.     

一种新的信噪比自适应Viterbi译码算法

Viterbi译码算法的复杂度会随着状态数的增加而增加,因此一般适用于约束长度较小的卷积码的译码。提出了一种新的信噪比自适应Viterbi译码改进算法,在每个接收时刻通过门限值选择幸存状态,从而进一步减小译码网格中的路径搜索范围,提高译码速度。仿真表明,本算法并不会降低译码性能,而在高信噪比、大状态数的应用条件下,与传统译码速度相比,可提高译码速度最高至15倍。     

LMS自适应滤波算法在FOG数据处理中的应用

针对光纤陀螺（fiber optic gyroscope, FOG）输出数据的随机噪声问题,提出将变步长最小均方（least mean square, LMS） 自适应滤波算法应用于FOG数据处理中。根据FOG数据特点,构造变步长LMS 自适应滤波器,对FOG输出数据进行实时预处理,自动地调节参数,达到降低FOG随机漂移及角度随机游走的目的。采用Allan方差对滤波前后的FOG数据进行分析,结果表明所提出的算法在FOG数据处理中效果明显,可以优化FOG的零偏稳定性0.019(°)/h及角度随机游走0.001 5(°)/h^1/2。     

基于扩频反馈滤波算法的多目标测控技术

针对航天测控技术发展中对多目标测控技术的需求,提出了采用特殊信息编码算法解决多目标测控中的问题。该算法采用与常用的扩频码分多址体制不同的编码方法和解算方法,可依靠现有的测控设备,应用扩频自适应反馈滤波算法,有效完成对多目标的测控任务,并可成功解决多用户冲突问题。给出了新型扩频自适应反馈滤波算法的编解码原理,通过分析计算验证了该算法的有效性。     

SAR图像斑点噪声滤除方法应用研究

SAR图像中相干斑点噪声的滤除方法很多,在不同情况下选择不同滤波方法的研究急待进行。分别利用常用空间域滤波方法和数种小波系数滤波算法对4幅不同的SAR图像进行斑点噪声的滤除,分析了各自在不同图像滤波中的优缺点,为在不同情况下使用不同的滤波算法提供了一种经验性分析结果。在大量实验的基础上,得到了小波滤波阈值系数比例值为1 5时的较好的滤波效果,利用小波变换细节子图间的近似比例关系,提高了运算的速度。     

航天器非线性鲁棒自适应姿态机动控制律

针对存在未知转动惯量和外部干扰力矩的敏捷航天器快速大角度姿态机动问题,结合非线性反步法和Lyapunovo稳定性分析方法设计控制力矩和转动惯量估计值的非线性鲁棒自适应控制律。在控制力矩控制律中,加入非线性阻尼项对外部干扰力矩进行补偿,证明了系统的全局一致最终有界稳定性。引入非线性动系数增加系统的动态性能,提高了姿态快速机动后的快速稳定能力。在Maltlab/Simulink环境下进行航天器姿态机动控制仿真研究,仿真结果验证了所设计控制器的有效性和可行性。     

自适应滤波在无源探测中对杂波抑制的应用

介绍了外照射源目标探测的作用和研究的必要性。重点分析了自适应LMS信号滤波处理方法和在直达波和多径干扰等杂波抑制中的应用。对自适应LMS滤波算法进行改进,即对归一化LMS(normalized LMS)算法进行推导和分析,提高了自适应滤波的收敛速度,对目标中的杂波起到更好的抑制作用。并在试验中对非归一化滤波、归一化滤波以及不同滤波步长μ进行了分析和比较。最后在试验结果中得到了30 dB的对消增益并获得了目标信号。     

New algorithm for robust H2/H∞ filtering with error variance assignment

We consider the robust H2/H∞ filtering problem for linear perturbed systems with steady-state error variance assignment. The generalized inverse technique of matrix is introduced, and a new algorithm is developed. After two Riccati equations are solved, the filter can be obtained directly, and the following three performance requirements are simultaneously satisfied: The filtering process is asymptotically stable; the steady-state variance of the estimation error of each state is not more than the individual prespecified upper bound; the transfer function from exogenous noise inputs to error state outputs meets the prespecified H∞ norm upper bound constraint. A numerical example is provided to demonstrate the flexibility of the proposed design approach.     

传递对准滤波中机翼变形噪声的在线补偿算法

针对机翼变形噪声对传递对准滤波的显著影响,通过特性分析将其处理为时变多阶有色观测噪声,提出了一种在线补偿算法。该算法以标准卡尔曼滤波方程为基础,推导了不扩维情况下补偿多阶有色观测噪声的滤波方程。算法依据滤波过程的序列量测数据,结合模型估计残差的F检验法,在线递推估计机翼变形噪声的自回归阶数、系数及白噪声,构建补偿方程的量测量、量测矩阵和量测噪声进行补偿滤波。通过将该算法应用于速度+姿态对准匹配方案,并与将机翼变形噪声等效为注入量测白噪声和扩充为系统状态的方法比较。仿真结果表明,该算法对时变机翼变形噪声影响下的新息适应性强,收敛稳定,估计精度高,适用于复杂空中环境下机载导弹快速精确传递对准。