Fractional Processing Based Adaptive Beamforming Algorithm

Fractional order algorithms have shown promising results in various signal processing applications due to their ability to improve performance without significantly increasing complexity.The goal of this work is to inves-tigate the use of fractional order algorithm in the field of adaptive beam-forming,with a focus on improving performance while keeping complexity lower.The effectiveness of the algorithm will be studied and evaluated in this context.In this paper,a fractional order least mean square(FLMS)algorithm is proposed for adaptive beamforming in wireless applications for effective utilization of resources.This algorithm aims to improve upon existing beam-forming algorithms,which are inefficient in performance,by offering faster convergence,better accuracy,and comparable computational complexity.The FLMS algorithm uses fractional order gradient in addition to the standard ordered gradient in weight adaptation.The derivation of the algorithm is provided and supported by mathematical convergence analysis.Performance is evaluated through simulations using mean square error(MSE)minimization as a metric and compared with the standard LMS algorithm for various parameters.The results,obtained through Matlab simulations,show that the FLMS algorithm outperforms the standard LMS in terms of convergence speed,beampattern accuracy and scatter plots.FLMS outperforms LMS in terms of convergence speed by 34%.From this,it can be concluded that FLMS is a better candidate for adaptive beamforming and other signal processing applications.

Adaptive broadband beamformer for nonuniform linear array based on second order cone programming

Adaptive broadband beamforraing is a key issue in array applications. The adaptive broadband beamformer with tapped delay line （TDL） structure for nonuniform linear array （NLA） is designed according to the rule of minimizing the beamformer＇s output power while keeping the distortionless response （DR） in the direction of desired signal and keeping the constant beamwidth （CB） with the prescribed sidelobe level over the whole operating band. This kind of beamforming problem can be solved with the interior-point method after being converted to the form of standard second order cone programming （SOCP）. The computer simulations are presented which illustrate the effectiveness of our beamformer.

DOA Estimation Algorithm Based on Adaptive Filtering in Spatial Domain

In this paper, a novel DOA estimation methodology based upon the technology of adaptive nulling antenna is proposed. Initially, the nulling antenna obtains the weight vector by LMS algorithm and power inversion criterion.Afterwards, reciprocal of the antenna pattern is defined as the spatial spectrum and the extracted peak values are corresponded to the estimated DOA. Through observation of the spectrum and data analysis of variable steps and SNRs, the simulation results demonstrate that the proposed method can estimate DOA above board. Furthermore, the estimation error of the proposed technique is directly proportional to step size and is inversely proportional to SNR. Unlike the existing MUSIC algorithm, the proposed algorithm has less computational complexity as it eliminates the need of estimating the number of signals and the eigenvalue decomposition of covariance matrix. Also it outperforms MUSIC algorithm, the recently proposed MUSIC-Like algorithm and classical methods by achieving better resolution with narrow width of peaks.

Multi-channel differencing adaptive noise cancellation with multi-kernel method

Although a various of existing techniques are able to improve the performance of detection of the weak interesting sig- nal, how to adaptively and efficiently attenuate the intricate noises especially in the case of no available reference noise signal is still the bottleneck to be overcome. According to the characteristics of sonar arrays, a multi-channel differencing method is presented to provide the prerequisite reference noise. However, the ingre- dient of obtained reference noise is too complicated to be used to effectively reduce the interference noise only using the clas- sical linear cancellation methods. Hence, a novel adaptive noise cancellation method based on the multi-kernel normalized least- mean-square algorithm consisting of weighted linear and Gaussian kernel functions is proposed, which allows to simultaneously con- sider the cancellation of linear and nonlinear components in the reference noise. The simulation results demonstrate that the out- put signal-to-noise ratio （SNR） of the novel multi-kernel adaptive filtering method outperforms the conventional linear normalized least-mean-square method and the mono-kernel normalized least- mean-square method using the realistic noise data measured in the lake experiment.

Adaptive Radio Frequency Interference Mitigation for HF Surface Wave Radar

The paper analyses the characteristics of radio frequency interference （RFI） in HF surface wave radar （HFSWR） which adopts the linear frequency modulated interrupted continuous wave （FMICW）. RFI will influence all the range cells including all the positive frequency and negative frequency, and the negative frequency range cells contain only the interference information. Based on the above characteristics, we introduce and analyze a new adaptive interference mitigation beamforming algorithm using the negative frequency range cells samples to estimate the interference covariance matrix. Experimental results confirm that this general and robust algorithm can achieve effective RFI suppression using the data recorded by the HFSWR, located near Zhoushan in Zhejiang China.

Robust adaptive beamforming for constant modulus signal of interest

It is required in the diagonally loaded robust adaptive beamforming the automatic determination of the loading level which is practically a challenging problem.A constant modulus restoral method is herein presented to choose the diagonal loading level adaptively for the extraction of a desired signal with constant modulus(a common feature of the phase modulation signals).By introducing the temporal smoothing technique,the proposed constant modulus restoral diagonally loaded robust adaptive beamformer provides increased capability compared with some existing robust adaptive beamformers in rejecting interferences and noise while protecting the signal-of-interest.Simulation results are included to illustrate the performance of the proposed beamformer.

Novel Adaptive Beamforming Algorithm Based on Wavelet Packet Transform

An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packet theory to adaptive beamforming, a wavelet packet transform-based adaptive beamforming algorithm (WP-ABF) is proposed . This WP-ABF algorithm uses wavelet packet transform as the preprocessing, and the wavelet packet transformed signal uses least mean square algorithm to implement the ~adaptive beamforming. White noise can be wiped off under wavelet packet transform according to the different characteristics of signal and white under the wavelet packet transform. Theoretical analysis and simulations demonstrate that the proposed WP-ABF algorithm converges faster than the conventional adaptive beamforming algorithm and the wavelet transform-based beamforming algorithm. Simulation results also reveal that the convergence of the algorithm relates closely to the wavelet base and series; that is, the algorithm convergence gets better with the increasing of series, and for the same series of wavelet base the convergence gets better with the increasing of regularity.

基于子阵波束设计的空时二维杂波抑制方法

机载雷达接收端采用子阵处理时面临栅瓣杂波导致的复杂空时耦合分布,使主瓣波束方向存在多个由栅瓣杂波导致的检测性能凹口,目标检测性能恶化严重。针对此问题,该文首先分析了子阵处理中栅瓣杂波空时谱分布特性,并在此基础上提出了基于接收子阵波束设计的空时二维杂波抑制方法。该方法采用重叠子阵构型方案,通过子阵方向图设计形成在子阵间栅瓣区域处的宽凹口,实现对子阵间栅瓣区域杂波的预滤波。进一步构建子阵级空时处理器,由于栅瓣杂波已经在子阵内完成预滤波,避免了栅瓣杂波在空时二维平面上的耦合扩散,从而提高了杂波抑制和动目标检测性能。仿真结果表明,所提方法显著改善了栅瓣杂波区的输出信杂噪比损失性能。

A framework of rank-reduced space-time adaptive processing for airborne radar and its applications

A new equivalent formulation of the joint domain space-time optimum processor for airborne phased array radar application is derived. Then a new framework of space-time adaptive processing (STAP) for airborne radar systems which includes most of suboptimum algorithms in the literature is proposed. The performance of two typical rank-reduced time-space joint-domain processors based on Doppler pre-filtering is analyzed in detail based on the proposed framework.

STAP method based on atomic norm minimization with array amplitude-phase error calibration

In this paper,a space-time adaptive processing(STAP)method is proposed for the airborne radar with the array amplitude-phase error considered,which is based on atomic norm minimization(ANM).In the conventional ANM-based STAP method,the influence of the array amplitude-phase error is not considered and restrained,which inevitably causes performance deterioration.To solve this problem,the array amplitude-phase error is firstly estimated.Then,by pre-estimating the array amplitude-phase error information,a modified ANM model is built,in which the array amplitude-phase error factor is separated from the clutter response and the clutter covariance matrix(CCM)to improve the estimation accuracy of the CCM.To prove that the atomic norm theory is applicable in the presence of the array amplitude-phase error,the clutter sparsity is analyzed in this paper.Meanwhile,simulation results demonstrate that the proposed method is superior to the state-of-the-art STAP method.Moreover,the measured data is used to verify the effectiveness of the proposed method.

IMPROVED DOPPLER WARPING METHOD FOR AIRBORNE RADAR WITH NON-SIDELOOKING ARRAY

Traditional range-dependency compensation space time adaptive processing(STAP)methods usually involve aligning the clutter spectrums in a certain point to reduce the clutter non-homogeneity.A novel compensation STAP method is proposed as an improved Doppler warping(DW)method for airborne radar with non-sidelooking radar.This method facilitates DW method to bring clutter spectrum of different range gates together in the mainlobe and subsequently compensation to accomplish space angle of different range gates alignment at multiple Doppler bins.Simulation results show that the proposed method can further reduce the clutter non-homogeneity of non-sidelooking array and significantly outperform traditional algorithms with only a little increase of the computation load.

Computer Control Techniques of Phased Array Radars

The computer control techniques applicable to electronically scanned multifunction radars are presented. The software and hardware architecture for the real time control and the data processing within a phased array radar are described. The software system comprising a number of tasks is written in C language and implemented. The results show that the algorithm for the multitask adaptive scheduling and the multitarget data processing is suitable for multifunction phased array radars.

Space discriminative function for microphone array robust speech recognition

Based on W-disjoint orthogonality of speech mixtures, a space d,scnmlnative tunetlon was proposer1 to enumerate and localize competing speakers in the surrounding environments. Then, a Wiener-like postfiherer was developed to adaptively suppress interferences. Experimental results with a hands-free speech recognizer under various SNR and competing speakers settings show that nearly 69 % error reduction can be obtained with a two-channel small aperture microphone array against the conventional single microphone baseline system. Comparisons were made against traditional delay-and-sum and Griffiths-Jim adaptive beamforming techniques to further assess the effectiveness of this method.

一种非均匀邻接子阵结构及其部分自适应处理性能分析

子阵级自适应处理可用较小的代价获得准最优的处理性能．对于幅度锥削的均匀线阵，本文提出用等噪声功率法来划分非均匀邻接子阵，计算机模拟结果表明该子阵结构的自适应方向图保形良好且没有明显栅瓣，其干扰抑制性能接近最优处理．

大气光通信中大气湍流影响抑制技术研究进展

大气湍流导致大气光通信链路的误码率上升。湍流影响抑制技术的研究成果有利于提升大气光通信的性能,提高链路的通信速率及距离。首先总结了大气湍流对光通信影响机理的最新研究成果,指出了不同大气湍流效应对光通信的影响形式,其中包括光强闪烁、光束漂移、到达角起伏、相位起伏、光束扩展等。综述了大气湍流影响抑制技术的研究动态和新进展,并根据抑制技术原理的不同,详细地论述了大孔径接收、分集、部分相干光传输、时域处理与阈值优化、自适应光学等技术。从抑制原理和效果出发,对各种大气湍流影响抑制技术进行了分析和讨论,最后简述了进一步开展工作的方向。

基于自适应双阈值的局部放电基本参数提取

局部放电基本参数自动化提取是高压设备局部放电在线PRPD分析的一项关键技术。针对现有方法因缺乏有效的参数选取方案导致适用性差的问题,提出了一种基于自适应双阈值的局部放电基本参数提取新方法。该方法利用放电幅值阈值和放电间隔阈值对PD信号的所有局部极值点进行双重过滤得到有效放电脉冲及其参数。为了减少整个处理过程的人工干预,提出采用最大类间方差法自适应选取上述双阈值。实验室中所测信号分析结果表明,所提方法能有效地提取PD信号的基本参数,对总数643例放电进行检测仅漏检13例、误检0例,且对80 MHz高采样率的放电信号的检测时间仍低于0.3 s,在准确性与计算效率上均优于现有方法。

遗传二进制多粒子群优化算法及其在子阵STAP中的应用

抑制杂波和干扰的子阵空时自适应处理的性能会受子阵方向图栅瓣的影响而严重下降,非均匀子阵划分和子阵权值设计可有效抑制天线方向图的栅瓣,消除STAP性能曲线上的栅凹口。由于子阵划分和子阵权值分别对应于整数和实数变量,使得该问题为一种特殊的混合优化问题。针对该特殊问题本文提出了一种新的遗传二进制多粒子群优化算法- GBMPSO。该算法不仅可处理二进制编码粒子,而且采取了多粒子群共同进化且在同一种群内部进行交叉和变异的机制,有效避免了算法早熟。针对四种典型测试函数的仿真实验表明,GBMPSO算法与二进制PSO算法和遗传算法相比在收敛速度和算法精度上均有明显的优势。最后,给出了该算法在子阵STAP中应用的实例。

一种子阵划分方法及子阵级STAP性能分析

对于幅度锥削的均匀线性阵列,本文首先提出了一种有效的基于遗传算法的子阵划分方法,在遗传算法中利用罚函数法避免子阵结构中出现阵元交叉项。然后对子阵级权值进行归一化,使得各子阵级噪声电平相等。最后通过计算机仿真分析了子阵级STAP处理器的性能。仿真结果表明,该子阵结构的天线方向图无明显栅瓣,其STAP杂波抑制性能接近于阵元级STAP处理性能。

不确定感知的自适应云计算服务组合

云计算服务组合是从众多分布在不同云计算平台上的远程服务中选择合适的组件服务来构建可伸缩的松耦合的增值应用.传统的服务组合方法通常将服务选择与服务组合分阶段进行,由于云计算环境的动态性和服务自身演化的随机性,不能保证选择阶段性能最优的服务在组合服务执行阶段依然是最优的.考虑到云计算环境服务组合的动态性和随机性,建立基于部分可观测Markov决策过程(partially observable Markov decision process,POMDP)的服务组合模型SC_POMDP(service composition based on POMDP),并设计用于模型求解的Q学习算法.SC_POMDP模型在组合服务运行中动态地进行服务质量(quality of service,QoS)最优的组件服务选择,且认为组合服务运行的环境状态是不确定的,同时SC_POMDP考虑了组件服务间的兼容性,可保证服务组合对实际情境的适应性.仿真实验表明,所提出的方法能成功地解决不同规模的服务组合问题,在出现不同比率的服务失效时,SC_POMDP仍然能动态地选择可用的最优组件服务,保证服务组合能成功地执行.与已有方法相比,SC_POMDP方法所选的服务有更优的响应时间和吞吐量,表明SC_POMDP可有效地提高服务组合的自适应性.

一种基于偏微分方程的车辆加速度信号自适应降噪方法

提出一种针对MEMS加速度计信号的基于偏微分方程的自适应降噪方法,该方法不仅能有效克服由于传感器本身原因及车载环境振动噪声带来的影响,获得准确的加速度信号,而且实现容易、实时性好。通过对车辆加速度信号进行建模并叠加真实加速度噪声作为仿真信号,将该方法与选用db6小波基、heursure自适应阈值、4层分解的最佳小波进行降噪性能对比,证明在车辆正常行驶的加速度幅值下,该方法不仅能够取得和小波近似的降噪性能,而且很大程度上减少了运算时间。最后通过对实际车载加速度信号的降噪处理和倾角测量中的应用,再次证明该方法在滤除噪声的同时能够较好体现细节信息,很适合应用在对实时性和准确性要求高的实际工程中。