Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics

In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial filtering.If the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation effect.To cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range dimension.The principle is presented,and the validity is proven by simulation results.

Method of combining space-time block coding with adaptive beamforming

A method of space-time block coding （STBC） system based on adaptive beamforming of cyclostationarity signal algorithm is proposed.The method uses cyclostationarity of signals to achieve adaptive beamforming,then constructs a pair of low correlated transmit beams based on beamform estimation of multiple component signals of uplink.Using these two selected transmit beams,signals encoded by STBC are transmitted to achieve diversity gain and beamforming gain at the same time,and increase the signal to noise ratio （SNR） of downlink.With simple computation and fast convergence performance,the proposed scheme is applicable for time division multiple access （TDMA） wireless communication operated in a complex interference environment.Simulation results show that the proposed scheme has better performance than conventional STBC,and can obtain a gain of about 5 dB when the bit error ratio （BER） is 10-4.

Adaptive beamforming and phase bias compensation for GNSS receiver

Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by the antenna array. However,the adaptive beamforming will change the array pattern in realtime, which has the potential to introduce phase center biases into the antenna array. For precise applications, these phase biases must be mitigated or compensated because they will bring errors in code phase and carrier phase measurements. A novel adaptive beamforming algorithm is proposed firstly, then the phase bias induced by the proposed algorithm is estimated, and finally a compensation strategy is addressed. Simulations demonstrate that the proposed beamforming algorithm suppresses effectively the strong interference and improves significantly the capturing performance of GNSS signals. Simultaneously, the bias compensation method avoids the loss of the carrier phase lock and reduces the phase measurement errors for GNSS receivers.

Fast and accurate covariance matrix reconstruction for adaptive beamforming using Gauss-Legendre quadrature

Most of the reconstruction-based robust adaptive beamforming(RAB)algorithms require the covariance matrix reconstruction(CMR)by high-complexity integral computation.A Gauss-Legendre quadrature(GLQ)method with the highest algebraic precision in the interpolation-type quadrature is proposed to reduce the complexity.The interference angular sector in RAB is regarded as the GLQ integral range,and the zeros of the threeorder Legendre orthogonal polynomial is selected as the GLQ nodes.Consequently,the CMR can be efficiently obtained by simple summation with respect to the three GLQ nodes without integral.The new method has significantly reduced the complexity as compared to most state-of-the-art reconstruction-based RAB techniques,and it is able to provide the similar performance close to the optimal.These advantages are verified by numerical simulations.

Semi-blind Adaptive Beamforming for High-throughput Quadrature Amplitude Modulation Systems

A semi-blind adaptive beamforming scheme is proposed for wireless systems that employ high-throughput quadrature amplitude modulation signalling. A minimum number of training symbols, equal to the number of receiver antenna arrayts elements, are first utilised to provide a rough initial least squares estimate of the beamformer＇s weight vector. A concurrent constant modulus algorithm and soft decision-directed scheme is then applied to adapt the beamformer. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study.

一种基于MVDR的改进型麦克风阵列语音增强算法

传统的最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)波束形成算法不能很好地跟踪信号统计特征的变化,适应时变环境的能力较差.本文对其进行改进,提出一种实时估计环境噪声及干扰的相关矩阵的方法,使用时变遗忘因子更新相关矩阵,遗忘因子根据目标语音的存在概率变化,最后引入对角加载技术更新滤波器权向量,以保证波束形成的质量.实验结果显示,相比传统的MVDR算法,改进后的MVDR波束形成算法具有更好的降噪效果,能获得更高的分段信噪比和PESQ得分.

Minimum variance adaptive beamforming combined with coherence factor weighting applied to ultrafast active cavitation imaging

The ultrafast active cavitation imaging(UACI)based on plane wave transmission and delay-and-sum(DAS)beamforming has been developed to monitor cavitation events with a high frame rate.However,DAS beamforming leads to images with limited resolution and contrast.In this paper,minimum variance(M V)adaptive beamforming and coherence factor(CF)weighting are combined to achieve an MVCF-based UACI,which can improve the cavitation imaging quality.The detailed algorithm evaluation has been investigated from both simulation and experimental data The simulation data include10point targets and a cyst,while the experimental data are obtained by detecting the dissipation of cavitation bubbles in water excited by a single element transducer with frequency of1.2MHz.The advantages of the proposed methodology as well as the comparison with conventional B-mode,DAS?M V,DAS-CF and MV on the basis of compressive sensing(CS)(called MVCS)beamformers are discussed.The results show that MVCF beamformer has a significant improvement in terms of both resolutions and signal-to-noise ratio(SN R).The MVCF-based UACI has a SNR at21.82dB higher,lateral and axial resolution at2.69times and1.93times?respectively,which were compared with those of B-mode active cavitation mapping.The MVCF-based UACI can be used to image the residual cavitation bubbles with a higher SNR and better spatial resolution

On Broadband Adaptive Beamforming in the Presence of Correlated Interferences

A novel approach of unitarily interpolated array MVDR （UIA-MVDR） is proposed, aiming at avoiding the signal cancellation caused by broadband signal-correlated interferences. UIA-MVDR belongs to the classic approaches of spectral averaging. However, it is distinguished from the conventional interpolated array MVDR （IA-MVDR） by two points： 1） It imposes a unitary constraint on the transform matrices. 2） It only optimizes the worst-case performance of array manifold approximation. As a result, the restriction on the order of Bessel function expansion is released, so that very accurate approximation can be achieved even in the case of small or middle arrays. Compared with many related approaches, UIA-MVDR destroys the correlation more completely and then achieves better performance. Its excellent performance in both correlated and uncorrelated broadband interferences suppression is confirmed via a n umber of numerical examples.

Efficient parallel adaptive array beamforming algorithm

For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. An efficient parallel digital beamforming （DBF） algorithm based on the least mean square algorithm （PLMS） is proposed. An appropriate method is found to partition the least mean square （LMS） algorithm into a number of operational modules, which can be easily executed in a distributed-parallel-processing fashion. As a result, the proposed PLMS algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. PLMS requires less computational load than that of the conventional parallel algorithms based on the recursive least square （RLS） algorithm, as well as it is easier to be implemented to do real time adaptive array processing. Moreover, low sidelobe of the beam pattern is obtained by constraining the static steering vector with Tschebyscheff coefficients. Finally, a scheme of the PLMS algorithm using distributed-parallel-processing system is also proposed. The simulation results demonstrate that the PLMS algorithm has the same interference cancellation performance as that of the conventional LMS algorithm. Moreover, the PLMS algorithm can obtain the same good beamforming performance, regardless how the algorithm is partitioned. It is expected that the proposed algorithm will be used in a large-scale adaptive array system to deal with real time adaptive digital beamforming processing.

最小范数约束的改进MVDR波束形成算法

针对传统的最小方差无畸变响应(MVDR)波束形成方法,难以有效均衡和同时优化干扰和噪声抑制的问题,提出一种基于最小范数解的改进算法。通过对阵列接收信号的自相关阵进行特征分解,取大特征值减去噪声功率及大特征值对应特征向量,构建线性约束方程的最小范数解,代替MVDR算法中的自相关阵的逆的形式形成加权系数,其中噪声功率由小特征值的平均值估计,获得的权系数对应于线性约束条件下的最小范数解。仿真分析表明,该算法能够有效地在干扰位置处形成零陷,利于后续在时间维的噪声滤波处理,较之于MVDR等算法有更好的干扰和噪声抑制性能。

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.

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.

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.

A Semi-blind Adaptive Beamforming Algorithm for Wideband Coherent CDMA

This paper presented a novel semi blind adaptive beamforming algorithm specially designed for wideband coherent CDMA mobile communication systems with multiplexd control and data channels. The presented algorithm uses a parallel structure to exploit not only the desired user’s pseudo noise sequence but also the information from multiplexed pilot and data symbols, thus help achieve faster convergence and lower bit error rate. Monte Carlo simulation results verified the performance improvement in terms of BER.

Speed-Sensitive Weighting Algorithm for Digital Beamforming of Adaptive Antenna Arrays

One of the main objectives of adaptive antenna array processing is reducing the computational complexity and convergence time in a joint state. This article proposes a speed-sensitive adaptive algorithm for estimating the weights of smart antenna systems based on least mean squares (LMS) or constant modulus (CM) algorithms. According to the next estimated location as well as the source velocity, this novel proposed weighting algorithm selects those weights that have a higher effect on the radiation pattern and will then form the antenna pattern by only changing these weights. In this research, 3 versions of the new algorithm named as: Not-zero (Leaves half number of weights as it is the other half), Zero (Sets half number of weights to be zero and estimates other half), and Updating (Leaves half of weights unchanged and estimates other half in one phase and updates all weights in the next phase) are proposed. Through simulation of these 3 versions of speed-sensitive algorithms and comparing among conventional full weight LMS and CM algorithms, new LMS-based and CM-based algorithms have been finally proposed that offer reduced complexity and acceptable performance at different signal to noise ratios (SNRs). In this investigation, three channel scenarios are simulated which are as follows: pure noisy channel, channel with one interferer and channel with two interferers. In accordance with the simulation results, an appropriate algorithm based on weighting half number of array elements and updating all existing weights between two consecutive times to avoid error propagation effect has been proposed.

Joint Closed-Loop Power Control and Adaptive Beamforming for Wireless Networks with Antenna Arrays in a 2D Urban Environment

The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to decrease the interference in wireless communication networks. In this paper, we propose smart step closed-loop power control (SSPC) algorithm in wireless networks in a 2D urban environment with constrained least mean squared (CLMS) algorithm. This algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. Also, we present switched-beam (SB) technique for enhancing signal to interference plus noise ratio (SINR) in wireless networks. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless networks in a 2D urban environment. The simulation results indicate that the convergence speed of the SSPC algorithm is faster than other algorithms. Also, we observe that significant saving in total transmit power (TTP) are possible with our proposed algorithm. Finally, we discuss three parameters of the PCE, number of antenna elements, and path-loss exponent and their effects on capacity of the system via some computer simulations.

Non-Negative Matrix Factorization Based UKF Algorithm for Constant Modulus Signals in Adaptive Beamforming

Blind adaptive beamforming is getting appreciated for its various applications in contemporary communication systems where sources are statistically dependent or independent that are allowed to formulate new algorithms. Qualitative performance and time complexity are the main issues. In this paper, we propose a technique for constant modulus signals applying basic non-negative matrix factorization (BNMF) in blind adaptive beamforming environment. We compared the existing Unscented Kalman Filter based Constant Modulus Algorithm (UKF-CMA) with proposed NMF-UKF-CMA algorithm. We see there is a better improvement of sensor array gain, signal to interference plus noise ratio (SINR) and mean squared deviation (MSD) as the noise variance and the array size increase with reduced computational complexity with the UKF-CMA.

时域解析信号的MVDR自适应波束形成方法

针对频域最小方差无失真响应(MVDR)方法在源方位快速变化情况下稳定性差的问题,提出了一种基于时域解析信号的MVDR自适应波束形成方法TAMVDR(Time-domain Aanlysis MVDR)。在构造时域解析信号的基础上,TAMVDR通过对每一路时域解析信号引入复权,利用期望方向的输出响应不变的约束使阵列输出功率最小。在一次快拍条件下,TAMVDR即可获得最优解。仿真及试验数据处理结果表明,在目标方位快速变化条件下,TAMVDR的信号检测和方位分辨性能明显优于频域MVDR方法,且计算量较小。

利用近场MVDR双聚焦波束成形方法实现被动测距

本文分析了近场环境下基于双聚焦波束成形的水下被动测距方法。通过修正MVDR方向矢量,得到了适用于近场环境的MVDR。仿真实验证明近场MVDR双聚焦波束成形测距方法优于普通波束成形和远场MVDR双聚焦波束成形,能明显减小目标距离估计的模糊区域。在相邻两个日标的定位性能上,MVDR双聚焦波束成形技术也比MVDR单聚焦系统体现出更大的优势,能较好地分辨目标。

矢量水听器阵列MVDR波束形成器的性能研究

针对矢量水听器阵列的最佳阵处理,研究了高斯背景噪声条件下MVDR波束器的输出性能,给出了系统输出信干噪比与各影响参数之间的解析关系式,并对三种典型情况进行了具体探讨,着重分析了信噪比、干扰强度、相关系数和样本长度对系统输出SINR的影响,证明了低信噪比时MVDR波束形成器为最佳空域滤波器,分析还表明,MVDR波束形成器对强信号存在抑制现象,高信噪比时输出的SINR为一常数。计算机仿真结果证明了理论分析的正确性。