一种共形阵主动声纳空时自适应混响抑制方法

运用平台自身运动补偿技术无法完全消除由空域锥角引起的多普勒扩展,因此影响主动声纳探测性能。因此为了提高鱼雷共形阵主动声纳混响抑制能力,文中对空时二维自适应抑制混响方法进行了研究,并分析了混响多普勒频率与空域锥角余弦存在特定关系,在此基础上进一步研究了以多普勒处理为基础的空时降维自适应处理方法(时空级联处理方法)在主动声自导鱼雷中的应用。仿真研究表明:时空级联处理方法在处理性能接近最优处理,同时,处理速度明显快于最优处理。因此,在鱼雷中远程主动自导中,空时二维自适应混响抑制方法具有研究价值。     

基于多普勒特征恢复的声矢量阵鲁棒自适应波束形成方法

在短快拍、信号导向矢量失配环境下,传统的自适应波束形成方法性能受到影响,对角加载技术是提高算法在复杂环境下性能鲁棒性的重要技术之一。针对水声环境和水声信号特点,提出一种基于声矢量阵的自适应波束形成方法。该方法利用水声信号的多普勒频率信息,在不同环境下自适应地选择最优对角加载因子,确定波束形成的权矢量,从而实现提取期望目标信号、抑制干扰和噪声的目的。无需任何用户参数,鲁棒性强、估计精度高。最后基于声矢量阵进行仿真实验,仿真结果证明了所提出的方法能够有效地获取目标信号,具有较好的抗干扰能力。     

双基雷达MTI杂波非静态特性消除方法

空时自适应处理(STAP)是机载和星载双基雷达中的关键技术.在双基雷达体系中分析了杂波非静态特性对空时自适应处理运动目标检测性能的影响.在统一条件下,推导出了局域化辅助数据区、距离变化加权和数据补偿等三类杂波非静态特性消除处理方法.对这些方法的改善因子性能进行了数据仿真比较研究和兼容性分析,并指出了它们的应用局限性.     

圆柱阵主动声纳混响抑制方法研究

圆柱阵主动声纳混响的强非均匀性,会降低空时自适应处理的性能。对圆柱阵主动声纳混响的空时二维分布特性以及混响数据的非均匀性进行分析,在此基础上研究了基于修正的角度-多普勒补偿(Modified Angle-Doppler Compensation,MADC)和导数更新技术(Derivative Based Updating,DBU)的降维自适应处理方法在圆柱阵声纳混响抑制中的应用。仿真结果表明:这两项技术可降低混响的非均匀程度,对运动中的圆柱阵主动声纳有较好的混响抑制效果,其性能更接近最优处理。     

天基多载频稀疏阵STAP方法的幅相误差影响

地面动目标检测 (GMTI) 是天基分布式雷达的重要应用之一, 采用多载频模式可有效减少孔径稀疏引起的动目标检测盲区, 提高 GMTI 性能. 针对多载频天基稀疏阵雷达的空时自适应处理 (STAP) 方法, 基于多通道幅相误差模型, 推导了多载频模式下存在幅相误差的杂波协方差矩阵表达式. 通过仿真分析了幅相误差对多载频稀疏阵最优 STAP 方法的影响.     

智能天线MC-CDMA系统中空频联合盲多用户检测算法

提出了智能天线多载波CDMA系统中一种空域和频域联合的盲多用户自适应检测算法,它是将空域波束形成和频域合并检测合二为一,使得检测器在空域和频域两维上同时优化,从而提高了系统的检测性能.对这种空频联合检测算法的误码性能进行了分析,并与先自适应波束形成然后再进行频域合并的分步算法进行了仿真比较,仿真结果表明,提出的空频联合盲多用户自适应检测算法的检测性能优于分步检测算法.     

一种具有多重稳健性的自适应波束形成算法

由于存在阵元幅相差、期望信号导向矢量误差和数据失配等问题,传统的自适应波束形成算法性能下降,针对这一问题,提出了一种新的对于上述多种误差同时具有稳健性的波束形成算法。该算法以最小二乘恒模算法为基础,结合最优对角加载和协方差矩阵锥消技术,使得算法适用于同时存在多种误差的情况。结果表明,与目前已有的同类算法相比,该算法克服了期望信号信噪比大时算法性能恶化的缺点,具有更好的输出信干噪比,并且通过计算机仿真验证了它的有效性和优越性。     

协作通信中一种非差分分布式空时码

构建了一种循环酉矩阵群的非差分分布式空时码,该码字基于一个简易的三跳通信信道模型,可以应用于信道状态不是特别优良,或者由于通信距离两节点之间不能实现直接通信的情况,也可以应用于Ad hoc网络.在源节点处用循环对角酉矩阵群来构建发送码字,利用分集和的方法得到最优生成矩阵.在中继处利用广义Hadamard矩阵构建中继酉矩阵,对信号进行酉线性处理.并得出三跳通信模型下部分相干分布式空时码的译码公式,根据此公式得到如何选择生成矩阵来提高系统性能.最后对该码字进行仿真对比,得出在低信噪比情况下,两跳通信系统性能比三跳模型的好,但是在高信噪比下三跳通信模型要比两跳的更为优良,并且比差分编码性能提高3dB左右.     

波达方向误差对对角加载波束形成的影响研究

文章回顾了对角加载波束形成理论的发展,列举了几种较常使用的求取对角加载因子的方法。通过多个仿真实例,着重分析了Xavier提出的基于无限随机矩阵理论的对角加载因子的方法．指出了其局限性一在期望信号的方向向量存在误差的时候,该方法产生自消现象,从而波束形成器的性能急剧下降。本文结合特征空间波束形成,根据期望信号的实际方向向量正交于噪声子空间,提出一种改进方法一先对期望信号的方向进行校正,再求取对角加载因子,从而加强了Xavier的方法对波达方向失配的稳健性。仿真实例验证了在信噪比不大的时候这个方法的有效性。     

一种新的稳健CAB盲波束形成算法

通过限制估计的方向向量与真实的方向向量之间的误差范数的边界,提出了一种新的稳健CAB（周期自适应波束形成）盲自适应波束形成算法。该算法克服了方向向量失配引起的自适应波束形成器的性能劣化问题。计算机仿真试验表明,较采用传统对角加载技术的R-CAB盲波束形成算法和WCPO-CAB算法而言,该算法进一步提高了稳健性和输出信干噪比。     

Adaptive detectors with diagonal loading for airborne multi-input multi-output radar

The problem of adaptive target detection for airborne multi-input multi-output (MIMO) radars with space-time receivers in the presence of Gaussian interference (including clutter and noise) is studied. Previous work has assumed the interference covariance matrix to be known. The case with unknown covariance matrix is investigated here. By exploiting the low rank property of clutter subspace, generalised likelihood ratio test detector and adaptive matched filter detector with diagonal loading are suggested to improve the detection performance of MIMO radars in limited secondary data case. The closed-form detection probabilities and false alarm probabilities of the two proposed detectors are derived and numerically evaluated. Theoretical analysis and numerical results show the advantages of the proposed detectors.     

宽带体制下混响和目标空时分布特征研究

传统的空时自适应处理(Space-Time Adaptive Processing,STAP)利用窄带混响和目标在空时平面的可分辨特征抑制窄带混响。对宽带混响和目标在空时平面分布特征进行研究,并通过理论推导,得出带宽对混响和目标空时分辨特征的影响公式。结果表明:宽带混响和目标在空时平面分布特征部分重叠,导致传统STAP效果不佳。在此基础上,借鉴STAP思想,并利用线性调频(Linear Frequency Modulation,LFM)信号在分数阶Fourier变换域上的聚焦性,分析了在空-分数阶Fourier域三维空间上抑制宽带LFM混响的可行性。     

Foundation for mitigating range dependence in radar space-time adaptive processing

The problem of detecting slow-moving targets using a space-time adaptive processing (STAP) radar is addressed. The determination of the optimum interference-rejection weights at each range is based on snapshots at neighbouring ranges. However, in virtually all bistatic configurations or/and when using conformal antenna arrays (CAA), snapshot statistics are range dependent, which results in poor detection performance. To address this issue, a foundation for range-dependence compensation in STAP in the case of Gaussian interference and noise is proposed. The realistic case where received snapshots are the only source of information for mitigating the range dependence is considered. To illustrate the usefulness of the proposed foundation, this foundation is used to design a method to adaptively compensate for range dependence in a challenging situation, that is, for a radar using a CAA and operating in a bistatic configuration.     

基于通用切比雪夫滤波器的有源噪声控制研究

针对前馈管道非线性有源噪声控制系统,提出一种基于通用切比雪夫滤波器的次级通道建模方法和通用切比雪夫滤波x最小均方误差算法(GCFXLMS,general Chebyshev filtered-x least mean square)。通用切比雪夫滤波器由第一类切比雪夫滤波器扩展获得,交叉项部分可通过对角结构实现,根据对角结构的性质,可以采用减少通道信号的实现策略以降低结构复杂度;使用该滤波结构建模次级通道,并给出了稀疏虚拟次级通道模型,基于此模型推导了GCFXLMS算法。该方法性能比较包括计算复杂度对比和控制效果对比。实验结果表明,在非线性有源噪声控制系统中,通用切比雪夫滤波器可达到与Volterra次级通道建模类似的建模效果,相比于传统的前馈滤波器,通用切比雪夫滤波器具有更优的控制性能。     

圆柱阵主动声纳空时混响仿真及空时特性分析

经典的单元散射模型混响仿真方法无法应用于主动声纳空时自适应处理（space-time adaptive processing,STAP）算法研究。提出了一种基于单元散射模型的适合主动声纳STAP算法研究的圆柱阵混响仿真方法。根据声纳发射信号的距离和多普勒分辨力将海洋空间划分成若干个散射单元,将每个散射单元对各个通道混响的贡献在时域分别进行求和,得到各个通道的混响时间序列。仿真综合考虑了多种影响混响的因素,包括发射信号的参数、声呐平台的运动、海洋环境等。对仿真结果的空时特性进行了分析,结果表明仿真数据能够满足STAP算法研究的需要。     

Adaptive ground clutter suppression for conformal array radar systems

Conformal arrays (CFAs) possess certain desirable characteristics for deployment on unmanned aerial vehicles and other payload-limited platforms. However, the CFA non-planar geometry induces clutter nonstationarity, resulting in elevated signal-to-interference-plus-noise ratio (SINR) loss when applying conventional space?time adaptive processing (STAP) algorithms. Non-stationary clutter leads to covariance matrix estimation error and, consequently, an erroneous STAP frequency response. In this study, the authors examine two practical conformal antenna configurations: a belly-mounted canoe and a nose-mounted, chined shape. Using high-fidelity signal models, the authors show traditional STAP losses in excess of 10 dB because of the effects of clutter nonstationarity. The authors then investigate a number of ameliorating techniques compatible with standard STAP implementation, including localised processing, localised processing with time-varying weights, equivalent uniform linear array transformation, angle ?Doppler warping and higher-order angle?Doppler warping. The authors demonstrate very good performance for the higher-order angle?Doppler warping method applied to the chined radome shape, with peak adaptive SINR losses reduced from nearly 16 dB for the uncompensated case to 3 dB of loss consistent with performance attainable in a homogeneous clutter environment. The authors also find good performance for three-dimensional angle?Doppler warping over azimuth, elevation and Doppler when applied to the tapered canoe shape, with uncompensated losses of roughly 14 dB reduced to 3 dB, again a level compatible with STAP applied in a homogeneous clutter environment. The authors thus show that CFA STAP can yield performance similar to that of a conventional planar array when using appropriate compensation methods.     

A Hybrid Particle Approach for GNSS Applications With Partial GPS Outages

To provide an accurate positioning, the land vehicle navigation applications are based on global positioning system (GPS). The addition of a digital road map allows locating the vehicle continuously and helps the driver to get the best path. These systems are usually enhanced with dead reckoning sensors due to GPS outages in urban areas in particular. For instance, the odometer sensors can be used to correct the vehicle location in this case. We present here a global estimation method of solving the fusion problem of the GPS, odometer, and digital road map measurements in the presence of GPS outages. It relies on a hybrid filter that takes advantage of the combination of a Kalman filter, which computes the linear part of the state equations and a particle filter to provide an optimal resolution scheme. When GPS fails, the filter fuses all available pseudorange measures to improve the vehicle positioning. In the case of an urban transport scenario, the results show that the number of particles is significantly reduced to achieve the same performance of a single particle filter in terms of accuracy. Moreover, software solutions can be developed for real-time applications.