Range walk and array rotation in space-time adaptive processing:effects and compensations

This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.

SPACE-TIME ADAPTIVE PROCESSING FOR AIRBORNE RADAR:A CONVENIENT IMPLEMENTATION APPROACH

A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon approach . It is of practical use for its small computational load. This approach possesses the ideal performance in the area of main-lobe clutter . In addition, the approach which is added by some auxiliary beams in the area of main-lobe clutter has also been discussed.

Direct data domain approach to space-time adaptive processing

In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.

PRECONDITIONED METHODS FOR SPACE-TIME ADAPTIVE PROCESSING

This paper introduces the preconditioned methods for Space-Time Adaptive Processing(STAP).Using the Block-Toeplitz-Toeplitz-Block(BTTB)structure of the clutter-plus-noise covari-ance matrix,a Block-Circulant-Circulant-Block(BCCB)preconditioner is constructed.Based on thepreconditioner,a Preconditioned Multistage Wiener Filter(PMWF)which can be implemented by thePreconditioned Conjugate Gradient(PCG)method is proposed.Simulation results show that thePMWF has faster convergence rate and lower processing rank compared with the MWF.

STATISTICAL SPACE-TIME ADAPTIVE PROCESSING ALGORITHM

For the slowly changed environment-range-dependent non-homogeneity, a new statistical space-time adaptive processing algorithm is proposed, which uses the statistical methods, such as Bayes or likelihood criterion to estimate the approximative covariance matrix in the non-homogeneous condition. According to the statistical characteristics of the space-time snapshot data, via defining the aggregate snapshot data and corresponding events, the conditional probability of the space-time snapshot data which is the effective training data is given, then the weighting coefficients are obtained for the weighting method. The theory analysis indicates that the statistical methods of the Bayes and likelihood criterion for covariance matrix estimation are more reasonable than other methods that estimate the covariance matrix with the use of training data except the detected outliers. The last simulations attest that the proposed algorithms can estimate the covariance in the non-homogeneous condition exactly and have favorable characteristics.

A NON－INCREMENTAL TIME－SPACE ALGORITHM FOR NUMERICAL SIMULATION OF FORMING PROCESS

A non-incremental time-space algorithm is proposed for numerical. analysis of forming process with the inclusion of geometrical, material, contact-frictional nonlinearities. Unlike the widely used Newton-Raphson counterpart, the present scheme features an iterative solution procedure on entire time and space domain. Validity and feasibility of foe present scheme are further justiced by the numerical investigation herewith presented.

W ideband interference suppression based on space-time filter

Based upon the diagonal loading technique and the structure of the space-time adaptive processors, a novel anti-jamming method of satellite navigation is proposed. According to matrix in- verse theorem, the range of the diagonal loading values for space-time adaptive wideband signal pro- cessing structure is deduced, and the optimum equation of diagonal loading beam forming algorithm of space-time structure is obtained. Then, by the analysis of two-dimensional oriented vector in di- rection of the perturbation interference, the wideband interference covariance matrix obtained in the weights training period is modified. Finally, the optimum weight of multi-linear constrained space- time adaptive beam-forming alogrithm is derived for anti-interference filter processing. The new method effectively widens the null steering beams tion results prove the robustness of the proposed when discrepancy happens. The computer simula- method.

A VERTICAL LAYERED SPACE-TIME CODE AND ITS CLOSED-FORM BLIND SYMBOL DETECTION

Vertical layered space-time codes have demonstrated the enormous potential to accommodate rapid flow data. Thus far, vertical layered space-time codes assumed that perfect estimates of current channel fading conditions are available at the receiver. However, increasing the number of transmit antennas increases the required training interval and reduces the available time in which data may be transmitted before the fading coefficients change. In this paper, a vertical layered space-time code is proposed. By applying the subspace method to the layered space-time code, the symbols can be detected without training symbols and channel estimates at the transmitter or the receiver. Monte Carlo simulations show that performance can approach that of the detection method with the knowledge of the channel.

QUADRATIC PROGRAMMING NEURAL NETWORK BASED INTEGRATED SPACE-TIME INTERFERENCE SUPPRESSION IN CDMA SYSTEMS

Quadratic programming models for integrated space-time interference suppression in CDMA systems are proposed in this paper. The models integrate the advantages of smart antenna and RAKE receiver, mitigate multiuser access interference (MAI) and interchip interference (ICI),and combine multipath components. The zero-forcing conditions are derived. Neural network implementation of the models is also studied.

Novel space-time multiuser detection algorithm of WCDMA system

The structure and performance of space-time multiuser detection receiver at base stations of WCDMA system is analyzed, in which smart antenna is employed. WCDMA uplink signal model is established in this paper. Space-time multiuser receiver presented in this paper combines 2D-RAKE with parallel interference cancellation (PIC), and the improved parallel interference cancellation methods are given. A novel space-time multiuser detection scheme, 2DRAKE-GPPIC is proposed. This scheme employs smart antenna to suppress unexpected DOA (Direction Of Arrival) signal, uses RAKE receiver to combine different delays of expected signal, and utilizes grouped partial parallel interference cancellation (GPPIC) algorithm to suppress further the interference signal in the main lobe of array antennas. The simulation results reveal that the scheme of space-time multiuser detection presented in this paper has better performance for WCDMA system.

Variance minimization for continuous-time Markov decision processes: two approaches

This paper studies the limit average variance criterion for continuous-time Markov decision processes in Polish spaces. Based on two approaches, this paper proves not only the existence of solutions to the variance minimization optimality equation and the existence of a variance minimal policy that is canonical, but also the existence of solutions to the two variance minimization optimality inequalities and the existence of a variance minimal policy which may not be canonical. An example is given to illustrate all of our conditions.

基于自适应字典校正的稀疏恢复STAP算法

空时自适应处理(Space-Time Adaptive Processing,STAP)技术在时间维(脉冲维)和空间维(阵元维)联合进行信号处理,以实现动目标检测功能。但是,传统STAP技术的计算复杂度非常高,而且在优化处理信号过程中需要大样本的支撑,在实际的工作场景中,杂波环境复杂易变,不易获取足够多的独立同分布样本,因此杂波抑制效果较差。稀疏恢复空时自适应处理(Sparse Recovery Space-Time Adaptive Processing,SR-STAP)算法可以利用很少的训练样本实现杂波抑制,但大多数SR-STAP算法的计算量巨大,运行速度慢,算法实时性不高。此外,SRSTAP算法需要对连续空时二维平面进行离散化处理,将空时二维平面划分为很多细小的网格,由于真实的杂波在空时平面上是连续分布的,同时考虑雷达接收信号中噪声、系统参数误差等因素的影响,真实杂波点与离散化网格点之间一定存在着偏差,会造成网格失配现象,导致SR-STAP算法杂波抑制性能下降。针对此问题,本文提出了基于自适应字典校正的稀疏恢复STAP算法。该算法首先通过子空间投影法筛选出与杂波最相关的原子;然后围绕选定原子由粗到细进行自适应局部网格划分,按照局部网格迭代选优准则,不断调整选择局域内的最优原子,直到满足迭代终止条件,以匹配真实的杂波点;最后利用选定的最优原子对应的空时导向矢量构造杂波子空间,更新噪声子空间上与杂波子空间正交的投影矩阵得到STAP权值。仿真实验表明,所提算法与传统SR-STAP算法相比,具有更高的稀疏恢复精度,更快的运行速度,改善了STAP性能。

基于KA-SRCN-pSTAP的低空风切变风速估计方法

针对由于独立同分布(IID)样本严重不足,导致极化空时自适应(pSTAP)处理性能下降,进而导致低空风切变风速估计不准确的问题,本文提出了一种基于知识辅助的稀疏表示杂波零陷极化空时自适应(KA-SRCN-pSTAP)的低空风切变风速估计方法。该方法首先利用杂波脊的先验知识辅助构造极化空时稀疏字典,然后利用极化空时稀疏字典,通过SRCN算法挑选原子并对到杂波线性子空间补空间上的投影矩阵进行估计,从而得到pSTAP权矢量,最后构造pSTAP滤波器对地杂波进行抑制,准确估计低空风切变风速。该方法仅使用少量IID样本,将SRCN算法与极化-空时域相结合,完成对风切变风速的有效估计。仿真实验结果证明该方法可以有效实现少样本情况下的风速准确估计。

多模式对四川盆地强降水过程的预报性能检验

为进一步认识当前数值预报模式的预报能力,选取2018—2020年发生在四川盆地的47次强降水过程进行分型,再基于多源降水融合产品和地面观测资料,通过TS评分、时空滑动等方法对欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)数值预报模式、国家气象中心区域中尺度数值预报模式(China Meteorological Administration Mesoscale Model,CMA_MESO)和西南区域数值预报系统(Southwest Center WRF ADAS Real-time Modeling System,SWC_WARMS)在强降水过程范围、强度、极值、时间和位移偏差等方面的预报能力进行检验评估。结果表明,各模式08:00(北京时,下同)预报优于20:00预报,ECMWF对中雨和大雨预报更优,SWC_WARMS的暴雨量级评分更高。各模式对中雨的预报范围普遍较实况偏大,随着降水量级增大,逐渐转为低估,其中SWC_WARMS更接近实况。对于降水强度,ECMWF和CMA_MESO的平均降水量和极值普遍较实况偏小,SWC_WARMS更接近实况。3种模式时间偏差不明显,仅个别起报时次有-6~3 h的时间偏差;ECMWF的位移偏差最小,纬向上ECMWF和SWC_WARMS以偏北为主,经向上ECMWF以偏西为主,CMA_MESO和SWC_WARMS以偏东为主。

机载多载频频控阵非均匀距离模糊杂波抑制方法

机载雷达下视工作面临严重的地海杂波,雷达平台运动造成杂波多普勒频率严重扩散,将微弱目标完全淹没。空时自适应处理(space time adaptive processing,STAP)技术通过联合多天线脉冲的接收信号,能够有效地抑制杂波,实现运动目标检测。对于非正侧视阵列高速平台雷达,杂波距离依赖和距离模糊严重制约着目标检测性能。基于多载频频控阵,通过发射一组载频不同的正交信号,在杂波回波中,获得新的发射维自由度,并根据不同模糊在发射维的差异分离各模糊区域。此外,通过进一步对分离后的近程进行杂波补偿,利用降维STAP实现杂波抑制。仿真结果验证了所提方法的有效性。

基于三维原子范数的机载MIMO雷达STAP算法

针对机载多输入多输出(MIMO)雷达空时自适应处理(STAP)使用稀疏恢复技术时存在的格点失配问题,提出了一种基于三维原子范数的机载MIMO雷达STAP算法。该方法利用杂波空时谱在角度-多普勒域上固有的稀疏性,根据低秩矩阵恢复理论构造了基于三维连续原子集的MIMO雷达杂波信号稀疏恢复模型,避免了稀疏恢复中的格点失配问题,实现了杂波空时谱的高分辨率估计,有效提高了机载MIMO雷达STAP杂波抑制性能。仿真实验表明,本文方法在存在格点失配情况下的MIMO雷达STAP处理性能优于已有的基于字典网格的稀疏恢复方法和二维原子范数方法。

基于可解释深度卷积网络的空时自适应处理方法

在实际应用中,空时自适应处理(STAP)算法的性能受限于足够多独立同分布(IID)样本的获取。然而,目前可有效减少IID样本需求的算法仍面临一些问题。针对这些问题,该文融合数据驱动和模型驱动思想,构建了具有明确数学含义的多模块深度卷积神经网络(MDCNN),实现了小样本条件下对杂波协方差矩阵快速、准确、稳定估计。所构建MDCNN网络由映射模块、数据模块、先验模块和超参数模块组成。其中,前后端映射模块分别对应数据的预处理和后处理;单组数据模块和先验模块共同完成一次迭代优化,网络主体由多组数据模块和先验模块构成,可实现多次等效迭代优化;超参数模块则用来调整等效迭代中可训练参数。上述子模块均具有明确数学表述和物理含义,因此所构造网络具有良好的可解释性。实测数据处理结果表明,在实际非均匀杂波环境下该文所提方法杂波抑制性能优于现有典型小样本STAP方法,且运算时间较后者大幅降低。

基于波束对消的车辆运动地物杂波抑制方法

针对在快速运动车辆载体上雷达目标检测中强地物杂波的抑制问题,借鉴机载雷达空时处理原理,分析了车辆运动地物杂波分布特性,探讨了运动车辆雷达差波束地物杂波对消和波束地物杂波的适用性。实测数据表明该方法可有效抑制主副瓣地物杂波,提高车辆运动中对慢速飞行目标的检测能力。

发射波束域MIMO-STAP雷达发射接收联合设计方法

研究了信号相关杂波背景下机载多输入多输出(multiple-input multiple-output,MIMO)雷达发射波束形成和接收滤波器的联合设计问题,建立了机载MIMO雷达发射波束域空时自适应处理(space-time adaptive processing,STAP)信号模型。为了提升杂波环境下目标的检测性能,通过最大化输出信干噪比构建了发射波束形成和接收滤波器的联合设计问题;然后,设计了一种新的基于优化最小化(majorization-minimization,MM)框架的迭代优化算法来解决联合设计问题。该算法通过合理寻找目标函数的下界可以有效提升算法的收敛速度并降低算法的运行时间。此外,与传统的相控阵雷达和MIMO雷达相比,优化后的发射波束形成和接收滤波器可以显著提升输出信干噪比,仿真实验验证了所提方法的有效性。

GNSS对流层湿延迟随机游走过程噪声时空变化特征分析

全球导航卫星系统GNSS对流层天顶湿延迟(zenith wet delay,ZWD)随机噪声不仅影响ZWD估计值大小,还会影响ZWD的趋势项变化。为揭示ZWD随机游走过程噪声(random walk process noise,RWPN)的时空变化特征,本文选取全球20个IGS(International GNSS Service)测站,基于JPL(Jet Propulsion Laboratory)、GFZ(Helmholtz-Centre Potsdam-German Research Centre for Geosciences)和CODE(Center for Orbit Determination in Europe)分析中心2010至2020年对流层产品,从不同地理位置和不同时间序列分析GNSS ZWD随机游走过程噪声的变化范围和特征;并且在扣除ZWD的趋势项和主要周期项后,进一步揭示了ZWD残差信号分量构成。结果表明:不同地理位置湿延迟RWPN具有显著差异,年均值范围在0.01~0.146 mm/√s之间,且在大气集中的中低纬地区湿延迟RWPN值较大,在大气相对稀薄的极地地区其值较小;同一测站的湿延迟RWPN具有明显的周年、半周年和季节性特征,极差值高达0.12 mm/√s以上;通过对ZWD残差值分析,发现ZWD残差信号除包含白噪声外,还具有4.8 h至2.43 d的高频信号分量。