Waveform design and high-resolution imaging of cognitive radar based on compressive sensing

We introduce the compressive sensing(CS) theory for waveform design of cognitive radar,and then propose an algorithm for the high-resolution radar signal waveform and its corresponding imaging method based on the sparse orthogonal frequency division multiplexing-linear frequency modulation(OFDM-LFM) signal.We first present the principle of spectrum synthesis and high-resolution imaging based on OFDM-LFM signals.Then,we propose the spectrum-sparse waveform design criterion and the reconstruction algorithm for a highresolution range profile(HRRP) based on CS.Based on this,we analyze in detail the relationship between the scattering characteristics of the target and the parameters of the designed signal,and we construct the feedback of the target characteristics on the waveforms.Therefore,the "cognitive" function of radar can be achieved by adaptively adjusting the waveform with the target characteristics.Simulations are given to validate the effectiveness of the proposed algorithm.     

On the role of waveform diversity in MIMO radar

MIMO radar employs multiple antennas to simultaneously transmit diverse waveforms, as well as multiple antennas to receive the radar returns. This paper studies the role of waveform diversity in MIMO radar as separate and distinct from the role of the multiple transmit antennas. This is done by comparing a MIMO radar system to a scanning phased array radar which uses the same transmit and receive arrays but only a single waveform. The performance characteristics of the two systems, in terms of the ambiguity function and the spatial response, are compared for single pulse operation as well as multi-pulse operation with coherent integration. Both element-space and beam-space systems are considered.     

Total ionizing radiation effects of 2-T SONOS for 130 nm/4 Mb NOR flash memory technology

In this paper,we have studied the total ionizing dose(TID)radiation response up to 2 Mrad(Si)of silicon-oxide-nitride-oxide-silicon(SONOS)memory cells and memory circuits,fabricated in a 130 nm complimentary metal-oxide-semiconductor(CMOS)SONOS technology.We explored the threshold voltage(VT)degradation mechanism and found that the VT shifts of SONOS cells depend on the charge state;simply programming the cell to a higher VT cannot compensate for the radiation induced VT loss.The off-state current(Ioff)increase in the SONOS cell is also studied in this paper.Both VT and Ioffdegradation would affect the memory system.Read data failures are mainly caused by VT shifts under irradiation,and program and erase failures are mainly caused by increased Ioff,which overloads the charge pumping circuit.By varying the reference current,our 4 Mb NOR flash chip has the potential to survive a radiation dose of 1 Mrad(Si)in read mode.     

OFDM wavefroms designed with piecewise nonlinear frequency modulation pulse for MIMO radar

ABSTRACT

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) waveform diversity design has drawn extensive attention since it has a great potential in remote sensing. The orthogonal frequency-division multiplexing (OFDM) waveform designing becomes one of the most significant tasks in MIMO SAR system. In this article, a novel piecewise nonlinear frequency modulation (NLFM) waveform is proposed. The OFDM waveform is composed of the piecewise NLFM waveforms as its subpulses, and each subpulse has a different subcarrier beginning frequency. The subpulse is centre symmetrical and can be divided into three segments. The first and third segments of the subpulse are linear frequency modulation waveforms, and the second segment of the subpulse is an NLFM waveform. A few parameters are used to control the duration and bandwidth of each segment in the subpulse. Genetic algorithm is used for the OFDM waveforms to optimize the sidelobes of autocorrelation and cross-correlation function. Compared with other OFDM waveform design methods, the proposed method is more flexible and has higher degrees of freedom and thus can yield waveforms with a better autocorrelation and cross-correlation properties. The performances of ambiguity function and cross ambiguity function are analysed to have low time delay and Doppler correlation peaks. Simulation results demonstrate the validity of the proposed method.     

An improved OFDM chirp waveform used for MIMO SAR system

Special attention has been devoted to multi-input multi-output(MIMO)synthetic aperture radar(SAR)systems in recent years.The applications of MIMO SAR systems which involve 3D imaging,highresolution wide-swath remote sensing,and multi-baseline interferometry are seriously limited to the orthogonal waveforms.Although orthogonal frequency division multiplexing(OFDM)chirp waveforms can be used for MIMO SAR systems to avoid intra-pulse interferences,there is a small frequency shift between the transmitted OFDM pulses.This vulnerable shift,which can not only affect the waveform orthogonality,but also introduce residual phase error,renders the OFDM waveforms impractical.In this paper,an improved OFDM chirp waveform which works without the mentioned shift is presented,along with the novel modulation and efficient demodulation procedures.Comparison between the improved and the conventional OFDM chirp waveforms is detailed.The influence of random noise,quantization error,and Doppler shift on the orthogonality of OFDM waveform is also investigated in this paper.Theoretical analysis and simulation results illustrate the feasibility of this waveform scheme.     

基于灰关联混合蛙跳算法的雷达波形设计

提出了一种基于灰关联混合蛙跳算法的雷达波形设计方法,以混合蛙跳算法为主体,在局部更 新算子中引入遗传算法的遗传算子,并改进原始蛙跳算法的分组方法,丰富了种群的多样性,同时引入灰关联综合评价法则对适应度函数值加以关联度分析。文中以设计具有低自相关旁瓣和互相关特性的正交多相编码为例,将该算法用于雷达波形设计中。仿真结果表明使用本文算法产生 的波形具备较好的低自相关特性和互相关特性,表明了该算法是有效和可行的。     

Entropy minimax expansions for waveform analysis

Consider a collection of waveforms, each of which is treated as a set of independent variables containing information about some other (dependent) variable. This paper addresses the problem of finding informationally efficient expansions of the waveforms. A procedure is described for determining conditional entropy efficient basis functions for the given collection of waveforms, where the entropy is conditioned on the specified dependent variable. Use of these basis functions for approximate waveform reconstruction minimizes the loss of information about the dependent variable (the degree of approximation depending upon the number of basis functions used).     

基于神经网络分类的星载雷达高度计近岸回波处理方法

对HY-2B卫星雷达高度计香港近岸波形进行了统计分析,将近岸非海洋波形分为似海洋波形、似陆地波形、单锥波形。在此基础上,提出基于神经网络分类的星载雷达高度计近岸回波处理方法,提取7项波形特征作为回波分类的输入,构建误差逆传播神经网络（Back propagation,BP）,不同的波形类别对应不同的重跟踪方法。其中针对似海洋波形,提出异常波峰剔除的重跟踪方法,有效提高了似海洋波形的重跟踪成功率。使用Jason-2卫星雷达高度计近岸数据进行实验,结果表明重跟踪成功率和数据有效性均得到提高;利用HY-2B卫星雷达高度计直湾岛海域数据进行实验,并将验潮站数据作为参照标准,重跟踪得到的海面高与验潮站的海面高进行差值比较,该方法得到差分序列的标准差为6.5 cm,优于传统处理方法的14.5 cm。     

Fault classification method for inverter based on hybrid support vector machines and wavelet analysis

A new classification method for fault waveform is proposed based on discrete orthogonal wavelet transform (DOWT) and hybrid support vector machine (hybrid SVM) for fault type of a three-phase voltage inverter. The waveforms of output voltage obtained from the faulty inverter are decomposed by DOWT into wavelet coefficient matrices, through which we can obtain singular value vectors acted as features of time-series periodic waveforms. And then a multi-classes classification method based on a new Huffman Tree structure is presented to realize 1-v-r SVM strategy. The extracted features are applied to hybrid SVM for determining fault type. Compared to employing the structure based on ordinary binary tree, the superiority of the proposed SVM method is shown in the success of fault diagnosis because the average Loo-correctness of the SVM based on Huffman tree structure exceed the general SVM 3.65%, and the correctness reaches 99.6%.     

小型化高频天线阵列的波形设计研究

主要研究了小型化表面波雷达阵列发射天线的波形特性。建立发射信号模型和波形优化目标函数，采用模拟退火算法优化求解目标函数。针对优化的跳频码序列进行仿真实验，得到仿真结果。对不同波形的自相关函数和模糊函数特性进行了研究和比较。仿真结果表明：所设计的波形较其他波形具有较优的自相关特性。研究结果可为小型化高频地波雷达的波形设计提供一种可行的方法和思路。     

基于模糊函数三维特征的雷达辐射源信号分选方法

提取并补充新的特征参数,是解决当前复杂体制雷达辐射源信号分选难题的有效途径.由于模糊函数能够很好地展现信号波形的内在信息,从主、侧视角分别提取模糊函数三维图的主岭重心、主峰分布半径作为雷达辐射源信号分选的特征向量.核模糊C均值聚类实验表明,所提出方法在10dB以上的固定信噪比环境下分选6类典型信号的成功率均为100{%     

The Optimality of Linear Estimation Algorithms in Minimax Identification

The optimality of linear estimates in minimax estimation of a stochastically uncertain vector in a linear observation model by mean-square criterion is studied. In the Gaussian case, a uniformly optimal linear estimate is shown to exist in the class of all unbiased estimates. Moreover, it is minimax in the class of all nonlinear estimates if the nonrandom parameters of the observation model are unbounded. If the a priori information on random parameters are given as constraints on the covariance matrix, linear estimates are shown to be minimax.     

On the expectation of the product of four matrix-valued Gaussianrandom variables

The formula for the expectation of the product of four scalar real Gaussian random variables is generalized to matrix-valued (real or complex) Gaussian random variables. As an application of the extended formula, a simple derivation is presented of the covariance matrix of instrumental variable estimates of parameters in multivariable regression models     

基于先验知识的自适应检测波形设计

研究了基于先验知识的认知雷达自适应检测波形设计问题,推导了发射波形对于检测性能影响的闭式解并提出了一种基于交替投影法的波形优化算法。算法根据所推导出的检测概率与发射波形、接收机滤波器之间关系的闭式表达式,通过联合优化发射波形和接收机滤波器,达到提高接收机的检测概率和降低信号相关杂波负面影响的目的。分析仿真结果可知,所设计波形的检测性能优于传统的恒包络LFM波形。当采用多组初始波形进行迭代优化时,检测概率趋向于相同值,这表明该算法的收敛性良好。     

Automated data acquisition and analysis of neural evoked potentials

A software system to collect, analyze and store trains of neural evoked potentials is presented. Real-time waveform capture permits sampling of a variable-duration data window of 6 to 399.6 ms with a sample delay accurately adjustable up to 1 001 ms (20 microseconds resolution). The digitized representation of each waveform is stored for individual analysis. Off-line processing determines 17 parameters of each waveform, including an arrow-selected amplitude and time. Individual processing of waveforms preserves all degrees of freedom for statistical analysis across waveforms. Ensemble averages may optionally be formed from the individual waveforms with processing performed on the averaged responses. The software provides MENU-selectable support functions including stimulus-to-artifact timing, storage and retrieval of data and calculated parameters, digital display of waveforms, data calibration and gain modification, table referenced data editing, file management, simple statistics, hardcopy output, and optional database interfacing with output formatted for compatibility with a statistics package (SAS).     

基于TF-IDF分类算法的雷达情报分发技术

为了提高情报分发的效率,解决雷达组网上信息过载的问题,提出了一种利用个性化推荐技术过滤情报用户感兴趣的情报信息的技术.根据情报用户兴趣多样性的特点和雷达情报的格式化特征,对情报用户兴趣的类别进行划分,并设计出基于层次向量空间模型;在此基础上,利用用户的历史情报信息和定制信息,运用TF-IDF算法挖掘用户兴趣,建立用户兴趣模型,通过实时情报与用户兴趣模型的匹配,将用户感兴趣的情报分发给用户.仿真实验结果表明,该算法能够较好地实现雷达情报的按需分发.     

An entropic criterion for minimum uncertainty sensing inrecognition and localization. I. Theoretical and conceptual aspects

A criterion is presented for the automatic selection of a sensor measurement aimed at observing the state of a system which is described both by discrete variables and by continuous ones. The criterion is based on the expected value of the entropy variation associated to the sensor observation. This criterion is then applied to object recognition and localization tasks, in which the observed system is characterized by the object class, represented by a discrete variable, and by the object pose, i.e., position and orientation, represented by a vector of continuous parameters. The proposed criterion also accounts for the information obtained in the case the observed object is missed by the measurement.     

基于互信息的有源压制干扰下相控阵雷达多目标跟踪时间资源优化配置算法

本文针对有源压制干扰下的相控阵雷达(Phased Array Radar)多目标跟踪时间资源优化配置问题,提出了一种基于互信息(Mutual Information, MI)的配置算法。采用MI准则作为目标跟踪性能量化指标,推导了包含时间变量的雷达回波与路径增益矩阵MI表达式,建立了时间资源优化配置模型,并采用改进的遗传算法实现了模型求解。仿真结果表明,该算法能在有源压制干扰条件下最大化有效跟踪目标数,并提高有效跟踪目标的整体跟踪性能,具有较高的理论和工程应用价值。     

ICESat waveform-based land-cover classification using a curve matching approach

Light detection and ranging waveforms record the entire one-dimensional backscattered signal as a function of time within a footprint, which can potentially reflect the vertical structure information of the above-ground objects. This study aimed to explore the potential of the Geoscience Laser Altimeter System sensor on board the Ice, Cloud, and Land Elevation Satellite to perform land-cover classification by using only the profile curve of the full waveform. For this purpose, a curve matching method based on Kolmogorov–Smirnov (KS) distance was developed to measure the curve similarity between an unknown waveform and a reference waveform. A set of reference waveforms were first extracted from the training data set based on a principal component analysis (PCA). The unknown waveform was then compared with individual reference waveforms derived using KS distance and assigned to the class with the closest similarity. The results demonstrated that the KS distance-based land-cover classification using the waveform curve was able to achieve an overall accuracy of 87.2% and a kappa coefficient of 0.80. It outperformed the widely adopted rule-based method using Gaussian decomposition parameters by 3.5%. The research also indicated that the PCA- selected reference waveforms achieved substantially better results than randomly selected reference waveforms.