High resolution range profile analysis based on multicarrier phase-coded waveforms of OFDM radar

Orthogonal frequency division multiplexing（OFDM） radar with multicarrier phase-coded waveforms has been recently introduced to achieve high range resolution.The conventional method for obtaining the high resolution range profile（HRRP） is based on matched filters.A method of synthesizing HRRP based on the fast Fourier transform（FFT） and decoding is proposed.The mathematical expressions of HRRP are derived by assuming an elementary scenario of point-scattering targets.Based on the characteristic of OFDM multicarrier signals,it mainly analyzes the influence on HRRP exerted by several factors,such as velocity compensation errors,the sampling frequency offset,and so on.The conclusions are significant for the design of the OFDM imaging radar.Finally,the simulation results demonstrate the validity of the conclusions.

Radar high resolution range profile recognition via multi-SV method

For radar high resolution range profile (HRRP) recognition, three aspects are of great importance to improve the performance, i.e. discrimination for outlier, classification for inner and an accurate description for feature space. To tackle these issues, a novel target recognition method is designed, denoted by the multiple support vectors (multi-SV) method. With the proposed method, a special framework is constructed by a treble correlate support vector model to segment the feature space to two regions with the distribution of density, and then the description and classification hyperplane for each region are achieved. Based on the support vector framework, this method needs less memory and computation complexity to fit practical radar HRRP recognition. Finally, the experiment based on the measured data verifies the excellent performance of this method.

HIGH RESOLUTION RANGE PROFILE FORMATION BASED ON LFM SIGNAL FUSION OF MULTIPLE RADARS

This paper presents a new method of High Resolution Range (HRR) profile formation based on Linear Frequency Modulation (LFM) signal fusion of multiple radars with multiple frequency bands. The principle of the multiple radars signal fusion improving the range resolution is analyzed. With the analysis of return signals received by two radars,it is derived that the phase difference between the echoes varies almost linearly with respect to the frequency if the distance between two radars is neg-ligible compared with the radar observation distance. To compensate the phase difference,an en-tropy-minimization principle based compensation algorithm is proposed. During the fusion process,the B-splines interpolation method is applied to resample the signals for Fourier transform imaging. The theoretical analysis and simulations results show the proposed method can effectively increase signal bandwidth and provide a high resolution range profile.

Length estimation of extended targets based on bistatic high resolution range profile

The approach to estimate the length of extended targets by using the bistatic high resolution range profile（ H RRP） is analyzed in this paper. The relationship between the bistatic H RRP and the monostatic H RRP of extended targets are investigated. It is demonstrated by simulations that the target length measured by the bistatic H RRP is more meaningful and accurate than that by the monostatic HRRP,though the monostatic H RRP has been well developed and widely used in target recognizing and classification. The estimation results of a cone shaped target are present and compared at the end of the paper. To assure the reliability of the simulation,the bistatic H RRP is obtained through the scattering field data calculated by a fullwave numerical method,FE-BI-MLFMA.

Multichannel noncoherent integration detection using high range resolution profile

A multichannel noncoherent integration detection method based on high range resolution profile was presented in this paper. According to the property of the moment generating function, the distribution characteristics of the noncoherent integrated signals with or without target presence were derived under the circumstance with noncorrelated Gaussian distribution noises. The loss of noncoherent integration was due to improper selection of integration range of cell numbers. A multi channel noncoherent integration detection scheme where the integration number in each channel va ries was proposed to solve this problem. The quality of this method for detection of various targets was evaluated. A comparison of fixed integration range cell number detection and multichannel inte gration detection for a high range resolution profile was presented. Simulation results indicated that the principle of the method was correct and performed well for unknown physical dimension targets. The method required little prior knowledge about target and was convenient for practical implementa tion.

THE INFLUENCE OF SPECKLE ON HIGH RESOLUTION RANGE PROFILE RECOGNITION BASED ON THE MATCHING SCORE

Template database is the key to radar automation target recognition based on High Resolution Range Profile (HRRP). From the traditional perspective, average HRRP is a valid template for it can represent each HRRP without scatterer Moving Through Range Cell (MTRC). However, template database based on this assumption is always challenged by measured data. One reason is that speckle happens in the frame without scatterer MTRC. Speckle makes HRRP fluctuate sharply and not match well with the average HRRP. We precisely introduce the formation mechanism of speckle. Then, we make an insight into the principle of matching score. Based on the conclusion, we study the properties of matching score between speckled HRRP and the average HRRP. The theoretical analysis and Monte Carlo experimental results demonstrate that speckle makes HRRP not to match well with the average HRRP according to the energy ratio of speckled scatterers. On the assumption of ideal scattering centre model, speckled HRRP has a matching score less than 85% with the average HRRP if speckled scatterers occupy more than 50% energy of the target.

Schemes for synthesizing high-resolution range profile with extended OFDM-MIMO

Two novel schemes are proposed to synthesize high resolution range profile (HRRP) based on co-located multiple-input multiple-output (MIMO) system in the context of the joint radar and communication system. The difference between two schemes is the pattern of selecting pulses, which depends on the demand for the velocity information. The system, a type of frequency diverse array (FDA), takes full advantage of the phase-coded orthogonal frequency division multiplexing (OFDM) signal. Furthermore, the complete discrete form of the phase-coded OFDM echoes is utilized to derive the HRRP processing. The velocity estimation in the second scheme aims to eliminate velocity ambiguity, and high velocity can be retrieved exactly. Meanwhile, the imaging method is investigated with random frequency coding applied to an array. The desired performance of resolving velocity ambiguity and suppressing noise is shown by means of comparisons with previous work. The advantages in the radar imaging and the significance of the work are concluded in the end.

RESEARCH ON MOTION COMPENSATION FOR HIGH RESOLUTION PROFILE OF EXTENDED TARGET FOR STEPPED CHIRP RADAR AND DSP IMPLEMENTATION

A discrete model is set up for High Resolution Range Profile (HRRP) of an extended target and the model of echo from an extended target for a Stepped Chirp Radar (SCR) is proposed. The effect of target motion on a range profile is thoroughly analyzed, and based on which precision re- quirement is developed for motion compensation. By studying the time domain correlation and the rule based on the least burst error, a motion compensation algorithm which satisfies the project requirement is presented, and the cyber-emulation confirms the conclusion. At last the processor is designed by using DSP devices to realize motion compensation and target recognition.

A DETECTION METHOD OF HIGH RESOLUTION RADAR TARGETS BASED ON POSITION CORRELATION

This paper studies a detection method of targets of high resolution radar operating at the band of millimeter-wave(32-38GHz) under the background of the clutters, and proposes a new nonparametric detection method, which not only does less computation, but also is able to detect multiple extended targets radially distributed along distance "corridor", based on the position (range) correlation information of one-dimensional range images(or called range profiles) of high resolution radar targets. The experimental results, on the real echo data of tank illuminated by the millimeter-wave stepped frequency high resolution radar, have certified that such a method presented in this paper is a very effective detection method for multiple extended targets.

High Range Resolution Profile Automatic Target Recognition Using Sparse Representation

Sparse representation is a new signal analysis method which is receiving increasing attention in recent years. In this article, a novel scheme solving high range resolution profile automatic target recognition for ground moving targets is proposed. The sparse representation theory is applied to analyzing the components of high range resolution profiles and sparse coefficients are used to describe their features. Numerous experiments with the target type number ranging from 2 to 6 have been implemented. Results show that the proposed scheme not only provides higher recognition preciseness in real time, but also achieves more robust performance as the target type number increases.

基于语义引导层次化分类的雷达地面目标HRRP识别方法

高分辨距离像(HRRP)反映了目标空间散射结构在雷达视线方向的投影,近年来被认为是地面目标识别的重要途径。现有的HRRP识别方法采用手工特征加传统机器学习分类器,均属于平面分类方法,即采用统一标准不加区别的优选特征并单次决策最终类别。然而该方法在实际应用中面临种类繁杂、数据不平衡、HRRP姿态敏感性等诸多问题,难以获取最佳的应用效果。层次化方法采取分而治之思想,将一个复杂的细粒度识别任务拆解为多个简单的识别子任务。本文采用层次化识别的思路,提出了一种基于语义引导层次化分类的雷达地面目标识别方法。该方法以联合语义和数据构建的树形结构将一个复杂的细粒度识别任务拆解为多个简单的识别子任务,并针对每一个识别子任务匹配一套优选特征集和一个局部分类器。本方法在仿真数据和实测数据上完成了验证。实验结果表明了本文方法处理地面目标识别任务的有效性。

A Target Recognition Approach to Projecting HRR Profiles onto Subspace

Abstract: A array of the azimuthally averaged range-profile vectors and the inter-class and intra-class divergence matrixesare constructed iwth many frames of the high resolution range profiles which result from radar echoes of airplanes. Takingthe methods of whitening transformation and SVD produces a system of subspace vectors for target recognition. Where-upon, a template library for target recognition is built by the projection of a class-mean vector made from the radar dataonto the subspace for recognition. By Euclidean distance, a comparison is made between the above projection and eachtemplate in the library, to decide which class the target belongs to. Finally, simulations with the experimental radar dataarte given to show that the proposed method is robust to variation in azimuth and immune to additive Gaussian noisewhen SNR≥5dB.

空中目标动态HRRP特征可重构模拟方法

针对目前无源模拟技术无法实现目标动态电磁特征模拟的问题,提出了一种利用相位调制表面(phase-switched screen, PSS)进行空中目标动态高分辨距离像(high resolution range profile, HRRP)特征可重构的模拟方法。以无人直升机旋翼为例,对旋翼的运动状态进行了建模,并详细分析了其动态HRRP特征。另外,通过建立PSS的周期调制信号模型,详细分析了PSS对雷达入射波的调控效果。在此基础上,提出了一种调制频率时变的PSS可重构模拟方法,该方法能够生成随时间变化的可控谐波分量,模拟产生的谐波分量与无人直升机旋翼的动态HRRP特征变化规律相似。通过仿真数据对比分析,调制频率时变的PSS可重构模拟方法能够实现无人直升机旋翼的动态HRRP特征模拟效果。

基于判别性无穷模糊受限玻尔兹曼机模型的HRRP序列识别

针对雷达高分辨率距离像(High Resolution Range Profiles, HRRP)序列数据在受干扰或背景杂波严重时目标识别性能较差的问题,提出一种判别性无穷模糊受限玻尔兹曼机(Discriminative Infinite Fuzzy Re-stricted Boltzmann Machine, Dis-iFRBM)模型。该模型结合判别性受限玻尔兹曼机分类和无穷受限玻尔兹曼机模型复杂度自适应特点,汲取模糊神经网络在低信噪比环境下提取特征更稳定的优点,将模型参数从实数扩展为模糊参数,实现了对HRRP序列数据原始特征的更稳定提取以及对雷达目标的更稳健识别。通过对多个HRRP序列的识别实验,验证了Dis-iFRBM的识别稳定性以及鲁棒性,与其他模型的对比实验验证了所提模型在“噪声”环境中的有效性和优越性。

AUTOMATIC TARGET RECOGNITION OF RADAR HRRP BASED ON HIGH ORDER CENTRAL MOMENTS FEATURES

The paper addresses the problem of target recognition using High-resolution Radar Range Profiles(HRRP).A novel approach of feature extraction and dimension reduction based on extended high order central moments is proposed in order to reduce the dimension of range profiles.Features extracted from radar HRRPs are normalized and smoothed,and then comparative analysis of the similar approaches is done.The range profiles are obtained by step frequency technique using the two-dimensional backscatters distribution data of four different aircraft models.The template matching method by nearest neighbor rules,which is based on the theory of kernel methods for pattern analysis,is used to classify and identify the range profiles from four different aircrafts.Numerical simulation results show that the proposed approach can achieve good performance of stability,shift independence and higher recognition rate.It is helpful for real-time identification and the engineering implements of automatic target recognition using HRRP.The number of required templates could be reduced con-siderably while maintaining an equivalent recognition rate.

基于Attention-Inception网络集成的雷达HRRP序列目标识别方法

传统的雷达高分辨距离像(High Resolution Range Profile,HRRP)序列识别方法依赖于人工提取特征,并且在使用现有的经典深度学习方法识别小数据集时存在梯度消失和过拟合问题,导致收敛速度慢,识别率低。针对上述问题,提出了一种基于注意力机制的集成Inception网络模型,通过集成Attention-Inception单分支网络,实现了HRRP序列更深层次特征的提取;通过对模型的损失函数加入L2正则化,缓解小数据集在集成网络中的过拟合问题;利用Inception Ⅰ和Inception Ⅱ结构提取HRRP序列多尺度特征,并引入注意力机制计算特征序列的分配权重;加入残差结构,减缓了集成网络梯度消失问题。在预处理后的HRRP序列上进行实验结果表明,所提方法的目标识别率达到93.3%,并且与未去除噪声的HRRP序列相比目标识别率提高了14.67%。

基于快速密度搜索聚类算法的极化HRRP分类方法

该文针对人造目标的极化高分辨距离像,提出一种基于快速密度搜索聚类算法的分类方法。首先根据散射结构在频率和极化维度的特性,对散射中心的类型进行判别,在此基础上构造目标分类的特征矢量。然后采用快速密度搜索聚类算法,实现目标的分类。仿真实验结果表明,文中构建的特征矢量能较好地描述目标的结构属性,具有较强的可分性。而快速密度搜索聚类算法简单高效,在人造目标的分类识别中具有极大的应用潜力。

加权KNN分类器在HRRP库外目标拒判中的应用

针对雷达自动目标识别中的库外目标拒判问题,提出了一种人工生成库外样本的方法和一种加权k最邻近(knearest neighbors,KNN)分类器。通过人工生成库外高分辨距离像样本,解决了在训练阶段无法获取库外样本的难题。加权KNN分类器同时满足了基于问题和基于数据两大设计要求,能够很好地处理拒判问题。通过基于接收机工作特性(receiver operating characteristic,ROC)准则和基于损失函数准则的仿真实验,证明了加权KNN分类器具备优良的拒判性能。

一种利用强度信息的雷达HRRP自动目标识别方法

针对雷达高分辨距离像(HRRP)的幅度敏感性,现有HRRP雷达自动目标识别(RATR)方法一般简单地能量归一化.本文借鉴切空间距离的思想,提出一种利用HRRP回波强度信息提高识别精度的方法,实测数据仿真试验证明与传统方法相比,该方法可提高识别率约5个百分点.

基于H/A/α分解的全极化HRRP目标识别方法

针对现有基于H/A/α分解提取全极化高分辨率距离像(high range resolution profile,HRRP)特征的方法都没有考虑度量尺度对所提取特征性能影响的问题,提取了平均度量尺度下的特征子集,给出联合动态互信息概念用于选择最优平均度量尺度,并剔除特征子集中的冗余特征;在此基础上,结合Bagging和Boosting算法,提出一种宽带全极化雷达目标识别方法;最后在多类飞机目标HRRP样本集上验证了该方法的有效性。