An accurate SISAR imaging method of ground moving target in forward scatter radar

In order to accurately extract the profile image of the ground moving targets(GMT) in the forward scatter radar(FSR),a forward scatter signal model of GMT is built based on the Fresnel-Kirchhoff diffraction formula,the multipath propagation model and the high order phase approximation method.The classical shadow inverse synthetic aperture radar(SISAR) imaging algorithm is modified using the proposed signal model.In the modified imaging algorithm,the impacts of ground reflection,non-linear variation of target Doppler frequency and the target motion direction on imaging accuracy are discussed.Meanwhile,non-linear and time-dependent parameters are used to compensate for the motion phase of the GMT forward scatter signal,and a novel estimation method of the height difference and median line height of the target profile is put forward under the multipath interference.Finally,both the accuracy of the proposed signal model and the effectiveness of the modified imaging algorithm are validated by the simulation results.     

Ground moving target signal model and power calculation in forward scattering micro radar

Forward scattering micro radar is used for situation awareness;its operational range is relatively short because of the battery power and local horizon,the free space propagation model is not appropriate. The ground moving targets,such as humans,cars and tanks,have only comparable size with the transmitted signal wavelength;the point target model and the linear change of observation angle are not applicable. In this paper,the signal model of ground moving target is developed based on the case of forward sca...     

Detection,parameter estimation and imaging of maneuvering target in wide-band signal

The signal-to-noise ratio may be increased by the cross-range coherence integration so as to detect the moving target in low signal-to-noise ratio (SNR) condition. But, the radial velocity, acceleration and the change of acceleration due to the maneuvering motion of target may induce serious range migration and cross-range high-order phase terms leading to the unfocused cross-range image, the reduction of signal-noise ratio and the invalidation of target detection. Therefore, in order to solve these problems, this paper proposes a new method based on the adjacent correlation and scale transform methods for detection, parameters estimation and imaging of maneuvering targets in wide-band signal. This method can align the range and remove the cross-range high-order phase terms induced by the radial motion of target, enabling us to detect the target and estimate its moving parameters better. Finally, the simulated target is used to confirm that the method proposed by this paper can perfectly detect the maneuvering target in low signal-to-noise ratio condition, estimate its motion parameters and obtain an ISAR image of target. Supported by the National Natural Science Foundation of China (Grant No. 60502044), and the Program for New Century Excellent Talents in University (Grant No. NCET-06-0861)     

Clutter suppression and ground moving target imaging approach for hypersonic vehicle borne multichannel radar based on two-step focusing method

In this paper, a novel clutter suppression and ground moving target imaging approach is proposed for hypersonic vehicle (HSV) borne multichannel (MC) synthetic aperture radar (SAR) system. Compared with the traditional MC SAR ground moving target indication (GMTI) methods, the proposed algorithm can suppress clutter and decrease the moving target energy loss based on the improved MC clutter suppression method in the chirp Fourier transform (CFT) domain. Moreover, the moving target can be accurately focused by compensating the range curvature and the third order phase item. In addition, the motion parameters can be estimated precisely and the moving target can be focused accurately. Finally, the effectiveness of the proposed method is validated by the simulation examples.     

合成孔径雷达图像目标的卷积神经网识别框架

针对合成孔径雷达（SAR）图像目标识别问题,在卷积神经网的基础上,提出了一种新的识别框架。 该框架通过连接多个基本操作单元并以层次结构构造一个集特征提取和分类器训练于一体的端到端网络,同时利用深度网络的反向传播完成分类器对特征提取的反馈以改进特征的效果。 在 MSTAR开数据集上,该网络框架分类十类目标达到了98.61％ 的精度,与其他方法相比,有效提高了SAR 图像目标的识别精度。 所提框架能有效分类SAR 图像目标,具有良好的识别精度,且具备模块化结构,无须复杂预处理,实现简单。     

Radar multipath scattering from the composite model: Specular image modified model and ISAR imaging analysis

The theoretical implementation aspect of high‐frequency electromagnetic scattering prediction from the composite model is proposed in this work. First, the composite model is described and the multipath scattering prediction method (physical optics + equivalent edge currents + four‐path model) is formulated. Then, by introducing the concept of the specular image facet, a modification, named specular image modified four‐path model (SIMFPM), is developed to calculate the coupling scattering field between the electrically large three‐dimensional perfect electric conducting target and the dielectric rough surface. The proposed procedure makes preparation for the analysis of the multipath scattering effects on inverse synthetic aperture radar (ISAR) imaging in the final part. Numerical examples demonstrate the accuracy of the SIMFPM and present the multipath effects on the ISAR image.     

Visual features and Deep Maxout Network-based moving target detection using radar signals under sea clutter

Radar echoes have emerged as a rapid technology that is utilized in a wide range of applications especially in target identification under sea-clutter background. The detection of moving targets under a sea-clutter background is still a complex task because of the entering and evacuating of targets, which is highly unpredictable and unexpectable. Because of the lack of essential information, target detection and parameter estimations have become key constraints. Besides, it is very difficult to differentiate directly the small targets from the clutter background. However, the accurate location of the target cannot be determined exactly by the existing approaches. To address such limitations, an efficient strategy is proposed in this study for recognizing the moving targets under sea-clutter background using the proposed Magnetic Ant Lion Optimization algorithm, which is derived by the integration of Magnetic Optimization and Ant Lion Optimization. However, the proposed method achieves effective performance in terms of detection rate, mean-squared error, and the missed target rate with the values of 0.988, 0.012, and 0.224 for vertical–horizontal polarity.     

Compressive sensing inverse synthetic aperture radar imaging based on Gini index regularization

In compressive sensing (CS) based inverse synthetic aperture radar (ISAR) imaging approaches, the quality of final image significantly depends on the number of measurements and the noise level. In this paper, we propose an improved version of CSbased method for inverse synthetic aperture radar (ISAR) imaging. Different from the traditional l ₁ norm based CS ISAR imaging method, our method explores the use of Gini index to measure the sparsity of ISAR images to improve the imaging quality. Instead of simultaneous perturbation stochastic approximation (SPSA), we use weighted l ₁ norm as the surrogate functional and successfully develop an iteratively re-weighted algorithm to reconstruct ISAR images from compressed echo samples. Experimental results show that our approach significantly reduces the number of measurements needed for exact reconstruction and effectively suppresses the noise. Both the peak sidelobe ratio (PSLR) and the reconstruction relative error (RE) indicate that the proposed method outperforms the l ₁ norm based method.     

Ground moving target detection and location based on SAR images for distributed spaceborne SAR

In recent years, a new concept of spaceborne SAR implementation has been propos- ed[1,2], i.e., the distributed (constellation) spaceborne SAR implementation in which sev-eral formation-flying small satellites (or micro-satellites) cooperates to perform multiple missions. The coherent combination of ground echoes acquired by all small satellites can significantly improve the performance of ground moving target indication (GMTI), SAR mapping, interferometric SAR (InSAR), etc. Since the …     

ISAR imaging via sparse frequency-stepped chirp signal

Frequency-stepped chirp signal can simplify the designation of radar system.However,it has a shortcoming of Doppler ambiguity for high-speed moving targets.Therefore,it is of great significance to study how to increase its equivalent pulse repeat frequency.The back scattering field of the ISAR target has strong sparsity;that is to say,most energy is contributed merely by a few scattering centers.Hence,based on the theory of the sparse signal representation,a novel method for ISAR imaging via sparse frequency-stepped chirp signals is proposed by analyzing the signal model of the target.In the proposed method,part of sub-pulses of the frequency-stepped chirp signal is randomly selected to transmit,and then the 2D high-resolution image of the target can be constructed by sparse signal decomposition.At the cost of computational resources,the method can effectively resolve the problem of Doppler ambiguity,decrease the sidelobes and obtain a super-resolution image.Furthermore,the validity of the proposed approach is confirmed by the results of numerical simulations and real data.     

基于稀疏线性调频步进信号的ISAR成像

线性调频步进信号在简化雷达系统设计的同时,也存在对高速运动目标易出现Doppler模糊的问题,因此研究如何提高其等效的重复频率具有重要意义.由于ISAR目标的后向散射场具有较强的稀疏性,即大部分能量仅由少数散射中心贡献,所以本文基于稀疏信号表示理论,通过对目标回波模型的分析,提出了一种基于稀疏步进频率信号的逆合成孔径雷达成像方法.该方法通过随机地选择线性调频步进信号的部分子脉冲进行发射,然后使用稀疏信号分解的方法对目标图像进行重建以得到目标的二维高分辨图像.该方法以计算资源为代价,能够有效地去除方位Doppler模糊,同时还能够压低旁瓣并得到超分辨的图像.仿真和实测数据处理结果验证了本文方法的有效性.     

匀速运动目标的聚束SAR成像特征分析

运动目标的合成孔径雷达(SAR)成像特征是SAR/GMTI系统中进行运动目标检测和成像的基础.以往研究都是在两维可分离条带SAR成像算法条件下讨论目标运动对成像的影响,而很少考虑高分辨聚束SAR成像算法处理后运动目标的成像特征.本文推导了两种典型高分辨聚束SAR成像算法(RMA和PFA)处理后的动目标误差谱表达式,并在此基础上从目标几何定位误差、残留距离徙动和散焦等方面给出了完整的聚束SAR运动目标响应特征分析.最后通过仿真数据处理验证了分析结果.     

复杂环境下多无人机协作式地面移动目标跟踪

针对多无人机(UAV)协同地面移动目标跟踪问题展开研究.提出一种基于主动感知的问题求解框架,建立多UAV协同目标跟踪问题模型;在此基础上,采用分布式无色信息滤波实现目标状态融合估计与预测;然后,基于预测目标状态,结合滚动时域控制与遗传算法设计一种多UAV在线协同航迹规划算法.仿真结果表明:结合预测目标状态在线优化UAV...     

合成孔径雷达图像中的动目标速度联合估计

为估计复数合成孔径雷达图像中动目标的速度,本文基于对称散焦滤波技术设计了联合速度估计方法.对于一个动目标雷达图像,该方法首先利用一距离向速度值在距离多普勒平面将目标的距离多普勒轨迹沿距离向对齐,然后利用一方位向速度值构建的对称散焦滤波器沿方位向将该目标图像重新聚焦,得到两个新的目标图像.通过计算这两幅散焦图像的锐度差,可建立一个以距离向速度和方位向速度为变量的锐度差曲面.在曲面的峰值或谷底处即可得到目标速度的估计值.理论分析和实验结果表明了该方法的可行性和有效性.     

A feature extraction method for synthetic aperture radar(SAR) automatic target recognition based on maximum interclass distance

Synthetic aperture radar(SAR) automatic target recognition is an important application in SAR.How to extract features has restricted the application of SAR technology seriously.In this paper,a new feature extraction method for SAR automatic target recognition based on maximum interclass distance is proposed,which integrates class and neighborhood information.This method can reinforce discriminative power using maximum interclass distance,so it can improve recognition rate effectively.     

An approach for refocusing of ground fast-moving target and high-order motion parameter estimation using Radon-high-order time-chirp rate transform

Long synthetic aperture time can improve the imaging quality of a ground moving target, whereas a moving target may be severely smeared in the cross-range image due to the range migration and the Doppler frequency migration. In this paper, the effects of the third-order Doppler broadening and Doppler ambiguity of a fast-moving target are considered. To address these issues, a novel motion parameter estimation method named high-order time-chirp rate transform (HTRT) is proposed, and then a new synthetic aperture radar (SAR) imaging method based on Radon-HTRT (RHTRT) for a ground moving target is developed. The major contributions are as follows: 1) The proposed SAR imaging method can eliminate the Doppler ambiguity effect. 2) The proposed method can realize longer time coherent integration than Radon–Fourier transform (RFT) and Radon–fractional Fourier transform (RFRFT) methods. 3) The proposed method is computationally efficient since HTRT can obtain the motion parameters of a moving target via performing the 2-dimensional (2-D) fast Fourier transform (FFT). Both the simulated and real data processing results show that the proposed method can finely image a ground moving target in a high signal-to-clutter and noise ratio (SCNR) environment.     

Influence factors of sparse microwave imaging radar system performance:approaches to waveform design and platform motion analysis

Sparse microwave imaging radar is a newly developed concept of microwave imaging system,which tries to combine the traditional radar imaging system with sparse signal processing theories,achieving the aim of reducing the complexity of microwave imaging systems and enhancing the system performance.In this paper,we introduce some basic concepts of sparse signal processing theory,and then apply it to the traditional radar imaging system to get the mathematical model of sparse microwave imaging system.We analyze the factors that determine the performance of sparse microwave imaging radar,including scene,waveform and platform.According to the radar model,we analyze how these factors influence the radar system and how to optimize them.Simulation results of the sparse microwave imaging radar system are also provided.     

克希霍夫积分偏移在探地雷达中的应用及实现

详细分析和论述了克希霍夫积分偏移原理及其在探地雷达成像中的应用,针对单目标和多目标做了仿真实验.实验结果证明:将克希霍夫积分偏移原理应用在探地雷达成像中具有精度和效率较高、算法简单等优势.