机动目标双基地ISAR越距离单元徙动校正算法

逆合成孔径雷达（Inverse syn thetic aperture radar, ISAR）使用距离多普勒算法成像时,当目标尺寸较大或转角过大 ,会发生越距离单元徙动（Migration through resolution cells, MTRC）现象,严重影 响 目标成像效果。基于双基地ISAR转台模型,针对成像的MTRC问题,对解线频调后的目标回波 进行研究,分析了机动目标MTRC的产生机理,并将匹配傅里叶变换（Match Fourier trans f orm, MFT）应用到MTRC的校正中,消除了快时间频率与慢时间的耦合项,有效解决了MTRC引 起的ISAR图像散焦问题。仿真结果表明,基于MFT的双基地ISAR MTRC校正算法能够有效校正 机动目标的距离徙动,提高ISAR成像质量。     

ISAR成像中PFA算法在MTRC中的应用

逆合成孔径雷达(ISAR)转台成像中散射点越距离单元徙动(MTRC)时有发生.在小目标远场情况下,极坐标格式算法(PFA)能够基本消除MTRC,这种算法需要在空间频域进行从极坐标分布到直角坐标分布的二维插值.文中就如何运用PFA算法解决MTRC问题进行了较深入地分析,在距离向给出滤波插值法,并提出了新的补域插值法,方位向则运用斜线投影方法,最终将扇形区域转换为矩形区域.仿真结果表明,此算法比线性距离-多普勒(R-D)算法能更有效的处理MTRC现象;在距离向插值中将滤波法与补域法做了比较,后者计算速度更快.     

ISAR imaging of maneuvering target with complex motions based on ACCF–LVD

This paper considers the inverse synthetic aperture radar (ISAR) imaging problem for a maneuvering target with complex motions, involving range migration (RM) and Doppler frequency migration (DFM) within the coherent integration period of radar imaging, which will degrade the imaging quality. A nonsearching ISAR imaging algorithm based on adjacent cross correlation function (ACCF) and Lv's distribution (LVD), i.e., ACCF–LVD, is proposed, where the ACCF is applied to correct the RM and reduce the order of DFM. Then the motion parameters are estimated via LVD and Fourier transform. With the estimated motion parameters, high quality ISAR images can be achieved. The advantage of the presented method is that it can estimate the motion parameters under low signal-to-noise ratio (SNR) without searching procedures. Finally, several simulation examples are shown to confirm the validity of the proposed algorithm.     

具有大旋翼一类旋转部件的雷达目标成像

由于目标本身或目标部件的振动和旋转运动而引入的微多普勒谱会对目标主体的ISAR像造成污染,严重时无法对目标主体进行成像。介绍了雷达目标回波信号中的微多普勒信号产生原理,提出了一种微多普勒信息分离与提取的方法,基于旋转部件的微多普勒谱与目标主体谱在谱图域表现形式的不同,将旋转部件的微多普勒谱与目标主体谱分离后获得了具有大旋转部件一类目标的清晰像,同时也获得了目标旋转部件的一些运动及结构信息。最后,仿真结果验证了此方法的有效性。     

基于ISAR成像的目标大角度RCS外推

传统逆合成孔径雷达(ISAR)转台成像算法对目标进行成像后只能外推小角度区域雷达散射截面(RCS)。针对这一问题,建立了大转角转台成像系统,提出了一种基于近场微波成像的RCS外推算法,分析了近场大转角转动带来的越距离单元徙动问题。通过将距离与方位域解耦,并对方位方向进行圆周卷积运算,得到高质量的目标成像,进而可以外推目标360度方位的RCS,并与传统ISAR小角度成像算法进行比对。仿真结果表明,外推算法不仅可以对目标进行成像,诊断目标的强散射点位置,还可以用来做远区RCS大角度外推,并结合成像结果分析目标散射机理。     

小转角下空间目标双基地ISAR二维成像算法

为了解决小转角下空间目标双基地ISAR方位向分辨率下降的问题,提出基于AR模型数据外推的双基地ISAR成像算法.双基地ISAR成像时,小转角下的方位向回波可认为服从AR模型,据此建立线性预测方程,利用Burg熵最大法中的Levions递推估计预测系数,然后对方位向回波进行外推,最后基于原始数据和外推后的数据共同进行谱估...     

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)     

A novel cognitive ISAR imaging method with random stepped frequency chirp signal

The random stepped frequency chirp signal(RSFCS)has better performance in anti-jamming than that of conventional stepped frequency chirp signal(SFCS).In combination with the theory of compressing sensing(CS),a novel ISAR imaging method is proposed based on RSFCS,in which the high resolution range profile(HRRP)is reconstructed by using the conventional OMP algorithm,whereas the cognitive approach is introduced to further reduce the number of sub-pulse in RSFCS.In the proposed method,via cognizing the characteristics of moving targets,the number of sub-pulse in each burst can be adjusted adaptively.Finally,in the cross-range direction,the accurate reconstruction of ISAR image by using CS theory is implemented,which can effectively accomplish unwrapping.With the proposed method,high quality HRRP and ISAR image can be achieved with fewer sub-pulses of RSFCS and lower burst repetition frequency(BRF).Some simulation results are given to validate the effectiveness and robustness of the proposed algorithm.     

基于Keystone变换和方位向加权的MTRC补偿算法

该文对keystone变换进行了详细的分析,发现了其在处理越距离单元走动（MTRC）问题时的局限性,提出了一种新的MTRC补偿算法,通过实测数据和仿真数据对新方法进行了实验,实验结果表明了新算法的有效性。     

Fast implementation of ground maneuvering target focusing

Ground maneuvering target detection is a hot topic in the applications of synthetic aperture radar (SAR), whereas its focusing performance is severely deteriorated by range migration and Doppler frequency migration during a long integration time. This paper proposes a novel method to image the target and estimate its parameters via performing two independent 2-dimensional (2-D) searches after a parameter separation operation. In order to improve the search speed, we set the limited search ranges and propose local mapping sparse Fourier transform (LMSFT) to replace fast Fourier transform (FFT). Compared with the traditional algorithms, the proposed method can realize fast coherent integration of multiple maneuvering targets via compensating the high-order range migration and Doppler frequency migration. In addition, the proposed method is stable under noise. Several simulation results have validated the effectiveness of the proposed method.     

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.     

超宽带步进变频连续波雷达近场成像算法

为了实现超宽带步进变频连续波雷达近场区高分辨率快速成像,提高成像的分辨率,根据步进变频连续波信号发射与传播的特点,采用角谱分析方法,通过对电磁波波动方程进行推导,提出一种适用于超宽带步进变频连续波雷达的成像算法,该算法省去了匹配滤波过程,成像准确。采用HFSS三维电磁场仿真软件进行建模仿真,在仿真结果中采集数据验证成像算法的可行性。结果表明,成像图像中目标能量集中,分辨率高,对于采用的频率范围0.5～1.5GHz,带宽为1GHz的发射信号,理论分辨率为0.15m,实际得到的分辨率约为0.2m。     

频率步进雷达多目标ISAR成像方法

针对频率步进雷达同一波束内多个运动目标在径向上重叠 而无法分辨时的ISAR成像问题,提出了一种基于调频傅里叶变换的ISAR多目标成像新方法。 在构建频率步进雷达多目标回波信号模型的基础上,采用调频傅里叶变换精确估计各个目标 的速度参数,结合 Clean方法实现对多目标回波信号的分离,完成多目标ISAR成像。仿真实 验结果进一步验证了文章所采用方法的有效性。     

Inverse synthetic aperture radar phase adjustment and cross-range scaling based on sparsity

Due to inherent sparsity of ISAR images, compressive sensing theory has been used to obtain a high resolution image. However, before applying sparse recovery methods, the phase error due to the translational motion of target is compensated by autofocusing algorithms and the target rotation rate is estimated by cross-range scaling methods. In this paper, a comprehensive matrix model for a uniformly rotating target that includes the phase error and chirp-rate of the target is derived. Then by using sparsity and minimum entropy criterion, the estimation of residual phase error and the rotation rate is refined. In order to reduce the computational load, we simplify the model and by an iterative method based on adaptive dictionary, the phase error and chirp-rate are estimated separately. Actually, by exploiting a two-dimensional (2D) optimization method and the Nelder–Mead algorithm the phase adjustment is performed and the chirp-rate is estimated by solving a 1D optimization method for dominant range cells of the target. Finally, both simulation and practical data have been used to verify the validity of the proposed approach.     

ISAR imaging of complex motion targets based on Radon transform cubic chirplet decomposition

For targets with complex motion, the echo of inverse synthetic aperture radar (ISAR) is a time-varying frequency signal in azimuth. Hence, the traditional range-Doppler (R-D) algorithm based on a constant frequency is invalid. In this letter, a novel ISAR imaging method for targets with complex motion is presented. The echo in azimuth is characterized as an amplitude-modulated (AM)-cubic phase signal, which is closer to the real ISAR scene, and Radon transform cubic chirplet decomposition (RTCCD) algorithm is proposed to process the signal. By introducing Radon transform and improved cubic chirplet function (CPF), the proposed algorithm estimates the chirp rate and the cubic chirp rate simultaneously to avoid error accumulation. Therefore, the parameter estimation precision is improved, and a high quality ISAR image can be obtained. Simulations and real data experiment validate the effectiveness of the proposed method.     

带距离徙动校正的压缩感知PFA成像方法

目的 极坐标格式算法（PFA）是合成孔径雷达（SAR）聚束模式下的一种高分辨率成像算法,方位向增加孔径长度带来了数据存储和传输的负担,利用压缩感知进行合成孔径雷达成像可以减小采样率,以前的研究往往认为图像是2维可分离的而忽略距离徙动的影响,造成了图像质量的下降。提出一种在方位向利用压缩感知处理的PFA成像算法,可以校正距离徙动,保证压缩感知成像的图像分辨率。方法 在方位向进行压缩感知处理的过程时,采用了随距离空间频率变化的傅里叶基。结果 该方法可以有效代替PFA处理过程中的方位向插值,消除距离徙动的影响,保证距离向和方位向的分辨率。结论 仿真和实测数据的处理结果证明了该方法的有效性。     

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.     

基于压缩感知的含旋转部件目标ＩＳＡＲ成像方法

在ISAR成像中,某些雷达目标的部件存在旋转运动,会对目标主体信息产生干扰导致目标成像质量下降,严重时甚至无法实现成像。本文结合压缩感知理论提出了一种含旋转部件目标成像方法。在成像时间内,由于目标主体部件相对于成像区域的位置保持不变,而旋转部件的位置在不断变化,因此,对回波信号运用压缩感知理论可得到目标主体部件的信息,从而有效剔除了旋转部件带来的影响并且大幅减少了回波数据量。最后仿真结果验证了该方法的有效性,并对其抗噪性能进行了分析。     

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.