运动单阵元被动合成阵列波达方向估计

 提出了一种运动单阵元被动合成阵列波达方向(DOA)估计算法。该算法基于被动合成阵列(PSA)的概念,结合空间谱估计的思想构建了运动单阵元被动合成阵列模型,通过多次不同速度合成阵列过程实现对信号DOA的无模糊估计。通过对单次匀速合成阵列过程进行分析得到,在假设信号频率已知条件下,合成阵列算法能够达到与同孔径实阵列多重信号分类（MUSIC）算法相当的DOA估计性能。仿真验证了被动合成阵列与同孔径实阵列的渐近等效性及算法的有效性。     

基于非圆对称特性的阵列扩展算法

根据入射信号的非圆对称性,提出了一种基于均匀线阵的阵列扩展算法。该方法以ESPRIT算法实现DOA估计,计算量较传统的MUSIC算法小,同时虚拟阵列有效地增加了阵列孔径,提高了算法的分辨力,并且能对更多的信号进行DOA估计。计算机仿真验证了该方法的可靠性和有效性。     

基于二维资源管理的多功能雷达任务调度算法

动态孔径分割技术为相控阵雷达针对不同任务灵活分配孔径资源提供了可能,而传统的资源调度方法仅基于单一孔径条件研究了时间资源的优化分配问题。针对雷达搜索、跟踪与成像任务的自适应调度问题,提出了一种基于时间-孔径二维资源管理的雷达资源调度算法。该算法建立了雷达孔径分割条件下的二维资源调度模型,确立了能量资源约束条件;利用基于压缩感知的稀疏孔径逆合成孔径雷达（ISAR）成像技术,使雷达在完成目标搜索和跟踪任务的同时实现对目标的成像;定义了调度算法性能的评价指标。在仿真实验中将该算法与另外2种算法进行对比,验证了所提算法在高度成功率、二维资源利用率与任务并行度这3种性能指标上具有优越性。     

基于改进TLS-ESPRIT算法的相干定位信号波达方向空间平滑

针对室内角度定位,在定位信号相干条件下无法实现准确估计波达方向(DOA)的问题,提出了一种基于TLS-ESPRIT算法的双向空间平滑方法。该算法先对定位相干信号进行双向空间平滑处理,然后用TLS-ESPRIT算法进行DOA的精确估计,使其最大限度地利用信号子空间的信息,从而解决了算法计算过程中输出信号的协方差矩阵秩亏损情况。该算法能够准确实现定位信号相干条件下DOA估计,与传统的空间平滑结合其他改进ESPRIT算法相比,具有更好的平稳性及抗干扰能力。最后通过仿真实验验证了算法的有效性和稳定性。     

基于改进ICPF的多分量LFM信号参数估计

针对线性调频信号参数估计中搜索匹配过程带来的计算量问题,提出一种基于改进ICPF的多分量线性调频信号参数估计方法。给出了一种基于非均匀快速傅立叶变换的ICPF改进算法,利用改进的ICPF算法估计线性调频信号的调频率,利用解线频调方法估计中心频率和幅度。方法避免了参数估计过程中的搜索匹配过程,计算复杂度低,在低信噪比条件下具有较好的估计性能。仿真结果验证了方法的有效性。     

稀疏孔径ISAR机动目标成像与相位补偿方法

现代逆合成孔径雷达(ISAR)可实现多模式下对多目标的交替测量工作,但波束切换使得任一目标的方位孔径具有稀疏性,同时目标的机动性也使得目标的方位维信号具有高次调制特性,这均导致以连续采样信号模型为基础的传统ISAR运动补偿和成像方法难以直接应用。本文提出一种新的稀疏孔径(SA)ISAR机动目标相位补偿和成像方法。该方法首先建立了稀疏孔径ISAR机动目标的信号模型,然后通过求解2范数最大化的优化函数,实现对相位误差的精确估计,并且通过迭代处理提高了相位误差的估计精度。相位误差补偿后,根据压缩感知理论,构造了机动目标情况下的Chirp-Fourier字典,通过对稀疏优化问题的求解,能够较精确地从稀疏孔径信号中重构出机动目标的全孔径(FA)信号。仿真和实测数据处理结果证明了本文方法的有效性。     

结合视线方向运动补偿的滑动聚束SAR子孔径成像算法

滑动聚束合成孔径雷达(SAR)是一种新兴的成像模式,既可以提高方位向分辨率又能够扩展成像范围。其数据处理时需要考虑两个关键问题:一是系统脉冲重复频率(PRF)不足,方位向信号发生混叠;二是合成孔径长度的增加使运动误差的影响更为突出,运动补偿(MOCO)精度要求提高。基于子孔径技术,提出了一种改进的高分辨率成像算法。划分子孔径克服了PRF不足的问题;子孔径数据处理采用结合视线(LOS)方向运动补偿的Omega-K算法,实现更高精度的运动补偿,提高了聚焦质量。最终的方位向分辨率达到0.1 m,具有实际工程应用价值。点目标仿真和实测数据处理验证了算法的有效性。     

基于双磁阻传感器的场面移动目标检测算法

针对无线磁阻传感器网络的场面移动目标检测系统,提出了一种基于双磁阻传感器的状态互补融合检测算法。算法综合考虑了目标地磁信号的实际特征,将双传感器获取的地磁信号进行数据融合,以避免由于航空器地磁信号的不连续特征而导致的误检为多个目标。验证结果表明,算法较于改进的自适应阈值算法,大大提高了场面移动目标的检测准确率,且算法简单,运行速度快,可以应用在无线节点的微处理器中检测场面移动目标。     

宽带信号近似最大似然方位估计快速算法

 针对短采样宽带信号近似最大似然方位估计（AML）计算量大的问题,将马尔可夫蒙特卡罗(MCMC)方法与近似最大似然方位估计相结合,提出一种基于完美抽样的近似最大似然方位估计快速算法（PAML）。该算法将AML算法的空间谱函数作为信号的概率分布函数,并利用完美抽样方法从该概率分布函数中抽样。与AML和遗传算法的对比实验研究表明,两目标情况下PAML算法在中低信噪比条件下的估计性能与AML和遗传算法性能相当,而计算量分别是二者的1/24和1/3。随着目标个数的增加,PAML算法的计算量优势将更加明显。     

BOC(2n,n)信号同步方法研究

分析了BOC信号的特性,BOC信号同步的难点在于其自相关函数的副峰会引起错误捕获和歧异跟踪。现有算法中只有单边带处理法适用于自相关函数峰值较多的信号,但算法中的滤波器实现复杂。对原算法进行改进,省去了复数滤波器,更便于软件实现。采用二维码相位估计来解决歧异跟踪的问题,但次载波的存在使载波频率跟踪范围减小,对跟踪策略进行改进,使跟踪范围满足需求。仿真结果表明,改进算法可在不损失跟踪精度的条件下,有效解决BOC信号的同步问题。     

Improved Three Subaperture Method for Elevation Angle Estimation

The three subaperture method is a technique for estimating the arrival angles of two targets located in the main beam of a radar. The problem of estimating the arrival angle of a target in the presence of multipath is considered, and it is shown how the accuracy of the three subaperture method can be improved by making use of the information that the amplitude of the direct ray is larger than that of the reflected ray.     

Precision tracking algorithms for ISAR imaging

The simultaneous imaging and tracking of a moving target is one of the most difficult problems in inverse synthetic aperture radar (ISAR) signal processing. The problem is addressed here using a two-antenna imaging radar. The target range shift is sensed with an exponentially averaged envelope correlation algorithm while the angle change is measured with a differential phase shift algorithm. The three state Kalman filters are used in range and azimuth dimensions to provide both a filtered estimate and a one-sample-ahead prediction for the purpose of target tracking. The filtered range shift provides an accurate information for range bin alignment, and the target angle change provides the angular positions of the synthetic array elements. Therefore, the ISAR imaging simply becomes processing of a circular-arc aperture. The algorithms are verified both by computer simulations and also with experimental data processing     

一种用于条带模式SAR成像的自聚焦算法

 针对现有条带模式合成孔径雷达（SAR）成像的自聚焦算法中,相位的拼接会引起误差的严重积累,本文结合相位梯度自聚焦（PGA）算法和子孔径偏移（MD）算法,提出了一种新的用于条带模式SAR成像的自聚焦算法（PGA-MD）。该算法先利用PGA算法有效估计各子孔径相位误差函数,再利用相邻子图间方位向偏移量和线性相位之间的关系,通过MD算法精确估计相邻子图间方位向偏移量,然后计算线性相位差,并基于—阶导数实现子孔径相位误差函数拼接。理论分析以及实测数据处理结果对比均表明PGA-MD算法可以有效提高对条带SAR图像的自聚焦效果。     

Imaging of a compact range using autoregressive spectral estimation[radiation patterns measurement]

The spurious scattering mechanisms of a compact range, which cause spurious signals as well as the desired plane wave to illuminate the test zone, are addressed. It is shown that an accurate estimation of the direction-of-arrival and amplitude of spurious signals in a compact range is beyond the resolution available from the Fourier transform. An estimation technique based on autoregressive (AR) modeling of field probe data is developed to locate and quantify the spurious signal sources. The probe aperture is divided into a number of overlapping subapertures so that the far-field criterion for each subaperture is satisfied. Then, the subaperture data are modeled as an AR process. Singular value decomposition and forward-backward linear prediction are used to estimate the model order and the AR parameters. Examples of probe measurements and analysis for an actual compact range are given     

基于MLR的机动平台传感器误差配准算法

 基于固定平台传感器误差极大似然配准(MLR)算法,针对机动平台存在姿态角系统误差的问题,提出了对机动平台传感器系统误差和目标状态进行批处理离线估计的机动极大似然配准(MLRM)算法.该算法利用所有传感器对目标的量测值,通过把传感器量测向目标状态进行投影、对传感器系统误差和目标状态进行期望最大化迭代以及对目标的状态进行融合估计,最终实现量测、姿态角系统误差和目标状态的有效估计.仿真结果表明,该算法迭代收敛速度快,对系统误差估计精度高,对系统误差可观测性较低的配准环境的适应性强并且对传感器姿态角的相关性不敏感,具有很强的工程实用性.     

基于3DT的空时自适应单脉冲参数估计算法

空时自适应处理(STAP)是机载预警雷达抑制杂波和干扰的一项关键技术,而多普勒三通道联合自适应处理(3DT)是适合工程实现的降维(RD)STAP方法。STAP目标检测后还需进一步估计目标的角度参数,因此将自适应单脉冲(AM)技术引入3DT,提出了一种高精度联合估计目标速度与方位空间角的空时自适应单脉冲算法。理论分析与仿真实验结果表明,当目标多普勒频率偏离检测多普勒单元中心频率时,该算法能同时减少目标多普勒跨越损失和空时导引矢量失配损失,进而提高输出信杂噪比(SCNR),改善目标测角精度。     

An improved multiple target angle tracking algorithm

An improved version of a multiple-target-angle tracking algorithm using sensor array outputs is presented. While retaining all the good features of the original algorithm, the improved version greatly reduces the error propagation due to the use of recursive approximations in updating target angle estimates. The assumption of a constant signal covariance matrix is no longer necessary. The improved performance of the proposed algorithm is demonstrated by computer simulations dealing with the tracking of two moving targets     

Estimation of Aircraft Target Motion Using Orientation Measurements

A new approach to estimating motion of a highly maneuverable aircraft target in an air-to-air tracking scenario is presented. An interactive filter system is developed that provides an improved estimate of target motion states by conditioning kinematic filter estimates on target aspect angle data. Pattern recognition techniques used with an electrooptical tracker are presumed to provide this target aspect information. A target orientation filter processes the aspect angle measurements by statistically weighting measured aspect angles with the current best estimate of target kinematics. The aerodynamic lift equation is used to relate approximate angle of attack to target velocity and acceleration. A novel statistical model for aircraft target normal acceleration is also developed to represent better the unknown target accelerations. Simulation results of realistic three-dimensional scenarios are presented to evaluate the performance of the interactive filter system.     

Radar measurement extraction in the presence of sea-surface multipath

In the presence of sea-surface multipath monopulse radar signals from a low elevation target have three alternative paths in addition to the direct (radar-to-target) path due to reflections from the sea surface. The specular reflection causes significant signal fading. The diffuse reflection causes an approximately constant bias to the in-phase component of the monopulse ratio, which is the standard extractor of the direction of arrival (DOA) in the monopulse processing. The diffuse reflection also causes higher standard deviation to the in-phase component of the monopulse ratio. We propose a maximum likelihood (ML) angle extraction technique for low elevation targets of known average signal strength having a Rayleigh fluctuation. The results show that this method reduces the error of the estimated angle compared with the conventional monopulse ratio estimator. Subsequently, the ML angle extractor is modified for the unknown average signal strength case. This modified angle extractor has only a small performance degradation compared with the known average signal strength case, but it performs much better than the monopulse ratio based estimator. An algorithm to calculate the accuracy of the estimated angle (or height) is also presented. This angle extractor reduces the root-mean-square error (RMSE) by more than 50% in the signal processing stage when used in a low flying target tracking scenario. The same algorithm can be used to track sea skimmers.