Radar target novel characteristic detection method

In this paper, a method of radar target detection based on 2-dimensional (2D) fractal dimension is proposed. The proposed approach exploits both range information and azimuth information to estimate fractal dimension. Moreover, the approach can increase the number of the data points. The above two merits result in the fractal dimension estimated by this method is more accurate and robust than the previous method. The detection performance is also better than the previous one, which only makes use of 1-dimensional (1-D) information to estimate fractal dimension. Theoretical analysis and experimental result show that the proposed method performs well in strong clutter background. The proposed method is also validated by real-life radar data, and the better result has been achieved.     

Fractal interpolation of radar signatures for detecting stationarytargets in ground clutter

The fundamentals of fractal geometry are reviewed, and its application to the millimeter-wave radar detection of stationary targets in a clutter background is described. First, high-range-resolution (HRR) profiles are used to determine the fractal interpolation functions needed to create fractal signatures. The fractal dimension is then determined for these signatures. On the basis of the value of the fractal dimension, the signature is declared to represent either a target of interest or clutter. The results of a CFAR (constant false alarm rate) simulation are presented to illustrate the performance of the method. They indicate that the fractal dimension feature used seems to be independent of amplitude. Thus, the fractal dimension information combined with traditional amplitude processing techniques will improve probabilities of detection     

Robust space-time adaptive processing for airborne radar in nonhomogeneous clutter environments

Space-time adaptive processing (STAP) holds tremendous potential for the new generation airborne surveillance radar, in which the phased array antennas and pulse Doppler processing mode are adopted. A new STAP approach using the multiple-beam and multiple Doppler channels is presented here for airborne phased array radar. The approach with space-time multiple-beam (STMB) architecture is robust to array errors and has very low system degrees of freedom (DOFs). Hence, it has low sample support requirement and it is very suitable for the practical planar phased array radar under nonhomogeneous clutter environments. Meanwhile, a new nonhomogeneous detector (NHD) based on the correlation dimension (CD) is also proposed here, which is used as an effective method to screen tracing data prior to detection processing. It can further improve the performance of the STAP approach in the severely nonhomogeneous clutter environments. Therefore, a scheme that incorporates the correlation dimension nonhomogeneity detector (CD-NHD) with the STMB is recommended, which we term CD-NHD-STMB. The experimental simulation results indicate that: 1) the STMB processor is robust to array element error and has high performance under nonhomogeneous clutter environments; 2) the CD-NHD is also effective on the nonhomogeneous clutter. As a result, the CD-NHD-STMB scheme is robust to array element error and nonhomogeneous clutter, and therefore available for airborne phased array radar applications.     

基于2－D熵的机载SAR图像分割迭代算法研究

机载合成孔径雷达(SAR)图像可用于检测识别机场跑道.由于SAR图像包含大量噪声,算法抗噪性能对于SAR图像处理很重要.2-D阈值方法的分割效果比传统的一维方法要好,特别是对受噪声影响的图像.然而,2-D阈值方法耗时长,难以实用.因此,本文在现有的2-D熵迭代分割算法的基础上提出了一种基于二维直方图统计特点的最大熵阈值分割算法.通过大量试验证明,本文提出的方法不仅获得了理想的分割效果,而且进一步提高了二维阈值选取速度.     

Robust altitude estimation for over-the-horizon radar using a state-space multipath fading model

In previous work, a matched-field estimate of aircraft altitude from multiple over-the-horizon (OTH) radar dwells was presented. This approach exploits the altitude dependence of direct and surface reflected returns off the aircraft and the relative phase changes of these micro-multipath arrivals across radar dwells. Since this previous approach assumed high dwell-to-dwell predictability, it has been found to be sensitive to mismatch between modeled versus observed micro-multipath phase and amplitude changes from dwell-to-dwell. A generalized matched-field altitude estimate is presented here based on a state-space model that accounts for random ionospheric and target-motion effects that degrade the dwell-to-dwell predictability of target returns. The new formulation results in an efficient, robust recursive maximum likelihood (ML) estimation of aircraft altitude. Simulations suggest that the proposed technique can achieve accuracy within 5,000 ft of the true aircraft altitude, even with relatively high levels of uncertainty in modeling of dwell-to-dwell changes in the target return. A real data result is also presented to illustrate the technique.     

基于分形维数的地磁图适配性研究

针对地磁匹配导航对匹配区适配性研究的需求,提出一种基于分形维数分析地磁匹配区适配性的方法,从原理上分析了分形维数与适配性之间的关系,在几块选定区域的地磁图上分别对分形维数进行了计算和分析,最后在上述选定区域进行了匹配仿真试验.结果表明:匹配仿真试验中所反映的地磁图适配特性与提出的方法分析所得结果具有良好的一致性,分形维数在指示地磁图适配性上具有优良的性能.     

价电子-分形燃烧模型燃速模拟计算

在价电子燃烧模型的基础上，运用分形理论建立了一个崭新的固体推进剂价电子．分形燃烧模型。针对AP颗粒形状不规则的特点，引进分形维数，进行了燃烧模拟计算方法的有关公式推导和编程计算研究，用价电子-分形燃烧模型编制出燃速计算软件。计算结果表明，该模型比价电子模型计算结果更接近实验值，这说明新型的价电子-分形燃烧模型更合理。     

出口宽高比对S形二元收敛喷管雷达散射截面的影响

在S形二元收敛喷管进出口面积、偏心距、面积变化规律及中心线变化规律不变的条件下,采用自适应超椭圆方法设计不同出口宽高比的S形二元收敛喷管.基于迭代物理光学法与等效边缘电磁流法自主开发计算腔体部件雷达散射截面（RCS）的程序;然后通过文献中的实验数据验证了计算程序的准确性和可靠性.通过计算程序分别分析了水平、垂直两种极化方式下不同S形二元收敛喷管的边缘绕射场与总散射场的电磁散射特性.结果表明:在水平、垂直两种极化方式下,喷管出口宽高比的变化对S形二元收敛喷管边缘绕射场的RCS影响较小,不同出口宽高比的S形二元收敛喷管边缘绕射场的RCS相差不超过4dB.喷管出口宽高比的变化对总散射场的RCS影响较大;正探测角时,宽高比为1.5时,在大部分探测角范围内总散射场有较低的RCS;负探测角时,宽高比为3.5时有较低的RCS.      

Adaptive imaging for forward-looking ground penetrating radar

Most of the current forward-looking ground-penetrating radar (FLGPR) systems use conventional delay-and-sum (DAS) based methods to form radar images for detection of the target (such as a landmine). However, DAS is a data-independent approach which is known to suffer from low resolution and poor interference and clutter rejection capability. We present a data-adaptive imaging approach for FLGPR image formation based on APES (amplitude and phase estimation) and rank-deficient RCB (robust Capon beamforming). Due to the data-adaptive nature of both APES and RCB, our approach has better resolution and much better interference and clutter rejection capability than the standard DAS-based imaging methods. The excellent performance of the proposed method is demonstrated using experimental data collected via two FLGPR systems recently developed by PSI (Planning Systems, Inc.) and SRI (Stanford Research Institute).     

Tracking with classification-aided multiframe data association

In most conventional tracking systems, only the target kinematic information from, for example, a radar or sonar or an electro-optical sensor, is used in measurement-to-track association. Target class information, which is typically used in postprocessing, can also be used to improve data association to give better tracking accuracy. The use of target class information in data association can improve discrimination by yielding purer tracks and preserving their continuity. In this paper, we present the simultaneous use of target classification information and target kinematic information for target tracking. The approach presented integrates target class information into the data association process using the 2-D (one track list and one measurement list) as well as multiframe (one track list and multiple measurement lists) assignments. The multiframe association likelihood is developed to include the classification results based on the "confusion matrix" that specifies the accuracy of the target classifier. The objective is to improve association results using class information when the kinematic likelihoods are similar for different targets, i.e., there is ambiguity in using kinematic information alone. Performance comparisons with and without the use of class information in data association are presented on a ground target tracking problem. Simulation results quantify the benefits of classification-aided data association for improved target tracking, especially in the presence of association uncertainty in the kinematic measurements. Also, the benefit of 5-D (or multiframe) association versus 2-D association is investigated for different quality classifiers. The main contribution of this paper is the development of the methodology to incorporate exactly the classification information into multidimensional (multiframe) association.     

High-resolution SAR imaging with angular diversity

We propose to use the APES (amplitude and phase estimation) approach for the spectral estimation of gapped data and synthetic aperture radar (SAR) imaging with angular diversity. A relaxation-based algorithm, referred to as GAPES (Gapped-data APES), is proposed, which includes estimating the spectrum via APES and filling in the gaps via a least squares (LS) fitting. For SAR imaging with angular diversity data fusion, we perform one-dimensional (1-D) windowed fast Fourier transforms (FFTs) in range, use the GAPES algorithm to interpolate the gaps in the aperture for each range, apply 1-D inverse FFTs (IFFTs) and dewindow in range, and finally apply the two-dimensional (2-D) APES algorithm to the interpolated matrix to obtain the 2-D SAR image. Numerical results are presented to demonstrate the effectiveness of the proposed algorithm     

联合截获威胁下的雷达射频隐身目标搜索算法

针对基于射频(RF)隐身需求的机载雷达目标搜索问题进行了研究。通过分析实际作战中射频辐射面临的截获威胁,提出了一种基于联合截获威胁的射频隐身性能表征方法,并给出了具体的值估算方法;对机载雷达搜索任务中辐射参数的优化问题进行了建模,并采用优化算法对目标函数进行求解。通过分析典型情景下解集的分布特点,给出了从最优解集中选取最终解的方法。结果表明,提出的射频隐身性能表征方法能更好地反映截获实现过程的多域需求,提出的雷达搜索方法能够在保证探测性能的同时,提高射频隐身性能和搜索速度,能够为相控阵雷达搜索任务中参数的优化控制提供方法和依据。     

一种超高分辨率机载聚束SAR两维自聚焦算法

受运动参数测量误差和大气扰动等因素影响,合成孔径雷达(SAR)图像通常会发生散焦,利用自聚焦对散焦的SAR图像进行后处理是一种有效的重聚焦手段。传统的自聚焦算法都只是针对方位一维相位误差的估计和补偿。随着成像分辨率的提高,自聚焦时残留距离徙动的校正成为SAR成像面临的一个新挑战。本文推导得到了极坐标格式算法处理后残留距离徙动和方位相位误差的解析表达式,分析了两者之间的内在关系,并利用该关系,提出了一种能够同时进行残留距离徙动和方位相位误差补偿的两维自聚焦算法。实测数据处理结果表明,在残留距离徙动效应不可忽略的条件下,该方法能够极大地改善原有自聚焦算法的聚焦性能。     

Optimum detection and location estimation of target lines in the range-time space of a search radar

The average likelihood ratio detector is derived as the optimum detector for detecting a target line with unknown normal parameters in the range-time data space of a search radar, which is corrupted by Gaussian noise. The receiver operation characteristics of this optimum detector is derived to evaluate its performance improvement in comparison with the Hough detector, which uses the return signal of several successive scans to achieve a non-coherent integration improvement and get a better performance than the conventional detector. This comparison, which is done through analytic derivations and also through simulation results, shows that the average likelihood ratio detector has a better performance for different SNR values. This result is justified by showing the disadvantages of the Hough method, which are eliminated by the optimum detector. To have an estimate for the location of the detected target line in the optimum detection method as the Hough method, which detects and localizes the target lines simultaneously, we present the maximum a posteriori probability estimator. The estimation performance of the two methods is then compared and it is shown that the maximum a posteriori probability estimator localizes the detected target lines with a better performance in comparison with the Hough method.     

基于Hilbert谱脊线粗糙度的微弱目标检测算法

为检测海杂波中的微弱目标,文中采用实测数据分析了海杂波的Hilbert谱脊线及其粗糙度,研究了目标对其Hilbert谱脊线及其粗糙度的影响。研究发现,目标的出现将导致海杂波Hilbert谱脊线起伏趋予平滑,Hilbert谱脊线粗糙度减小,在此基础上,文中提出了采用Hilbert谱脊线粗糙度检测微弱目标的方法。仿真结果表...     

Multiple model particle flter track-before-detect for range ambiguous radar

The middle pulse repetition frequency（MPRF）and high pulse repetition frequency（HPRF）modes are widely adopted in airborne pulse Doppler（PD）radar systems,which results in the problem that the range measurement of targets is ambiguous.The existing data processing based range ambiguity resolving methods work well on the condition that the signal-to-noise ratio（SNR）is high enough.In this paper,a multiple model particle flter（MMPF）based track-beforedetect（TBD）method is proposed to address the problem of target detection and tracking with range ambiguous radar in low-SNR environment.By introducing a discrete variable that denotes whether a target is present or not and the discrete pulse interval number（PIN）as components of the target state vector,and modeling the incremental variable of the PIN as a three-state Markov chain,the proposed algorithm converts the problem of range ambiguity resolving into a hybrid state fltering problem.At last,the hybrid fltering problem is implemented by a MMPF-based TBD method in the Bayesian framework.Simulation results demonstrate that the proposed Bayesian approach can estimate target state as well as the PIN simultaneously,and succeeds in detecting and tracking weak targets with the range ambiguous radar.Simulation results also show that the performance of the proposed method is superior to that of the multiple hypothesis（MH）method in low-SNR environment.     

海杂波FRFT域分形特征在动目标检测中的应用

文中研究了海上动目标雷达回波与海杂波在分数阶Fourier域(FRFT域)的分形特性,利用两者幅值起伏程度的不同,提出了一种基于FRFT域分形维数差异的动目标检测方法。该方法以处处连续而不可导的非平稳不规则信号模型——分数布朗运动作为FRFT域分形模型,通过仿真分析实测海杂波数据的分形曲线,证明海杂波在FRFT域的无标度区间内具有分形特性。提取出FRFT域海杂波与动目标回波的分形维数,并利用其固有的差异进行目标检测。经不同极化方式下海杂波数据仿真,验证了算法的有效性。     

Space-time registration of radar and ESM using unscented Kalman filter

Space and time alignments are the prerequisites for the successful fusion of multiple sensors. A space-time registration model is proposed to estimate the system biases and to perform time synchronization together for mobile radar and electronic support measure (ESM) systems. A space-time registration model for radar and ESM is first developed, and an unscented Kalman filter (UKF) is proposed to estimate the space-time biases and target states simultaneously. The posterior Cramer-Rao bounds (PCRBs) are derived for the proposed UKF registration algorithm for ESM detection probability less than or equal to one. Theoretical analyses are performed to evaluate the accuracy and robustness of the proposed method. Computer simulations show that the UKF registration algorithm is indeed effective and robust for different radar and ESM tracking scenarios.     

无需辅助数据的分布式目标自适应检测器

在非高斯背景和没有辅助数据的条件下,研究了高分辨率雷达分布式目标的自适应检测问题.首先采用有序检测理论和协方差矩阵的迭代估计方法粗略估计散射点集合,进一步利用迭代估计方法获得协方差矩阵的近似最大似然估计,提出了无需辅助数据的自适应检测器(ADWSD).ADWSD在非高斯背景下具有近似恒虚警率特性,且检测性能远好于修正的...     

非均匀噪声稀疏均匀圆阵的二维DOA估计

针对在机载雷达、通信等领域有着广泛应用的均匀圆阵(UCA),研究了非均匀噪声下稀疏均匀圆阵的二维波达方向(DOA)估计.首先采用改进的相位模式方法构造非均匀噪卢稀疏均匀圆阵的波柬空间似然函数;之后,在分析非均匀噪声稀疏均匀圆阵的波束空间似然函数特点的基础上,修改了Burg的逆迭代算法以适应稀疏均匀圆阵下非均匀噪声自相关...