Fast method for SAR echo simulation of a three-dimensional ground scene

Due to huge calculation of SAR echo simulation of a three-dimensional (3D) ground scene, a fast simulation method is proposed. First, the data of a 3D ground scene are fractionally interpolated based on the Fractional Brownian Motion (FBM) model. Second, the data interpolated are divided into lots of small facets whose precision meets the simulation requirement, the backscattering coefficients of the small facets are calculated. Third, the shaded area is judged by the comparison method of overlook angles. Three parallel levels are analyzed and the kernel function is designed. Finally, the computing method of reduction adding and external thread are also utilized under the framework of GPU in order to get high efficiency. With the methods mentioned above, the imaging result of experimental DEM data verifies the validity and superiority of the proposed method.     

Single Radar Measurement Method for Antiaircraft Projectile Miss Distance

To measure miss distance for antiaircraft projectile,a radial velocity identification and positioning method with a single radar is proposed.By analyzing the spatial resolution of multi-frequency ranging radar,the discrimination and testing model of this radar for multi-targets (projectile and target) is established to analyze the systematic error of antiaircraft miss distance.Then through the aerial target flight test and contrast test with optical test equipment,the validity of the measurement method is verified.This new method has the potential to be used in the measurement of antiaircraft projectile miss distance.     

采用自适应字典学习的InSAR降噪方法

We consider the phase noise filtering problem for interferometric synthetic aperture radar (InSAR) based on the dictionary learning technique. Due to the non-convexity of the optimization problem is difficult to solve. By using the splitting technique and employing the augmented Lagrangian framework, we obtain a relaxed nonlinear constraint optimization problem with l₁-norm regularization which can be solved efficiently by the alternating direction method of multipliers (ADMM). Specifically, we firstly train dictionaries from the InSAR complex phase data, and then reconstruct the desired complex phase image from the sparse representation. Simulation results based on simulated and measured data show that this new InSAR phase noise reduction method has a much better performance than several classical phase filtering methods in terms of residual count, mean square error (MSE) and preservation of the fringe completeness.     

Polarimetric super-resolution algorithm for radar range imaging via spatial smoothing processing

A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional (1-D) radar imaging. The coherence between scattering centers is minimized by using spatial smoothing processing (SSP). Then the range and polarimetric scattering matrix of the scattering centers are estimated. The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios (SNR). Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.     

Multistatic passive radar imaging algorithm for the gapped aperture

Due to usually a small number of narrowband external illuminators and their uneven distribution, a single external illuminator and several receivers are used to synthetize aperture equivalently. The form of the target echo of the multistatic passive radar system is analyzed, and then the relationship of Fourier transform pair between target scattering function and the echo received by radar is deduced. Based on the prior knowledge of sparse distribution of the target, the algorithm of Compressed Sensing is used to recover the scattering coefficient of targets. Finally, the positions of receivers have been optimized by minimizing the correlation of the dictionary matrix based on minimizing the correlation coefficient of the dictionary matrix by the algorithm of Simulated Annealing (SA). Simulations show that the performance of the recovery of the image is improved significantly after optimizing.     

ISAR imaging algorithm for targets with the complex motion based on the high-order ambiguity function-Lv's distribution

In ISAR imaging for targets with the complex motion, since the azimuth high order phase terms caused by the time-varying rotation vector will deteriorate the azimuth focusing quality, the traditional RD algorithm and LFM model are not appropriate. Thereby, in the case when the received signal can be modeled as cubic phase signals (CPSs), this paper proposes an ISAR imaging algorithm based on HAF-LVD (high-order ambiguity function-Lv's distribution). First, this algorithm defines a novel double lag parametric instantaneous autocorrelation function, and then applies the scaling operator to remove the coupling and utilizes FFT to achieve the energy accumulation. Finally, the non-searching estimation of the moving parameter and the ISAR images for targets are accomplished by the obtained HAF-LVD. Because of the introduction of the scaling factor, this algorithm can flexibly deal with more changeful and hostile ISAR environment without loss of the anti-noise performance and computational efficiency. Simulation results validate the effectiveness of the ISAR imaging approach.     

基于双迭代与二阶锥规划的机载雷达稳健降维STAP方法

针对机载雷达空时自适应处理（STAP）中期望目标导向矢量的失配问题,提出一种基于双迭代与二阶锥规划的稳健降维STAP方法。该方法首先将权矢量分解为空域与时域两个低维权矢量的Kronecker积,然后分别限定实际空域、时域导向矢量与假定导向矢量之间的误差范数边界,并通过对各自最差性能进行优化,转化为相应的SOCP形式,进而利用双迭代算法实现了对两个低维权矢量的分别求解,最终合成全维STAP权矢量。该方法在保证稳健STAP性能的同时,通过双迭代降维处理,能够有效降低训练样本数需求与运算复杂度,因此更具有实际应用价值。仿真结果验证了算法的有效性。     

基于ANSYS的某型雷达稳定平台的有限元分析与优化

针对某方提出的在能实现功能的基础上,质量更轻、刚度更大的要求,设计了某型雷达稳定平台。运用Creo软件进行了雷达稳定平台的建模,简化后导入ANSYS软件中建立有限元模型。在建立有限元模型时,分别采用了不同划分网格的方法。改变了网格划分的方法,改变网格的关联中心,改变网格的关联度,改变网格细化度,进行网格质量比较,最终得到网格质量最好的有限元模型。网格畸变度从0.6达到了0.27。进一步改变平台的材料,并进行了模态分析,得到了平台前六阶固有频率。分析结果表明,改进设计使刚度基本不变,但是质量减轻了34.5kg,减轻了17.7%。稳定平台的结构设计方法、提高网格质量的方法和材料的改变方法,为同类设计与分析提供了参考。     

基于改进灰色关联算法的雷达反隐身能力评估

针对复杂电磁环境下雷达获取隐身目标特性存在不完整性、多样性等特点,提出一种基于改进灰色关联算法和距离优化评估模型的雷达反隐身能力评估方法.该方法针对一般的主观权重可靠性不足的缺点,依据指标的主观、客观和关联属性实时计算并修正了指标权值.建立了基于性能与作战效能的雷达反隐身能力评估指标体系,并结合样本序列的稳定程度和指标值的优劣程度给出了雷达反隐身能力的优化评估距离,得出客观、准确的评估结果.理论分析和仿真试验表明,与一般的灰色关联算法相比,复合权重的灰色关联算法具有更好的系统评估能力和更高的准确性.     

Micro-motion feature analysis and parameter estimation methods for moving ship

Micro-motion parameter estimation is an important way to improve ability of radar to detect the ship target. Focusing on the difficulty and speed problems existing in the current parameter estimation method of a complex moving ship, based on the analytical result of the echo's time-frequency features, a novel method to estimate the micro-motion period by calculating the backward shift cross-correlation coefficients of the echo's sparse time-frequency matrix is proposed in this paper. Firstly, the backward shift cross-correlation coefficients of the echo's sparse time-frequency matrix are calculated using the FFT (fast Fourier transform) algorithm. The peaks positions of the cross-correlation coefficients matrix are then detected. Finally, the period can be figured out quickly. Compared with the general method, the proposed method can estimate the micro-motion period accurately and quickly. A computer simulation is given to illustrate the effectiveness of the proposed method.