稳健的杂波抑制与参数估计方法研究

发布时间：2018-11-21 21:09

【摘要】：机载预警雷达作为一种军用传感器,在现代战争中发挥着重要作用。机载雷达在探测低空目标时,处于俯视工作状态,不可避免地会接收到许多地面杂波。地面杂波强度大、范围广,运动目标往往淹没在杂波中,从而导致了机载雷达的检测性能下降。机载雷达杂波抑制技术包括超低副瓣天线、偏置相位中心天线和空时自适应处理(STAP)。空时自适应处理是一种二维的自适应滤波技术,其利用阵列天线提供的空域自由度与相参脉冲串提供的时域自由度来构造二维滤波器,具有较好的杂波抑制能力,有效地提高了机载雷达的运动目标检测性能。STAP的理论已经较为完善,但是在实际的工程应用中,依然面临着较多问题。小样本条件下的STAP方法、非均匀环境下的STAP方法、稳健的STAP方法、知识辅助的STAP方法以及复杂电磁环境下的STAP方法是目前STAP研究领域的热点问题同时也是亟需解决的问题。本文围绕以上五个方面展开研究,主要工作内容概括如下:第二章研究了对角加载参数的估计问题。对角加载可以提高空时自适应处理在小样本情况下的性能。然而,在实际中加载参数的确定是一个较为困难的问题。为了解决这个问题,提出了一种基于回波数据的自适应的对角加载参数估计方法。该方法首先将对角加载问题转化为Tikhonov规划问题,然后利用广义交叉验证准则构造优化问题,最后采用割线法求解优化问题、计算加载参数。仿真数据实验结果表明该方法可以准确的估计加载参数,提高了对角加载在实际中的应用性。第三章研究了密集目标的检测问题。机载雷达在地面运动目标检测时,主波束照射范围内的运动目标密度较大。协方差矩阵受到目标信号严重扰动,传统的非均匀检测器性能下降。为了解决这个问题,提出一种基于重加权自适应功率剩余的稳健非均匀检测器。该方法通过对训练样本集自适应重加权来降低奇异样本对协方差矩阵计算的影响。仿真与实测数据实验结果表明该方法可以有效剔除训练样本中的奇异样本,提高了传统的自适应功率剩余检测器的稳健性。第四章研究了阵元幅相误差估计问题。机载雷达的阵元幅相误差会影响运动目标的参数估计与定位性能。为了解决这个问题,提出了杂波子空间正交法与杂波Frobenius范数拟合法两种阵元幅相误差估计方法。杂波子空间正交法利用杂波补空间与最大左奇异值矢量的正交性来估计阵元幅相误差,而杂波Frobenius范数拟合法通过拟合重构的数据和实际的接收数据来估计阵元幅相误差。仿真数据实验结果表明与现有方法相比,这两种方法在低脉冲数目、低样本数目、低杂噪比的情况下均能取得良好的参数估计精度和稳健性。第五章研究了载机速度与偏航角的估计问题。速度与偏航角是知识辅助空时自适应处理中的必要参数,然而,在某些情况下,这两个参数无法获得或者精度较低。为了解决这个问题,提出了一种基于曲线拟合的参数估计方法。该方法首先利用子孔径平滑capon谱估计接收数据的功率谱,然后利用门限检测方法提取杂波对应的功率谱轨迹,最后将杂波轨迹的空时二维频率值与已知的雷达构型参数代入最小截断二乘估计器求解。仿真与实测数据实验结果表明该方法改善了传统的曲线拟合方法的精度与稳健性。第六章研究了相干转发式干扰的对抗问题。相干转发式干扰会导致雷达在接收端产生大量虚假目标,降低雷达对真实目标的检测性能。为了解决这个问题,提出了一种自适应发射技术对抗相干转发式干扰。该方法首先利用雷达预先发射的高重频脉冲串对转发式干扰进行检测和参数估计;然后在正常工作模式时利用估计得到的干扰参数优化阵列发射方向图,使其在干扰侦察方向形成零陷,从而达到降低干扰机截获雷达发射信号的概率的目的。仿真数据实验结果表明该方法可以对转发式干扰实现准确的检测和参数估计。与其它的信号处理方法相比,该方法有效减轻了接收端信号处理的负担。
[Abstract]:As a kind of military sensor, the airborne early-warning radar plays an important role in the modern war. The airborne radar is in a top-down state when the low-altitude target is detected, and many ground clutter is inevitably received. The ground clutter intensity is large, the range is wide, the moving target is often inundated in the clutter, thus the detection performance of the airborne radar is reduced. The airborne radar clutter suppression technique includes the ultra-low sidelobe antenna, the offset phase center antenna and the time-time adaptive processing (STAP). when the space-time adaptive processing is a two-dimensional adaptive filtering technology, the two-dimensional filter is constructed by utilizing the time domain freedom degree provided by the array antenna and the time domain degree of freedom provided by the phase parameter pulse train, and the moving target detection performance of the airborne radar is effectively improved. The theory of STAP is perfect, but in the practical engineering application, there are still more problems. The STAP method under the condition of the small sample, the STAP method in the non-uniform environment, the robust STAP method, the knowledge-assisted STAP method, and the STAP method under the complex electromagnetic environment are the hot issues in the current STAP research field, and the problem of the urgent need to be solved at the same time. In this paper, the research is carried out about the above five aspects, the main contents of the work are as follows: the second chapter studies the estimation of the diagonal loading parameters. The diagonal loading can improve the performance of the self-adaptive processing in the case of small samples when the space is empty. However, the determination of the loading parameters in practice is a more difficult problem. In order to solve this problem, an adaptive diagonal loading parameter estimation method based on echo data is proposed. The method comprises the following steps of: firstly, converting a diagonal loading problem into a Tikhonov planning problem, then constructing an optimization problem by using a generalized cross-verification criterion, and finally solving the optimization problem by adopting a secant method, and calculating a loading parameter. The results of the simulation data show that the method can estimate the loading parameters accurately, and the application of the diagonal loading in practice is improved. The third chapter studies the detection of dense target. When the airborne radar is in the ground motion target detection, the moving target density in the main beam irradiation range is large. the covariance matrix is severely disturbed by the target signal and the conventional non-uniform detector performance is reduced. In order to solve this problem, a robust non-uniform detector based on weight-weighted adaptive power is proposed. the method reduces the influence of the singular sample on the calculation of the covariance matrix by self-adaptive weight weighting of the training sample set. The experimental results of the simulation and the measured data show that the method can effectively eliminate the singular samples in the training samples and improve the robustness of the traditional adaptive power residual detector. In the fourth chapter, the estimation of the phase error of the matrix is studied. The phase error of the array of airborne radar will affect the parameter estimation and positioning performance of the moving target. In order to solve this problem, two phase error estimation methods of clutter sub-space orthogonal method and clutter Frobenius norm are proposed. The clutter subspace orthogonal method uses the orthogonality of the clutter compensation space and the maximum left singular value vector to estimate the matrix phase error, and the clutter Frobenius norm is to be used to estimate the matrix phase error by fitting the reconstructed data and the actual received data. The results of the simulation data show that the two methods can obtain good parameter estimation precision and robustness under the condition of low pulse number, low sample number and low noise ratio. The fifth chapter studies the estimation of the speed and the yaw angle of the carrier. The speed and yaw angle are the necessary parameters in the adaptive processing at the time of knowledge-assisted air-air, however, in some cases, these two parameters are not available or have a lower accuracy. In order to solve this problem, a parameter estimation method based on curve fitting is proposed. The method comprises the following steps of: firstly, using a sub-aperture smoothing capon spectrum estimation to receive the power spectrum of the received data, then extracting the power spectrum track corresponding to the clutter by using a threshold detection method, and finally, substituting the two-dimensional frequency value of the clutter track and the known radar configuration parameters into a minimum truncation two-by-by-by-factor estimator for solving. The experimental results of the simulation and the measured data show that the method improves the accuracy and robustness of the traditional curve fitting method. In chapter 6, the countermeasure of coherent forward interference is studied. Coherent forward interference can cause a large number of false targets to be generated by the radar at the receiving end, and the detection performance of the radar to the real object can be reduced. In order to solve this problem, a self-adaptive transmission technique is proposed to combat coherent forward interference. The method comprises the following steps of: firstly, carrying out detection and parameter estimation on the forwarding-type interference by using a high-weight-frequency pulse train which is pre-transmitted by the radar; then, optimizing the array emission direction map by utilizing the estimated interference parameters in the normal working mode, so that the radar is formed into a zero-trap in the interference detection direction, so that the purpose of reducing the probability of the interference machine to intercept the radar transmitting signal is achieved. The results of the simulation data show that the method can accurately detect and estimate the forwarding-type interference. Compared with other signal processing methods, the method effectively reduces the burden of signal processing at the receiving end.
【学位授予单位】：西安电子科技大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：TN959.73

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