基于空时自适应的天地波混合雷达海杂波抑制方法研究

发布时间：2019-02-22 18:50

【摘要】：高频天地波混合雷达是一种天波发射-地波接收的双基地雷达。它具有探测距离远、覆盖范围大、反隐身等能力,可以实现对我国广阔海域进行有效而经济地远程监控和海态遥感。然而,天地波混合雷达的杂波背景复杂,海杂波污染严重,不利于对目标进行检测。因此,研究展宽海杂波抑制方法对于雷达性能的提升具有重要的理论意义和实际应用价值。本文从天地波混合雷达一阶海杂波展宽的机理入手,首先分析擦地角、双基地角和电离层扰动这三个因素对一阶海杂波展宽的影响。其中,应用两种方法研究电离层对海杂波展宽的影响:第一、不同积累时间,电离层扰动对一阶海杂波的展宽影响不同;第二、应用高阶模糊函数(HAF)分析电离层扰动对一阶海杂波的影响,并依据此标准,提出了电离层扰动有无的判断准则。其次,理论上分析了一阶海杂波的空时耦合性并在此基础上首次推导了理想情况下的一阶海杂波的有效秩。基于多训练样本的降维空时自适应(Space Time Adaptive Processing,STAP)算法需要分析样本之间的相关性,本文从Doppler维、方位维和距离维分析了检测样本与训练样本之间相关性。Doppler维和方位维的分析结果,确定了降维STAP算法的局域处理自由度;距离维相关性为多样本选择提供依据(相关系数门限均设为0.7)。为下文算法研究提供了理论依据。再次,对于存在多个训练样本情况下,研究了基于多训练样本的降维STAP算法,包括局域空时联合处理算法、改进的局域空时联合处理算法和空时多波束算法。本文从海杂波被抑制前后目标SNR的变化和主要计算量两个方面比较了三种算法的性能。最后,针对当某检测样本受到电离层快相径扰动时,很难在邻近的样本中找到与检测样本具有同态性的多个样本的情况,本课题研究了基于快速近似幂迭代算法(Fast Approximation of Power Iteration,FAPI)的单样本STAP算法。不同于机载雷达,天地波混合雷达杂波环境复杂,其杂波协方差矩阵的杂波子空间维数不能确定。本文结合FAPI算法的目标函数提出了FAPI-STAP算法数据构建评价准则和基于二分法的杂波子空间维数估计方法。提出的算法不仅可以快速估计出杂波维数,而且计算速度快。同时,本文从海杂波被抑制前后的目标SNR的变化和主要计算量两个方面评价了FAPI-STAP算法的性能。
[Abstract]:The high frequency ground wave radar is a kind of bistatic radar which transmits the sky wave and receives the ground wave. It has the capability of long detection distance, large coverage and anti-stealth. It can realize effective and economical remote monitoring and remote sensing of sea state in the vast sea area of China. However, the clutter background is complex and the sea clutter pollution is serious, which is not conducive to target detection. Therefore, it is of great theoretical significance and practical application value to study the suppression method of broadening sea clutter for improving radar performance. In this paper, the mechanism of the first order sea clutter broadening of the mixed radar is discussed. Firstly, the influence of three factors, namely, the ground erasing angle, the bistatic angle and the ionospheric disturbance, on the first order sea clutter broadening is analyzed. Two methods are used to study the influence of ionosphere on the broadening of sea clutter: first, the influence of ionospheric disturbance on the broadening of first-order sea clutter is different at different accumulation time; Second, the influence of ionospheric disturbance on first-order sea clutter is analyzed by using high-order fuzzy function (HAF). According to this criterion, a criterion for judging whether ionospheric disturbance exists or not is proposed. Secondly, the space-time coupling of the first-order sea clutter is theoretically analyzed and the effective rank of the first-order sea clutter is derived for the first time in the ideal case. Space time adaptive (Space Time Adaptive Processing,STAP algorithm based on multi-training samples needs to analyze the correlation between samples. The correlation between the detection samples and the training samples is analyzed in the azimuth dimension and the range dimension. The results of the Doppler and the azimuth dimension analysis are used to determine the local processing freedom of the reduced dimension STAP algorithm. Distance correlation provides a basis for the selection of multiple samples (the threshold of correlation coefficient is set to 0.7). It provides a theoretical basis for the following algorithm research. Thirdly, the dimensionality reduction STAP algorithm based on multiple training samples is studied, including the local space-time joint processing algorithm, the improved local space-time joint processing algorithm and the space-time multi-beam algorithm. In this paper, the performance of the three algorithms is compared in terms of the changes of the target SNR before and after the sea clutter is suppressed and the main computational complexity. Finally, when a detected sample is disturbed by the ionospheric fast phase path, it is very difficult to find multiple samples with homomorphism with the detected sample in the adjacent samples. In this paper, the fast approximate power iteration algorithm (Fast Approximation of Power Iteration, is studied. FAPI) single sample STAP algorithm. Unlike airborne radar, the clutter environment of the hybrid radar is complex, and the clutter covariance matrix of the clutter can not be determined in space dimension. In this paper, based on the objective function of FAPI algorithm, an evaluation criterion for data construction of FAPI-STAP algorithm and a method for estimating the dimension of clutter subspace based on dichotomy are proposed. The proposed algorithm not only can estimate the clutter dimension quickly, but also can calculate quickly. At the same time, the performance of the FAPI-STAP algorithm is evaluated from two aspects: the change of the target SNR before and after the sea clutter is suppressed and the main computational complexity.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN958

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