非均匀杂波环境下机载雷达STAP方法研究
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摘要
空时二维自适应信号(STAP)处理技术可以有效对杂波进行抑制,改善机载机载雷达的目标检测性能。经过30多年的发展,国内外对STAP技术已经逐渐从理论研究转向实际应用中。
由于机载雷达往往工作在复杂的环境中对运动目标的检测,但是由于载机平台的运动,导致杂波谱在多普勒上严重扩散,使得运动目标会被淹没在杂波中,传统的一维时域或空域滤波器均不能形成与杂波相匹配的凹口,难以达到有效抑制杂波的目的。然而杂波谱在空域和时域上是耦合的,空时二维自适应信号处理是在空域和时域上的二维联合滤波,同时具有空域和时域自由度,二维域上杂波与目标重合的概率很小,它可以在空时二维谱平面上形成凹口有效地抑制杂波,提高机载雷达系统的目标检测性能。因此空时二维自适应滤波就成为了机载雷达抑制杂波的一项关键技术。
空时二维自适应处理的基本原理已经清楚,但是在实际应用还有一系列的问题需要解决。本论文针对空时二维自适应处理技术在机载雷达中应用所遇到的问题展开研究,提出和改进了一些信号处理算法,并针对一些具体问题给出了解决方案。本论文的研究内容主要包括以下几个方面:
1.第二章系统地研究了机载雷达杂波谱结构和降维STAP方法,提出了JDF$A和JRF$A方法,表明在处理器维数一定、辅助样本数有限的条件下,降维处理可以取得较好的处理结果。
2.第三章针对前视阵中雷达杂波谱的距离依赖关系,而呈现严重的非平稳性,导致杂波协方差矩阵估计困难,提出了几种谱补偿的方法以减轻这种杂波谱对距离的依赖性。这些方法分别是空域导向矢量拟合方法、杂波子空间方法、级数展开的方法和传播算子方法,它们是利用相干信号的处理的方法对杂波谱进行有效的补偿,实验结果证明具有运算量较小优点。
3.在研究了非正侧阵中杂波谱的补偿方法的基础上,提出了基于空域导向矢量拟合的剔除强散射点的STAP方法,该方法利用非均匀检测器消除孤立干扰对采样协方差矩阵的估计的影响,以构造出与杂波相近的杂波协方差矩阵,提高机载雷达STAP的检测性能,;为了提高数据处理的速度,降低运算量,提出了基于CZT的空域导向矢量拟合方法;但这些方法都需要对数据进行FFT变换,因此提出了DBU-MWF方法,该方法可以直接对接收的数据进行处理,并降低矩阵的求逆运算量;通过衡量训练单元与待检单元数据的相似性,提出了一种相似性度量的杂波谱补偿方法。
4.重点研究了机载双基雷达杂波二维分布与双基几何构型,由于双基结构复杂多变,给出了四种经典的双基STAP结构和杂波谱,并结合第三章的方法对其中两种结构下的杂波谱进行了补偿,并且通过分析证明变换矩阵是一种无损失的变换。
Space Time Adaptive Processing(STAP)can suppress clutter effectively and improve the detection performance of airborne phased array radar. The research on STAP has been performed for more than 30 years. At present, this technique has been gradually applied to airborne phased array radar for moving targets indication (MTI) from the theory research to the practical applications at home and abroad.
It is an important task that the clutter has to be suppressed effectively for airborne phased array radar in the complicated environment. However, due to the motion of airborne platform, the ground clutter spectrums are expended in space-time domain, which leads to the target would be submerged into the clutter. So, the traditional one-dimensional filter can not form a notch that matches for the ground clutter, and it can not suppress clutter effectively. If the clutter has the characteristic of space-time-coupling, the Space Time Adaptive Processing is a two-dimensional filter in space-time domain, which has both the temporal degrees of freedom and the spatial degrees of freedom; the coincidence probability is very small between the clutters and targets, so it can suppress ground clutter perfectly and improve the performance of the moving targets indication. Therefore, STAP becomes a key technique in airborne phased array radar for clutter suppression.
Focusing on the STAP applying to airborne phased array radar and the related problems of airborne radar for reduced-rank, suppress clutter and MTI, the dissertation presents and improves some signal processing algorithms. The main contents of the dissertation are described as following.
1. Chapter 2 study the relationship between the clutter distribution of phased array airborne radar and its radar system parameters. In succession, we specifically analyzes the general principle of STAP and reduced rank (RR) STAP, the means of JDF$A and JRF$A is presented, which shows that the result will be probably near as the full rank STAP.
2. Chapter 3 specifically analyzes the clutter spectrum depends highly on range for forward-looking radar, which results in heterogeneous ground clutter and inaccurately estimation of clutter covariance matrix in space-time adaptive processing (STAP), we propose four approaches to mitigating the effect of the range dependence. These methods are spatial steering vector fitting, clutter-subspace, series expansion and propagator, which use the coherent signal method to compensate the clutter spectrum and the result shows these means reduce the computational load.
3. Chapter 4 study the clutter spectrum compensation in the squint radars. In order to mitigate the influence of isolated interference on the covariance matrix estimation, we use the non-homogeneity detector (NHD) to remove these interferences in the preprocessing data. The method starts by transforms clutter returns from element-pulse domain into element-Doppler domain by Chirp z-transform (CZT), which can improve the efficiency of spectrum samples, and has lower computational burden of spectrum analysis than that produced by DFT. Following that, the spatial steering vector fitting method is used to process the new space-time data that can eliminate the nonstationarity of the ground clutter. However, these means need FFT, so a method of DBU-MWF is presented. This method could process it in the data domain, and reduce the computation load of matrix inversion. A method for compensation of clutter spectrum base on similar measure, which the similarity for spectrum structure by a set of values defined by the inner product between the steering vector of range bin under test and of adjacent range bins.
4. Chapter 5 studies the STAP application to bistatic airborne radar. According to the clutter model, this dissertation specifically analyzes the relationship between the bistatic clutter distribution and the bistatic geometry. Under the chapter 3 studies, this chapter uses the spatial steering vector fitting means to compensate the clutter spectrum for the first two schemes.
由于机载雷达往往工作在复杂的环境中对运动目标的检测,但是由于载机平台的运动,导致杂波谱在多普勒上严重扩散,使得运动目标会被淹没在杂波中,传统的一维时域或空域滤波器均不能形成与杂波相匹配的凹口,难以达到有效抑制杂波的目的。然而杂波谱在空域和时域上是耦合的,空时二维自适应信号处理是在空域和时域上的二维联合滤波,同时具有空域和时域自由度,二维域上杂波与目标重合的概率很小,它可以在空时二维谱平面上形成凹口有效地抑制杂波,提高机载雷达系统的目标检测性能。因此空时二维自适应滤波就成为了机载雷达抑制杂波的一项关键技术。
空时二维自适应处理的基本原理已经清楚,但是在实际应用还有一系列的问题需要解决。本论文针对空时二维自适应处理技术在机载雷达中应用所遇到的问题展开研究,提出和改进了一些信号处理算法,并针对一些具体问题给出了解决方案。本论文的研究内容主要包括以下几个方面:
1.第二章系统地研究了机载雷达杂波谱结构和降维STAP方法,提出了JDF$A和JRF$A方法,表明在处理器维数一定、辅助样本数有限的条件下,降维处理可以取得较好的处理结果。
2.第三章针对前视阵中雷达杂波谱的距离依赖关系,而呈现严重的非平稳性,导致杂波协方差矩阵估计困难,提出了几种谱补偿的方法以减轻这种杂波谱对距离的依赖性。这些方法分别是空域导向矢量拟合方法、杂波子空间方法、级数展开的方法和传播算子方法,它们是利用相干信号的处理的方法对杂波谱进行有效的补偿,实验结果证明具有运算量较小优点。
3.在研究了非正侧阵中杂波谱的补偿方法的基础上,提出了基于空域导向矢量拟合的剔除强散射点的STAP方法,该方法利用非均匀检测器消除孤立干扰对采样协方差矩阵的估计的影响,以构造出与杂波相近的杂波协方差矩阵,提高机载雷达STAP的检测性能,;为了提高数据处理的速度,降低运算量,提出了基于CZT的空域导向矢量拟合方法;但这些方法都需要对数据进行FFT变换,因此提出了DBU-MWF方法,该方法可以直接对接收的数据进行处理,并降低矩阵的求逆运算量;通过衡量训练单元与待检单元数据的相似性,提出了一种相似性度量的杂波谱补偿方法。
4.重点研究了机载双基雷达杂波二维分布与双基几何构型,由于双基结构复杂多变,给出了四种经典的双基STAP结构和杂波谱,并结合第三章的方法对其中两种结构下的杂波谱进行了补偿,并且通过分析证明变换矩阵是一种无损失的变换。
Space Time Adaptive Processing(STAP)can suppress clutter effectively and improve the detection performance of airborne phased array radar. The research on STAP has been performed for more than 30 years. At present, this technique has been gradually applied to airborne phased array radar for moving targets indication (MTI) from the theory research to the practical applications at home and abroad.
It is an important task that the clutter has to be suppressed effectively for airborne phased array radar in the complicated environment. However, due to the motion of airborne platform, the ground clutter spectrums are expended in space-time domain, which leads to the target would be submerged into the clutter. So, the traditional one-dimensional filter can not form a notch that matches for the ground clutter, and it can not suppress clutter effectively. If the clutter has the characteristic of space-time-coupling, the Space Time Adaptive Processing is a two-dimensional filter in space-time domain, which has both the temporal degrees of freedom and the spatial degrees of freedom; the coincidence probability is very small between the clutters and targets, so it can suppress ground clutter perfectly and improve the performance of the moving targets indication. Therefore, STAP becomes a key technique in airborne phased array radar for clutter suppression.
Focusing on the STAP applying to airborne phased array radar and the related problems of airborne radar for reduced-rank, suppress clutter and MTI, the dissertation presents and improves some signal processing algorithms. The main contents of the dissertation are described as following.
1. Chapter 2 study the relationship between the clutter distribution of phased array airborne radar and its radar system parameters. In succession, we specifically analyzes the general principle of STAP and reduced rank (RR) STAP, the means of JDF$A and JRF$A is presented, which shows that the result will be probably near as the full rank STAP.
2. Chapter 3 specifically analyzes the clutter spectrum depends highly on range for forward-looking radar, which results in heterogeneous ground clutter and inaccurately estimation of clutter covariance matrix in space-time adaptive processing (STAP), we propose four approaches to mitigating the effect of the range dependence. These methods are spatial steering vector fitting, clutter-subspace, series expansion and propagator, which use the coherent signal method to compensate the clutter spectrum and the result shows these means reduce the computational load.
3. Chapter 4 study the clutter spectrum compensation in the squint radars. In order to mitigate the influence of isolated interference on the covariance matrix estimation, we use the non-homogeneity detector (NHD) to remove these interferences in the preprocessing data. The method starts by transforms clutter returns from element-pulse domain into element-Doppler domain by Chirp z-transform (CZT), which can improve the efficiency of spectrum samples, and has lower computational burden of spectrum analysis than that produced by DFT. Following that, the spatial steering vector fitting method is used to process the new space-time data that can eliminate the nonstationarity of the ground clutter. However, these means need FFT, so a method of DBU-MWF is presented. This method could process it in the data domain, and reduce the computation load of matrix inversion. A method for compensation of clutter spectrum base on similar measure, which the similarity for spectrum structure by a set of values defined by the inner product between the steering vector of range bin under test and of adjacent range bins.
4. Chapter 5 studies the STAP application to bistatic airborne radar. According to the clutter model, this dissertation specifically analyzes the relationship between the bistatic clutter distribution and the bistatic geometry. Under the chapter 3 studies, this chapter uses the spatial steering vector fitting means to compensate the clutter spectrum for the first two schemes.
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