非均匀杂波环境下相控阵机载雷达STAP技术研究
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摘要
机载雷达所面临的真实杂波环境往往是非均匀的,缺乏足够的与待检测样本中的干扰独立同分布(IID)的训练样本,而常规STAP方法性能最优的前提条件是有充足的与待检测样本中的干扰独立同分布(IID)的训练样本估计协方差矩阵,因此常规STAP方法在真实杂波环境中性能会受到影响。研究适应于真实杂波环境的新型STAP算法是目前STAP技术的研究热点之一。本论文着重研究的就是各种杂波非均匀情况下的相控阵机载雷达的STAP杂波抑制方法与目标检测问题,主要工作和创新点概括如下:
1、建立了双基地机载雷达杂波模型,并利用杂波模型分析了机载雷达内部因素导致的杂波非均匀现象。接着还定量分析了内部、外部因素导致的杂波非均匀现象对STAP处理器的影响。
2、对机载雷达接收数据模型进行了研究,建立并分析了适合非均匀杂波环境的机载雷达接收数据模型,最后对适合于非均匀杂波环境的机载雷达接收数据模型运用的相关问题进行了研究。适合非均匀杂波环境的机载雷达接收数据模型为后续的适合于非均匀杂波环境的STAP方法提供了基础。
3、研究了杂波非均匀检测器,针对杂波谱移动非均匀和杂波功率非均匀,提出了“频心”法杂波非均匀检测器。结合本文提出的机载雷达杂波数据模型,针对干扰目标及孤立干扰提出了基于“残差”的杂波非均匀检测器,仿真表明这种杂波非均匀检测器对干扰目标及孤立干扰有较好的杂波非均匀检测效果。
4、结合本文提出的机载雷达接收数据模型,对两种新型STAP方法(PAMF方法和STAR方法)具有较好的杂波非均匀处理性能的物理本质进行了分析,分析表明这两种方法有内在联系,本文统称为线性预测类STAP方法。线性预测类STAP方法利用了脉冲维数据的平稳性,本质上是一类降维降秩相结合的STAP方法。通常对线性预测类STAP方法的定阶采用信息论准则,计算量大,不易实现,利用线性代数定阶法给出了线性预测类STAP方法的定阶公式,降低了线性预测类STAP方法的计算量。
5、结合本文提出的机载雷达接收数据模型,提出了结构化降维STAP算法框架。结构化降维STAP方法充分利用了机载雷达接收数据特性,在极小样本数下也能计算出性能稳定的自适应权。针对结构化降维STAP方法需要实时计算空时二维自适应权,计算量大,工程实现不便的缺点,结合共轭梯度算法与基于“残差”的杂波非均匀检测器,提出了一种结构化降维STAP方法的实现算法。新算法使基于“残差”的杂波非均匀检测器与共轭梯度算法有机的结合在一起,有效的降低了计算量,使非均匀杂波环境下的结构化降维STAP算法更具工程可实现性。
6、从分析滤波器频率响应入手,提出了基于杂波参数的STAP方法,这种方法利用估计的杂波参数在杂波区形成有效的抑制凹口,与常规STAP方法相比,在清晰区能较明显的减少信号通道的损失,可使性能改善2dB左右。基于杂波参数的STAP方法利用杂波参数只对杂波形成凹口,因此自适应抑制干扰的能力较差。针对这个缺点,本文利用基于杂波参数STAP方法中的杂波抑制滤波器作为预滤波,在滤除杂波后再进行STAP处理,经预处理后,不仅杂波得到了充分的抑制,而且使后续的STAP处理有更多的自由度对抗干扰,因此与不进行预滤波的STAP方法相比有更好的潜在杂波非均匀处理能力。
7、对机载雷达实测数据进行了理论分析,并结合前面各章的研究结果,构成了一种适合非均匀杂波环境的实用化STAP处理系统。新系统经实测数据验证,不仅具有较强的杂波非均匀处理能力,而且具有较强的工程可实现性。
The real clutter enviroment of airborne radar is nonhomogeneous, while the training samples which shall be iid with detecting samples are not enough for this case. The optimum performance of regular STAP algorithms needs suffice training samples to calculate covariance matrix, so the performance will worsen seriously in real clutter enviroment. New STAP algorithms for this problem are studied widely and the dissertation here discusses the problems such as STAP clutter suppression algorithms and targets detecting of phase array airborne radar in some kinds of nonhomogeneous clutter environments. The main contributions of this dissertation can be summarized as follows:
1、Bistatic clutter model is set up to analyze some clutter nonhomogeneous problems caused by inner reasons of airborne radar, and the influence to STAP of clutter nonhomogeneous phenomena caused by outer reasons is analyzed quantitatively. 2、The received data model of airborne radar is studied, and the model of nonhomogeneous clutter environment is set up to analyze some questions when it is used. The model of nonhomogeneous clutter environment is the precondition of the following research.
3、Clutter non-homogeneity detector is studied, and a new clutter non-homogeneity detector is proposed by using frequency center idea for clutter spectrum shifting and nonhomogeneity of clutter power. Another clutter non-homogeneity detector using the residual error idea based on the proposed data model is brought to interferential targets and isolated jamming, simulation results show that the new detector performs well for interferential targets and isolated jamming.
4、The physical essences of two new STAP methods (PAMF and STAR) are analyzed based on the proposed data model. They are called as linear forecasting STAP methods because there are some inner relations between them. Linear forecasting STAP methods use the stationarity of pulse dimension data, which can be seen as a kind of reduced dimension combined with reduced rank STAP algorithm. The formula of calculating rank is shown to reduce the computational load of linear forecasting STAP methods.
5、Structured reduced dimension STAP algorithm is proposed based on the proposed data model. Structured reduced dimension STAP algorithm which uses the characteristic of received data of airborne radar can get the good adaptive weights with very few samples. Because the computational load of structured reduced dimension STAP algorithm is too great to be deal with real time, a new structured reduced dimension STAP algorithm idea is discussed by combining conjugate grads and clutter non-homogeneity detector based on the residual error to reduce the computational load.
6、Clutter parametric applied STAP method which shapes suppressing notch in clutter field by using estimated clutter parameters is proposed by analyzing frequency response of filter. Compared with the regular STAP method, this method performs worse in clutter field, but signal channel loss can be reduced in clear filed, which improves the performance about 2dB. The above method does not suppress interfere well because it only shapes notch to suppress clutter. In order to solve this problem the clutter suppressing filter in clutter parametric STAP method is used as advance filtering followed with STAP processing. After the above processing, clutter can be suppressed entirely and the following STAP processing will have more degree of freedom for interfere, so the proposed method has better nonhomogeneous processing performance.
7、The measured data of airborne radar is analyzed theoretically. Based on the former research conclusions a STAP processing system is proposed for nonhomogeneous clutter environment. The experimental results show that the new system performs well for the current studied clutter nonhomogeneous cases, and the computational load is not great for realization.
1、建立了双基地机载雷达杂波模型,并利用杂波模型分析了机载雷达内部因素导致的杂波非均匀现象。接着还定量分析了内部、外部因素导致的杂波非均匀现象对STAP处理器的影响。
2、对机载雷达接收数据模型进行了研究,建立并分析了适合非均匀杂波环境的机载雷达接收数据模型,最后对适合于非均匀杂波环境的机载雷达接收数据模型运用的相关问题进行了研究。适合非均匀杂波环境的机载雷达接收数据模型为后续的适合于非均匀杂波环境的STAP方法提供了基础。
3、研究了杂波非均匀检测器,针对杂波谱移动非均匀和杂波功率非均匀,提出了“频心”法杂波非均匀检测器。结合本文提出的机载雷达杂波数据模型,针对干扰目标及孤立干扰提出了基于“残差”的杂波非均匀检测器,仿真表明这种杂波非均匀检测器对干扰目标及孤立干扰有较好的杂波非均匀检测效果。
4、结合本文提出的机载雷达接收数据模型,对两种新型STAP方法(PAMF方法和STAR方法)具有较好的杂波非均匀处理性能的物理本质进行了分析,分析表明这两种方法有内在联系,本文统称为线性预测类STAP方法。线性预测类STAP方法利用了脉冲维数据的平稳性,本质上是一类降维降秩相结合的STAP方法。通常对线性预测类STAP方法的定阶采用信息论准则,计算量大,不易实现,利用线性代数定阶法给出了线性预测类STAP方法的定阶公式,降低了线性预测类STAP方法的计算量。
5、结合本文提出的机载雷达接收数据模型,提出了结构化降维STAP算法框架。结构化降维STAP方法充分利用了机载雷达接收数据特性,在极小样本数下也能计算出性能稳定的自适应权。针对结构化降维STAP方法需要实时计算空时二维自适应权,计算量大,工程实现不便的缺点,结合共轭梯度算法与基于“残差”的杂波非均匀检测器,提出了一种结构化降维STAP方法的实现算法。新算法使基于“残差”的杂波非均匀检测器与共轭梯度算法有机的结合在一起,有效的降低了计算量,使非均匀杂波环境下的结构化降维STAP算法更具工程可实现性。
6、从分析滤波器频率响应入手,提出了基于杂波参数的STAP方法,这种方法利用估计的杂波参数在杂波区形成有效的抑制凹口,与常规STAP方法相比,在清晰区能较明显的减少信号通道的损失,可使性能改善2dB左右。基于杂波参数的STAP方法利用杂波参数只对杂波形成凹口,因此自适应抑制干扰的能力较差。针对这个缺点,本文利用基于杂波参数STAP方法中的杂波抑制滤波器作为预滤波,在滤除杂波后再进行STAP处理,经预处理后,不仅杂波得到了充分的抑制,而且使后续的STAP处理有更多的自由度对抗干扰,因此与不进行预滤波的STAP方法相比有更好的潜在杂波非均匀处理能力。
7、对机载雷达实测数据进行了理论分析,并结合前面各章的研究结果,构成了一种适合非均匀杂波环境的实用化STAP处理系统。新系统经实测数据验证,不仅具有较强的杂波非均匀处理能力,而且具有较强的工程可实现性。
The real clutter enviroment of airborne radar is nonhomogeneous, while the training samples which shall be iid with detecting samples are not enough for this case. The optimum performance of regular STAP algorithms needs suffice training samples to calculate covariance matrix, so the performance will worsen seriously in real clutter enviroment. New STAP algorithms for this problem are studied widely and the dissertation here discusses the problems such as STAP clutter suppression algorithms and targets detecting of phase array airborne radar in some kinds of nonhomogeneous clutter environments. The main contributions of this dissertation can be summarized as follows:
1、Bistatic clutter model is set up to analyze some clutter nonhomogeneous problems caused by inner reasons of airborne radar, and the influence to STAP of clutter nonhomogeneous phenomena caused by outer reasons is analyzed quantitatively. 2、The received data model of airborne radar is studied, and the model of nonhomogeneous clutter environment is set up to analyze some questions when it is used. The model of nonhomogeneous clutter environment is the precondition of the following research.
3、Clutter non-homogeneity detector is studied, and a new clutter non-homogeneity detector is proposed by using frequency center idea for clutter spectrum shifting and nonhomogeneity of clutter power. Another clutter non-homogeneity detector using the residual error idea based on the proposed data model is brought to interferential targets and isolated jamming, simulation results show that the new detector performs well for interferential targets and isolated jamming.
4、The physical essences of two new STAP methods (PAMF and STAR) are analyzed based on the proposed data model. They are called as linear forecasting STAP methods because there are some inner relations between them. Linear forecasting STAP methods use the stationarity of pulse dimension data, which can be seen as a kind of reduced dimension combined with reduced rank STAP algorithm. The formula of calculating rank is shown to reduce the computational load of linear forecasting STAP methods.
5、Structured reduced dimension STAP algorithm is proposed based on the proposed data model. Structured reduced dimension STAP algorithm which uses the characteristic of received data of airborne radar can get the good adaptive weights with very few samples. Because the computational load of structured reduced dimension STAP algorithm is too great to be deal with real time, a new structured reduced dimension STAP algorithm idea is discussed by combining conjugate grads and clutter non-homogeneity detector based on the residual error to reduce the computational load.
6、Clutter parametric applied STAP method which shapes suppressing notch in clutter field by using estimated clutter parameters is proposed by analyzing frequency response of filter. Compared with the regular STAP method, this method performs worse in clutter field, but signal channel loss can be reduced in clear filed, which improves the performance about 2dB. The above method does not suppress interfere well because it only shapes notch to suppress clutter. In order to solve this problem the clutter suppressing filter in clutter parametric STAP method is used as advance filtering followed with STAP processing. After the above processing, clutter can be suppressed entirely and the following STAP processing will have more degree of freedom for interfere, so the proposed method has better nonhomogeneous processing performance.
7、The measured data of airborne radar is analyzed theoretically. Based on the former research conclusions a STAP processing system is proposed for nonhomogeneous clutter environment. The experimental results show that the new system performs well for the current studied clutter nonhomogeneous cases, and the computational load is not great for realization.
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