双站合成孔径雷达成像算法研究
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摘要
双站合成孔径雷达(Bistatic Synthetic Aperture Radar,BISAR)是将发射机与接收机分置于两个独立平台的新体制SAR系统。由于发射机与接收机的分置,可以根据测绘需求配置运动平台的几何关系。与传统的单站系统相比,双站SAR构型灵活,具备前视成像、高频率监控、抗击毁能力强、大基线干涉等多种优势。此外,双站SAR还是单发多收的分布式SAR系统的基本构成单元,因而拥有极为广阔的应用前景。
由于收发平台的分置,导致了双站SAR在系统实现时面临着频率同步、时间同步、成像算法、天线指向、理论建模与仿真等难题。其中,成像算法是双站SAR研究工作的理论基础与核心问题。本文的主要任务是对双站SAR的成像算法进行深入的研究。
回波信号的方位平移不变性特征是现代单站SAR的频域快速成像算法成功的基础。因为将具备该特性的回波信号变换到距离-多普勒域内,同一距离门上任意点目标的能量轨迹重合,可以通过统一化处理完成该距离门上所有目标轨迹的距离徙动矫正,从而大大提高了成像处理的效率。
双站SAR的收发平台构型灵活,可以组成多种配置形式。根据收发平台的几何关系可分为以下四种构型:单运动平台式、前后追逐式、平行分置式和一般式。根据回波信号的方位向特性,又可分为方位平移不变型和方位平移可变型两种。与单站SAR不同,一般情况下由于双站平台的速度矢量不同,双站SAR的回波信号是方位平移可变的。但在前后追逐式和平行分置式构型条件下,双站SAR回波信号具备方位平移不变性特征,这类构型是本文的主要研究对象。
考虑到由于收发分置导致的回波信号的复杂性,以及双站SAR成像处理研究所面临的诸多技术难题,本文主要做了以下几点工作:
首先,提出基于多项式斜距模型的双站SAR回波信号的二维频谱变换方法与成像算法。双站SAR的回波斜距历程是两个独立的双曲线函数之和(也称平顶双曲线),传统的二维频谱变换方法并不适用于这种双站回波数据。为了克服该难题,本文提出了基于多项式斜距模型的频谱变换方法。该方法不仅保证了频谱变换的精度,而且推得的二维频谱函数与单站频谱函数形式类似,适合后续的双站成像算法推导。
其次,提出精确、高效的双站Chirp-Scaling算法。双站回波数据的频域特性,使得传统的Chirp-Scaling算法难以应用于双站成像处理。本文在精确的频谱函数的基础之上,通过改进距离徙动矫正和方位压缩实现方法,得到了适合高分辨率处理的双站Chirp-Scaling算法。
第三,提出适合大基线、宽测绘带数据的双站扩展非线性Chirp-Scaling算法。与单站回波信号相比,双站SAR回波信号的斜距特性更为复杂,尤其是在宽测绘带条件下,二维大基线的存在将导致成像算法性能急剧下降。为了克服此类因素的影响,本文提出了适合大基线、宽测绘带数据的扩展非线性Chirp-Scaling算法。
第四,提出分布式SAR分辨率自动合成算法。分布式SAR是双站SAR的一个重要应用领域。为了提高分布式SAR的图像分辨率,本文提出了基于图像质量测度函数的分布式SAR分辨率自动合成算法。
Bistatic Synthetic Aperture Radar (BISAR) is a new type of radar, where the transmitter and receiver are carried on two different platforms. Due to the separation of the transmitter and the receiver, the BISAR can configure the geometry of platforms according to the surveillance requirements. In comparison with the conventional monostatic systems, the increased flexibility of the bistatic systems brings several additional benefits like forward-looking SAR imaging, frequent monitoring, reduced vulnerability of military applications, and ability to use multilevel interferometry, etc. In addition, the BISAR is a fundamental component of the spaceborne constellation SAR systems. Therefore, the BISAR system is in possession of a wide potential of application.
Due to the separation of the transmitter and the receiver, many technical problems such as synchronization of frequency, involved adjustment of transmitter pulse versus receiver gate timing, antenna pointing, and theoretical modeling are not sufficiently solved. Besides, the imaging algorithm is another difficulty, and the purpose of this dissertation is to propose a set of precise efficient algorithms for focusing the azimuth-invariant BISAR data.
The azimuth-invariant property is significant for the modern monostatic SAR imaging algorithms that the main processing steps are carried out in the frequency domain, because all point targets with the same closest range collapse to the same migration curve in the range-Doppler domain. As a result, the efficiency of these imaging algorithms is achieved by taking advantage of block processing.
Because of the separation of the transmitter and the receiver, the BISAR configurations are much diverse. To rank the complexity of the geometry situation, the BISAR configurations could be divided into four cases: one fixed platform case, tandem case, translational invariant (TI) case, and general case. According to the azimuth property of the echo data, they can also be divided into the azimuth-invariant configuration and the azimuth-variant configuration. Unlike the monostatic system, the BISAR is in general azimuth-variant system as both the transmitter and the receiver move along different motion trajectories with unequal velocities. Nevertheless, the azimuth-invariant property is remained in both the TI and tandem cases.
Considering the increased complexities induced by the separation of the transmitter and the receiver, this dissertation summarizes the current algorithms, studies on the problems of BISAR imaging, and proposes the following novel algorithms:
First, we propose a polynomial model of the bistatic range history and approximate point target spectrum. The bistatic range history is the sum of two individual hyperbolas, which is referred to as the‘flat-top hyperbola’. This makes it impossible to obtain a precise analytic point target spectrum for the BISAR data. To overcome this difficulty, the bistatic range history is approximated by a polynomial of the azimuth time. In this way, an analytic 2-D point target spectrum is derived, and efficient monostatic imaging algorithms are easily modified to handle the BISAR data.
Second, a precise efficient bistatic Chirp-Scaling (CS) algorithm is proposed. Due to the range property of the BISAR data in the frequency domain, the conventional CS algorithm is hardly applied to process the BISAR data. Based on the analytic spectrum, a bistatic CS algorithm is proposed by two modified key operations: the range cell migration correction and azimuth compression implementation, which is able to achieve the high precision imaging with negligible approximations.
Third, an Extended Nonlinear Chirp-Scaling (ENCS) algorithm for large baseline BISAR data is proposed. In comparison with the monostatic echo data, the range property of the BISAR data is much more intricate. The 2-D large baseline will severely deteriorate the performance of imaging algorithm under a wide swath configuration. To eliminate the affect of these factors, we propose the ENCS algorithm which greatly enhances the performance of the BISAR processing, particularly under a large baseline and a wide range swath.
Finally, a sub-image auto-combination algorithm for constellation SAR system is proposed. The constellation SAR system is an important application of the BISAR technique. To enhance the image resolution of the constellation SAR system, we propose an auto-combination algorithm which is based on the image quality estimation functions.
由于收发平台的分置,导致了双站SAR在系统实现时面临着频率同步、时间同步、成像算法、天线指向、理论建模与仿真等难题。其中,成像算法是双站SAR研究工作的理论基础与核心问题。本文的主要任务是对双站SAR的成像算法进行深入的研究。
回波信号的方位平移不变性特征是现代单站SAR的频域快速成像算法成功的基础。因为将具备该特性的回波信号变换到距离-多普勒域内,同一距离门上任意点目标的能量轨迹重合,可以通过统一化处理完成该距离门上所有目标轨迹的距离徙动矫正,从而大大提高了成像处理的效率。
双站SAR的收发平台构型灵活,可以组成多种配置形式。根据收发平台的几何关系可分为以下四种构型:单运动平台式、前后追逐式、平行分置式和一般式。根据回波信号的方位向特性,又可分为方位平移不变型和方位平移可变型两种。与单站SAR不同,一般情况下由于双站平台的速度矢量不同,双站SAR的回波信号是方位平移可变的。但在前后追逐式和平行分置式构型条件下,双站SAR回波信号具备方位平移不变性特征,这类构型是本文的主要研究对象。
考虑到由于收发分置导致的回波信号的复杂性,以及双站SAR成像处理研究所面临的诸多技术难题,本文主要做了以下几点工作:
首先,提出基于多项式斜距模型的双站SAR回波信号的二维频谱变换方法与成像算法。双站SAR的回波斜距历程是两个独立的双曲线函数之和(也称平顶双曲线),传统的二维频谱变换方法并不适用于这种双站回波数据。为了克服该难题,本文提出了基于多项式斜距模型的频谱变换方法。该方法不仅保证了频谱变换的精度,而且推得的二维频谱函数与单站频谱函数形式类似,适合后续的双站成像算法推导。
其次,提出精确、高效的双站Chirp-Scaling算法。双站回波数据的频域特性,使得传统的Chirp-Scaling算法难以应用于双站成像处理。本文在精确的频谱函数的基础之上,通过改进距离徙动矫正和方位压缩实现方法,得到了适合高分辨率处理的双站Chirp-Scaling算法。
第三,提出适合大基线、宽测绘带数据的双站扩展非线性Chirp-Scaling算法。与单站回波信号相比,双站SAR回波信号的斜距特性更为复杂,尤其是在宽测绘带条件下,二维大基线的存在将导致成像算法性能急剧下降。为了克服此类因素的影响,本文提出了适合大基线、宽测绘带数据的扩展非线性Chirp-Scaling算法。
第四,提出分布式SAR分辨率自动合成算法。分布式SAR是双站SAR的一个重要应用领域。为了提高分布式SAR的图像分辨率,本文提出了基于图像质量测度函数的分布式SAR分辨率自动合成算法。
Bistatic Synthetic Aperture Radar (BISAR) is a new type of radar, where the transmitter and receiver are carried on two different platforms. Due to the separation of the transmitter and the receiver, the BISAR can configure the geometry of platforms according to the surveillance requirements. In comparison with the conventional monostatic systems, the increased flexibility of the bistatic systems brings several additional benefits like forward-looking SAR imaging, frequent monitoring, reduced vulnerability of military applications, and ability to use multilevel interferometry, etc. In addition, the BISAR is a fundamental component of the spaceborne constellation SAR systems. Therefore, the BISAR system is in possession of a wide potential of application.
Due to the separation of the transmitter and the receiver, many technical problems such as synchronization of frequency, involved adjustment of transmitter pulse versus receiver gate timing, antenna pointing, and theoretical modeling are not sufficiently solved. Besides, the imaging algorithm is another difficulty, and the purpose of this dissertation is to propose a set of precise efficient algorithms for focusing the azimuth-invariant BISAR data.
The azimuth-invariant property is significant for the modern monostatic SAR imaging algorithms that the main processing steps are carried out in the frequency domain, because all point targets with the same closest range collapse to the same migration curve in the range-Doppler domain. As a result, the efficiency of these imaging algorithms is achieved by taking advantage of block processing.
Because of the separation of the transmitter and the receiver, the BISAR configurations are much diverse. To rank the complexity of the geometry situation, the BISAR configurations could be divided into four cases: one fixed platform case, tandem case, translational invariant (TI) case, and general case. According to the azimuth property of the echo data, they can also be divided into the azimuth-invariant configuration and the azimuth-variant configuration. Unlike the monostatic system, the BISAR is in general azimuth-variant system as both the transmitter and the receiver move along different motion trajectories with unequal velocities. Nevertheless, the azimuth-invariant property is remained in both the TI and tandem cases.
Considering the increased complexities induced by the separation of the transmitter and the receiver, this dissertation summarizes the current algorithms, studies on the problems of BISAR imaging, and proposes the following novel algorithms:
First, we propose a polynomial model of the bistatic range history and approximate point target spectrum. The bistatic range history is the sum of two individual hyperbolas, which is referred to as the‘flat-top hyperbola’. This makes it impossible to obtain a precise analytic point target spectrum for the BISAR data. To overcome this difficulty, the bistatic range history is approximated by a polynomial of the azimuth time. In this way, an analytic 2-D point target spectrum is derived, and efficient monostatic imaging algorithms are easily modified to handle the BISAR data.
Second, a precise efficient bistatic Chirp-Scaling (CS) algorithm is proposed. Due to the range property of the BISAR data in the frequency domain, the conventional CS algorithm is hardly applied to process the BISAR data. Based on the analytic spectrum, a bistatic CS algorithm is proposed by two modified key operations: the range cell migration correction and azimuth compression implementation, which is able to achieve the high precision imaging with negligible approximations.
Third, an Extended Nonlinear Chirp-Scaling (ENCS) algorithm for large baseline BISAR data is proposed. In comparison with the monostatic echo data, the range property of the BISAR data is much more intricate. The 2-D large baseline will severely deteriorate the performance of imaging algorithm under a wide swath configuration. To eliminate the affect of these factors, we propose the ENCS algorithm which greatly enhances the performance of the BISAR processing, particularly under a large baseline and a wide range swath.
Finally, a sub-image auto-combination algorithm for constellation SAR system is proposed. The constellation SAR system is an important application of the BISAR technique. To enhance the image resolution of the constellation SAR system, we propose an auto-combination algorithm which is based on the image quality estimation functions.
引文
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