高频地波雷达阵列优化与校正算法研究
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摘要
高频地波雷达利用高频电波(3～30MHz)在海洋表面绕射传播衰减小的特点,采用垂直极化天线辐射电波,能超视距探测海面流场、风场和浪场参数分布,实现对海洋环境大范围、高精度和全天候的实时监测。经过40多年的发展,海流探测已达到可用于常规业务化观测的要求,但对于风、浪的探测,还处于研究和发展阶段。在高频地波雷达实际应用中,不同的布阵形式使得测向性能不一致,实际阵列复杂的背景环境使得天线阵列对来自不同方位信号的响应产生畸变,会导致多重信号分类算法(MUSIC算法)等超分辨测向算法性能严重下降,为此需要进行阵列优化与校正。
本文就雷达阵列进行了分析和优化,对阵列误差进行了分类并研究了误差校正的方法。论文主要分为以下几个方面的内容：
第一、阵列的误差分析
对阵列信号处理进行数学建模,分析了阵列误差产生的机理并且通过建模介绍了以MUSIC为代表的子空间类高分辨算法的原理,对阵列误差进行了分类,并通过仿真数据分析,直观地给出了阵列误差对雷达测向性能的影响,对DOA估计误差给出了一个直观的理解和认识。
第二、基于阵列方向图和阵列测向灵敏度的阵列优化问题
针对MUSIC算法存在模型误差时测向性能降低的问题,分析了MUSIC算法测向的误差,通过泰勒展开分析,定义了误差的灵敏度,并且详细分析了直线阵和圆形阵的阵列灵敏度特性。通过计算机仿真,对理论分析进行了验证。将测向灵敏度的分析应用到雷达的接收阵列,得到雷达阵列灵敏度的规律,应用于雷达阵列的优化。雷达阵列的优化从方向图的波束主瓣旁瓣控制和灵敏度控制两个方面进行,通过给定不同的权值,进行多目标的阵列优化,并采用了遗传优化算法达到寻优的目的。
第三、阵列的误差校正
对阵列的校正算法进行了分析,对以AIS为代表的有源校正进行了初步分析；针对阵列的无源校正问题,提出了基于海洋回波的无源校正算法,通过仿真证实了该方法的有效性,并将这个方法应用到阵列误差和互耦误差的校正。针对阵列的互耦误差校正问题,分别进行了循环迭代方法和特征分解方法的研究,并对两种方法的性能进行了比较。针对多种误差联合估计,给出了利用MUSIC子空间正交特性进行循环迭代寻优的无源校正方法,并对仿真性能进行了分析。
第四、雷达实测数据的校正分析
对雷达的实测试验数据进行了误差校正分析,分别以十一五国家863课题——多频率雷达阵列和分布式雷达阵列为例,介绍了高频地波雷达阵列校正的分析过程,提出了基于智能算法结合海洋回波的阵列误差无源校正方法。阵列幅相误差和互耦误差的校正结果表明了文中算法的有效性。
High frequency surface wave radar (HFSWR) operated in the HF band (3-30MHz), as the name suggests, employs the ground wave mode of radio wave propagation where the radar signal is guided by a good conducting surface such as the ocean surface to follow a path that essentially matches the earth's curvature. It is capable of all-weather remote sensing of large area ocean surface dynamics with relatively high precision. After more than40years' development, its capability of currents detection has been considered satisfying the requirements for routine marine observations while its wind and wave outputs have not reached the matched status.
In the application of HFSWR, DOA performance is different with the different array pattern. Besides, the complicated environment of the antenna array will distort the array directional response, and the distortion will weaken the performance of various super-resolution methods, such as Multiple Signal Classification. Therefore, it is necessary to optimize and calibrate the array.
This thesis analyzes and optimizes the radar array. The array errors were classified and the methods of error correction were studied. The thesis is divided into the following aspects:
First, Based on the analysis of array error. Mathematical model of array signal process is founded to introduce the spatial spectrum estimation algorithm (e.g. MUSIC etc.).In order to comprehend the DOA (Direction of Arrival) estimate error, the impacts to radar direction finding from different kinds of array error are also introduced by simulation.
Second, array optimization based on the array pattern and the array direction finding sensitivity. For the problem of performance degradation about direction estimation of multiple signal classification algorithm (MUSIC algorithm) considering the model error, the error of direction estimation of MUSIC algorithm is discussed. Through the Taylor expansion analysis, error sensitivity is defined, detailed analysis about the array sensitivity characteristics of the linear array and circular array are also presented. The analysis of theory is validated by the computer simulation. When the analysis of the sensitivity to direction is applied to the radar receiver array, the law of radar array sensitivity is drawn, which can be used in the optimization of radar array. The radar array is optimized based on the control of beam main disc and side-lobe and sensitivity. Given different weights, multi-objective array optimization is carried out, and the genetic optimize algorithm is used to achieve finding optimization.
Third, Calibration of Array Errors. The method of array calibration is analyzed here, and AIS, as a typical method of active calibration, is discussed; In the area of passive calibration, this paper addresses a method based on sea echo, which is proved to be efficiency by simulation and applied in calibration of array error and mutual coupling error. For the problem of mutual coupling error calibration, two methods 'loop iteration' and 'characteristic decomposition'are discussed and compared by their performance. A loop iteration optimization method based on MUSIC subspace orthogonal characteristics is used here, as a passive calibration method solving the problem of error joint estimation, which is demonstrate by simulation.
Fourth, Error Calibration Analysis for the Measured Data of HFSWR. Error calibration analysis is done for the measured data of HFSWR, taking the array of multi-frequency Radar for the11th Five-Year Plan and the array of distributed radar for the12th Five-Year Plan as examples respectively, this paper gives the analysis processing of array calibration for the HFSWR. Intelligent algorithm, combined with the passive calibration algorithm using sea echo, is proposed. The results for both the gain-phase error calibration and the mutual couplings error calibration show that the validity of algorithm of this paper.
本文就雷达阵列进行了分析和优化,对阵列误差进行了分类并研究了误差校正的方法。论文主要分为以下几个方面的内容：
第一、阵列的误差分析
对阵列信号处理进行数学建模,分析了阵列误差产生的机理并且通过建模介绍了以MUSIC为代表的子空间类高分辨算法的原理,对阵列误差进行了分类,并通过仿真数据分析,直观地给出了阵列误差对雷达测向性能的影响,对DOA估计误差给出了一个直观的理解和认识。
第二、基于阵列方向图和阵列测向灵敏度的阵列优化问题
针对MUSIC算法存在模型误差时测向性能降低的问题,分析了MUSIC算法测向的误差,通过泰勒展开分析,定义了误差的灵敏度,并且详细分析了直线阵和圆形阵的阵列灵敏度特性。通过计算机仿真,对理论分析进行了验证。将测向灵敏度的分析应用到雷达的接收阵列,得到雷达阵列灵敏度的规律,应用于雷达阵列的优化。雷达阵列的优化从方向图的波束主瓣旁瓣控制和灵敏度控制两个方面进行,通过给定不同的权值,进行多目标的阵列优化,并采用了遗传优化算法达到寻优的目的。
第三、阵列的误差校正
对阵列的校正算法进行了分析,对以AIS为代表的有源校正进行了初步分析；针对阵列的无源校正问题,提出了基于海洋回波的无源校正算法,通过仿真证实了该方法的有效性,并将这个方法应用到阵列误差和互耦误差的校正。针对阵列的互耦误差校正问题,分别进行了循环迭代方法和特征分解方法的研究,并对两种方法的性能进行了比较。针对多种误差联合估计,给出了利用MUSIC子空间正交特性进行循环迭代寻优的无源校正方法,并对仿真性能进行了分析。
第四、雷达实测数据的校正分析
对雷达的实测试验数据进行了误差校正分析,分别以十一五国家863课题——多频率雷达阵列和分布式雷达阵列为例,介绍了高频地波雷达阵列校正的分析过程,提出了基于智能算法结合海洋回波的阵列误差无源校正方法。阵列幅相误差和互耦误差的校正结果表明了文中算法的有效性。
High frequency surface wave radar (HFSWR) operated in the HF band (3-30MHz), as the name suggests, employs the ground wave mode of radio wave propagation where the radar signal is guided by a good conducting surface such as the ocean surface to follow a path that essentially matches the earth's curvature. It is capable of all-weather remote sensing of large area ocean surface dynamics with relatively high precision. After more than40years' development, its capability of currents detection has been considered satisfying the requirements for routine marine observations while its wind and wave outputs have not reached the matched status.
In the application of HFSWR, DOA performance is different with the different array pattern. Besides, the complicated environment of the antenna array will distort the array directional response, and the distortion will weaken the performance of various super-resolution methods, such as Multiple Signal Classification. Therefore, it is necessary to optimize and calibrate the array.
This thesis analyzes and optimizes the radar array. The array errors were classified and the methods of error correction were studied. The thesis is divided into the following aspects:
First, Based on the analysis of array error. Mathematical model of array signal process is founded to introduce the spatial spectrum estimation algorithm (e.g. MUSIC etc.).In order to comprehend the DOA (Direction of Arrival) estimate error, the impacts to radar direction finding from different kinds of array error are also introduced by simulation.
Second, array optimization based on the array pattern and the array direction finding sensitivity. For the problem of performance degradation about direction estimation of multiple signal classification algorithm (MUSIC algorithm) considering the model error, the error of direction estimation of MUSIC algorithm is discussed. Through the Taylor expansion analysis, error sensitivity is defined, detailed analysis about the array sensitivity characteristics of the linear array and circular array are also presented. The analysis of theory is validated by the computer simulation. When the analysis of the sensitivity to direction is applied to the radar receiver array, the law of radar array sensitivity is drawn, which can be used in the optimization of radar array. The radar array is optimized based on the control of beam main disc and side-lobe and sensitivity. Given different weights, multi-objective array optimization is carried out, and the genetic optimize algorithm is used to achieve finding optimization.
Third, Calibration of Array Errors. The method of array calibration is analyzed here, and AIS, as a typical method of active calibration, is discussed; In the area of passive calibration, this paper addresses a method based on sea echo, which is proved to be efficiency by simulation and applied in calibration of array error and mutual coupling error. For the problem of mutual coupling error calibration, two methods 'loop iteration' and 'characteristic decomposition'are discussed and compared by their performance. A loop iteration optimization method based on MUSIC subspace orthogonal characteristics is used here, as a passive calibration method solving the problem of error joint estimation, which is demonstrate by simulation.
Fourth, Error Calibration Analysis for the Measured Data of HFSWR. Error calibration analysis is done for the measured data of HFSWR, taking the array of multi-frequency Radar for the11th Five-Year Plan and the array of distributed radar for the12th Five-Year Plan as examples respectively, this paper gives the analysis processing of array calibration for the HFSWR. Intelligent algorithm, combined with the passive calibration algorithm using sea echo, is proposed. The results for both the gain-phase error calibration and the mutual couplings error calibration show that the validity of algorithm of this paper.
引文
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