战场监视雷达广域GMTI模式关键信号处理方法研究
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摘要
机载远程战场监视雷达可以对地面和海面的广阔区域进行实时侦察、监视，是现代战场最重要的传感器之一。它们采用SAR-GMTI模式和广域GMTI模式获得对战场动目标的探测能力，其中广域模式可以对运动目标进行检测、定位和跟踪，在现代战场中发挥越来越重要的作用。目前许多军事强国都在大力发展机载战场监视雷达，一些高校和科研单位正在积极研究先进的广域GMTI理论和技术，努力寻求各种高效、实用的目标检测技术。
在分析国内外广域GMTI技术的研究进展基础上，本文以提高动目标检测定位性能为宗旨，对广域GMTI信号处理进行了深入研究。具体而言，本文主要包括四个方面的内容。首先，建立了广域GMTI模式的基本信号模型。在此基础上，提出了一种相控阵雷达通道误差估计算法、两种多普勒波束锐化(Doppler beamsharpening, DBS)图像拼接算法和两种运动目标定位方法，并通过实测数据处理对这些方法进行了验证。本文主要工作概括如下：
1.第二章给出了广域GMTI模式的观测模型和数学基础。本章定义了本领域的重要概念和基本符号体系，建立了机载多通道广域GMTI系统的几何模型，同时对基本信号处理流程进行描述，这些内容是后面几章的理论基础。
2.雷达的通道相位误差会影响杂波抑制效果和运动目标参数估计性能。在分析系统通道幅相误差来源的基础上，第三章提出了一种基于多波位杂波的通道相位误差估计方法。首先对不同接收通道的杂波数据进行干涉处理，然后结合扫描角来求解通道相位误差。为了减小系统噪声影响、提高估计精度，本文提出两种估计策略，一方面选取主杂波内独立同分布的距离样本单元进行估计，另一方面利用多个波位杂波求平均以进一步降低通道估计误差。机载雷达实测数据处理结果表明该方法可以较好地补偿通道相位误差，并且显著提高系统的目标定位能力。
3.在上述工作的基础上，论文研究了相控阵雷达体制和机械扫描体制下的多普勒波束锐化(DBS)波位图像拼接算法。第四章研究相控阵雷达的DBS图像拼接问题。通过将所有扫描波位获得的主瓣DBS图像进行拼接，可得到大范围的地面场景图像。然而实际中雷达平台的非理想运动（载机速度矢量和姿态的变化）会造成DBS图像拼接困难。为解决此问题，本文提出了一种有效的DBS图像拼接方法。首先利用惯导信息估计载机瞬时位置和雷达波束指向，然后将它们转化到初始时刻定义的参考坐标系下，得到图像校正参数。最后利用这些参数，完成图像拼接。实测数据的处理结果表明该方法不仅较好地补偿了载机运动误差，而且与传统方法相比可以更好地改善DBS数据的拼接性能。
4.第五章主要研究机械扫描雷达的高分辨DBS图像拼接方法。电子扫描阵列(electronically steered array, ESA)是机载雷达的主流模式，目前的多普勒波束锐化图像拼接算法主要用于ESA的数据处理。本文首先讨论传统机械扫描雷达(mechanical scanning antenna, MSA)与ESA的不同点，然后在ESA图像拼接算法基础上提出一种有效的专门针对MSA的图像拼接算法。对通过机械转动实现波束扫描的MSA而言，其相邻多个波位接收的脉冲信号具有很强相干性，将这些脉冲回波按照一定几何关系进行相干处理，便可获得高分辨率的DBS图像。该方法最突出的特点是根据MSA的几何构型进行多波位联合，保证了DBS图像获得尽可能高的分辨率，且通过多普勒域图像取大处理实现有效拼接。实测数据的处理结果表明本文方法运算量小，且图像拼接性能显著优于传统方法。
5.由于运动目标定位性能会受到通道一致性和基线误差等系统非理想因素的影响，论文深入研究了广域GMTI系统的运动目标精确定位方法。第六章提出了用误差等效基线来描述以上误差，并在此基础上提出了一种新的广域GMTI运动目标定位方法。该方法的主要步骤包括测量不同误差等效基线对应的杂波抑制锐化比，确定最优误差等效基线及运动目标定位。本方法的关键步骤是通过令杂波抑制比最大化来估计最优误差等效基线，这确保了估计的最优误差等效基线与数据真实误差特性相吻合。因而，其定位性能明显优于采用名义基线的定位结果。实测数据处理结果验证了本文方法的性能。
6.第七章研究了一种双通道广域GMTI系统中的运动目标间接定位方法。由于广域GMTI系统中存在通道失配、沿航向基线误差、垂直基线等，要实现目标精确定位非常困难。为解决此问题，本文提出了一种目标定位新方法。该方法的核心思想是基于这样一个简单的事实，即运动目标与其邻近杂波（在观测场景中，与目标处于相同的距离单元和方位单元）拥有相同的干涉相位。这个新的间接定位办法，不依赖于传统的目标定位公式，因而可以免受大多数干涉相位误差的影响。实测数据处理结果表明本文算法可以获得较高的目标定位精度。
The airborne long-range battlefield surveillance radar system can provide real timereconnaissance and surveillance over a vast area on the ground or the sea, and hence isone of the most important sensors that are used for modern military applications. Theradar’s two working modes, i.e., synthetic aperture radar (SAR) ground moving targetindication (GMTI) mode or wide-area surveillance (WAS) GMTI mode, offer thedetection of moving targets in the battlefield. The WAS-GMTI mode, especially turnsout to be a particularly effective way to detect, locate and track moving targets, and thusis becoming more and more important in modern warfare. Recently, most militarypowers in the world have been engaging in developing airborne battlefield surveillanceradar systems, and a great number of universities and research institutes are developingpractical GMTI techniques and exploring novel moving target detection and locationalgorithms with high efficiency.
Based on the airborne WAS-GMTI research development of home and abroad, thisdissertation aims to improve moving target detection and location, and additionally togive in-depth discussion on WAS-GMTI signal processing method. More specifically,there were four key areas that we wished to address. First, this dissertation containssome basic materials on signal model of WAS-GMTI mode. Then, more importantly,this dissertation consists of a channel phase error estimation method, two imagestitching algorithms for ESA mode and MSA mode, and two moving target relocationalgorithms, all verified through real data processing. The main content of thisdissertation is summarized as follows.
1. Chapter2provides the reader with the observation models and mathematicalpreliminaries required to understand the WAS-GMTI mode. The purposes of Chapter2are to define important concepts and notations in WAS-GMTI, to describe WAS-GMTIdata acquisition geometry, and to represent more specially signal processing techniqueswhich form the basis for the proposed algorithms carried out in the subsequent chapters.
2. The channel phase error presented in radar will affect clutter suppression anddecline the parameter estimation accuracy as well. To deal with this problem, anestimation method of channel phase error is proposed in Chapter3for the phased arrayantenna. First the clutter of different channels is processed using the interferometrictechnique, after which the channel errors are estimated with the known scan angles. Toreduce the influence of noise and enhance the estimation accuracy, two strategies areintroduced for phase error estimation. On one hand, the independent and identically distributed (i. i. d.) range cells are proposed to be chosen as estimation samples. On theother hand, clutter of multiple wave positions is employed to further average theestimation error. Processing results with measured data validate that the proposedmethod can compensate the channel phase error very well and enhance the ability ofmoving target relocation significantly.
3. Based on the discussion about observation models and mathematicalpreliminaries, this dissertation contains descriptions and analyses of the image stitchingalgorithms of Doppler beam sharpening (DBS) image for ESA system and MSA system,respectively. Chapter4is concerned with image stitching in ESA. By stitching Dopplerbeam sharpening (DBS) images together the main-lobe DBS images obtained from allthe beam positions, a wide swath ground image is obtained. In practice, however, thereare some difficulties in stitching the DBS images due to the nonideal movement(variation of the velocity vector and the attitude) of the radar platform. To deal withthese problems, a novel method is proposed, which can stitch the DBS imageseffectively. The inertial navigation system (INS) information is employed to estimatethe instantaneous position of the aircraft and the radar beam direction, both of which arethen transformed to the original reference coordinate so that the corrected parameters ofthe image can be obtained. Finally, by using these parameters, the image stitching isachieved. Processing results of measured data show that the proposed method not onlycompensates the motion error excellently, but also significantly outperforms thetraditional algorithm in stitching performance.
4. Chapter5deals primarily with high resolution image stitching algorithm forDBS images in MSA system. The current image stitching algorithms are primarilysuited to process electronically steered array (ESA) data. However, these algorithmswill give rise to degradation of the performance for mechanical scanning antenna(MSA). In this paper, we develop an effective mulitsubbeam combination algorithm thatapplies to the MSA. For MSA whose beam is steered with physical antenna motion, thesuccessive pulses of adjacent subbeams are temporally correlated, and thus can becoherently integrated to generate a DBS image. The most prominent contributions of theproposed method are mulitsubbeam combination according to MSA geometry, whichguarantees that a high resolution DBS image can be obtained, and good data selection inthe way of Doppler spectrum combination. Results from real data show that theproposed method is computationally quite efficient for high-resolution imaging andsignificantly outperforms the traditional algorithm.
5. The system factors that affect the performance of moving targets relocation can be examined through channel imbalance and antenna array misalignment etc. Thisdissertation derivates and developes two algorithms by which a moving target can beaccurately relocated in the SCAN-GMTI system. In Chapter6, we introduce a conceptcalled error equivalent baseline (EEB) to describe the influence of these factors anddevelop a novel method of moving targets location for the scan-ground moving targetindication (SCAN-GMTI) system. The proposed method involves measuring the cluttersuppression sharpness ratio (CSSR) corresponding to the potential EEBs, determiningthe optimal EEB, and locating the moving targets. The key procedure of estimating theoptimal EEB that maximizes the CSSR virtually provides a good fit for the errorcharacteristic of the measured data. Therefore, the location performance of the obtainedoptimal EEB is superior to that of the nominal baseline. Processing results of measureddata validate the effectiveness of the proposed method.
6. Chapter7deals with the issue of moving target relocation for wide-area groundmoving target indication (GMTI) using dual-channel radar systems. Due to channelmismatch, along-track baseline error, the existence of across-track baseline, and etc, it isdifficult to accurately relocate the detected targets. In this letter, we propose a newknowledge-based (KB) method for target relocation. The key idea of the proposedmethod is to use such a fact that a moving target and its neighboring clutter which issituated at the same azimuth angular position and the same range cell as this target inthe observed scene, have the same interferometric phase. This new KB method, as anindirect one, does not employ the conventional relocation formula, and therefore is notinfluenced by most of (if not all) interferometric-phase errors. Experimental results forreal radar data demonstrate a fairly high degree of target-relocation accuracy.
在分析国内外广域GMTI技术的研究进展基础上，本文以提高动目标检测定位性能为宗旨，对广域GMTI信号处理进行了深入研究。具体而言，本文主要包括四个方面的内容。首先，建立了广域GMTI模式的基本信号模型。在此基础上，提出了一种相控阵雷达通道误差估计算法、两种多普勒波束锐化(Doppler beamsharpening, DBS)图像拼接算法和两种运动目标定位方法，并通过实测数据处理对这些方法进行了验证。本文主要工作概括如下：
1.第二章给出了广域GMTI模式的观测模型和数学基础。本章定义了本领域的重要概念和基本符号体系，建立了机载多通道广域GMTI系统的几何模型，同时对基本信号处理流程进行描述，这些内容是后面几章的理论基础。
2.雷达的通道相位误差会影响杂波抑制效果和运动目标参数估计性能。在分析系统通道幅相误差来源的基础上，第三章提出了一种基于多波位杂波的通道相位误差估计方法。首先对不同接收通道的杂波数据进行干涉处理，然后结合扫描角来求解通道相位误差。为了减小系统噪声影响、提高估计精度，本文提出两种估计策略，一方面选取主杂波内独立同分布的距离样本单元进行估计，另一方面利用多个波位杂波求平均以进一步降低通道估计误差。机载雷达实测数据处理结果表明该方法可以较好地补偿通道相位误差，并且显著提高系统的目标定位能力。
3.在上述工作的基础上，论文研究了相控阵雷达体制和机械扫描体制下的多普勒波束锐化(DBS)波位图像拼接算法。第四章研究相控阵雷达的DBS图像拼接问题。通过将所有扫描波位获得的主瓣DBS图像进行拼接，可得到大范围的地面场景图像。然而实际中雷达平台的非理想运动（载机速度矢量和姿态的变化）会造成DBS图像拼接困难。为解决此问题，本文提出了一种有效的DBS图像拼接方法。首先利用惯导信息估计载机瞬时位置和雷达波束指向，然后将它们转化到初始时刻定义的参考坐标系下，得到图像校正参数。最后利用这些参数，完成图像拼接。实测数据的处理结果表明该方法不仅较好地补偿了载机运动误差，而且与传统方法相比可以更好地改善DBS数据的拼接性能。
4.第五章主要研究机械扫描雷达的高分辨DBS图像拼接方法。电子扫描阵列(electronically steered array, ESA)是机载雷达的主流模式，目前的多普勒波束锐化图像拼接算法主要用于ESA的数据处理。本文首先讨论传统机械扫描雷达(mechanical scanning antenna, MSA)与ESA的不同点，然后在ESA图像拼接算法基础上提出一种有效的专门针对MSA的图像拼接算法。对通过机械转动实现波束扫描的MSA而言，其相邻多个波位接收的脉冲信号具有很强相干性，将这些脉冲回波按照一定几何关系进行相干处理，便可获得高分辨率的DBS图像。该方法最突出的特点是根据MSA的几何构型进行多波位联合，保证了DBS图像获得尽可能高的分辨率，且通过多普勒域图像取大处理实现有效拼接。实测数据的处理结果表明本文方法运算量小，且图像拼接性能显著优于传统方法。
5.由于运动目标定位性能会受到通道一致性和基线误差等系统非理想因素的影响，论文深入研究了广域GMTI系统的运动目标精确定位方法。第六章提出了用误差等效基线来描述以上误差，并在此基础上提出了一种新的广域GMTI运动目标定位方法。该方法的主要步骤包括测量不同误差等效基线对应的杂波抑制锐化比，确定最优误差等效基线及运动目标定位。本方法的关键步骤是通过令杂波抑制比最大化来估计最优误差等效基线，这确保了估计的最优误差等效基线与数据真实误差特性相吻合。因而，其定位性能明显优于采用名义基线的定位结果。实测数据处理结果验证了本文方法的性能。
6.第七章研究了一种双通道广域GMTI系统中的运动目标间接定位方法。由于广域GMTI系统中存在通道失配、沿航向基线误差、垂直基线等，要实现目标精确定位非常困难。为解决此问题，本文提出了一种目标定位新方法。该方法的核心思想是基于这样一个简单的事实，即运动目标与其邻近杂波（在观测场景中，与目标处于相同的距离单元和方位单元）拥有相同的干涉相位。这个新的间接定位办法，不依赖于传统的目标定位公式，因而可以免受大多数干涉相位误差的影响。实测数据处理结果表明本文算法可以获得较高的目标定位精度。
The airborne long-range battlefield surveillance radar system can provide real timereconnaissance and surveillance over a vast area on the ground or the sea, and hence isone of the most important sensors that are used for modern military applications. Theradar’s two working modes, i.e., synthetic aperture radar (SAR) ground moving targetindication (GMTI) mode or wide-area surveillance (WAS) GMTI mode, offer thedetection of moving targets in the battlefield. The WAS-GMTI mode, especially turnsout to be a particularly effective way to detect, locate and track moving targets, and thusis becoming more and more important in modern warfare. Recently, most militarypowers in the world have been engaging in developing airborne battlefield surveillanceradar systems, and a great number of universities and research institutes are developingpractical GMTI techniques and exploring novel moving target detection and locationalgorithms with high efficiency.
Based on the airborne WAS-GMTI research development of home and abroad, thisdissertation aims to improve moving target detection and location, and additionally togive in-depth discussion on WAS-GMTI signal processing method. More specifically,there were four key areas that we wished to address. First, this dissertation containssome basic materials on signal model of WAS-GMTI mode. Then, more importantly,this dissertation consists of a channel phase error estimation method, two imagestitching algorithms for ESA mode and MSA mode, and two moving target relocationalgorithms, all verified through real data processing. The main content of thisdissertation is summarized as follows.
1. Chapter2provides the reader with the observation models and mathematicalpreliminaries required to understand the WAS-GMTI mode. The purposes of Chapter2are to define important concepts and notations in WAS-GMTI, to describe WAS-GMTIdata acquisition geometry, and to represent more specially signal processing techniqueswhich form the basis for the proposed algorithms carried out in the subsequent chapters.
2. The channel phase error presented in radar will affect clutter suppression anddecline the parameter estimation accuracy as well. To deal with this problem, anestimation method of channel phase error is proposed in Chapter3for the phased arrayantenna. First the clutter of different channels is processed using the interferometrictechnique, after which the channel errors are estimated with the known scan angles. Toreduce the influence of noise and enhance the estimation accuracy, two strategies areintroduced for phase error estimation. On one hand, the independent and identically distributed (i. i. d.) range cells are proposed to be chosen as estimation samples. On theother hand, clutter of multiple wave positions is employed to further average theestimation error. Processing results with measured data validate that the proposedmethod can compensate the channel phase error very well and enhance the ability ofmoving target relocation significantly.
3. Based on the discussion about observation models and mathematicalpreliminaries, this dissertation contains descriptions and analyses of the image stitchingalgorithms of Doppler beam sharpening (DBS) image for ESA system and MSA system,respectively. Chapter4is concerned with image stitching in ESA. By stitching Dopplerbeam sharpening (DBS) images together the main-lobe DBS images obtained from allthe beam positions, a wide swath ground image is obtained. In practice, however, thereare some difficulties in stitching the DBS images due to the nonideal movement(variation of the velocity vector and the attitude) of the radar platform. To deal withthese problems, a novel method is proposed, which can stitch the DBS imageseffectively. The inertial navigation system (INS) information is employed to estimatethe instantaneous position of the aircraft and the radar beam direction, both of which arethen transformed to the original reference coordinate so that the corrected parameters ofthe image can be obtained. Finally, by using these parameters, the image stitching isachieved. Processing results of measured data show that the proposed method not onlycompensates the motion error excellently, but also significantly outperforms thetraditional algorithm in stitching performance.
4. Chapter5deals primarily with high resolution image stitching algorithm forDBS images in MSA system. The current image stitching algorithms are primarilysuited to process electronically steered array (ESA) data. However, these algorithmswill give rise to degradation of the performance for mechanical scanning antenna(MSA). In this paper, we develop an effective mulitsubbeam combination algorithm thatapplies to the MSA. For MSA whose beam is steered with physical antenna motion, thesuccessive pulses of adjacent subbeams are temporally correlated, and thus can becoherently integrated to generate a DBS image. The most prominent contributions of theproposed method are mulitsubbeam combination according to MSA geometry, whichguarantees that a high resolution DBS image can be obtained, and good data selection inthe way of Doppler spectrum combination. Results from real data show that theproposed method is computationally quite efficient for high-resolution imaging andsignificantly outperforms the traditional algorithm.
5. The system factors that affect the performance of moving targets relocation can be examined through channel imbalance and antenna array misalignment etc. Thisdissertation derivates and developes two algorithms by which a moving target can beaccurately relocated in the SCAN-GMTI system. In Chapter6, we introduce a conceptcalled error equivalent baseline (EEB) to describe the influence of these factors anddevelop a novel method of moving targets location for the scan-ground moving targetindication (SCAN-GMTI) system. The proposed method involves measuring the cluttersuppression sharpness ratio (CSSR) corresponding to the potential EEBs, determiningthe optimal EEB, and locating the moving targets. The key procedure of estimating theoptimal EEB that maximizes the CSSR virtually provides a good fit for the errorcharacteristic of the measured data. Therefore, the location performance of the obtainedoptimal EEB is superior to that of the nominal baseline. Processing results of measureddata validate the effectiveness of the proposed method.
6. Chapter7deals with the issue of moving target relocation for wide-area groundmoving target indication (GMTI) using dual-channel radar systems. Due to channelmismatch, along-track baseline error, the existence of across-track baseline, and etc, it isdifficult to accurately relocate the detected targets. In this letter, we propose a newknowledge-based (KB) method for target relocation. The key idea of the proposedmethod is to use such a fact that a moving target and its neighboring clutter which issituated at the same azimuth angular position and the same range cell as this target inthe observed scene, have the same interferometric phase. This new KB method, as anindirect one, does not employ the conventional relocation formula, and therefore is notinfluenced by most of (if not all) interferometric-phase errors. Experimental results forreal radar data demonstrate a fairly high degree of target-relocation accuracy.
引文
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