多载频MIMO高频雷达关键技术研究
|
摘要
高频地波雷达是一种有效探测海面超视距隐身目标的雷达系统，通常采用宽波束照射目标、单方向窄波束接收回波。由于高频段目标特性处于瑞利区前段或者谐振区，不确定的RCS随机起伏极易导致回波能量微弱而丢失目标。为了克服目标的闪烁，本研究充分利用不同频率和角度目标RCS差异，将多输入多输出（MIMO）体制与高频雷达相结合，利用MIMO体制的优势来提高雷达系统时间、空间、频率管理的自由度，通过有效综合多方向、多载频的回波信息，达到改善系统分辨力的目的，进而提高雷达系统的探测能力。
因此，MIMO体制与高频地波雷达结合的关键技术研究具有重要意义。本研究将MIMO的体制结合高频雷达的特点，建立了区别于一般MIMO雷达的多载频MIMO高频雷达模型，分别讨论了集中式和分布式MIMO雷达两种模型，针对不同模型提出了有效的信号处理算法，得到了一些具有积极意义和参考价值的方法和结论。总体来说，本研究主要包括以下几个方面：
第一，本文改进了MIMO模糊函数，突破了传统模糊函数理论的局限性，使其适应于复杂的MIMO雷达系统速度距离分辨力的分析评估。集中MIMO模型采用分集发射非连续频点相位编码信号，针对系统空域与时域耦合问题进行了研究，通过扩展的模糊函数有效评估该模型下角度距离分辨力，并得到了非连续频谱发射信号参数准则；进一步在多载频分布式MIMO模型下，通过扩展传统模糊函数的研究评估系统空间分辨力，得到了分布式MIMO雷达的传感器布放规律。模糊函数的扩展改进研究对于MIMO高频雷达全局分辨力分析具有重要的意义，为后续关键问题的提出和研究打下了坚实的基础。
第二，为了有效提高高频雷达距离分辨力，针对非连续谱信号产生的较高距离副瓣，本研究提出了两种方法来解决非连续谱信号较高旁瓣问题——接收端非连续谱旁瓣抑制和发射端波形设计。区别于以往非连续谱时分复用构造形式，本研究采用不同天线分集发射不同载频编码信号，接收端将非连续谱信号相参拼接，对相参处理后主瓣附近产生的较高旁瓣进行抑制。基于凸优化算法优化旁瓣抑制滤波器，对有限长数据产生的伪峰进行滑窗剔除，较好的解决了多目标环境下弱目标副瓣遮挡问题。本算法实时性好且简单实用，便于工程实现。基于发射端波形设计，本研究利用波形平均通带阻带功率比与自相关旁瓣关系，建立波形优化的代价函数。通过量子遗传算法优化低自相关旁瓣波形，仿真实验取得了预期的效果，优化的波形实现了频谱约束下最优副瓣等级。本章通过非连续谱信号的设计处理充分利用非连续的频谱资源，改善了MIMO高频雷达恶劣电磁环境的较差分辨力。
第三，针对高频雷达的角度分辨力差问题，区别于以往MIMO模型虚拟阵列技术，本研究提出多载频聚焦算法虚拟大的阵列孔径。针对虚拟孔径的单元间距大于半波长，阵列综合产生栅瓣的问题，本研究进一步提出了预条件共轭梯度法重构非均匀空域信息，有效抑制阵列稀疏产生的栅瓣问题。在重构标准频率下均匀空域信息时，需要求解高维方程，预条件的引入显著提高了算法的收敛速度。另外，针对不同频率下，目标不一致的幅度相位响应、回波信噪比及多普勒信息，提出了相应的预处理流程。最后，分析了发射频率的选择对空域综合性能的影响。多载频MIMO空域综合提出了一种新的信号融合思路，有效扩展了高频雷达的孔径尺寸。
第四，本研究建立了多载频分布式MIMO高频雷达模型，针对该模型产生空间和多普勒域稀疏采样问题，基于压缩感知提出一种分布式雷达系统算法。本系统采用非均匀周期发射多载频相位编码信号，有效减少多脉冲雷达系统不同节点数据传输负担。针对稀疏回波信号恢复问题，构造统一的空域和多普勒域感知矩阵，有效解决了分布式系统多站点回波信息集中处理问题，及分布式系统产生的目标定位模糊。针对空间网格细化导致压缩矩阵相关性变强，将多载频信息的引入，较好的解决了感知矩阵RIP（空间等距）条件的限制。此外，针对实际情况中，不同方向产生的未知相位响应无法准确重构问题，提出测量矩阵附加目标未知的相位响应来改善目标定位误差。最后，讨论了感知矩阵的列向量相关性，系统估计误差性能与脉冲个数的关系，以及空间分辨网格的划分准则。本研究对于感知压缩算法应用于实际的分布式MIMO雷达模型提供了重要理论依据。
HFSWR is an effective surveillance radar system, which can detect the horizonstealth targets over the sea, usually adopts wide beam irradiation, receives the echonarrow beam in single direction. Since in HF band the target characteristics in theRayleigh region or resonance regions, uncertain target attitude and RCS fluctuationscan easily lead to weak echoes and missed targets. To overcome the targetscintillation, the study takes full advantage of RCS differences in differentfrequencies and angles, combining multiple-input multiple-output (MIMO) systemand HF radar, exploiting the advantages of the MIMO system to enhance the radarsystem time, space, frequency management DOF, synthesizing multi-directional,multi-frequency target echo information effectively, to improve the resolution of theobjective system, and improving the system's resolution. Therefore, the researchabout key technologies of MIMO system and HFSWR combination has importantsignificance.
In this study, we combined the MIMO system with HFSWR characteristics, andestablished a multi-carrier MIMO HF radar model which is different from thegeneral MIMO radar. This research established a centralized and distributed MIMOradar model, for different model proposed an effective signal processing algorithms,and obtained some positive significance and reference value methods andconclusions. Overall, this study includes the following aspects:
First, the research improved MIMO ambiguity function to adapt complexMIMO radar system speed range resolution analysis, breaking the traditional theoryof ambiguity function limitations. This paper presents a discontinuous spectrumMIMO HF radar ambiguity function, and discusses spatial and temporal couplingunder collocated MIMO model which adopts different carrier frequency diversitytransmission signals, effectively assesses the range resolution of the system, andobtains discontinuous spectrum waveform parameter selection criteria; furtherextends the traditional ambiguity functions to evaluate system spatial resolution, andgets distributed MIMO radar sensor deployment general law in a multi-carrierMIMO model. This study proposes improves MIMO radar ambiguity functionglobally for high resolution analysis, which has important significance for thesubsequent key issues raised and resolved.
Second, in order to effectively improve HF radar range resolution, fordiscontinuous spectrum signal generating higher sidelobes shortcomings, this studyproposes two kind of discontinuous spectrum signals to solve higher sidelobe problem-the receiving sidelobe suppression and transmitter discontinuous spectrumwaveform design. Different from the previous time multiplexing structurediscontinuous spectrum waveform, this study adopts antenna diversity to transmitdifferent carrier frequency phase coded signal, the receiver suppress highersidelobes around the mainlobe after signal coherent processing. Based on convexoptimization algorithm we design sidelobe suppression filter to remove pseudo peakwhich is produced by a finite length data sliding window, effectively solving weaktargets are submerged by higher sidelobes under multi-target environment. Theproposed algorithm has good real-time and simple characters, is easy to practicalimplement. Based on the transmitter waveform design, the study obtained therelationship of waveform between average passband-stopband power ratio and theautocorrelation sidelobe level, and proposed waveform optimized cost function. Byquantum genetic algorithm we optimize the low autocorrelation sidelobes waveformto obtain the desired results, the optimized waveform under constraint spectrumachieved the optimal sidelobe levels. This chapter on discontinuous spectrum signaldesign improves HFSWR working performance under harsh electromagneticenvironment.
Third, in the perspective of HF radar poor angle resolution, different from theprevious model of virtual MIMO array technology, the study proposed amulti-frequency focus algorithm to synthesize virtual array aperture. For virtualaperture array element interval greater than half the wavelength, the beamformingwill generate grating lobes, this study further proposed based preconditionedconjugate gradient method to reconstruct non-uniform spatial information efficientlyto suppress higher grating lobes. In the reconstruction of the standard frequencyuniform spatial information, high-dimensional equation need to solve, theintroduction of the pre-conditions significantly improves the convergence speed.Meanwhile, for different amplitude and phase response, Doppler and SNR of thedifferent frequencies, we proposed corresponding preprocessesing, and analysis howthe transmitter carrier frequency selection impacts on the overall performance of thespatial synthesize in addition. Multi-carrier MIMO spatial synthesis proposes a newsignal fusion ideas, effectively extends the HFSWR aperture size.
Fourth, this study established a multi-carrier Distributed MIMO HF radarmodel, which exists space and Doppler domain sparse sampling problem, andproposed distributed radar system algorithms based on compressed sensing. In thisstudy, we adopt inhomogeneous period to radiates phase-coded multi-carrier signal,that can reduce multi-pulse system radar different nodes' data transfer burdeneffectively. For sparse echo signal recovery problems, we construct a spatial andDoppler domain in single CS matrix, the algorithm figure out multistatic distributed system centralize processing and distributed systems target location ambiguityeffectively. For mesh refinement causing CS matrix column stronger correlation,multi-frequency information is introduced, it is better to solve CS matrix RIPconditions. Furthermore, in view of the actual situation, unknown differentdirections response results in reconstructing inaccurately, we propose additionalrandom phase CS matrix to improve target location errors. Finally, the studyanalysis the CS matrix column vectors correlation relationship between theestimation error and the number of pulses, and the spatial resolution of the griddivision criteria. This study is important theoretical basis of CS distributed MIMOradar model applied to practical application.
因此，MIMO体制与高频地波雷达结合的关键技术研究具有重要意义。本研究将MIMO的体制结合高频雷达的特点，建立了区别于一般MIMO雷达的多载频MIMO高频雷达模型，分别讨论了集中式和分布式MIMO雷达两种模型，针对不同模型提出了有效的信号处理算法，得到了一些具有积极意义和参考价值的方法和结论。总体来说，本研究主要包括以下几个方面：
第一，本文改进了MIMO模糊函数，突破了传统模糊函数理论的局限性，使其适应于复杂的MIMO雷达系统速度距离分辨力的分析评估。集中MIMO模型采用分集发射非连续频点相位编码信号，针对系统空域与时域耦合问题进行了研究，通过扩展的模糊函数有效评估该模型下角度距离分辨力，并得到了非连续频谱发射信号参数准则；进一步在多载频分布式MIMO模型下，通过扩展传统模糊函数的研究评估系统空间分辨力，得到了分布式MIMO雷达的传感器布放规律。模糊函数的扩展改进研究对于MIMO高频雷达全局分辨力分析具有重要的意义，为后续关键问题的提出和研究打下了坚实的基础。
第二，为了有效提高高频雷达距离分辨力，针对非连续谱信号产生的较高距离副瓣，本研究提出了两种方法来解决非连续谱信号较高旁瓣问题——接收端非连续谱旁瓣抑制和发射端波形设计。区别于以往非连续谱时分复用构造形式，本研究采用不同天线分集发射不同载频编码信号，接收端将非连续谱信号相参拼接，对相参处理后主瓣附近产生的较高旁瓣进行抑制。基于凸优化算法优化旁瓣抑制滤波器，对有限长数据产生的伪峰进行滑窗剔除，较好的解决了多目标环境下弱目标副瓣遮挡问题。本算法实时性好且简单实用，便于工程实现。基于发射端波形设计，本研究利用波形平均通带阻带功率比与自相关旁瓣关系，建立波形优化的代价函数。通过量子遗传算法优化低自相关旁瓣波形，仿真实验取得了预期的效果，优化的波形实现了频谱约束下最优副瓣等级。本章通过非连续谱信号的设计处理充分利用非连续的频谱资源，改善了MIMO高频雷达恶劣电磁环境的较差分辨力。
第三，针对高频雷达的角度分辨力差问题，区别于以往MIMO模型虚拟阵列技术，本研究提出多载频聚焦算法虚拟大的阵列孔径。针对虚拟孔径的单元间距大于半波长，阵列综合产生栅瓣的问题，本研究进一步提出了预条件共轭梯度法重构非均匀空域信息，有效抑制阵列稀疏产生的栅瓣问题。在重构标准频率下均匀空域信息时，需要求解高维方程，预条件的引入显著提高了算法的收敛速度。另外，针对不同频率下，目标不一致的幅度相位响应、回波信噪比及多普勒信息，提出了相应的预处理流程。最后，分析了发射频率的选择对空域综合性能的影响。多载频MIMO空域综合提出了一种新的信号融合思路，有效扩展了高频雷达的孔径尺寸。
第四，本研究建立了多载频分布式MIMO高频雷达模型，针对该模型产生空间和多普勒域稀疏采样问题，基于压缩感知提出一种分布式雷达系统算法。本系统采用非均匀周期发射多载频相位编码信号，有效减少多脉冲雷达系统不同节点数据传输负担。针对稀疏回波信号恢复问题，构造统一的空域和多普勒域感知矩阵，有效解决了分布式系统多站点回波信息集中处理问题，及分布式系统产生的目标定位模糊。针对空间网格细化导致压缩矩阵相关性变强，将多载频信息的引入，较好的解决了感知矩阵RIP（空间等距）条件的限制。此外，针对实际情况中，不同方向产生的未知相位响应无法准确重构问题，提出测量矩阵附加目标未知的相位响应来改善目标定位误差。最后，讨论了感知矩阵的列向量相关性，系统估计误差性能与脉冲个数的关系，以及空间分辨网格的划分准则。本研究对于感知压缩算法应用于实际的分布式MIMO雷达模型提供了重要理论依据。
HFSWR is an effective surveillance radar system, which can detect the horizonstealth targets over the sea, usually adopts wide beam irradiation, receives the echonarrow beam in single direction. Since in HF band the target characteristics in theRayleigh region or resonance regions, uncertain target attitude and RCS fluctuationscan easily lead to weak echoes and missed targets. To overcome the targetscintillation, the study takes full advantage of RCS differences in differentfrequencies and angles, combining multiple-input multiple-output (MIMO) systemand HF radar, exploiting the advantages of the MIMO system to enhance the radarsystem time, space, frequency management DOF, synthesizing multi-directional,multi-frequency target echo information effectively, to improve the resolution of theobjective system, and improving the system's resolution. Therefore, the researchabout key technologies of MIMO system and HFSWR combination has importantsignificance.
In this study, we combined the MIMO system with HFSWR characteristics, andestablished a multi-carrier MIMO HF radar model which is different from thegeneral MIMO radar. This research established a centralized and distributed MIMOradar model, for different model proposed an effective signal processing algorithms,and obtained some positive significance and reference value methods andconclusions. Overall, this study includes the following aspects:
First, the research improved MIMO ambiguity function to adapt complexMIMO radar system speed range resolution analysis, breaking the traditional theoryof ambiguity function limitations. This paper presents a discontinuous spectrumMIMO HF radar ambiguity function, and discusses spatial and temporal couplingunder collocated MIMO model which adopts different carrier frequency diversitytransmission signals, effectively assesses the range resolution of the system, andobtains discontinuous spectrum waveform parameter selection criteria; furtherextends the traditional ambiguity functions to evaluate system spatial resolution, andgets distributed MIMO radar sensor deployment general law in a multi-carrierMIMO model. This study proposes improves MIMO radar ambiguity functionglobally for high resolution analysis, which has important significance for thesubsequent key issues raised and resolved.
Second, in order to effectively improve HF radar range resolution, fordiscontinuous spectrum signal generating higher sidelobes shortcomings, this studyproposes two kind of discontinuous spectrum signals to solve higher sidelobe problem-the receiving sidelobe suppression and transmitter discontinuous spectrumwaveform design. Different from the previous time multiplexing structurediscontinuous spectrum waveform, this study adopts antenna diversity to transmitdifferent carrier frequency phase coded signal, the receiver suppress highersidelobes around the mainlobe after signal coherent processing. Based on convexoptimization algorithm we design sidelobe suppression filter to remove pseudo peakwhich is produced by a finite length data sliding window, effectively solving weaktargets are submerged by higher sidelobes under multi-target environment. Theproposed algorithm has good real-time and simple characters, is easy to practicalimplement. Based on the transmitter waveform design, the study obtained therelationship of waveform between average passband-stopband power ratio and theautocorrelation sidelobe level, and proposed waveform optimized cost function. Byquantum genetic algorithm we optimize the low autocorrelation sidelobes waveformto obtain the desired results, the optimized waveform under constraint spectrumachieved the optimal sidelobe levels. This chapter on discontinuous spectrum signaldesign improves HFSWR working performance under harsh electromagneticenvironment.
Third, in the perspective of HF radar poor angle resolution, different from theprevious model of virtual MIMO array technology, the study proposed amulti-frequency focus algorithm to synthesize virtual array aperture. For virtualaperture array element interval greater than half the wavelength, the beamformingwill generate grating lobes, this study further proposed based preconditionedconjugate gradient method to reconstruct non-uniform spatial information efficientlyto suppress higher grating lobes. In the reconstruction of the standard frequencyuniform spatial information, high-dimensional equation need to solve, theintroduction of the pre-conditions significantly improves the convergence speed.Meanwhile, for different amplitude and phase response, Doppler and SNR of thedifferent frequencies, we proposed corresponding preprocessesing, and analysis howthe transmitter carrier frequency selection impacts on the overall performance of thespatial synthesize in addition. Multi-carrier MIMO spatial synthesis proposes a newsignal fusion ideas, effectively extends the HFSWR aperture size.
Fourth, this study established a multi-carrier Distributed MIMO HF radarmodel, which exists space and Doppler domain sparse sampling problem, andproposed distributed radar system algorithms based on compressed sensing. In thisstudy, we adopt inhomogeneous period to radiates phase-coded multi-carrier signal,that can reduce multi-pulse system radar different nodes' data transfer burdeneffectively. For sparse echo signal recovery problems, we construct a spatial andDoppler domain in single CS matrix, the algorithm figure out multistatic distributed system centralize processing and distributed systems target location ambiguityeffectively. For mesh refinement causing CS matrix column stronger correlation,multi-frequency information is introduced, it is better to solve CS matrix RIPconditions. Furthermore, in view of the actual situation, unknown differentdirections response results in reconstructing inaccurately, we propose additionalrandom phase CS matrix to improve target location errors. Finally, the studyanalysis the CS matrix column vectors correlation relationship between theestimation error and the number of pulses, and the spatial resolution of the griddivision criteria. This study is important theoretical basis of CS distributed MIMOradar model applied to practical application.
引文
[1][1] Eran Fishler, Alex Haimovich, Rick Blum, Dmitry Chizhik, LenCimini, Reinaldo Valenzuela. MIMO RADAR: AN IDEA WHOSE TIMEHAS COME [C]. Radar Conference Proceedings of the IEEE.2004:71-78.
[2] J. Li, P. Stoica. MIMO radar with collocated antennas: Review of somerecent work [J]. IEEE Signal Process. Mag.2007,24(5):106-114.
[3] B. Chen, S. Zhang, Y. Wang, and J. Wang. Analysis and experimentalresults on sparse-array synthetic impulse and aperture radar [J]. Proc.2001CIE Int. Conf. Radar, Oct.2001:76-80.
[4] E. Fishler, A. Haimovich, R. S. Blum. Spatial diversity in radars—modelsand detection performance [J]. IEEE Trans. Signal Processing.2006,54(3):823-838.
[5] N. H. Lehmann, A. M Haimovich, R. S. Blum, L. J. Cimini. High resolutioncapabilities of MIMO radar [C]. Proc.40th Asilomar Conf. Signals,Systems and Computers, Nov.2006:12-14
[6] D. R. Fuhrmann and G. San Antonio, Transmit beamforming for MIMOradar systems using partial signal correlation [C], Proc.38th Asilomar Conf.Signals, Systems and Computers, Nov.2004:295-299.
[7] D. W. Bliss and K. W. Forsythe, Multiple-input multiple-output (MIMO)radar and imaging: Degrees of freedom and resolution [C], Proc.37thAsilomar Conf. Signals, Systems and Computers, Nov.2003:54-59.
[8] D. Rabideau, Ubiquitous MIMO digital array radar [C], Proc.37th AsilomarConf. Signals, ystems, and Computers, Nov.2003:1057-1064.
[9] Nadav Levanon.“Multifrequency radar signals”, Records of the IEEE2000International Radar Conference, Alexandria, VA,2000a:683-688.
[10] F. C. Robey, S. Coutts, D. Weikle, J. C. McHarg, and K. Cuomo, MIMOradar theory and experimental results [C], Proc.38th Asilomar Conf.Signals, Systems and Computers, Nov.2004:300-304.
[11] I. Bekkerman and J. Tabrikian, Target detection and localization usingMIMO radars and sonars [J], IEEE Trans. Signal Process200654(5):3873--3883.
[12] L. Xu, J. Li, and P. Stoica, Adaptive techniques for MIMO radar [C], Proc.14th IEEE Workshop on Sensor Array and Multi-channel Processing,Waltham, MA, July2006:55-58
[13] N. Lehmann, A. M. Haimovich, R. S. Blum, and L. Cimini, MIMO-radarapplication to moving target detection in homogenous clutter, Proc.14thIEEE Workshop on Sensor Array and Multi-channel Processing [C],Waltham, MA, July2006:706-715.
[14] Hightower J, Borriello G. Location Systems for Ubiquitous Computing [J].IEEE Computer.2001,34:57-66.
[15] N. H. Lehmann, A. M Haimovich, R. S. Blum, and L. J. Cimini, Highresolution capabilities of MIMO radar, Proc.40th Asilomar Conf. Signals,Systems and Computers, Nov.2006:71-75
[16] E. Fishler, A. Haimovich, R. Blum, L. Cimini, D. Chizhik, and R.Valenzuela, Performance of MIMO radar systems: Advantages of angulardiversity, Proc.38th Asilomar Conf. Signals, Systems and Computers, Nov.2004:305-309.
[17] Y. Yang and R. S. Blum, Radar waveform design based on mutualinformation and mean-square error estimation, IEEE Trans. AerospaceElectron. Syst. Jan.2007,43:330-343.
[18] J. Li, P. Stoica, and Y. Xie, On probing signal design for MIMO radar [C],Proc.40th Asilomar Conf. Signals, Systems and Computers, Pacific Grove,CA, Oct.2006：331-334
[19] J. Li, P. Stoica, L. Xu, and W. Roberts, On parameter identifiability ofMIMO radar [J], IEEE Signal Process. Lett.14(12) Dec.2007:968-971.
[20] J. Li, L. Xu, P. Stoica, K. W. Forsythe, and D. W. Bliss, Range compressionand waveform optimization for MIMO radar: A Crame′r-Rao bound basedstudy [C], IEEE Trans. Signal Process.56(1) Jan.2008:218-232.
[21] V. F. Mecca, D. Ramakrishnan, and J. L. Krolik, MIMO radar space-timeadaptive processing for multipath clutter mitigation [C], Proc.4th IEEEWorkshop on Sensor Array and Multi-channel Processing, Waltham, MA,July2006:227-231
[22] D. J. Rabideau and P. Parker, Ubiquitous MIMO multifunction digital arrayradar [C], Proc.37th Asilomar Conf. Signals, Systems and Computers,Pacific Grove, CA, Nov.2003:114-117
[23] P. Stoica, J. Li, and Y. Xie, On probing signal design for MIMO radar [J],IEEE Trans. Signal Process.55(8) Aug.2007:4151-4161.
[24] J. Tabrikian, Barankin bounds for target localization by MIMO radars [C],Proc.4th IEEE Workshop on Sensor Array and Multi-channel Processing,Waltham, MA, July2006:231-234
[25] K. W. Forsythe, D. W. Bliss, and G. S. Fawcett, Multiple-inputmultiple-output (MIMO) radar: Performance issues [C], Proc.38thAsilomar Conf. Signals, Systems and Computers, Pacific Grove, CA, Nov.2004, Vol.1:310-315.
[26] T. Aittomaki and V. Koivunen, Low-complexity method for transmitbeamforming in MIMO radars [C], Proc.2007IEEE Int. Conf. Acoustics,Speech, and Signal Processing, Honolulu, April2007:512-514
[27] G. San Antonio and D. R. Fuhrmann, Beampattern synthesis for widebandMIMO radar systems [C], Proc.1st IEEE Int. Workshop CAMSAP, PuertoVallarta, Mexico, Dec.2005:105-108.
[28] D. R. Fuhrmann and G. San Antonio, Transmit beamforming for MIMOradar systems using partial signal correlation, IEEE Trans. AerospaceElectron. Syst.43(4)(Oct.2007):42-47.
[29] D. Bliss and K. Forsythe, Multiple-input multiple-output (MIMO) radar andimaging: Degrees of freedom and resolution, Proc.37th Asilomar Conf.Signals, Systems, and Computers, Monterey, CA,2003:54–59.
[30] K. W. Forsythe and D. W. Bliss, Waveform correlation and optimizationissues for MIMO radar, Proc.39th Asilomar Conf. Signals, Systems andComputers, Pacific Grove, CA, Nov.2005:1306-1310.
[31] J. Tabrikian and I. Bekkerman, Transmission diversity smoothing formulti-target localization [C], Proc.2005IEEE Int. Conf. Acoustics, Speech,and Signal Processing, Philadelphia, PA, March2005, Vol.4:1041–1044.
[32] L. Xu, J. Li, and P. Stoica, Adaptive techniques for MIMO radar [C], Proc.4th IEEE Workshop on Sensor Array and Multi-channel Processing,Waltham, MA, July2006:105-108
[33] L. Xu, J. Li, P. Stoica, K. W. Forsythe, and D. W. Bliss, Waveformoptimization for MIMO radar: A Cramer-Rao bound based study [C], Proc.2007IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Honolulu,April2007:512-514
[34] L. Xu and J. Li, Iterative generalized likelihood ratio test for MIMOradar,IEEE Trans. Signal Process.55(6)2007:2375-2385.
[35] Gordon J. Frazer, Yuri I. Abramovich, Ben A. Johnson. Spatially WaveformDiverse Radar: Perspectives for High Frequency OTHR [C], In Proc. RadarConference. Boston, MA, USA: IEEE, Apr17-202007:385-390.
[36] Gordon J. Frazer, Ben A. Johnson, Yuri I. Abramovich. OrthogonalWaveform Support in MIMO HF OTH Radars [C], In Proc. WaveformDiversity and Design Conference. June4-82007:423-427.
[37] G. Dickel, D.J. Emery, D.G. Money, The architecture and operatingcharacteristics a multi-frequency HF surface wave Radar–part two, Intl.Radar Conf. RADAR2007, Edinburgh, UK, Oct15-18,2007:3-10.
[38] Y. Teng, H.D. Griffiths, C.J. Baker, K. Woodbridge. Netted radar sensitivityand ambiguity”, IET Radar Sonar Naving.,2007,1(6):479-486.
[39] Qu JinYou, Zhang Jian Yun, Liu ChunQuan. The Ambiguity Function ofMIMO Radar [C], Microwave, Antenna, Propagation and EMCTechnologies for Wireless Communications,2007International Symposiumon,16-17Aug.2007:265-268
[40] Fred Daum, Jim Huang MIMO radar: snake oil or good idea, Signals,Systems and Computers [C],200842nd Asilomar Conference on,2008:183–187.
[41] Shenghua Zhou, Hui Xu, Liangbing Hu, Hongwei Liu Research forScattering Properties of Spatial and Frequency Diversity MIMO Radartargets [C], Signal Processing,2008. ICSP2008.9th InternationalConference on,2008:2533–2537.
[42] Alexander M. Haimovich, Rick S.Blum, and Leonard J. Cimini, Jr. MIMORadar Widely Seperated Antennas, Information Sciences and Systems,2008.CISS2008.42nd Annual Conference on,2008:123–127.
[43] P.F. Sammartino, C.J. Baker. The Frequency Diverse Bistatic System,Waveform Diversity and Design Conference,2009International,2009:155–159.
[44] Xizeng Dai, Jia Xu, Yingning Peng High Resolution Frequency MIMORadar, Radar Conference2007IEEE,2007:693–698.
[45] Earnest Lock, Raviraj S. Adve. Othogonal Frequency Division Multiplexingin Distributed Radar Apertures, Radar Conference,2008. RADAR '08.IEEE,2008:1–6.
[46] Chen Duofang, Chen Baixiao, Zhang Shouhong. Multiple-inputMultiple-output Radar and Sparse Array Synthetic Impulse and ApertureRadar, Radar,2006. CIE '06. International Conference on,2006:1–4.
[47] Raviraj S. Adve, Richard A. Schneible, Gerard Genello, Paul Antonik.Waveform-Space-Time Adaptive Processing for Distributed ApertureRadars, Radar Conference,2005IEEE International,2005:93-97.
[48] Raviraj S. Adve, Lorne Applebaum, Michael C. Wicks, Richard A.Schneible. Space-Time-Wave Adaptive Processing for Frequency DiverseDistributed Radar Apertures, Information Sciences and Systems,200640thAnnual Conference on,2006:1413-1417.
[49] Jiang Wei, Wang Ju, Wu Siliang, Wang Dajun. Coherent Detection andAmbiguity Resolution for Frequency Diversity Separated Subarray Radar.Signal Processing,2008. ICSP2008:2364-2367.
[50] Chunyang Chen, P.P. Vaidyanathan. Beamforming issues in modern MIMORadars with Doppler [C], Signals, Systems and Computers,2006. ACSSC'06. Fortieth Asilomar Conference on,2006:41-45.
[51] Long Zhuang, Xingzhao Liu. Coherent Synthesis Sparse Aperture Radarwith Grating lobes Suppressed Using Freqency MIMO Technique [J], RadarConference,2008. RADAR '08. IEEE,2008:1–5.
[52] D.J. Emery, G. Dickel. The Operation and Performance of a Multi-FreqencyHF Surfacewave Radar [C], Radar Conference,2008. RADAR '08. IEEE:1-6.
[53] Qian He, Rick S. Blum, Hana Godrich, Alexander M. Haimovich.Cramer-Rao Bound for Target Velocity Estimation in MIMO Radar withWidely Separated Antennas, Information Sciences and Systems,2008. CISS2008.42nd Annual Conference on:123–127.
[54] K.W. Forsythe, D.W. Bliss, G.S. Fawcett. Multiple-InputMultiple-Output(MIMO) Radar: Performance Issues, Signals, Systems andComputers,2004. Conference Record of the Thirty-Eighth AsilomarConference on, Vol.1:310-315.
[55] R.Mohseni, A.Sheikhi, M.A. Masnadi Shirazi. A new approach to compressmulticarrier phase-coded signals, Radar Conference,2008. RADAR '08.IEEE:1–6.
[56] W.X. Liu, Y.L. Lu, M. Lesturgie. Optimal sparse waveform design forHFSWR system, Waveform Diversity and Design Conference,2007.International,2007:127–130.
[57] Zengjiankui, Hezishu, Liubo. Adaptive Space-time-waveform processingfor MIMO Radar, Communications, Circuits and Systems,2007. ICCCAS2007. International Conference on,2007:641–643.
[58] Raviraj Adve, Richard Schneible, Robert McMillan. AdaptiveSpace/Frequency Processing for Distributed Aperture Radars, RadarConference,2003. Proceedings of the2003IEEE,2003:160–164.
[59] Hai Deng. Polyphase code design for orthogonal netted radar systems,Signal Processing, IEEE Transactions on,2004:3126–3135.
[60] Bo Liu, Zishu He, Jiankui Zeng, Benyong Liu. Polyphase orthogonal codedesign for MIMO radar systems [C], Radar,2006. CIE '06. InternationalConference on,2006:1–4.
[61] Chunyang Chen, P.P. Vaidyanathan. Properties of the MIMO radarambiguity function, Acoustics, Speech and Signal Processing,2008.ICASSP2008. IEEE International Conference on,2008:2309–2312.
[62] Jian Li, Luzhou Xu, Petre Stoica, Keith W. Forsythe, Daniel W. Bliss.Range Compression and Waveform Optimization for MIMO Radar: ACramér–Rao Bound Based Study, Signal Processing, IEEE Transactions on,2008:218–232.
[63] Jian Li, Petre Stoica, Luzhou Xu, William Roberts. On ParameterIdentifiability of MIMO Radar, Signal Processing Letters, IEEE,2007:968–971.
[64] D.W. Bliss, K.W. Forsythe. Multiple-input Multiple-out (MIMO) Radar andImaging Degrees of Freedom and Resolution, Signals, Systems andComputers,2003. Conference Record of the Thirty-Seventh AsilomarConference on,2003Vol.1:54-59.
[65] S D Green, S P Kingsley. Investigation of wide bandwith HF radarwaveforms, Advanced Transmission Waveforms, IEE Colloquium on,1995:2/1-2/8.
[66] S D Green, S P Kingsley. Improving the range/time sidelobe of largebandwidth discontinuous spectra HF radar waveforms, HF Radio Systemsand Techniques, Seventh International Conference on (Conf. Publ. No.441),1997:246–250.
[67] Nikolaus H. Lehmann, Alexander M. Haimovich, Rick S. Blum, Len Cimini.High Resolution Capabilities of MIMO Radar, Signals, Systems andComputers,2006. ACSSC '06. Fortieth Asilomar Conference on,2006:25–30.
[68] Ioannis Papoutsis. Netted Radar and Ambiguity Function,2006. CIE '06.International Conference on,2006:1–4.
[69] G.J. Frazer, Y.I. Abramovich, B.A. Jonson. Use of Adaptive Non-CausalTransmit Beamforming in OTHR: Experimental Results, Radar2008International Conference on,2008:311–316.
[70] G.J. Frazer, Y.I. Abramovich, B.A. Jonson, F.C. Robey. Recent Results inMIMO Over-the-Horizon Radar [C],2008. RADAR '08. IEEE,2008:1-6.
[71] Jeffrey Krolik, Vito Mecca, Oguz Kazanci, Igal Bilik. MultipathSpread-Doppler Clutter Mitigation for Over-the-Horizon Radar[C], RadarConference,2008. RADAR '08. IEEE,2008:1-5.
[72] Frank C. Robey, Scott Coutts, Dennis Weikle, Jeffrey C.McHarg, KevinCuomo. MIMO Radar Theory and Experimental Results, Signals, Systemsand Computers,2004. Conference Record of the Thirty-Eighth AsilomarConference on,2004Vol.1:300-304.
[73] G.J. Frazer, Y.I. Abramovich, B.A. Johnson. MIMO Radar Limitations inClutter, Radar Conference,2009IEEE,2009:1-5.
[74] M. Lesturgie. Improvement of high-frequency surface waves radarperformance by use of multi-input multi-output configurations, Radar,Sonar&Navigation, IET,2009:49-61.
[75] Guohua Wang, Yilong Lu. High Resolution MIMO-HFSWR Using SparseFrequency Waveform, Signal Processing,2008. ICSP2008.9thInternational Conference on,2008:2238–2241.
[76] Eran Fishler, Alex Haimovich, Rick S.Blum. Spatial Diversity inRadars-Models and Detecttion Performance, Signal Processing, IEEETransactions on,2006:823-838.
[77] Eran Fishler, Alex Haimovich, Rick S.Blum. Performance of MIMO RadarSystems: Advantages of Angular Diversity, Signals, Systems andComputers,2004. Conference Record of the Thirty-Eighth AsilomarConference on,2004,:305-309.
[78] P.F. Sammartino, C.J. Baker, H.D. Griffiths. Target Model Effects onMIMO Radar Performance, Acoustics, Speech and Signal Processing,2006.ICASSP2006Proceedings.2006IEEE International Conference on,2006:20-24.
[79] Jun Jason Zhang, Antonia Papandreou-Suppappola MIMO Radar withFrequency Diversity, Waveform Diversity and Design Conference,2009International,2009:208–212.
[80] Abbas Sheikhi, Ali Zamani. Coherent Detection for MIMO Radars, RadarConference,2007IEEE,2007:302-307.
[81] Byung Wook Jung, Raviraj S. Adve, Joohwan. Frequency Diversity inMultistatic Radars, Radar Conference,2008. RADAR '08. IEEE,2008:1-6.
[82]王怀军,粟毅,朱宇涛,许洪波，基于空间谱域填充的MIMO雷达成像研究[J].电子学报,2009,(06):1242-1246.
[83]王怀军，许洪波，陆珉，粟毅,基于MIMO雷达的高分辨成像方法[J],微波学报,2009,(10):79-83.
[84]赵光辉，陈伯孝，黄白，多频体制下虚拟阵列影射聚焦方法[J],西安交通大学学报，2009，43(4):66-69.
[85]张祥坤，张云华，姜景山，多视角聚束合成孔径雷达成像[J]电波科学学报,2007,(4):577-582.
[86]王怀军，许洪波，朱宇涛，粟毅，发射分集MIMO雷达融合成像处理方法[J]电子与信息学报，2010,32(1):7-11.
[87]陈伯孝,张守宏.大型随机稀布阵列雷达的脉冲综合方法及其性能[J].系统工程与电子技术.1998,11:46-54..
[88]陈伯孝,张守宏.稀布阵综合脉冲孔径雷达发射信号频率编码的研究.[J]1997,25(09):64-68.
[89]陈伯孝,张守宏.稀布阵综合脉冲孔径雷达时域与频域脉冲综合方法[J].现代雷达.1997,6:12-17.
[90]陈伯孝,张守宏.相位编码信号在综合脉冲孔径雷达中的应用[J].西安电子科技大学学报.1997,24(3):335-341.
[91]冀振元,孟宪德，周和秘.高频地波超视距雷达海杂波信号分析[J].系统工程与电子技术.2000,22(5):12-14.
[92]刘春波，陈伯孝，陈多芳，张守宏.岸-舰双基地高频地波雷达一阶海杂波特性分析[J].电波科学学报.2007,22(4):599-603.
[93]曲翠萍，李秀峰.高频地波超视距雷达的特点和用途[J].雷达与对抗.2007,2:1-3.
[94]鲁振兴，李斌，袁业术.高频地波舰载OTH双基地雷达目标回波特性分析[J].电子与信息学报.2008,30(8):1959-1962.
[95]董英凝，李芳芳，宋晋敏，张宁.高频地波雷达海杂波特性仿真与分析[J].现代防御技术.2008,36(5):243-27.
[96]刘炳奇，肖文书，一种多基地雷达接收信号相参处理的方法现代雷达[J],2009,31(5):30-34.
[97]杨明磊，张守宏，陈伯孝，张焕颖多载频MIMO雷达的一种新的信号处理方法[J]电子与信息学报，2009,31(1):147-151.
[98]戴喜增，许稼，彭应宁，夏香根FD-MIMO距离高分辨雷达及其旁瓣抑制[J]电子与信息学报，2008,30(9):2033-2037.
[99]王成，胡卫东，杜小勇，郁文贤稀疏子带的多频段雷达信号融合超分辨距离成像[J]，电子学报，2006,34(6):985-990.
[100]杨明磊，陈伯孝，秦国栋，张守宏多载频MIMO雷达雷达的空时超分辨算法[J]，电子与信息学报，2009，31(9):2048-2052.
[101]Jian Li, Petre Stoica MIMO Radat with Colocated Antennas, Acoustics,Speech and Signal Processing,2009. ICASSP2009. IEEE InternationalConference on,2009:2089–2092.
[102]位寅生,刘永坦,许荣庆.准随机跳频信号的二维处理[J].电子学报，2003,31(6):801-804..
[103]位寅生,刘永坦.随机断续高频雷达波形设计和处理[J].电子学报，2002,30(3)：437-440.
[104]王勤,万显荣,杨子杰,熊俊志.基于CLEAN算法的非连续谱线性调频中断波信号处理[J].电波科学学报，2009,24(2):243-248.
[105]熊俊志,杨子杰,王勤.基于内插／外推的非连续谱高频雷达二维处理[J].电波科学学报，2006,21(5):735-739.
[106]G. Wang, Y. Lu. Designing single/multiple sparse frequency waveformswith sidelobe constraint [J]. Radar, Sonar&Navigation, IET,2011,5(1):32-38.
[107]Guohua Wang. Optimal Sparse Waveform Design for HFSWR System[C].Waveform Diversity and Design Conference,2007. International,4-8June2007:127-130.
[108]MICHAEL J. LINDENFELD. Sparse Frequency Transmit and ReceiveWaveform Design [J]. Aerospace and Electronic Systems, IEEETransactions on,2004,40(3):851-861.
[109]G. Wang, Y. Lu. Bounds on generalized integrated sidelobe level inwaveforms with stopbands [J]. Electronics Letters,2010,46(23):1561-1562.
[110]Wang guohua. Sparse frequency waveform design based on PSD fitting [C].Acoustics, Speech and Signal Processing (ICASSP),2011IEEEInternational Conference on,22-27May2011:2860-2863.
[111]刘喜武，刘洪，刘彬,反假频非均匀地震数据重建方法研究[J].地球物理学报，2004,47(2):299-305.
[112]Xiang-Ru Li, Zhao Zhang, Wu-Xing Mao, et al. A Study of FrequencyDiversity MIMO Radar Beamforming [C]. ICSP2010IEEE10thInternational Conference on Signal Processing,4-8October2010:352-356.
[113]田建生，吴雄斌，高频雷达工作频率在线实时优化选择[J].现代雷达，2005,27(7):8-10.
[114]Zhang J.J., Papandreou Suppappola A. MIMO Radar with FrequencyDiversity [C], Waveform Diversity and Design Conference2009,8-13Feb.2009:208-212.
[115]陈晓峰,王士同,曹苏群,等.新的稀疏支持向量回归机算法及实验研究[J].计算机工程与应用.2008,44(36)：24-28.
[116]徐蓉,姜峰,姚鸿勋.流形学习概述[J].智能系统学报.2006,1(1)：44-51.
[117]Wen-Qin Wang. Space-Time Coding MIMO-OFDM SAR forHigh-Resolution Imaging [J], Geoscience and Remote Sensing, IEEETransactions on,2011,49(8):3094-3104.
[118]杨海亮，唐劲松，陈鸣，陈昕，基于方位非均匀采样的多子阵合成孔径声呐波数域成像算法，武汉理工大学学报，2011,35(5):993-996.
[119]I. Bradaric, G.T. Capraro, D.D. Weiner, et al. Multistatic Radar SystemsSignal Processing [C]. Radar2006IEEE Conference on，24-27April2006,pp.8.
[120]Michael C. Wicks, Braham Himed, L Justin E. Bracken, et al. Ultra narrowband adaptive tomographic radar, Computational Advances in Multi-SensorAdaptive Processing [C].20051st IEEE International Workshop on,13-15Dec.2005:36.
[121]Braham Himed, Harry Bascom, John Clancy, et al, Tomography of MovingTargets (TMT)[J]. Proc. SPIE4540,608(2001).
[122]Amin Jaffer, Bruce Evans. Parameter Estimation Based CoherentMultistatic Processing [C]. Radar Conference2009IEEE,26may2009:1.
[123]Matthew Herman, Thomas Strohmer. COMPRESSED SENSING RADAR[C]. Radar Conference2008IEEE,22December2008:55.
[124]Ivana Stojanovic, W. Clem Karl, Mujdat Cetin, Compressed sensing ofmono-static and multi-static SAR [J]. Proc. SPIE7337,733705(2009).
[125]D. R. Kirk, J. S. Bergin, P. M. Techau, et al. Multi-Static Coherent SparseAperture Approach to Precision Target Detection and Engagement. RadarConference2005IEEE International, June2005:579.
[126]石光明，刘丹华，高大化，刘哲，林杰，王良军,压缩感知理论及其研究进展[J],电子学报,2005.5,pp.1070-1081.
[127]P.F. Sammartino, C.J. Baker, M. Rangaswamy. Moving target localizationwith multistatic radar systems. Radar Conference2008IEEE,22December2008:17.
[128]Gabriel Lellouch, Radmila Pribic, Piet van Genderen, Merging FrequencyAgile OFDM Waveforms and Compressive Sensing into a Novel RadarConcept. Radar Conference2009European,30October2009:137.
[129]周升辉,杨强,邓维波,压缩感知分布式多输入多输出高频雷达信息处理[J],电波科学学报,2012,pp.409-414
[2] J. Li, P. Stoica. MIMO radar with collocated antennas: Review of somerecent work [J]. IEEE Signal Process. Mag.2007,24(5):106-114.
[3] B. Chen, S. Zhang, Y. Wang, and J. Wang. Analysis and experimentalresults on sparse-array synthetic impulse and aperture radar [J]. Proc.2001CIE Int. Conf. Radar, Oct.2001:76-80.
[4] E. Fishler, A. Haimovich, R. S. Blum. Spatial diversity in radars—modelsand detection performance [J]. IEEE Trans. Signal Processing.2006,54(3):823-838.
[5] N. H. Lehmann, A. M Haimovich, R. S. Blum, L. J. Cimini. High resolutioncapabilities of MIMO radar [C]. Proc.40th Asilomar Conf. Signals,Systems and Computers, Nov.2006:12-14
[6] D. R. Fuhrmann and G. San Antonio, Transmit beamforming for MIMOradar systems using partial signal correlation [C], Proc.38th Asilomar Conf.Signals, Systems and Computers, Nov.2004:295-299.
[7] D. W. Bliss and K. W. Forsythe, Multiple-input multiple-output (MIMO)radar and imaging: Degrees of freedom and resolution [C], Proc.37thAsilomar Conf. Signals, Systems and Computers, Nov.2003:54-59.
[8] D. Rabideau, Ubiquitous MIMO digital array radar [C], Proc.37th AsilomarConf. Signals, ystems, and Computers, Nov.2003:1057-1064.
[9] Nadav Levanon.“Multifrequency radar signals”, Records of the IEEE2000International Radar Conference, Alexandria, VA,2000a:683-688.
[10] F. C. Robey, S. Coutts, D. Weikle, J. C. McHarg, and K. Cuomo, MIMOradar theory and experimental results [C], Proc.38th Asilomar Conf.Signals, Systems and Computers, Nov.2004:300-304.
[11] I. Bekkerman and J. Tabrikian, Target detection and localization usingMIMO radars and sonars [J], IEEE Trans. Signal Process200654(5):3873--3883.
[12] L. Xu, J. Li, and P. Stoica, Adaptive techniques for MIMO radar [C], Proc.14th IEEE Workshop on Sensor Array and Multi-channel Processing,Waltham, MA, July2006:55-58
[13] N. Lehmann, A. M. Haimovich, R. S. Blum, and L. Cimini, MIMO-radarapplication to moving target detection in homogenous clutter, Proc.14thIEEE Workshop on Sensor Array and Multi-channel Processing [C],Waltham, MA, July2006:706-715.
[14] Hightower J, Borriello G. Location Systems for Ubiquitous Computing [J].IEEE Computer.2001,34:57-66.
[15] N. H. Lehmann, A. M Haimovich, R. S. Blum, and L. J. Cimini, Highresolution capabilities of MIMO radar, Proc.40th Asilomar Conf. Signals,Systems and Computers, Nov.2006:71-75
[16] E. Fishler, A. Haimovich, R. Blum, L. Cimini, D. Chizhik, and R.Valenzuela, Performance of MIMO radar systems: Advantages of angulardiversity, Proc.38th Asilomar Conf. Signals, Systems and Computers, Nov.2004:305-309.
[17] Y. Yang and R. S. Blum, Radar waveform design based on mutualinformation and mean-square error estimation, IEEE Trans. AerospaceElectron. Syst. Jan.2007,43:330-343.
[18] J. Li, P. Stoica, and Y. Xie, On probing signal design for MIMO radar [C],Proc.40th Asilomar Conf. Signals, Systems and Computers, Pacific Grove,CA, Oct.2006：331-334
[19] J. Li, P. Stoica, L. Xu, and W. Roberts, On parameter identifiability ofMIMO radar [J], IEEE Signal Process. Lett.14(12) Dec.2007:968-971.
[20] J. Li, L. Xu, P. Stoica, K. W. Forsythe, and D. W. Bliss, Range compressionand waveform optimization for MIMO radar: A Crame′r-Rao bound basedstudy [C], IEEE Trans. Signal Process.56(1) Jan.2008:218-232.
[21] V. F. Mecca, D. Ramakrishnan, and J. L. Krolik, MIMO radar space-timeadaptive processing for multipath clutter mitigation [C], Proc.4th IEEEWorkshop on Sensor Array and Multi-channel Processing, Waltham, MA,July2006:227-231
[22] D. J. Rabideau and P. Parker, Ubiquitous MIMO multifunction digital arrayradar [C], Proc.37th Asilomar Conf. Signals, Systems and Computers,Pacific Grove, CA, Nov.2003:114-117
[23] P. Stoica, J. Li, and Y. Xie, On probing signal design for MIMO radar [J],IEEE Trans. Signal Process.55(8) Aug.2007:4151-4161.
[24] J. Tabrikian, Barankin bounds for target localization by MIMO radars [C],Proc.4th IEEE Workshop on Sensor Array and Multi-channel Processing,Waltham, MA, July2006:231-234
[25] K. W. Forsythe, D. W. Bliss, and G. S. Fawcett, Multiple-inputmultiple-output (MIMO) radar: Performance issues [C], Proc.38thAsilomar Conf. Signals, Systems and Computers, Pacific Grove, CA, Nov.2004, Vol.1:310-315.
[26] T. Aittomaki and V. Koivunen, Low-complexity method for transmitbeamforming in MIMO radars [C], Proc.2007IEEE Int. Conf. Acoustics,Speech, and Signal Processing, Honolulu, April2007:512-514
[27] G. San Antonio and D. R. Fuhrmann, Beampattern synthesis for widebandMIMO radar systems [C], Proc.1st IEEE Int. Workshop CAMSAP, PuertoVallarta, Mexico, Dec.2005:105-108.
[28] D. R. Fuhrmann and G. San Antonio, Transmit beamforming for MIMOradar systems using partial signal correlation, IEEE Trans. AerospaceElectron. Syst.43(4)(Oct.2007):42-47.
[29] D. Bliss and K. Forsythe, Multiple-input multiple-output (MIMO) radar andimaging: Degrees of freedom and resolution, Proc.37th Asilomar Conf.Signals, Systems, and Computers, Monterey, CA,2003:54–59.
[30] K. W. Forsythe and D. W. Bliss, Waveform correlation and optimizationissues for MIMO radar, Proc.39th Asilomar Conf. Signals, Systems andComputers, Pacific Grove, CA, Nov.2005:1306-1310.
[31] J. Tabrikian and I. Bekkerman, Transmission diversity smoothing formulti-target localization [C], Proc.2005IEEE Int. Conf. Acoustics, Speech,and Signal Processing, Philadelphia, PA, March2005, Vol.4:1041–1044.
[32] L. Xu, J. Li, and P. Stoica, Adaptive techniques for MIMO radar [C], Proc.4th IEEE Workshop on Sensor Array and Multi-channel Processing,Waltham, MA, July2006:105-108
[33] L. Xu, J. Li, P. Stoica, K. W. Forsythe, and D. W. Bliss, Waveformoptimization for MIMO radar: A Cramer-Rao bound based study [C], Proc.2007IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Honolulu,April2007:512-514
[34] L. Xu and J. Li, Iterative generalized likelihood ratio test for MIMOradar,IEEE Trans. Signal Process.55(6)2007:2375-2385.
[35] Gordon J. Frazer, Yuri I. Abramovich, Ben A. Johnson. Spatially WaveformDiverse Radar: Perspectives for High Frequency OTHR [C], In Proc. RadarConference. Boston, MA, USA: IEEE, Apr17-202007:385-390.
[36] Gordon J. Frazer, Ben A. Johnson, Yuri I. Abramovich. OrthogonalWaveform Support in MIMO HF OTH Radars [C], In Proc. WaveformDiversity and Design Conference. June4-82007:423-427.
[37] G. Dickel, D.J. Emery, D.G. Money, The architecture and operatingcharacteristics a multi-frequency HF surface wave Radar–part two, Intl.Radar Conf. RADAR2007, Edinburgh, UK, Oct15-18,2007:3-10.
[38] Y. Teng, H.D. Griffiths, C.J. Baker, K. Woodbridge. Netted radar sensitivityand ambiguity”, IET Radar Sonar Naving.,2007,1(6):479-486.
[39] Qu JinYou, Zhang Jian Yun, Liu ChunQuan. The Ambiguity Function ofMIMO Radar [C], Microwave, Antenna, Propagation and EMCTechnologies for Wireless Communications,2007International Symposiumon,16-17Aug.2007:265-268
[40] Fred Daum, Jim Huang MIMO radar: snake oil or good idea, Signals,Systems and Computers [C],200842nd Asilomar Conference on,2008:183–187.
[41] Shenghua Zhou, Hui Xu, Liangbing Hu, Hongwei Liu Research forScattering Properties of Spatial and Frequency Diversity MIMO Radartargets [C], Signal Processing,2008. ICSP2008.9th InternationalConference on,2008:2533–2537.
[42] Alexander M. Haimovich, Rick S.Blum, and Leonard J. Cimini, Jr. MIMORadar Widely Seperated Antennas, Information Sciences and Systems,2008.CISS2008.42nd Annual Conference on,2008:123–127.
[43] P.F. Sammartino, C.J. Baker. The Frequency Diverse Bistatic System,Waveform Diversity and Design Conference,2009International,2009:155–159.
[44] Xizeng Dai, Jia Xu, Yingning Peng High Resolution Frequency MIMORadar, Radar Conference2007IEEE,2007:693–698.
[45] Earnest Lock, Raviraj S. Adve. Othogonal Frequency Division Multiplexingin Distributed Radar Apertures, Radar Conference,2008. RADAR '08.IEEE,2008:1–6.
[46] Chen Duofang, Chen Baixiao, Zhang Shouhong. Multiple-inputMultiple-output Radar and Sparse Array Synthetic Impulse and ApertureRadar, Radar,2006. CIE '06. International Conference on,2006:1–4.
[47] Raviraj S. Adve, Richard A. Schneible, Gerard Genello, Paul Antonik.Waveform-Space-Time Adaptive Processing for Distributed ApertureRadars, Radar Conference,2005IEEE International,2005:93-97.
[48] Raviraj S. Adve, Lorne Applebaum, Michael C. Wicks, Richard A.Schneible. Space-Time-Wave Adaptive Processing for Frequency DiverseDistributed Radar Apertures, Information Sciences and Systems,200640thAnnual Conference on,2006:1413-1417.
[49] Jiang Wei, Wang Ju, Wu Siliang, Wang Dajun. Coherent Detection andAmbiguity Resolution for Frequency Diversity Separated Subarray Radar.Signal Processing,2008. ICSP2008:2364-2367.
[50] Chunyang Chen, P.P. Vaidyanathan. Beamforming issues in modern MIMORadars with Doppler [C], Signals, Systems and Computers,2006. ACSSC'06. Fortieth Asilomar Conference on,2006:41-45.
[51] Long Zhuang, Xingzhao Liu. Coherent Synthesis Sparse Aperture Radarwith Grating lobes Suppressed Using Freqency MIMO Technique [J], RadarConference,2008. RADAR '08. IEEE,2008:1–5.
[52] D.J. Emery, G. Dickel. The Operation and Performance of a Multi-FreqencyHF Surfacewave Radar [C], Radar Conference,2008. RADAR '08. IEEE:1-6.
[53] Qian He, Rick S. Blum, Hana Godrich, Alexander M. Haimovich.Cramer-Rao Bound for Target Velocity Estimation in MIMO Radar withWidely Separated Antennas, Information Sciences and Systems,2008. CISS2008.42nd Annual Conference on:123–127.
[54] K.W. Forsythe, D.W. Bliss, G.S. Fawcett. Multiple-InputMultiple-Output(MIMO) Radar: Performance Issues, Signals, Systems andComputers,2004. Conference Record of the Thirty-Eighth AsilomarConference on, Vol.1:310-315.
[55] R.Mohseni, A.Sheikhi, M.A. Masnadi Shirazi. A new approach to compressmulticarrier phase-coded signals, Radar Conference,2008. RADAR '08.IEEE:1–6.
[56] W.X. Liu, Y.L. Lu, M. Lesturgie. Optimal sparse waveform design forHFSWR system, Waveform Diversity and Design Conference,2007.International,2007:127–130.
[57] Zengjiankui, Hezishu, Liubo. Adaptive Space-time-waveform processingfor MIMO Radar, Communications, Circuits and Systems,2007. ICCCAS2007. International Conference on,2007:641–643.
[58] Raviraj Adve, Richard Schneible, Robert McMillan. AdaptiveSpace/Frequency Processing for Distributed Aperture Radars, RadarConference,2003. Proceedings of the2003IEEE,2003:160–164.
[59] Hai Deng. Polyphase code design for orthogonal netted radar systems,Signal Processing, IEEE Transactions on,2004:3126–3135.
[60] Bo Liu, Zishu He, Jiankui Zeng, Benyong Liu. Polyphase orthogonal codedesign for MIMO radar systems [C], Radar,2006. CIE '06. InternationalConference on,2006:1–4.
[61] Chunyang Chen, P.P. Vaidyanathan. Properties of the MIMO radarambiguity function, Acoustics, Speech and Signal Processing,2008.ICASSP2008. IEEE International Conference on,2008:2309–2312.
[62] Jian Li, Luzhou Xu, Petre Stoica, Keith W. Forsythe, Daniel W. Bliss.Range Compression and Waveform Optimization for MIMO Radar: ACramér–Rao Bound Based Study, Signal Processing, IEEE Transactions on,2008:218–232.
[63] Jian Li, Petre Stoica, Luzhou Xu, William Roberts. On ParameterIdentifiability of MIMO Radar, Signal Processing Letters, IEEE,2007:968–971.
[64] D.W. Bliss, K.W. Forsythe. Multiple-input Multiple-out (MIMO) Radar andImaging Degrees of Freedom and Resolution, Signals, Systems andComputers,2003. Conference Record of the Thirty-Seventh AsilomarConference on,2003Vol.1:54-59.
[65] S D Green, S P Kingsley. Investigation of wide bandwith HF radarwaveforms, Advanced Transmission Waveforms, IEE Colloquium on,1995:2/1-2/8.
[66] S D Green, S P Kingsley. Improving the range/time sidelobe of largebandwidth discontinuous spectra HF radar waveforms, HF Radio Systemsand Techniques, Seventh International Conference on (Conf. Publ. No.441),1997:246–250.
[67] Nikolaus H. Lehmann, Alexander M. Haimovich, Rick S. Blum, Len Cimini.High Resolution Capabilities of MIMO Radar, Signals, Systems andComputers,2006. ACSSC '06. Fortieth Asilomar Conference on,2006:25–30.
[68] Ioannis Papoutsis. Netted Radar and Ambiguity Function,2006. CIE '06.International Conference on,2006:1–4.
[69] G.J. Frazer, Y.I. Abramovich, B.A. Jonson. Use of Adaptive Non-CausalTransmit Beamforming in OTHR: Experimental Results, Radar2008International Conference on,2008:311–316.
[70] G.J. Frazer, Y.I. Abramovich, B.A. Jonson, F.C. Robey. Recent Results inMIMO Over-the-Horizon Radar [C],2008. RADAR '08. IEEE,2008:1-6.
[71] Jeffrey Krolik, Vito Mecca, Oguz Kazanci, Igal Bilik. MultipathSpread-Doppler Clutter Mitigation for Over-the-Horizon Radar[C], RadarConference,2008. RADAR '08. IEEE,2008:1-5.
[72] Frank C. Robey, Scott Coutts, Dennis Weikle, Jeffrey C.McHarg, KevinCuomo. MIMO Radar Theory and Experimental Results, Signals, Systemsand Computers,2004. Conference Record of the Thirty-Eighth AsilomarConference on,2004Vol.1:300-304.
[73] G.J. Frazer, Y.I. Abramovich, B.A. Johnson. MIMO Radar Limitations inClutter, Radar Conference,2009IEEE,2009:1-5.
[74] M. Lesturgie. Improvement of high-frequency surface waves radarperformance by use of multi-input multi-output configurations, Radar,Sonar&Navigation, IET,2009:49-61.
[75] Guohua Wang, Yilong Lu. High Resolution MIMO-HFSWR Using SparseFrequency Waveform, Signal Processing,2008. ICSP2008.9thInternational Conference on,2008:2238–2241.
[76] Eran Fishler, Alex Haimovich, Rick S.Blum. Spatial Diversity inRadars-Models and Detecttion Performance, Signal Processing, IEEETransactions on,2006:823-838.
[77] Eran Fishler, Alex Haimovich, Rick S.Blum. Performance of MIMO RadarSystems: Advantages of Angular Diversity, Signals, Systems andComputers,2004. Conference Record of the Thirty-Eighth AsilomarConference on,2004,:305-309.
[78] P.F. Sammartino, C.J. Baker, H.D. Griffiths. Target Model Effects onMIMO Radar Performance, Acoustics, Speech and Signal Processing,2006.ICASSP2006Proceedings.2006IEEE International Conference on,2006:20-24.
[79] Jun Jason Zhang, Antonia Papandreou-Suppappola MIMO Radar withFrequency Diversity, Waveform Diversity and Design Conference,2009International,2009:208–212.
[80] Abbas Sheikhi, Ali Zamani. Coherent Detection for MIMO Radars, RadarConference,2007IEEE,2007:302-307.
[81] Byung Wook Jung, Raviraj S. Adve, Joohwan. Frequency Diversity inMultistatic Radars, Radar Conference,2008. RADAR '08. IEEE,2008:1-6.
[82]王怀军,粟毅,朱宇涛,许洪波，基于空间谱域填充的MIMO雷达成像研究[J].电子学报,2009,(06):1242-1246.
[83]王怀军，许洪波，陆珉，粟毅,基于MIMO雷达的高分辨成像方法[J],微波学报,2009,(10):79-83.
[84]赵光辉，陈伯孝，黄白，多频体制下虚拟阵列影射聚焦方法[J],西安交通大学学报，2009，43(4):66-69.
[85]张祥坤，张云华，姜景山，多视角聚束合成孔径雷达成像[J]电波科学学报,2007,(4):577-582.
[86]王怀军，许洪波，朱宇涛，粟毅，发射分集MIMO雷达融合成像处理方法[J]电子与信息学报，2010,32(1):7-11.
[87]陈伯孝,张守宏.大型随机稀布阵列雷达的脉冲综合方法及其性能[J].系统工程与电子技术.1998,11:46-54..
[88]陈伯孝,张守宏.稀布阵综合脉冲孔径雷达发射信号频率编码的研究.[J]1997,25(09):64-68.
[89]陈伯孝,张守宏.稀布阵综合脉冲孔径雷达时域与频域脉冲综合方法[J].现代雷达.1997,6:12-17.
[90]陈伯孝,张守宏.相位编码信号在综合脉冲孔径雷达中的应用[J].西安电子科技大学学报.1997,24(3):335-341.
[91]冀振元,孟宪德，周和秘.高频地波超视距雷达海杂波信号分析[J].系统工程与电子技术.2000,22(5):12-14.
[92]刘春波，陈伯孝，陈多芳，张守宏.岸-舰双基地高频地波雷达一阶海杂波特性分析[J].电波科学学报.2007,22(4):599-603.
[93]曲翠萍，李秀峰.高频地波超视距雷达的特点和用途[J].雷达与对抗.2007,2:1-3.
[94]鲁振兴，李斌，袁业术.高频地波舰载OTH双基地雷达目标回波特性分析[J].电子与信息学报.2008,30(8):1959-1962.
[95]董英凝，李芳芳，宋晋敏，张宁.高频地波雷达海杂波特性仿真与分析[J].现代防御技术.2008,36(5):243-27.
[96]刘炳奇，肖文书，一种多基地雷达接收信号相参处理的方法现代雷达[J],2009,31(5):30-34.
[97]杨明磊，张守宏，陈伯孝，张焕颖多载频MIMO雷达的一种新的信号处理方法[J]电子与信息学报，2009,31(1):147-151.
[98]戴喜增，许稼，彭应宁，夏香根FD-MIMO距离高分辨雷达及其旁瓣抑制[J]电子与信息学报，2008,30(9):2033-2037.
[99]王成，胡卫东，杜小勇，郁文贤稀疏子带的多频段雷达信号融合超分辨距离成像[J]，电子学报，2006,34(6):985-990.
[100]杨明磊，陈伯孝，秦国栋，张守宏多载频MIMO雷达雷达的空时超分辨算法[J]，电子与信息学报，2009，31(9):2048-2052.
[101]Jian Li, Petre Stoica MIMO Radat with Colocated Antennas, Acoustics,Speech and Signal Processing,2009. ICASSP2009. IEEE InternationalConference on,2009:2089–2092.
[102]位寅生,刘永坦,许荣庆.准随机跳频信号的二维处理[J].电子学报，2003,31(6):801-804..
[103]位寅生,刘永坦.随机断续高频雷达波形设计和处理[J].电子学报，2002,30(3)：437-440.
[104]王勤,万显荣,杨子杰,熊俊志.基于CLEAN算法的非连续谱线性调频中断波信号处理[J].电波科学学报，2009,24(2):243-248.
[105]熊俊志,杨子杰,王勤.基于内插／外推的非连续谱高频雷达二维处理[J].电波科学学报，2006,21(5):735-739.
[106]G. Wang, Y. Lu. Designing single/multiple sparse frequency waveformswith sidelobe constraint [J]. Radar, Sonar&Navigation, IET,2011,5(1):32-38.
[107]Guohua Wang. Optimal Sparse Waveform Design for HFSWR System[C].Waveform Diversity and Design Conference,2007. International,4-8June2007:127-130.
[108]MICHAEL J. LINDENFELD. Sparse Frequency Transmit and ReceiveWaveform Design [J]. Aerospace and Electronic Systems, IEEETransactions on,2004,40(3):851-861.
[109]G. Wang, Y. Lu. Bounds on generalized integrated sidelobe level inwaveforms with stopbands [J]. Electronics Letters,2010,46(23):1561-1562.
[110]Wang guohua. Sparse frequency waveform design based on PSD fitting [C].Acoustics, Speech and Signal Processing (ICASSP),2011IEEEInternational Conference on,22-27May2011:2860-2863.
[111]刘喜武，刘洪，刘彬,反假频非均匀地震数据重建方法研究[J].地球物理学报，2004,47(2):299-305.
[112]Xiang-Ru Li, Zhao Zhang, Wu-Xing Mao, et al. A Study of FrequencyDiversity MIMO Radar Beamforming [C]. ICSP2010IEEE10thInternational Conference on Signal Processing,4-8October2010:352-356.
[113]田建生，吴雄斌，高频雷达工作频率在线实时优化选择[J].现代雷达，2005,27(7):8-10.
[114]Zhang J.J., Papandreou Suppappola A. MIMO Radar with FrequencyDiversity [C], Waveform Diversity and Design Conference2009,8-13Feb.2009:208-212.
[115]陈晓峰,王士同,曹苏群,等.新的稀疏支持向量回归机算法及实验研究[J].计算机工程与应用.2008,44(36)：24-28.
[116]徐蓉,姜峰,姚鸿勋.流形学习概述[J].智能系统学报.2006,1(1)：44-51.
[117]Wen-Qin Wang. Space-Time Coding MIMO-OFDM SAR forHigh-Resolution Imaging [J], Geoscience and Remote Sensing, IEEETransactions on,2011,49(8):3094-3104.
[118]杨海亮，唐劲松，陈鸣，陈昕，基于方位非均匀采样的多子阵合成孔径声呐波数域成像算法，武汉理工大学学报，2011,35(5):993-996.
[119]I. Bradaric, G.T. Capraro, D.D. Weiner, et al. Multistatic Radar SystemsSignal Processing [C]. Radar2006IEEE Conference on，24-27April2006,pp.8.
[120]Michael C. Wicks, Braham Himed, L Justin E. Bracken, et al. Ultra narrowband adaptive tomographic radar, Computational Advances in Multi-SensorAdaptive Processing [C].20051st IEEE International Workshop on,13-15Dec.2005:36.
[121]Braham Himed, Harry Bascom, John Clancy, et al, Tomography of MovingTargets (TMT)[J]. Proc. SPIE4540,608(2001).
[122]Amin Jaffer, Bruce Evans. Parameter Estimation Based CoherentMultistatic Processing [C]. Radar Conference2009IEEE,26may2009:1.
[123]Matthew Herman, Thomas Strohmer. COMPRESSED SENSING RADAR[C]. Radar Conference2008IEEE,22December2008:55.
[124]Ivana Stojanovic, W. Clem Karl, Mujdat Cetin, Compressed sensing ofmono-static and multi-static SAR [J]. Proc. SPIE7337,733705(2009).
[125]D. R. Kirk, J. S. Bergin, P. M. Techau, et al. Multi-Static Coherent SparseAperture Approach to Precision Target Detection and Engagement. RadarConference2005IEEE International, June2005:579.
[126]石光明，刘丹华，高大化，刘哲，林杰，王良军,压缩感知理论及其研究进展[J],电子学报,2005.5,pp.1070-1081.
[127]P.F. Sammartino, C.J. Baker, M. Rangaswamy. Moving target localizationwith multistatic radar systems. Radar Conference2008IEEE,22December2008:17.
[128]Gabriel Lellouch, Radmila Pribic, Piet van Genderen, Merging FrequencyAgile OFDM Waveforms and Compressive Sensing into a Novel RadarConcept. Radar Conference2009European,30October2009:137.
[129]周升辉,杨强,邓维波,压缩感知分布式多输入多输出高频雷达信息处理[J],电波科学学报,2012,pp.409-414
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |