极化敏感阵列信号处理的研究
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摘要
极化敏感阵列是指极化敏感阵元按一定方式在空间放置所构成的阵列系统,利用极化敏感阵元可获取空间电磁信号的极化信息,利用阵列几何结构进行空域采样可获取信号的空域信息。和普通阵列相比,极化敏感阵列具有优越的系统性能:较强的抗干扰能力、稳健的检测能力、较高的分辨能力以及极化多址能力,因此极化敏感阵列具有重要的军事和民事应用价值。论文以极化敏感阵列为研究对象,研究了信号滤波、检测及参量估计等一系列信号处理过程,从理论上定量地证明了极化敏感阵列的优势和潜能。研究将丰富阵列信号处理理论,指导极化敏感阵列系统设计,为现代战场信息感知与处理提供有力的技术支撑,为解决移动通信领域中的关键问题提供崭新的研究思路。
     极化敏感阵列信号滤波主要研究利用干扰信号与期望信号空域和极化域的特征差异抑制干扰、增强信号的问题。首先,分析了已有滤波准则的性能并提出了一种新的滤波准则。然后,研究了完全极化、部分极化以及相关干扰条件下极化敏感阵列的滤波性能。证明了极化敏感阵列比普通阵列具有更强的抗干扰能力,干扰方要想获得有效的干扰效果,“最佳”干扰信号不仅到达角要和期望信号接近或相同,而且极化状态也要和期望信号接近或相同。在相同硬件设备量的前提下和普通阵列相比,在牺牲了部分空域滤波能力的条件下换取了极化域滤波能力。期望信号极化度越高,阵列滤波性能越好;干扰信号极化度越高,干扰越容易被抑制。期望信号和干扰信号相关性越强,阵列滤波性能差异越明显,且相关系数的相位影响着“最佳”干扰信号的空间到达角。最后,提出了一种双信息信号传输的方案并导出了无互扰传输的充要条件:两期望信号的信号矢量在以干扰噪声协方差矩阵的逆矩阵为加权矩阵的加权内积空间中正交,在给定的电磁环境下设计了双信息信号的极化状态。
     极化敏感阵列信号检测主要研究待检测方向上广义噪声背景中未知极化信号的检测问题。首先,研究了匹配子空间检测理论和自适应子空间检测理论。归结起来,当噪声水平已知时,匹配子空间检测器属于“能量型”检测器;当噪声水平未知时,匹配子空间检测器属于“角度型”检测器。所有匹配子空间检测器都具有CFAR特性。在背景噪声协方差矩阵未知条件下,借鉴Kelly的研究思路,利用GURR思想导出了自适应子空间检测器。然后,利用匹配子空间检测理论研究了极化敏感阵列对完全极化信号的检测问题,极化状态未知的信号必定落入一个与到达方向有关的确定的二维子空间内。当附近存在干扰信号或信号到达角偏离波束方向时,信号的检测性能均下降。和普通阵列检测性能相比,极化敏感阵列对于任意极化信号具有恒定的检测特性,称为“恒极化”检测特性。最后,研究了极化敏感阵列对部分极化信号检测问题。
     极化敏感阵列信号参量估计主要研究利用极化敏感阵列的一系列采样数据对信号空间到达角和极化状态角的联合估计问题。首先,利用典型的子空间类高分辨谱估计MUSIC
    
    国防科学技术大学研究生院学位论文
    算法构建了极化域一空域联合谱,根据谱峰位置估计信号的到达角和极化状态角。其次,
    深入研究了联合谱的两项重要性能指标:谱估计精度和分辨力。用克拉美一劳限(CRB)来
    衡量信号到达角和极化角的估计精度,利用Fisher信息矩阵求逆导出信号到达角和极化角
    CRB的解析表达式,两信号特征参量接近时,它们的估计精度均下降。借助于MUsIC零
    谱的统计特性研究了极化域一空域联合谱的分辨力,提出极化域一空域模糊图和极化敏感
    阵列信号模糊函数的概念描述系统的分辨性能,当两信号到达角相同时信号不能被分辨开
    来;当信号到达角不同时,极化状态的差别可以改善系统的分辨力;信号特征参量固定时
    要将信号成功分辨需要的信噪比与采样点数总量是恒定的。然后,提出了“序贯”处理方
    式下联合谱的自适应递推估计算法对信号参量进行实时测量。最后,将己获得的极化信息
    应用到目标跟踪领域解决目标关联问题,提出广义“最近邻”数据关联算法。
     最后总结了极化敏感阵列信号滤波、检测以及参量估计三部分的区别与联系,构建了
    极化敏感阵列实验系统框架,归纳了论文的创新点,并指出了后续值得研究的方向。
    关键词:极化敏感阵列;滤波;期望信号;干扰信号;完全极化;部分极化;相关;检测;
    匹配子空间检测;自适应子空间检测;估计;极化域一空域联合谱;估计精度;克拉美一
    劳限;分辨力;模糊图;模糊函数;“序贯”处理;广义“最近邻’,;
    第n页
Polarization Sensitive Array (PSA) can acquire the polarization information besides the spatial information of the Electromagnetic signals, which consists of a group of polarization sensitive elements. PSA outperforms the common arrays due to the additional polarization information. PSA possesses strong anti-jamming ability, robust detecting performance, high resolving power and polarization multi-address capability. Therefore, PSA will play an important role in both military and civil areas due to these advantages. This dissertation focuses on the signal processing of PSA, including signal filtering, signal detection and signal parameter estimation to demonstrate the advantages of PSA over common arrays quantitatively, theoretically. The investigation will enrich the theory of array signal processing and guide the systemic design of PAS. In addition, it will avail to gather and process the information of modem war and provide novel ideas for the bottle-neck in the 3rd generation mobile communication.Signal filtering of PSA means suppressing interference and enhancing the desired signal, using the difference between desired signal and interference in spatial and polanzational domains. At first, the well-known filtering criterions are analyzed comparatively and a novel criterion is brought forth under multiple desired signals case. Then, the filtering performance is investigated under completely polarized case, partially polarized case and correlative case. It is showed that the PSA is more difficult to jam. To produce a poor SINR, the optimal interference signal must both arrive from the same direction and have the same polarization as the desired signal. With equal hardware equipment, PSA obtain the polarizational filtering ability at the cost of losing partial spatial filtering ability. The higher the polarization degree of desired signal being, the better filtering performance is. The higher the polarization degree of interference being, the interference can be suppressed more easily. The correlative coefficient between desired signal and interference affects the filtering performance strongly, which changes the direction of optimal interference. At last, the Double Message Signal is proposed and the non-interfere condition is presented that the steering vectors are orthogonal in the weighted inner product space, with the inverse matrix of background covariance as the weighting matrix. The optimal polarization states are designed, according to the EM background.Signal detection of PSA means detecting the signal at given direction with unknown polarization state under generalized noise background. At first, Matched Subspace Detector (MSD) and Adaptive Subspace Detector (ASD) are derived theoretically. With known noise level, the MSD is of "power type". With unknown noise level, the MSD is of "angle type". All the MSDs possess CFAR property. When the covariance of noise is unknown, the ASD is derived by using Kelly's thought for reference. Then, the signal detection of completely polarized is
    
    investigated with exploiting the MSD theory. It is shown that the detection probability decreases when interference approaches signal in spatial domain and when the signal direction is misaligned with the look direction. Compared with the common arrays, the detection performance is independent of polarization state of signal, called "Constant Polarization Detection". At last, the signal detection of partially polarized is investigated thoroughly.Signal parameter estimation of PSA means estimating the angles of arrival and the polarization angles simultaneously according to the samples of PSA. Firstly, the joint spectrum is established in polarizational and spatial domains utilizing the MUSIC algorithm. The positions of spectrum peaks indicate the characteristic parameters of EM signals. Secondly, the estimation accuracy and resolving power of joint spectrum are investigated. The Cramer-Rao bound (CRB) is used to evaluate the estimation accuracy, obtained thought inversing the Fisher Information Matrix. The estimation accuracy of
引文
[1] 庄钊文,削顷平,王雪松,雷达极化信息处理及应用,北京:国防工业出版社,1999
    [2] 王雪松,宽带极化信息处理的研究,长沙:国防科技大学博士论文,1999
    [3] 张贤达,现代信号处理,北京,清华大学出版社,1995
    [4] 柳重堪,信号处理中的数学方法,南京:东南大学出版社,1992
    [5] 张贤达,信号处理中的线性代数,北京:科学出版社,1997
    [6] 张明淳,工程矩阵理论,南京:东南大学出版社,1995
    [7] 戴华,矩阵论,北京:科学出版社,2002
    [8] 刘克成,宋学诚,天线原理,长沙:国防科技大学出版社,1989
    [9] H.莫特(著),林昌禄(译),天线和雷达中的极化,成都:电子科技大学出版社,1989
    [10] Dino Giuli. Polarization diversity in radars. IEEE Proc., 1986, 74(2): 245~269
    [11] 王永良,彭应宁,空时自适应信号处理,北京:清华大学出版社,1999
    [12] 张光义,相控阵雷达系统,北京:国防工业出版社,1994
    [13] 刘德树,雷达反对抗的基本理论与技术,北京:北京理工大学出版社,1989
    [14] 王永德,龙宪惠(译),自适应信号处理,成都:四川大学出版社,1989
    [15] 沈铁汉,梁福生,石镇(译),自适应阵导论,北京:国防工业出版社,1988
    [16] 石镇,自适应天线原理,北京:国防工业出版社,1991
    [17] 马凉(译),无线通信中的智能天线:IS—95和第三带CDMA中的应用,北京:机械工业出版社,2002
    [18] Richard A. Poisel(著),吴汉平等(译),通信电子战系统导论,北京:电子工业出版社,2003
    [19] Simon Haykin. Adaptive Filter Theory (Third Edition), Prentice Hall, 1996
    [20] 张贤达,保铮,通信信号处理,北京:国防工业出版社,2000
    [21] 吴伟陵,移动通信中的关键技术,北京:北京邮电大学出版社,2000
    [22] 何振亚,自适应信号处理,北京:科学出版社,2002
    [23] R. T. Compton, JR. On the performance of a polarization sensitive adaptive array. IEEE Trans. AP, 1981, 29(5): 718~725
    [24] R. T. Compton, JR. The tripole antenna: an adaptive array with full polarization flexibility. IEEE Trans. AP, 1981, 29(6): 944~952
    [25] R. T. Compton, JR. The performance of a tripole adaptive array against cross-polarized jamming. IEEE Trans. AP, 1983, 31(4): 682~4585
    [26] Ioannis Kaptsis, Keith G. Balmain. Base station polarization-sensitive adaptive antenna for mobile radio. IEEE Third Annual International Conference on Universal Personal Communications, 1994, 230~235
    
    [27] Arye Nehaorai, Kwok-Chiang Ho, B.T.G Tan. Minimum-noise-variance beamformer with an electromagnetic vector sensor. IEEE Trans. SP, 1999,47(3):601~618
    [28] Mitoshi Fujumoto, Kunitoshi Nishikawa, Analysis of adaptive array using polarization characteristics of arrival waves, Electronics and Communications in Japan, Part 1, 2000, 83(12):37~48
    [29] R.G Vaughan, J. Bach Andersen. Antenna diversity in mobile communications. IEEE Trans. VT, 1987,36(4):149~172
    [30] R.G Vaughan. Polarization diversity in mobile communications. IEEE Trans. VT, 1990, 39(3): 177-186
    [31] Randolph L. Moses, A.A. (Louis) Beex. Instrumental variable adaptive array processing. IEEE Trans. AES, 1988,24(2):192~201
    [32] Y. Wang. K. Oumansour, E. Potter, J. Sailard. Adaptive processing in radar polarimetry. SPIE, 1992, 1748,225-233
    [33] H.S. LU. Polarization Separation by an adaptive filter. IEEE Trans. AES, 1973, 9(6):954~956
    [34] SIDNEY P. APPLERAUM. Adaptive arrays. IEEE Trans. AP, 1976,24(5):585~598
    [35] L.E.Brennan, L.S.Reed. Theory of Adaptive Radar. IEEE Trans. AES, 1973, 9(2):237-252
    [36] D.M. BOROSON. Sample size considerations for adaptive arrays. IEEE Trans. AES, 1980, 16(4):446~451
    [37] KAZUAKI TAKAO, KOJI KOMIYAMA. An adaptive antenna for rejection of wideband interference. IEEE Trans. AES, 1980,16(4):452~459
    [38] AKIRAISHIDE, R.T.COMPTON,JR.. On grating nulls in adaptive arrays. IEEE Trans. AP, 1980,28(4):467-475
    [39] INDER J.GUPTA, AHARON A.KSIENSKI. Effect of mutual coupling on the performance of adaptive arrays. IEEE Trans. AP, 1983, 31(5):785~791
    [40] D.Giuli, M.Fossi, M.Gherardelli. A technique for adaptive polarization filtering in radars. IEEE International radar conference, 1985,213-219
    [41] Loutin, E.A.; Kozlov, A.I.; Logvin, A.I. The synthesis of optimal structure of radar using polarization adaptive. IGARSS, 1996, Vol. 1:299-304
    [42] Chul Jai Lee, Hong Wang, Clifford Tsao. An adaptive clutter polarization canceler for UWB radar. SPIE, 1993, 1875:23-32
    [43] Wang, H., Yuhong Zhang; Qingwen Zhang. A view of current status of space-time processing algorithm research. Radar Conference, 1995, 635-640
    [44] Czyz, Z.H. New concept of virtual polarisation adaptation. Eighth International Conference on Antennas and Propagation, 1993, Vol.2:890~893
    [45] Clark, C.R. Main beam jammer cancellation and target angle estimation with a polarization-agile monopulse antenna. Radar Conference, 1989, 95~100
    [4
    
    [46] Michel, G. E., Durand, J. C., Carrara, B. Effect of jamming on efficiency of anti-clutter polarimetric filter. International Radar Conference, 1992, 510~513
    [47] Dujardin, E., Durrand, J. C., Carrara, B. Polarimetric features of ground clutter: experimental results, impact on coherent vectorial clutter-map design. Radar Conference, 1993, 46~50
    [48] R. S. Raghavan, N. Pulsone. Adaptive estimation of the polarization of a signal. IEEE Trans. AES, 1995, 31(2): 845~852
    [49] Andrei A. Monakov. Estimation of the covariance matrix for dependent signal samples: polarization diversity systems. IEEE Trans. AES, 1994, 30(2): 484~492
    [50] Worms, J. G. About the influences of polarization agile jammers to adaptive antenna arrays. Radar Conference, 1995, 619~623
    [51] Leonid B. Preiser. Polarization diversity of the general nonuniformly spaced adaptive array. IEEE, 1988, 553~556
    [52] 林晖,对旁辦对消雷达的变极化干扰研究,航天电子对抗,1992(3):39~45
    [53] 王新,王威,乔小林,具有极化滤波的地波超视距雷达正交双极化天线,系统工程与电子技术,1995,17(18):18~23
    [54] 张国毅,高频地波雷达极化抗干扰技术的研究,哈尔滨:哈尔滨工业大学博士论文,2002
    [55] 李卓林,雷达极化滤波在抗干扰中的应用研究,北京:航天二院硕士论文,1997
    [56] 倪晋麟,郑学誉,何东元,单元交叉极化对自适应阵列性能的影响,电子与信息学报,2002,24(1):97~101
    [57] 陈希孺,数理统计引论,北京:科学出版社,1999
    [58] A. D. 惠伦,噪声中信号的检测,北京:科学出版社,1977
    [59] 何友,关键,彭应宁等,雷达自动检测与恒虚警处理,北京:清华大学出版社,1999
    [60] 林昌禄,极化技术在雷达目标检测中的应用,现代雷达,1994,16(6):20~30
    [61] 张良,保铮,廖桂生,基于空时自适应处理的恒虚警检测算法研究,西安电子科技大学学报(自然科学版),2000,27(3):265~269
    [62] I. S. Reed, J. R. Mallett, L. E. Brennan. Rapid convergence rate in adaptive arrays. IEEE Trans. AES, 1974, 10(6): 853~863
    [63] Ramon Nitzberg. Detection loss of the sample matrix inversion technique. IEEE Trans. AES, 1984, 20(6): 824~827
    [64] E. J. Kelly. An adaptive detection algorithm. IEEE Trans. on AES, 1986, 22(1): 115~127
    [65] E. J. Kelly. Performance of an adaptive detection algorithm: rejection of unwanted signals. IEEE Trans. AES, 1989, 25(2): 122~133
    [66] Frank C Robey, Daniel R. Fuhrmann, Edward J. Kelly, Ramon Nitzberg. A CFAR adaptive matched filter detector. IEEE Trans. AES, 1992,28(l):208~216
    
    [67] Russell Brown, Hong Wang. An adaptive multiscan processor for polarimetric radar. IEEE Radar Conference, 1994, 95-100
    [68] Chui Jai Lee, Hong Wang. An adaptive multiband clutter polarization canceler, IEEE, AP-S, 1992,1011-1014
    [69] Russell Brown, Hong Wang. Adaptive signal processing techniques for multiband polarimetric radar. 308-311
    [70] Hyung-Rae Park, Hong Wang, Jian Li. An adaptive polarization-space-time processor for radar system, Antennas and Propagation Society International Symposium, 1993. AP-S, Vol.2:698~701
    [71] Hyung-Rae Park, Jian Li, Hong Wang. Polarization-space-time domain generalized likelihood ratio detection of radar targets, Signal Processing, 1995,41:153-164
    [72] Debora Pastina, Piefrancesco Lombardo, Vincenzo Pedicini, Tullio Bucciarelli. Adaptive polarimetric target detection with coherent radar. IEEE International Radar Conference, 2000, 93-97
    [73] Keith A.Burgess, Barry D. Van Veen. Subspace-based adaptive generalized likelihood ratio detection. IEEE Trans. SP, 1996,44(4):912~927
    [74] Keith A.Burgess, Barry D. Van Veen. Improved adaptive detection performance via subspace processing. IEEE Conf. ICASSP, 1992 ,V353~V356
    [75] Keith A.Burgess, Barry D. Van Veen. A subspace GLRT for vector-sensor array detection. IEEE ICASSP, 1994, IV:253~256
    [76] Louis L. Scharf, Benjamin Friedlander. Matched subspace detectors. IEEE Trans. SP, 1994, 42(8):2146~2157
    [77] Shawn Kraut, Louis L. Scharf. The CFAR adaptive subspace detector is a scale-invariant GLRT. IEEE Trans. SP, 1999, 47(9):2538~2541
    [78] Louis L. Scharf, Shawn Kraut, Michael L. McCloud. A review of matched and adaptive subspace detectors. DEEE, 2000, 82-86
    [79] R.S.Raghavan, N.Pulsone, D.J.Mclanghlin. Performance of the GLRT for adaptive vector subspace detection. IEEE Trans. AES, 1996,32(4): 1473-1486
    [80] Seth Z.Kalson. An adaptive array detector with mismatched signal rejection. IEEE Trans. AES, 1992, 28(1): 195-207
    [81] Hong Wang, Lujing Cai. On adaptive multiband signal detection with GLR algorithm. IEEE Trans. AES, 1991, 27(2):225~232
    [82] P. Lombardo, D. Pastina. Multiband coherent radar detection against compound-Gaussian clutter. IEEE Trans. AES, 1999, 35(4): 1266-1281
    [83] Seth Z. Kalson. Adaptive Array CFAR detection. IEEE Trans. AES, 1995, 31 (2):534~541
    
    [84] KARL GERLACH. A comparison of two adaptive detection schemes. IEEE Trans. AES, 1994, 30(l):3(K40
    [85] R.S.Raghavan, H.E.Qiu, D.J.Mclanghlin. CFAR detection in clutter with unknown correlation properties. IEEE Trans. AES, 1995, 31(2):647~657
    [86] L.S.Reed, Y.L.Gau, T.KTruong. CFAR detection and estimation for STAP radar,. IEEE Trans. AES, 1998, 34(3):722~734
    [87] C.G KHATRI, C.RADHAKRISHAN RAO. Effects of estimated noise covariance matrix in optimal signal detection. IEEE Trans. ASSP, 1987, 35(5):671~679
    [88] Sandip Bose, Allan O.Steinhardt. A maximal invariant framework for adaptive detection with structured and unstructured covariance matrices. IEEE Trans. SP, 1995, 43(9):2164~2175
    [89] Ivars P.Kirsteins, Donald W.Tufts. Adaptive detection using low rank approximation to a data matrix. IEEE Trans. AES, 1994, 30(l):55~67
    [90] Sandip Bose, Allan O. Steinhardt. Adaptive array detection of uncertain rank one waveforms. IEEE Trans. SP, 1996,44(ll):2801~2808
    [91] Guoqing Liu, Jian Li. Moving target detection via airborne HRR phased array radar. IEEE Trans. AES, 2001, 37(3):914~923
    [92] Earl R.Ferraraa, Jr.and Terry M.Parks. Direction finding with an array of antennas having diverse polarizations. IEEE Trans. AP, 1983, 31(2):231~236
    [93] Jian Li, R.T. Compton, Jr. Angle and polarization estimation using ESPRIT with a polarization sensitive array. EEEE Trans. AP, 1991, 39(9): 1376-1383
    [94] Jian Li, R.T.Compton,Jr. Angle estimation using a polarization sensitive array. IEEE Trans. AP, 1991,39(10):1539~1543
    [95] Jian Li. On polarization estimation using a polarization sensitive array. IEEE Proc. Sixth Workshop on Satistical Signal and Array Processing, 1992, 465~468
    [96] Jian Li, R.T. Comptonjr. Two-dimensional angle and estimation using the ESPRIT algorithm. IEEE Trans. AP, 1992, 40(5):550~555
    [97] Jian Li. Direction and polarization estimation using arrays with small loops and short dipoles. IEEE Trans. AP, 1993, 41(3):379~387
    [98] Jian Li, P.Stoica. Efficent paramerer estimation of partially polarized electromagnetic waves. IEEE Trans. SP, 1994, 42(7):3114-3125
    [99] Jian Li, Petre Stoica, Dunmin Zheng. Efficient direction and polarization estimation with a COLD array. IEEE Trans. AP, 1996, 44(4):539~547
    [100] Yingbo Hua. A pencil-music algorithm for finding two-dimensional angles polarizations using crossed dipoles. IEEE Trans. AP, 1993,41(3):370~376
    [101] Qi Cheng, Yingbo Hua. Further study of the pencil-music algorithm. IEEE Trans. AES, 1996, 32(l):284-299
    
    [102]Arye Nehorai, Eytan Paldi. Vector-sensor array processing for electromagnetic source localization, IEEE Trans. SP, 1994, 42(2):376~398
    [103] B. Hochwald, A. Nehorai. Identifiability in array processing models with vector-sensor application. IEEE Trans. SP, 1996,44(1):83~95
    [104]Kah-Chye Tan, Kwok-Chiang Ho, Arye Nehorai. Uniqueness study of measurements obtainable with arrays of electromagnetic vector sensors. IEEE Trans. SP, 1996, 44(4): 1036-1039
    [105] Kah-Chye Tan, Kwok-Chiang Ho, Arye Nehorai. Linear independence of steering vectors of an electromagnetic vector sensor. IEEE Trans. SP, 1996,44(12):3099~3107
    [106] Peng-Huat Chua, Chong-Meng Samson See, Arye Nehorai. Vector sensor array processing for estimating angles and times of arrival of multipath communication signals, IEEE Proc. ICASSP, 1998, 3325-3328
    [107]Kwok_chiang Ho, Kah-Chye Tan, Arye Nehorai. Estimating directions of arrival of completely and incompetely polarized signals with electromagnetic vector sensors. IEEE Trans. SP, 1999,47(10):2845~2852
    [108] Arye Nehorai, Petr Tichavsky. Cross-product algorithms for source tracking using an EM vector sensor. IEEE Trans. SP, 47(10):2863~2867
    [109] Anthony J. Weiss, Benjamin Friedlander. Direction finding for diversely polarized signals using polynomial rooting. IEEE Trans. SP, 1993,41(5):1893~1905
    [110] Anthony J. Weiss, Benjamin Friedlander. Maximum likelihood signal estimation for polarization sensitive arrays. IEEE Trans. AP, 1993,41(7):918-925
    [111] Anthony J. Weiss, Benjamin Friedlander. Analysis of a signal estimation algorithm for diversely polarized arrays. IEEE Trans. SP, 1993,41(8):2628-2638
    [112] K.T. Wong, M.D. Zoltowski. Diversely polarized root-MUSIC for azimuth-elevation angle of arrival estimation, IEEE AP-S, 1996,1352-1355
    [113]K.T. Wong, M.D. Zoltowski. High accuracy 2D angle estimation with extended aperture vector sensor arrays, IEEE Proc. ICASSP, 1996,2789-2792
    [114]K.T. Wong, M.D. Zoltowski. Uni-Vector-Sensor ESPRIT for multisource azimuth, elevation, and polarization estimation. IEEE Trans. AP, 1997,45(10):1467~1474
    [115JK.T. Wong, M.D. Zoltowski. Closed-form direction finding and polarization estimation with arbitrarily spaced electromagnetic vector-sensors at unkown locations. IEEE Trans. AP, 2000,48(5):671~680
    [116]K.T. Wong, M.D. Zoltowski, K.T. Self-initiating MUSIC-based direction finding and polarization estimation in spatio-polarizational beamspace. IEEE Trans. AP, 2000, 48(8):1235~1245
    
    [117] M. D. Zoltowski, K. T. Wong. ESPRIT-based 2D direction finding with a sparse uniform array of electromagnetic vector sensors. IEEE Trans. SP, 2000, 48(8): 2195~2204
    [118] M. D. Zoltowski, K. T. Wong. Cloesd-form eigenstructure-based direction finding using arbitrary but identical subarrays on a sparse uniform cartesian array grid. IEEE Trans. SP, 2000, 48(8): 2205~2210
    [119] K. T. Wong. Blind beamforming/geolocation for wideband-FFHs with unknown hop-sequences. IEEE Trans. AES, 2001, 37(1): 65~75
    [120] K. T. Wong. Direction finding/polarization estimation-dipole and/or loop triads. IEEE Trans. AES, 2001, 37(2): 679~684
    [121] ILAN ZISKIND, MATI WAX. Maximum likelihood localization of diversely polarized sources by simulated annealing. IEEE Trans. AP, 1990, 38(7): 1111~1114
    [122] A. Swindlehurst, M. Viberg. Subspace fitting with diversely polarized antenna arrays. IEEE Trans. AP, 1993, 41(12): 1687~1694
    [123] Harry Lee, Robert Stovall. Maximum likelihood methods for determining the direction of arrival for a single electromagnetic source with unknown polarization. IEEE Trans. SP, 1994, 42(2): 474~479
    [124] Kwok-Chiang Ho, Kah-Chye Tan, B. T. G. Tan. Efficient method for estimating directions-of-arrival of partially polarized signals with electromagnetic vector sensors. IEEE Trans. SP, 1997, 45(10): 2485~2497
    [125] 王建英,阵列信号多参量联合估计技术研究,成都:电子科技大学博士论文,2000
    [126] 王建英,王激扬,陈天麒,宽频段空间信号频率、二维到达角和极化联合估计,中国科学(E辑),2001,31(6):526~532
    [127] 王建英,陈天麒,频率、二维到达角和极化联合估计,电子学报,1999,27(11):74~76
    [128] 周云钟,陈天麒,多信号极化与到达角估计算法,电波科学学报,1997,12(2):220~224
    [129] Bertrand Hochwald, Arye Nehorai. Electromagnetic vector sensors and active target localization and identification. 1993, Ⅳ: 25~28
    [130] Bertrand Hochwald, Arye Nehorai. Polarization modeling and parameter estimation with electromagnetic vector sensors. 1994, 1129~1132
    [131] Bertrand Hochwald, Arye Nehorai. Polarization modeling and parameter estimation with applications to remote sensing. IEEE Trans. SP, 1995, 43(8): 1923~1935
    [132] S. M. 凯依[美],现代谱估计原理与应用,北京,科学出版社,1994
    [133] 刘德树,罗景青,张剑云,空间谱估计及其应用,合肥:中国科学技术大学出版社,1997
    [134] 孙超,李斌,加权子空间拟合算法理论与应用,西安:西北工业大学出版社,1994
    
    [135]MATI WAX, THOMAS KAILATH. Detection of signals by information theoretic criteria. IEEE Trans. ASSP, 1985, 33(2):387~392
    [136]Hsien-Tsai Wu, Jar-Ferr Yang, Fwu-Kuen Chen. Source number estimators using transformed gerschgorin radii. IEEE Trans. SP, 1995,43(6): 1325-1333
    [137] RICHARD ROY, THOMAS KAILATH. ESPRIT-Estimation of signal parameters via rotational invariance techniques. IEEE Trans. ASSP, 1989, 37(7):984~995
    [138] Mats Viberg, Bjorn Ottersten. Sensor array processing based on subspace fitting. IEEE Trans. SP, 1991, 39(5):1110~1121
    [139] Bjorn Ottersten, Mats Viberg, Thomas Kailath. Performance analysis of the total least squares. IEEE Trans. SP, 1991, 39(5): 1122-1135
    [140] Mats Viberg, Bjorn Ottersten, Thomas Kailath. Detection and estimation in sensor arrays using weighted subspace fitting. IEEE Trans. SP, 1991, 39(11):2436~2448
    [141] Anthony J. Weiss, Motti Gavish. Direction finding using ESPRIT with interpolated arrays. IEEE Trans. SP, 1991, 39(6): 1473-1478
    [142]MATI WAX, ILAN ZISKIND. On unique localization of multiple sources by passive sensor arrays. IEEE Trans. ASSP, 1989,37(7): 996-1000
    [143]K.T. Wong, M.D. Zoltowski. Direction-finding with sparse rectangular dual-size spatial invariance array. IEEE Trans. AES, 1998, 34(4): 1320-1335
    [144] Anthony J.Weiss, Benjamin Friedlander. Performance analysis of diversely polarized antenna arrays. IEEE Trans. SP, 1991, 39(7):1589~1603
    [145] Benjamin Friedlander, Anthony J. Weiss. Performance of diversely polarized antenna arrays for correlated signals. IEEE Trans. AES, 1992,28(3):869-879
    [146]PETRE STOICA, ARYE NEHORAI. MUSIC, Maximum likelihood, and Cramer-Rao Bound. IEEE Trans. ASSP, 1989, 37(5):720-741
    [147] BOAZ PORAT, Benjamin Friedlander. Analysis of the asymptotic relative efficiency of the MUSIC algorithm. IEEE Trans. ASSP, 1988, 36(4):532~543
    [148] A. Lee Swindlehurst, Thomas Kailath. A performance analysis of subspace-based methods in the presence of model errors, Part I: the MUSIC algorithm. IEEE Trans. SP, 1992, 40(7): 1758-1773
    [149] Hong Wang, Mostafa Kaveh. On the performance of signal subspace processing-Part I: narrow-band systems. IEEE Trans. ASSP, 1986, 34(5): 1201-1209
    [150]Petre Stoica, Arye Nehorai. Performance comparison of subspace rotation and MUSIC methods for direction estimation. IEEE Trans. SP, 1991,39(2):446~453
    [151]Petre Stoica, Arye Nehorai. Performance study of conditional and unconditional Direction-of-Arrival estimation. IEEE Trans. ASSP, 1990, 38(10):1783~1795
    [152] S. UNNIKRISHNA PILLAI, BYUNG HO KWON. Performance analysis of MUSIC-type high resolution estimation for direction finding in correlated and coherent scenes. IEEE Trans. ASSP, 1989, 37(8): 1176~1189
    [1
    
    [153] Qi Cheng, Yingbo Hua. Performance analysis of the MUSIC and Pencil-MUSIC algorithms for diversely polarized array. IEEE Trans. SP, 1994, 42(11): 3150~3165
    [154] 林茂庸,柯有安,雷达信号理论,北京:国防工业出版社,1984
    [155] MOSTAFA KAVEN, ARTHUR J. BARABELL. The statistical performance of the MUSIC and the Minimum-Norm algorithms in resolving plane waves in noise. IEEE Trans. ASSP, 1986, 34(2): 331~340
    [156] HARRY B. LEE, MICHAEL S. WENGROVITZ. Resolution threshold of beamspace MUSIC for two closely spaced emitters. IEEE Trans. ASSP, 1990, 38(9): 1545~1559
    [157] Benjamin Friedlander. A sensitivity analysis of the MUSIC algorithm. IEEE Trans. ASSP, 1990, 39(10): 1740~1751
    [158] Benjamin Friedlander, Anthony J. Weiss. The resolution threshold of a direction-finding algorithm for diversely polarized arrays. IEEE Trans. SP, 1994, 42(7): 1719~1727
    [159] 孙继广,矩阵扰动分析(第二版),科学出版社,2001.11,北京
    [160] 陈辉,王永良,秩-1子空间跟踪算法,电子与信息学报,2002,24(5):626~630
    [161] JAR-FERR YANG, MOSTAFA KAVEN. Adaptive eigensubspace algorithms for direction or frequency estimation and tracking. IEEE Trans. ASSP, 1988, 36(2): 241~251
    [162] Benoit Champagne. Adaptive eigendecomposition of data covariance matrices based on first-order perturbations. IEEE Trans. SP, 1994, 42(10): 2758~2770
    [163] Benoit Champagne. Adaptive signal-subspace processing based on first-order perturbation analysis. IEEE Conf. on Communications, Computers and Signal Processing, May 9-10, 1991, 120~123
    [164] Kai-Bor Yu. Recursive updating the eigenvalue decomposition of a covariance matrix. IEEE Trans. SP, 1991, 39(5): 1136~1145
    [165] Kai-Bor Yu. Efficient, parallel adaptive eigenbased techniques for direction of arrival estimation and tracking. Proc. Fifth ASSP Workshop Spectrum Estimation Modeling, Oct.10-12, 1990, 347-351
    [166] Christian H. Bischof, Gautam M. Shroff. On updating signal subspaces. IEEE Trans. SP, 1992, 40(1): 96~105
    [167] Ronald D. DeGroat. Noniterative subspace tracking. IEEE Trans. SP, 1992, 40(3): 571~577
    [168] G. W. Stewart. An updating algorithm for subspace tracking. IEEE Trans. SP, 1992, 40(6): 1535~1541
    [169] F. Vincent, O. Besson. Estimating time-varying DOA and Doppler shift in radar array processing, IEE RSN, 2000, 147(6): 285~290
    [170] 周宏仁,敬忠良,机动目标跟踪,北京:国防工业出版社,1994
    
    [171] 刘源,谢维信,杜文吉,李隐峰,基于多传感器多目标特征信息的模糊数据关联算法,系统工程与电子技术,1998,20(12):18~23
    [172] D. LERRO, Y. BAR-SHALOM. Interaction multiple model tracking with target amplitude feature, IEEE Trans. AES, 1993, 29(2): 494~508
    [173] LONG-HUAI Wang, HSUEN-JYH LI. Using range profiles for data association in multiple-target tracking. IEEE Trans. AES, 1996, 32(1): 445~450
    [174] X. RONG LI, Y. BAR-SHALOM. Tracking in clutter with nearest neighbor filters: analysis and performance. IEEE Trans. AES, 1996, 32(3): 995~1009
    [175] T. KIRUBARAJAN, Y. BAR-SHALOM. Low observable target motion analysis using amplitude information. IEEE Trans. AES, 1996, 32(4): 1367~1383
    [176] X. RONG LI. Tracking in clutter with strongest neighbor measurements-Part Ⅰ: theoretical analysis. IEEE Trans. AC, 1998, 43(11): 1560~1578
    [177] C. R. Rao, C. R. Sastry, B. Zhou. Tracking the direction of arrival of multiple moving targets. IEEE Trans. SP, 1994, 42(5): 1133~1143
    [178] H. Zheng, M. Farooq, R. main. Multi-target tracking algorithm performance evaluation. SPIE, 1999, 3719: 300~309
    [179] 倪晋麟,苏为民,储晓彬,幅相不一致性对自适应阵列的影响,应用科学学报,2000,18(3):223~226
    [180] 林敏,龚铮权,超分辨测向中阵元间互耦的校正,电子与信息学报,2002,24(5):631~636
    [181] 高式昌,钟顺时,一种高隔离度的双极化微带天线阵的理论和实验,电子学报,1999,27(8):64~66

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