相位编码MIMO雷达信号处理技术研究
|
摘要
受MIMO (Multiple Input Multiple Output)技术在现代无线通信领域发展的启发及其所体现出的优越性,雷达工程师近年来提出了一种新体制雷达——MIMO雷达,并已成为当前国际上研究的热点。MIMO雷达可分为统计MIMO雷达和共址MIMO雷达两种类型：统计MIMO雷达发射／接收阵列的阵元间距较大,可利用收／发阵元的空间分集来抑制目标的RSC闪烁,以提高雷达的检测性能；共址MIMO雷达使用传统天线阵列发射和接收信号,即通过阵元间的紧密排列实现相干发射和相干接收,可利用虚拟阵列的形成来提高雷达的角度分辨力以及增加最大可辨识的目标数量。MIMO雷达的探测信号可以采用码分正交波形,频分正交波形,或者上述两类波形的复合。本文所研究的MIMO雷达使用了码交正交发射波形,文中对相位编码雷达/MIMO雷达的多普勒敏感问题,统计MIMO雷达的信号处理算法,共址MIMO雷达角度估计算法以及MIMO雷达在高速运动目标探测应用等方面进行了详细研究。
本文的主要工作和贡献可以归纳如下：
1.相位编码雷达/MIMO雷达的脉压性能分析
以m序列调相连续波雷达为例,研究了该雷达脉压主旁瓣比与目标多普勒频率之间的变化关系,并推导了其数学表达式。由于m序列调相连续波雷达在非目标距离门上的脉冲压缩是一种“宽带输入窄带输出的过程”,那么脉压旁瓣实部和虚部分别近似服从正态分布,由此可计算出脉压后峰值旁瓣实部和虚部的值,从而可获得脉压输出主旁瓣比的数学表达式。当m序列的周期长度P≥31时,由脉压主旁瓣比数学表达式计算数据与仿真数据能很好地吻合。然后在此基础上,研究了相位编码MIMO雷达的多普勒敏感问题,主要包括多普勒频率所导致的脉压失配以及相位编码信号正交性破坏这两方面。这部分的研究可为后续工作开展提供帮助。
2.发射分集统计MIMO雷达的非相参角度估计方法及其相参信号处理算法
发射分集统计MIMO雷达利用天线空间发射分集能较好地克服目标RCS的角闪烁所带来的性能损失,以提高其接收阵列的角度估计精度。首先基于仅考虑目标空域特性的回波信号模型,探讨了发射分集统计MIMO雷达的非相参角度估计方法,分别从阵列直接接收的回波和经脉压以及数据重排后的回波中估计目标角度,其中后者的角度估计性能优于前者。然后基于实际的慢起伏目标回波信号模型,研究了发射分集统计MIMO雷达的相参信号处理方法,将同一目标在不同观测角度的回波经距离延时、多普勒频移和相位补偿后再作相参合并,以提高其信噪比,从而使目标角度估计精度高于非相参角度估计方法。
3.接收分集统计MIMO雷达的多目标定位算法
针对“宽波束发射-宽波束接收”多基地雷达存在定位精度低和易产生虚假目标等缺点,讨论了一种空间接收分集的MIMO雷达,它是一种特殊结构的一发多收多基地雷达,其工作模式也为“宽波束发射-宽波束接收”,能避免复杂的波束同步扫描问题。对接收分集统计MIMO雷达提出了一种基于Capon谱估计的多目标定位方法,并与普通一发多收多基地雷达的定位精度进行了比较。结果表明：接收分集统计MIMO雷达能有效解决“宽波束发射-宽波束接收”多基地雷达的低定位精度和易产生虚假目标的问题。
4.双基地共址MIMO雷达的发射角和接收角联合估计算法
(1)在空间高斯白噪声环境下的角度估计算法：A)为避免运算量巨大的Capon二维谱峰搜索,提出了一种基于ESPRIT算法的二维方位角参数自动配对估计方法。该方法利用ESPRIT算法把信号二维方位角参数同时估计问题转化为两个一维方位角参数估计问题,然后提取两次参数估计之间的关联性,实现发射角和接收角自动配对估计,且其角度估计性能与需要参数配对过程的ESPRIT算法类似。B)双基地共址MIMO雷达在接收端合成了比其实际阵元更多的虚拟阵元,因此在ESPRIT方法实现过程中需要估计一个高维协方差矩阵及其特征分解,运算量极大。为此,利用传播算子方法实现发射角和接收角的快速联合估计,以避免协方差矩阵的估计及其特征值分解。
(2)在空间色噪声环境下的角度估计算法：利用相对不同发射子阵的匹配输出数据互协方差矩阵中附加噪声互协方差矩阵为零这一特性,研究了一种新的发射角和接收角联合估计算法。该算法利用匹配输出数据的互协方差矩阵,再结合ESPRIT算法估计目标发射角和接收角,所估计的参数自动配对。该算法适用于三个或更多发射阵元数的双基地共址MIMO雷达,能有效抑制空间色噪声的影响,且其空间色噪声的抑制能力随着发射阵元数的增加而增强。
5.基于单基地共址MIMO雷达的高速运动目标探测技术
针对传统体制雷达对高速运动目标不能进行长时间有效相参积累检测问题,提出了一种基于单基地共址MIMO雷达的高速运动目标探测方法。该方法利用MIMO雷达在短时间内输出的多路回波数据进行相参并行处理来取代回波数据的长时间相参积累检测,以避免距离走动,径向速度变化以及反射截面积(RCS)快起伏等非平稳因素对目标探测的影响。由于单基地共址MIMO雷达的角度估计具有分辨力高以及可测目标数量大等优点,因此它具有对大量密集高速运动目标进行探测的能力。
Motivated by recent developments and attractive advantages of MIMO (multiple-input multiple-output) technology in modern wireless communication field, a new concept of MIMO radar is explored recently, which has become a hot international research area. Two kinds of MIMO radar are put forward. One is statistical MIMO radar in which the transmit and receive antennas are widely spaced. It can resist the RCS scintillation effect encountered in radar systems by capitalizing on the spatial diversity with the improvement of the detection performance. The other is MIMO radar with collocated antennas which employs standard array to transmit multiple probing signals and receive the backscattered signals reflected from the targets. The signals transmitted and received respectively via collocated antennas are fully coherent. MIMO radar with collocated antennas can improve the angular resolution and increase the upper limit on the number of targets which can be detected and localized by the array. MIMO radar could employ code diversity, frequency diversity or both to derive the orthogonal waveform. MIMO radar using code diversity is studied in this paper. The problems of Doppler sensitivity of phase-coded radar and MIMO radar, target detection and parameter estimation of tatistical MIMO radar, angle estimation of MIMO radar with collocated antennas, and high speed moving target detection using MIMO radar are considered herein.
The main works and contributions are summarized as follow:
1. The performances analysis of pulse compression for phase-coded radar and MIMO radar
Take m-sequence phase modulation radar for example, the relation between main-to-sidelobe ratio and Doppler frequency after the pulse compression is studied, and the deduction of its mathematical expression is presented. Since the pulse compression with the non-target range gate in m-sequence phase modulation CW radar is a "wide-band input, narrow-band output process", the sidelobe's real part and imaginary part after the pulse compression approximately obey normal distribution, respectively. Thus, the peak sidelobe's real part and imaginary part after the pulse compression can be calculated. Then the mathematical expression of the main-to-sidelobe ratio after the pulse compression is also gained. The data calculated by the mathematical expression of the main-to-sidelobe ratio is close to the data attained by the simulation, when the period length of m-sequence P≥31. On this basis, the problem of Doppler sensitivity of phase-coded MIMO radar is also studied. It mainly includes the mismatch of pulse compression and orthogonality damage of phase coded signals caused by Doppler frequency. This could provide some help to our subsequent work.
2. Non-coherent angle estimation and coherent signal processing for statistical MIMO radar with transmit diversity only
The statistical MIMO radar with transmit diversity only can overcome target's radar cross section (RCS) fluctuations by exploring transmit diversity to improve the direction finding performance. Non-coherent angle estimation for statistical MIMO radar with transmit diversity only is discussed, the signal model of which focuses on the effect of the target spatial properties ignoring range and Doppler effects. The received signals of array are processed directly or after pulse compression and data rearrangement for angle estimation. The latter has better performance than the former. Then, based on the complex signal model for the moving and slow fluctuating targets that focuses on the effect of the target spatial properties and range and Doppler frequency, a scheme for coherent signal processing using statistical MIMO radar with transmit diversity only is studied. The echoes of the same target from different transmit antennas are added after the compensations of range delay, Doppler frequency shift and phase. Thus, the highly precise estimation of target azimuth can be obtained from the added target's signal with the high signal noise ratio, which is better than that of Non-coherent angle estimation method.
3. Multi-target localization using statistical MIMO radar with receiving diversity only
Aiming at the disadvantages of low positioning accuracy and target ghosts generation in multistatic radar with broad transmit beam and broad receive beam, statistical MIMO radar with receiving diversity only is discussed in this paper. This MIMO radar is a special structure of STMR (single transmitting station and multiple receiving stations)-multistatic radar with broad transmit beam and broad receive beam, and it avoids the complicated beam scan synchronization. A scheme for multi-target localization using Capon space spectrum estimation algorithm in MIMO radar with receiving diversity only is proposed, and the positioning accuracies of the MIMO radar and STMR multistaic radar are compared. Simulations show that statistical MIMO radar with receiving diversity only solves effectively the problems of low positioning accuracy and target ghosts generation in multistatic radar with broad transmit beam and broad receive beam.
4. A joint direction of departures (DODs) and direction of arrivals (DOAs) estimation for bistatic MIMO radar with collocated antennas
(1) Angle estimation in the presence of spatial Gaussian white noise:A) In order to avoid two-dimension (2-D) angle search for Capon algorithm, ESPRIT algorithm is used for targets'directions estimation with the utilization of the invariance property of the transmit array and the receive array, which decomposes the 2-D angles estimation problem into two independent one-dimensional (1-D) angles estimation problems. Then the interrelationship between the two 1-D ESPRIT is exploited to obtained automatically paired transmit angles and receive angles estimation without debasing the performance of angles estimation. B) Due to the formed virtual array with more elements than the physical array elements, ESPRIT algorithm requires the estimation and SVD (Singular Value Decomposition) of the high dimension covariance matrix of the received signals which are the main computational burden in traditional subspace method. Thus, a fast joint DODs and DOAs estimation using propagator method without the estimation and SVD of the covariance matrix is studied.
(2) Angle estimation in the presence of spatial colored noise: A new method for joint DOD and DOA estimation is studied by exploiting the characteristic that the cross-covariance matrix of noises in the cross-correlation matrix of two received data from two transmit subarrays is 0. The DODs and DOAs of targets are estimated via both ESPRIT and SVD of cross-correlation matrix of the received data from two transmit subarrays. The DOAs and DODs of targets can be solved in closed form and paired automatically. It could be effective for three-or more-transmitters configuration system with the influence of spatial colored noise eliminated, and the ability of the spatial colored noise elimination can be improved with the increase of the number of transmitters.
5. High speed moving target detection using monostatic MIMO radar with collocated antennas
It is difficult for the traditional radar to detect effectively the high speed moving target with the long time coherent integration method. In this paper, the monostatic MIMO radar with collocated antennas, in which the parallel coherent processing of the multi-channel echo data in a short time is exploited to replace the long time coherent integrative detection, is used for high speed moving target detection. Thus the detection performance of MIMO radar may not be affected by the range migration, the radial velocity variety and the fast Radar Cross-Section (RCS) fluctuation. Meanwhile, MIMO radar with collocated antennas can improve the angular resolution and increase the maximum number of identified targets. Thus, it has the ability to effectively detect a large number of dense high speed moving targets.
本文的主要工作和贡献可以归纳如下：
1.相位编码雷达/MIMO雷达的脉压性能分析
以m序列调相连续波雷达为例,研究了该雷达脉压主旁瓣比与目标多普勒频率之间的变化关系,并推导了其数学表达式。由于m序列调相连续波雷达在非目标距离门上的脉冲压缩是一种“宽带输入窄带输出的过程”,那么脉压旁瓣实部和虚部分别近似服从正态分布,由此可计算出脉压后峰值旁瓣实部和虚部的值,从而可获得脉压输出主旁瓣比的数学表达式。当m序列的周期长度P≥31时,由脉压主旁瓣比数学表达式计算数据与仿真数据能很好地吻合。然后在此基础上,研究了相位编码MIMO雷达的多普勒敏感问题,主要包括多普勒频率所导致的脉压失配以及相位编码信号正交性破坏这两方面。这部分的研究可为后续工作开展提供帮助。
2.发射分集统计MIMO雷达的非相参角度估计方法及其相参信号处理算法
发射分集统计MIMO雷达利用天线空间发射分集能较好地克服目标RCS的角闪烁所带来的性能损失,以提高其接收阵列的角度估计精度。首先基于仅考虑目标空域特性的回波信号模型,探讨了发射分集统计MIMO雷达的非相参角度估计方法,分别从阵列直接接收的回波和经脉压以及数据重排后的回波中估计目标角度,其中后者的角度估计性能优于前者。然后基于实际的慢起伏目标回波信号模型,研究了发射分集统计MIMO雷达的相参信号处理方法,将同一目标在不同观测角度的回波经距离延时、多普勒频移和相位补偿后再作相参合并,以提高其信噪比,从而使目标角度估计精度高于非相参角度估计方法。
3.接收分集统计MIMO雷达的多目标定位算法
针对“宽波束发射-宽波束接收”多基地雷达存在定位精度低和易产生虚假目标等缺点,讨论了一种空间接收分集的MIMO雷达,它是一种特殊结构的一发多收多基地雷达,其工作模式也为“宽波束发射-宽波束接收”,能避免复杂的波束同步扫描问题。对接收分集统计MIMO雷达提出了一种基于Capon谱估计的多目标定位方法,并与普通一发多收多基地雷达的定位精度进行了比较。结果表明：接收分集统计MIMO雷达能有效解决“宽波束发射-宽波束接收”多基地雷达的低定位精度和易产生虚假目标的问题。
4.双基地共址MIMO雷达的发射角和接收角联合估计算法
(1)在空间高斯白噪声环境下的角度估计算法：A)为避免运算量巨大的Capon二维谱峰搜索,提出了一种基于ESPRIT算法的二维方位角参数自动配对估计方法。该方法利用ESPRIT算法把信号二维方位角参数同时估计问题转化为两个一维方位角参数估计问题,然后提取两次参数估计之间的关联性,实现发射角和接收角自动配对估计,且其角度估计性能与需要参数配对过程的ESPRIT算法类似。B)双基地共址MIMO雷达在接收端合成了比其实际阵元更多的虚拟阵元,因此在ESPRIT方法实现过程中需要估计一个高维协方差矩阵及其特征分解,运算量极大。为此,利用传播算子方法实现发射角和接收角的快速联合估计,以避免协方差矩阵的估计及其特征值分解。
(2)在空间色噪声环境下的角度估计算法：利用相对不同发射子阵的匹配输出数据互协方差矩阵中附加噪声互协方差矩阵为零这一特性,研究了一种新的发射角和接收角联合估计算法。该算法利用匹配输出数据的互协方差矩阵,再结合ESPRIT算法估计目标发射角和接收角,所估计的参数自动配对。该算法适用于三个或更多发射阵元数的双基地共址MIMO雷达,能有效抑制空间色噪声的影响,且其空间色噪声的抑制能力随着发射阵元数的增加而增强。
5.基于单基地共址MIMO雷达的高速运动目标探测技术
针对传统体制雷达对高速运动目标不能进行长时间有效相参积累检测问题,提出了一种基于单基地共址MIMO雷达的高速运动目标探测方法。该方法利用MIMO雷达在短时间内输出的多路回波数据进行相参并行处理来取代回波数据的长时间相参积累检测,以避免距离走动,径向速度变化以及反射截面积(RCS)快起伏等非平稳因素对目标探测的影响。由于单基地共址MIMO雷达的角度估计具有分辨力高以及可测目标数量大等优点,因此它具有对大量密集高速运动目标进行探测的能力。
Motivated by recent developments and attractive advantages of MIMO (multiple-input multiple-output) technology in modern wireless communication field, a new concept of MIMO radar is explored recently, which has become a hot international research area. Two kinds of MIMO radar are put forward. One is statistical MIMO radar in which the transmit and receive antennas are widely spaced. It can resist the RCS scintillation effect encountered in radar systems by capitalizing on the spatial diversity with the improvement of the detection performance. The other is MIMO radar with collocated antennas which employs standard array to transmit multiple probing signals and receive the backscattered signals reflected from the targets. The signals transmitted and received respectively via collocated antennas are fully coherent. MIMO radar with collocated antennas can improve the angular resolution and increase the upper limit on the number of targets which can be detected and localized by the array. MIMO radar could employ code diversity, frequency diversity or both to derive the orthogonal waveform. MIMO radar using code diversity is studied in this paper. The problems of Doppler sensitivity of phase-coded radar and MIMO radar, target detection and parameter estimation of tatistical MIMO radar, angle estimation of MIMO radar with collocated antennas, and high speed moving target detection using MIMO radar are considered herein.
The main works and contributions are summarized as follow:
1. The performances analysis of pulse compression for phase-coded radar and MIMO radar
Take m-sequence phase modulation radar for example, the relation between main-to-sidelobe ratio and Doppler frequency after the pulse compression is studied, and the deduction of its mathematical expression is presented. Since the pulse compression with the non-target range gate in m-sequence phase modulation CW radar is a "wide-band input, narrow-band output process", the sidelobe's real part and imaginary part after the pulse compression approximately obey normal distribution, respectively. Thus, the peak sidelobe's real part and imaginary part after the pulse compression can be calculated. Then the mathematical expression of the main-to-sidelobe ratio after the pulse compression is also gained. The data calculated by the mathematical expression of the main-to-sidelobe ratio is close to the data attained by the simulation, when the period length of m-sequence P≥31. On this basis, the problem of Doppler sensitivity of phase-coded MIMO radar is also studied. It mainly includes the mismatch of pulse compression and orthogonality damage of phase coded signals caused by Doppler frequency. This could provide some help to our subsequent work.
2. Non-coherent angle estimation and coherent signal processing for statistical MIMO radar with transmit diversity only
The statistical MIMO radar with transmit diversity only can overcome target's radar cross section (RCS) fluctuations by exploring transmit diversity to improve the direction finding performance. Non-coherent angle estimation for statistical MIMO radar with transmit diversity only is discussed, the signal model of which focuses on the effect of the target spatial properties ignoring range and Doppler effects. The received signals of array are processed directly or after pulse compression and data rearrangement for angle estimation. The latter has better performance than the former. Then, based on the complex signal model for the moving and slow fluctuating targets that focuses on the effect of the target spatial properties and range and Doppler frequency, a scheme for coherent signal processing using statistical MIMO radar with transmit diversity only is studied. The echoes of the same target from different transmit antennas are added after the compensations of range delay, Doppler frequency shift and phase. Thus, the highly precise estimation of target azimuth can be obtained from the added target's signal with the high signal noise ratio, which is better than that of Non-coherent angle estimation method.
3. Multi-target localization using statistical MIMO radar with receiving diversity only
Aiming at the disadvantages of low positioning accuracy and target ghosts generation in multistatic radar with broad transmit beam and broad receive beam, statistical MIMO radar with receiving diversity only is discussed in this paper. This MIMO radar is a special structure of STMR (single transmitting station and multiple receiving stations)-multistatic radar with broad transmit beam and broad receive beam, and it avoids the complicated beam scan synchronization. A scheme for multi-target localization using Capon space spectrum estimation algorithm in MIMO radar with receiving diversity only is proposed, and the positioning accuracies of the MIMO radar and STMR multistaic radar are compared. Simulations show that statistical MIMO radar with receiving diversity only solves effectively the problems of low positioning accuracy and target ghosts generation in multistatic radar with broad transmit beam and broad receive beam.
4. A joint direction of departures (DODs) and direction of arrivals (DOAs) estimation for bistatic MIMO radar with collocated antennas
(1) Angle estimation in the presence of spatial Gaussian white noise:A) In order to avoid two-dimension (2-D) angle search for Capon algorithm, ESPRIT algorithm is used for targets'directions estimation with the utilization of the invariance property of the transmit array and the receive array, which decomposes the 2-D angles estimation problem into two independent one-dimensional (1-D) angles estimation problems. Then the interrelationship between the two 1-D ESPRIT is exploited to obtained automatically paired transmit angles and receive angles estimation without debasing the performance of angles estimation. B) Due to the formed virtual array with more elements than the physical array elements, ESPRIT algorithm requires the estimation and SVD (Singular Value Decomposition) of the high dimension covariance matrix of the received signals which are the main computational burden in traditional subspace method. Thus, a fast joint DODs and DOAs estimation using propagator method without the estimation and SVD of the covariance matrix is studied.
(2) Angle estimation in the presence of spatial colored noise: A new method for joint DOD and DOA estimation is studied by exploiting the characteristic that the cross-covariance matrix of noises in the cross-correlation matrix of two received data from two transmit subarrays is 0. The DODs and DOAs of targets are estimated via both ESPRIT and SVD of cross-correlation matrix of the received data from two transmit subarrays. The DOAs and DODs of targets can be solved in closed form and paired automatically. It could be effective for three-or more-transmitters configuration system with the influence of spatial colored noise eliminated, and the ability of the spatial colored noise elimination can be improved with the increase of the number of transmitters.
5. High speed moving target detection using monostatic MIMO radar with collocated antennas
It is difficult for the traditional radar to detect effectively the high speed moving target with the long time coherent integration method. In this paper, the monostatic MIMO radar with collocated antennas, in which the parallel coherent processing of the multi-channel echo data in a short time is exploited to replace the long time coherent integrative detection, is used for high speed moving target detection. Thus the detection performance of MIMO radar may not be affected by the range migration, the radial velocity variety and the fast Radar Cross-Section (RCS) fluctuation. Meanwhile, MIMO radar with collocated antennas can improve the angular resolution and increase the maximum number of identified targets. Thus, it has the ability to effectively detect a large number of dense high speed moving targets.
引文
[1]Skolnik M. Radar handbook. 2nd ed. New York: McGraw-hill,1990
[2]Siebert W M. A radar detection philosophy. IEEE Transactions on Information Theory, 1956,2(3):204-221
[3]Woodward P M. Probability and information theory with application to radar.1st ed. New York: McGraw-hill,1953
[4]丁鹭飞,耿富录.雷达原理.第二版.西安：西安电子科技大学出版社,2000
[5]Alamouti S M. A simple transmit diversity technique for wireless communications.IEEE Journal on Selected Areas in Communications,1998, 16(8):1451-1458
[6]Foscnini G J, Golden G D, Valenzuela R A, et al. Simplified processing for nigh spectral efficiency wireless communication employing multi-element arrays. IEEE Journal on Selected Areas in Communications,1999,17(11):1841-1852
[7]Telatar I E. Capacity of multi-antenna gaussian channels. European Transactions on Telecommunications,1999,10(6):585-596
[8]Foschini G. J. Layered space-time architecture for wireless communication in a fading environment when using multiple antennas. Bell Labs Technical Journal.1996,1(2): 41-59.
[9]Foschini G J, Gans M J. On limits of wireless communications in a fading environment when using multi-element antennas. Wireless Personal Communications, 1998,6:311-335.
[10]Wolniansky P W, Foschini G J, Golden G D, et al. V-BLAST: an architecture for realizing very high data rates over the rich-scattering wireless channels. Proceedings of URSI International Symposium on Signal, Systems, and Electronics, Pisa, Italy, 1998:295-300
[11]Fishler E, Haimovich A, Blum R, Cimini L, Chizhik D, and Valenzuela R. MIMO radar: an idea whose time has come. Proceedings of 2004 IEEE International Conference on Radar, Philadelphia, PA, United States,2004:71-78
[12]Fisher E, Haimovich A, Blum, R S, et al. Spatial diversity in radars models and detection performance. IEEE Transactions on Signal Processing,2006,54(3):823-838
[13]何子述,韩春林,刘波.MIMO雷达概念及其技术特点分析.电子学
报,2005,33(12A)：2441-2445
[14]Haimovich A M, Blum R S, Leonard J, et al, MIMO radar with widely separated antennas. IEEE Signal Processing Magazine,2008,25(1):116-129
[15]Fishler E, Haimovich A M, Blum R S, et al. Performance of MIMO radar systems: advantages of angular diversity. Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, United States,2004:305-309.
[16]Lehmann N H, Fisher E, Haimovich A M,et al. Evaluation of transmit diversity in MIMO radar direction finding. IEEE Transactions on Signal Processing,2007,55(5): 2215-2225
[17]Baumgarten D. Optimum detection and receiver performance for multistatic radar configurations. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Paris, France,1982:359-362.
[18]Chernyak V S. Fundamentals of multisite radar systems. New York: Gordon and Breach,1998.
[19]Johnsen T, Olsen K E, Johnsrud S, et al. Simultaneous use of multiple pseudo random noise codes in multistatic CW radar. Proceedings of IEEE International Conference on Radar, Philadelphia, PA, USA,2004:266-270
[20]张光斌.双／多基地雷达参数估计算法研究.西安电子科技大学博士学位论文,2006
[21]Papoutsis I, Baker C J, Griffiths H D. Fundamental performance limitations of radar networks. Proceedings of 1 st EMRS DTC Technical Conference, Edinburgh, England, 2004: A7
[22]Viswanathan R, Varshney P K. Distributed detection with multiple sensors I: Fundamentals. Proceedings of the IEEE,1997,85(1):54-63
[23]Blum R S, Kassam S A, Poor H V. Distributed detection with multiple sensors II: Advanced topics," Proceedings of the IEEE,1997,85(1):64-79
[24]Blum R S. Distributed detection for diversity reception of fading signals in noise. IEEE Transactions on Information Theory,1999,45(1):158-164
[25]Gorji A A, Tharmarasa R, Kirubarajan T. MIMO vs. multistatic radars for target localization. Proceedings of the SPIE,2009,7445(2009):744502-744502-12
[26]Lehmann N, Haimovich A M, Blum R S, et al. MIMO radar application to moving target detection in homogenous clutter. Waltham, MA, USA: Adaptive Sensor Array Processing Workshop at MIT Lincoln Laboratory,2006 [Online]. Available: http://www.ll.mit. edu/asap/asap_06/pdf/Presentations/05_Haimovich_P.pdf
[27]Sheikhi A, Zamani A, Norouzi Y. Model-based adaptive target detection in clutter using MIMO radar. Proceedings of 2006 International Conference on Radar(CIE'06), Shanghai, China,2006:57-60
[28]Sheikhi A, Zamani A. Adaptive target detection in clutter using MIMO radar. Proceedings of 2006 International Radar Symposium (IRS 2006), Krakow, Poland, 2006:1-4
[29]Sammartino P F, Baker C J, Griffiths H D. MIMO radar performance in clutter environment. Proceedings of 2006 International Conference on Radar (CIE '06), Shanghai, China,2006:32-37
[30]Akcakaya M, Hurtado M, NehoraiA. MIMO radar detection of targets in compound-gaussian clutter. Proceedings of 2008 42nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA,USA,2008:208-212
[31]Sheikhi A, Zamani A. Temporal coherent adaptive target detection for multi-input multi-output radars in clutter. IET Radar, Sonar & Navigation,2008,2(2):86-96
[32]Lehmann N H. Some contributions on MIMO radar [PhD Dissertation]. University Heights, Newark, NJ,2007
[33]Lehmann N H, Haimovich A M, Blum R S, et al. High resolution capabilities of MIMO radar. Proceedings of 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA,2006:25-30
[34]Godrich H, Haimovich A M, Blum R S. Target localization techniques and tools for MIMO radar. Proceedings of 2008 IEEE Radar Conference, Rome, Italy,2008:1-6
[35]Godrich H, Haimovich A M, Blum R S. Target localisation techniques and tools for multiple-input multiple-output radar. IET Radar, Sonar & Navigation, 2009,3(4):314-327
[36]Rabideau D J, Parker P. Ubiquitous MIMO multifunction digital array radar. Conference Record of the 37th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA,2003:1057-1064
[37]Li J, Stoica P. MIMO radar with colocated antennas, IEEE Signal Processing Magazine,2007,24(5):106-114
[38]Bekkerman I, Tabrikian J. Target detection and localization using MIMO radars and sonars. IEEE Transactions on Signal Processing,2006,54(10):3873-3883.
[39]Robey F C, Coutts S, Weikle D. MIMO radar theory and experimental results. Conference Record of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United states,2004:300-304
[40]曾建奎.MIMO雷达信号检测的若干问题研究.电子科技大学博士学位论文,2008.
[41]刘波.MIMO雷达正交波形设计及信号处理研究.电子科技大学博士学位论文,2007.
[42]Dorey J, Gamier G. RIAS, synthetic impulse and antenna radar.Proceedings of international conference on radar, Paris, France,1989:36-44
[43]保铮,张庆文.一种新型的米波雷达一综合脉冲与孔径雷达.现代雷达,1995,17(1)：1-13
[44]陈伯孝.四维跟踪及其长相干积累等技术研究.西安电子科技大学博士学位论文,1997
[45]陈伯孝,张守宏.稀布阵综合脉冲孔径雷达低距离旁瓣与距离高分辨技术.电子学报,1998,26(9)：29-33
[46]陈伯孝,张守宏.综合脉冲孔径雷达的主要特点及其“四抗”性能.西安电子科技大学学报(雷达信号处理专辑),1997,24：140-146
[47]赵光辉.基于SIAR体制的稀布阵米波雷达若干问题研究.西安电子科技大学博士学位论文,2008
[48]Bliss D W, Forsythe K W. Multiple-input multiple-output (MIMO) radar and imaging degrees of freedom and resolution. Conference Record of the 37th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United states,2003:54-59
[49]De Maio A, Lops M. Design principles of MIMO radar detectors. IEEE Transactions on Aerospace and Electronic Systems,2007,43(3):886-898
[50]Khan H A, Malik W Q, Edwards D J, et al. Ultra wideband multiple-input multiple-output radar. Conference Record of 2005 IEEE International Radar, Arlington, VA, USA,2005:900-904
[51]Tang J, Li N, Wu Y, et al. Diversity order and detection performance of MIMO radar a relative entropy based study. IEEE Signal Processing Letters,2009,16(3):184-187
[52]Tang J, Wu Y, Peng Y, et al. On detection performance and system configuration of MIMO radar. Science in China Series F: Information Sciences, 2009, 52(7):1250-1257.
[53]Tang J, Wu Y, Peng Y, et al. On detection performance of MIMO radar for Rician target. Science in China Series F:Information Sciences,2009,52(8):1456-1465
[54]Petillot Y, Du C, Thompson J S. Predicted detection performance of MIMO radar. IEEE Signal Processing Letters,2008,15:83-86
[55]Godrich H, Haimovich A M, Blum R S. A comparative study of target localization in MIMO radar systems. Proceedings of 2009 International Waveform Diversity and Design Conference, Kissimmee, FL, United states,2009:124-128
[56]Godrich H, Haimovich A M, Blum R S. Cramer Rao bound on target localization estimation in MIMO radar systems. Proceedings of The 42nd Annual Conference on Information Sciences and Systems, Princeton, NJ, United states,2008:134-139
[57]He Q, Blum R S, Godrich H. Cramer-Rao bound for target velocity estimation in MIMO radar with widely separated antennas. Proceedings of The 42nd Annual Conference on Information Sciences and Systems, Princeton, NJ, United states, 2008:123-127
[58]He Q, Blum R S. Cramer-Rao bound for MIMO radar target localization with phase errors. IEEE Signal Processing Letters,2010,17(1):83-86
[59]Tabrikian J. Barankin Bounds for Target localization by MIMO radars. Processing of Fourth IEEE Workshop on Sensor Array and Multichannel, Waltham, MA, USA, 2006:278-281
[60]Bekkerman I, Tabrikian J. Spatially coded transmission for active arrays. Processing of IEEE International Conference on Acoustics, Speech and Signal Processing, Montreal, Que, Canada,2004:209-212
[61]Tabrikian J, Bekkerman I. Transmission diversity smoothing for multi-target localization. Processing of IEEE International Conference on Acoustics. Speech, and Signal, Philadelphia, PA, United states,2005:1041-1044
[62]Frazer G J, Johnson B A, Abramovich Y. Orthogonal waveform support in MIMO HF OTH radars. Processing of 2007 International Waveform Diversity and Design Conference, Pisa, Italy,2007:423-427
[63]Frazer G J, Abramovich Y, Johnson B A. Spatially waveform diverse radar: Perspectives for high frequency OTHR. Processing of IEEE National Radar Conference, Waltham, MA, United states,2007:385-390
[64]Frazer G J, Abramovich Y I, Johnson B A recent results in MIMO over-the-horizon radar. Processing of 2008 IEEE Radar Conference, Rome, Italy,2008:1-6
[65]Xu L, Li J, Stoica P. Adaptive techniques for MIMO radar. Processing of 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop, Waltham, MA, United states,2006:258-262
[66]Li J, Stoica P, Xu L. On parameter identifiability of MIMO radar. IEEE Signal Processing Letters,2007,14(12):968-971
[67]Stoica P, Xu L, Li J. Parameter estimation and number detection of MIMO radar targets. Conference Record of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United states,2007:177-181
[68]Xu L, Li J. Iterative generalized-likelihood ratio test for MIMO radar. IEEE Transactions on Signal Processing,2007,55(6):2375-2385
[69]Romberg J. Imaging via compressive sampling:Introduction to compressive sampling and recovery via convex programming. IEEE Signal Processing Magazine, 2008, 25(2):14-20.
[70]Bajwa W, Haupt J. Sayeed A, et al. Compressive wireless sensing. Processing of the Fifth International Conference on Information Processing in Sensor Networks, Piscataway, NJ, USA,2006:134-142.
[71]Yu Y, Petropulu A P, Poor H V. Compressive sensing for MIMO radar. Processing of 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, Taipei, Taiwan.2009:3017-3020
[72]Petropulu A, Yu Y, Poor H V. Distributed MIMO radar using compressive sampling. Conference Record of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United states,2008:203-207
[73]Chen C, Vaidyanathan P P. MIMO radar space-time adaptive processing using prolate spheroidal wave functions. IEEE Transactions on Signal Processing, 2008.56(2):623-635
[74]Chen C, Vaidyanathan P P. A subspace method for MIMO radar space-time adaptive processing. Processing of 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, Piscataway, NJ, USA,2007:Ⅱ925-Ⅱ928
[75]Rabideau D J. Non-adaptive multiple-input, multiple-output radar techniques for reducing clutter. IET Radar, Sonar and Navigation,2009,3(4):304-313.
[76]Zeng J, He Z, Liu B. Adaptive space-time-waveform processing for MIMO radar. Processing of 2007 International Conference on Communications, Circuits and Systems, Kokura, Japan,2008:641-643
[77]Wang G, Lu Y. Clutter rank of MIMO radar with a speical class of waveforms. Processing of 2009 International Waveform Diversity and Design Conference, Kissimmee, FL, United states,2009:108-112
[78]Deng H, Himed B. Detection of low-speed ground moving targets using MIMO radar. Processing of 2009 IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting, North Charleston, SC, United states, 2009:1-4
[79]Mecca V F, Ramakrishnan D, Krolik J. MIMO radar space-time adaptive processing for multipath clutter mitigation. Processing of 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop, Waltham, MA, United states, 2006:249-253
[80]Mecca V F, Krolik J L. MIMO enabled multipath clutter rank estimation. Processing of IEEE National Radar Conference, Pasadena, CA, United states,2009:1-6
[81]Bergin J, Techau P, Greenspan M. MIMO phased-array for airborne radar. Processing of 2008 IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting. San Diego, CA, United states, 2008:1-4
[82]Li J, Stoica P, Zheng X. Signal synthesis and receiver design for MIMO radar imaging. IEEE Transactions on Signal Processing,2008,56(8):3959-3968
[83]Wang D, Duan N, Xiao Y, et al. High-resolution imaging using a wideband MIMO radar system. Processing of 2009 IEEE International Conference on Information and Automation, Zhuhai, Macau, China,2009:1150-1155
[84]Ma X, Wang D, Su Y. High-resolution imaging using a narrowband MIMO radar system. Processing of International Conference on Signal Processing, Beijing, China,2008:2263-2266.
[85]Wang H, Su Y. Narrowband MIMO radar imaging with two orthogonal linear TR arrays Processing of International Conference on Signal Processing, Beijing, China.2008:2513-2516
[86]Roberts W, Li J, Stoica P, et al. MIMO radar angle-range-doppler imaging. Processing of IEEE National Radar Conference, Pasadena, CA, United states,2009:1-6
[87]Xue M, Zhu X, Li J, et al. MIMO radar angle-Doppler imaging via iterative space-time adaptive processing. Processing of 2009 International Waveform Diversity and Design Conference, Kissimmee, FL, United states,2009:129-133
[88]Zhu Q, Yuan Y. A method of MIMO system for synthetic aperture radar imaging. Processing of 2008 9th International Conference on Signal Processing, Piscataway, NJ, USA,2008:2404-2408.
[89]Deng H. Polyphase code design for orthogonal netted radar systems. IEEE Transactions on Signal Processing,2004,52(11):3126-3135
[90]Deng H, Wang B, Gu C, et al. Synthesis of binary sequences with good autocorrelation and cross-correlation properties by simulated annealing. Processing of 1998 International Conference on Communication Technology, Beijing, China,1998: PS051-PS055
[91]Deng H. Discrete frequency-coding waveform design for netted radar systems. IEEE Signal Processing Letters,2004,11(2):179-182
[92]Yang Y, Blum R S. Waveform design for MIMO radar based on mutual information and minimum mean-square error estimation. Processing of 2006 IEEE Conference on Information Sciences and Systems, Princeton, NJ, United states,2007:111-116
[93]戴喜增,彭应宁,汤俊.MIMO雷达检测性能.清华大学学报(自然科学版),2007,47(1)：88-91
[94]屈金佑,张剑云.MIMO雷达的相干脉冲串检测性能.电子与信息学报,2009,31(2):378-381
[95]关键,黄勇.Guass色噪声中MIMO分布孔径雷达检测性能分析.中国科学F辑：信息科学,2009,39(3)：363-369.
[96]Feng D, Li X, Lv H, et al. Two-sided minimum-variance distortionless response beamformer for MIMO radar. Signal Processing,2009,89(3):328-332.
[97]Qu Y, Liao G, Zhu S, et al. Performance analysis of beamforming for MIMO radar. Progress in Electromagnetics Research,2008,84:123-134
[98]Yan H, Li J, Liao G. Multitarget Identification and Localization Using Bistatic MIMO Radar Systems. EURASIP Journal on Advances in Signal Processing. 2008.2008(2008):Article ID 283483,8pp.
[99]Duofang C, Baixiao C, Guodong Q. Angle estimation using ESPRIT in MIMO radar. Electronics Letters,2008,44(12), 770-771.
[100]Jin M, Liao G, Li J. Joint DOD and DOA Estimation for Bistatic MIMO Radar. Elsevier Signal Processing,2009,89(2):244-251.
[101]Zhao G, Chen B, Zhu S. Direction synthesis in DOA estimation for monostatic multiple input multiple output (MIMO) radar based on synthetic impulse and aperture radar (SIAR) and its performance analysis. Science in China, Series E:Technological Sciences,2008,51(6):656-673
[102]Xia W, He Z. Multiple-target localization and estimation of MIMO radars using Capon and APES techniques. Processing of 2008 IEEE Radar Conference, Rome, Italy,2008: 6pp.
[103]Lv H, Feng D, Liu H, et al. Tri-iterative least-square method for bearing estimation in MIMO radar. Signal Processing,2009,89(12):2686-2691
[104]王怀军,粟毅,朱宇涛,等.基于空间谱域填充的MIMO雷达成像研究.电子学报,2009,37(6)：1242-1246
[105]杨明磊,陈伯孝,张守宏,等.多载频FMCW在MIMO雷达中的应用研究.电子学报,2008,36(12)：2351-2356
[106]Li J, Liu H, He Z, et al. Range migration compensation based on range-direction coupling in SFDLFM MIMO radar. WSEAS Transactions on Signal Processing,2009, 5(4):137-146
[107]Dai X, Xu J, Ye C, et al. Low-sidelobe HRR profiling based on the FDLFM-MIMO radar. Proceedings of 2007 1st Asian and Pacific Conference on Synthetic Aperture Radar, Huangshan, China,2007:132-135
[108]Haleem M A, Haimovich A M, Blum R S. Sidelobe Mitigation in MIMO Radar with Multiple Subcarriers. Proceedings of IEEE National Radar Conference, Pasadena, CA, United states,2009:6pp
[109]Wu Y, Tang J, Peng Y. Models and performance evaluation for multiple-input multiple-output space-time adaptive processing radar. IET Radar, Sonar and Navigation,2009,3(6):569-582
[110]张直中.雷达信号的选择与处理.北京：国防工业出版社,1979
[111]Liu G, Qian G,Yang G. Properties of noise code phase-modulated CW radar. Proceedings of ICSP'90, Beijing, China,1990:643-645.
[112]Liu G, Gu H, Su W. Development of random signal radar. IEEE Transactions on Aerospace and Electronic Systems,1999,35(3):770-777.
[113]Liu G, Gu H, Zhu X, et al. The present and the future of random signal radars. IEEE Aerospace and Electronic Systems Magazine,1997,12 (10):35-40
[114]张艳艳.雷达相位编码信号的研究和应用.西安电子科技大学硕士学位论文,2007
[115]盛建锋.相位编码雷达信号处理及其性能分析.南京理工大学硕士学位论文,2004
[116]Khan H A, Edwards D J. Doppler problems in orthogonal MIMO radars. Proceedings of 2006 IEEE Radar Conference, New York, United states,2006:244-247
[117]Chen X, Oksman J. A new algorithm to optimize Barker code sidelobe suppression filter. IEEE Transactions on Aerospace and Electronic Systems,1990,26(4):673-677
[118]金淑芳,顾红,盛剑锋,等.基于子空间投影的相位编码雷达旁瓣抑制方法.数据采集与处理,2004,19(4)：361-364
[119]张仕元,吴乐南.基于RLS的脉压雷达数字旁瓣抑制滤波器设计方法.测控技术,2006,25(7)：79-82
[120]熊张亮,张永胜,是湘全,等.一种大多普勒容限的伪码调相连续波雷达.南京理工大学学报,2005,29(5)：514-517,520
[121]赵菁菁,胡学成.巴克码多普勒容限带宽扩展的神经网络法研究.现代雷达,2004,26(8)：33-35.
[122]王毅鹰苏兮.基于m序列信号的多普勒补偿方法.现代雷达,2007,29(2)：48-51.
[123]祁玉生,邵世祥.现代移动通信系统.北京：人民邮电出版社,1999.
[124]樊昌信,张甫翊,徐炳祥,等.通信原理.第五版.北京：国防工业出版社,2002
[125]张永胜.伪码调相连续波雷达的性能与应用研究.南京理工大学硕士学位论文,2004.
[126]章潜五.随机信号分析.陕西：西北电讯工程学院出版社,1986
[127]Chen C. Signal processing algorithms for MIMO radar. California, USA:California Institute of Technology,Electrical Engineering/DSP Lab,2009[Online]. Available: http://www.systems.caltech.edu/cyc/presentations/Candidacy_new.ppt
[128]夏威.MIMO雷达模型与信号处理研究.电子科技大学博士学位论文,2008
[129]Liu N, Zhang L R, Zhang J, et al. Direction finding of MIMO radar through ESPRIT and Kalman filter. Electronics Letters,2009,45(17):908-910
[130]Chen J, Gu H, Su W. A new method for joint DOD and DOA estimation in bistatic MIMO radar. Signal Processing,2010,90(2):714-718
[131]Chen J, Gu H, Su W. Angle estimation using ESPRIT without pairing in MIMO radar. Electronics Letters,2008,44(24):1422-1423.
[132]Xia W, He Z, Liao Y. Subspace-based method for multiple-target localization using MIMO radars. Proceedings of IEEE International Symposium on Signal Processing and Information Technology, Giza, Egypt,2007:715-720
[133]Calvary P, Janer D. Spatio-temporal coding for radar array processing. Proceedings of 1998 IEEE International Conference on Acoustics, Speech, and Signal Processing, Seattle, WA, USA,1998:2509-2512
[134]杨振起,张永顺,骆永军.双(多)基地雷达系统.北京：国防工业出版社,1998
[135]王永良,陈辉,彭应宁,等.空间谱估计理论与算法.北京：清华大学出版社,2004
[136]张涛麟,刘颖,廖桂生.一种未知信源数的高分辨DOA估计算.电子与信息学报,2008,30(2)：375-378
[137]朱敏,游志胜,聂健荪.双(多)基地雷达系统中的若干关键技术研究.现代雷达,2002,24(6)：1-5
[138]Jao J K. Coherent multilateral radar processing for precise target geolocation. Proceedings of 2006 IEEE conference on radar, Piscataway, NJ, USA,2006:325-330.
[139]Krim H, Viberg M. Two decades of array signal processing research:The parametric approach. IEEE Signal Processing Magazine,1996,13(4):67-94
[140]任勋立,廖桂生,曾操.一种低复杂度的二维波达方向估计方法.电报科学学报,2005,20(4),526-530.
[141]唐明,王定江,冯鸣,等.线性代数.杭州：浙江大学出版社,2004
[142]Wu H T, Yang J F, Chen F K. Source number estimators using transformed gerschgorin radii. IEEE Transactions on Signal Processing,1995,43(6):1325-1333.
[143]刁鸣,缪善林.一种二维ESPRIT算法参数配对新方法.系统工程与电子技术,2007,29(8),1226-1229.
[144]Golub G H, VanLoan C F. Matrix Computations.3rd ed. Baltimore, MD:John Hopkins University Press,1996
[145]Golub G H, Reinsch C. Singular value decomposition and least squares solutions. Numerische Mathematik,1970,14(4):403-420.
[146]Zhou C G, Haber F, Jaggard D L. The resolution threshold of MUSIC with unknown spatially correlated noise. IEEE Transactions on Signal Processing,1993, 41(1):511-516.
[147]Sinath H, Reddy V U. Analysis of MUSIC algorithm with sensor gain and phase perturbations. Signal Processing,1991.23(3):245-256.
[148]Li F, Vaccaro R J. Performance degradation of DO A estimators due to unknown noise field. IEEE Transactions on Signal Processing,1992,40(3):656-690
[149]Qiang W, Kon M. UN-Music and UN-CLE:An application of generalized correlation analysis to the estimation of the direction of arrival of signal in unknown correlated noise, IEEE Transactions on Signal Processing,1994,42(9):2331-2343.
[150]陈校平,曾祥能.MIMO雷达在防空反导作战中的优势分析.电讯技术,2009,49(10)：53-57
[151]搜狐科学.NASA:空间站若受冲击宇航员将转至联盟号[Online].Available: http://news.cqnews.net/special/wxxz/wxxz_zxxx/200902/t20090213_2960995.htm
[152]Chen J J, Chen J, and Wang S L. Detection of ultra-high speed moving target based on matched Fourier transform. Proceedings of International conference on radar, Shanghai, China,2006:1-4.
[153]冯德军,王雪松,肖顺平,等.高速目标解调频处理的相位特性及其补偿.电子与信息学报,2008,30(4),916-920.
[154]莫力.雷达微弱目标长时间积累检测算法的研究.北京理工大学博士学位论文,2004.
[155]王俊.微弱目标信号积累检测的方法研究.西安电子科技大学博士学位论文,1999.
[156]陈远征,朱永锋,赵宏钟,等.基于包络插值移位补偿的高速运动目标的积累检测算法研究.信号处理,2004,20(4)：387-390.
[157]韩兴斌,胡卫东,郁文贤,等.分布式多通道雷达成像技术.电子与信息学报,2007,29(10)：2354-2358.
[158]孙立宏,王俊.高速运动雷达弱小目标检测方法研究.系统工程与电子技术,2008,30(2)：257-260.
[159]张顺生,曾涛.基于Keystone变换的微弱目标检测.电子学报,2005,33(9)：1675-1678.
[160]Gray D A and Capria A. MIMO noise radar-matched filters and coarrays. Proceedings of IEEE Radar Conference, Roma, Italy,2008:1-6.
[161]Liu B, He Z, and Zeng J. Receiving signal processing of MIMO radar based on transmitting diversity. Proceedings of 6th International Conference on ITS Telecommunications, Chengdu, China,2006:1224-1227.
[162]Liu G S, Gu H, and Su W M. The development of random signal radars. IEEE Transactions on Aerospace and Electronic Systems,1999,35(3):770-777.
[163]刘国岁,顾红,苏卫民.随机信号雷达.北京：国防工业出版社.2005.
[2]Siebert W M. A radar detection philosophy. IEEE Transactions on Information Theory, 1956,2(3):204-221
[3]Woodward P M. Probability and information theory with application to radar.1st ed. New York: McGraw-hill,1953
[4]丁鹭飞,耿富录.雷达原理.第二版.西安：西安电子科技大学出版社,2000
[5]Alamouti S M. A simple transmit diversity technique for wireless communications.IEEE Journal on Selected Areas in Communications,1998, 16(8):1451-1458
[6]Foscnini G J, Golden G D, Valenzuela R A, et al. Simplified processing for nigh spectral efficiency wireless communication employing multi-element arrays. IEEE Journal on Selected Areas in Communications,1999,17(11):1841-1852
[7]Telatar I E. Capacity of multi-antenna gaussian channels. European Transactions on Telecommunications,1999,10(6):585-596
[8]Foschini G. J. Layered space-time architecture for wireless communication in a fading environment when using multiple antennas. Bell Labs Technical Journal.1996,1(2): 41-59.
[9]Foschini G J, Gans M J. On limits of wireless communications in a fading environment when using multi-element antennas. Wireless Personal Communications, 1998,6:311-335.
[10]Wolniansky P W, Foschini G J, Golden G D, et al. V-BLAST: an architecture for realizing very high data rates over the rich-scattering wireless channels. Proceedings of URSI International Symposium on Signal, Systems, and Electronics, Pisa, Italy, 1998:295-300
[11]Fishler E, Haimovich A, Blum R, Cimini L, Chizhik D, and Valenzuela R. MIMO radar: an idea whose time has come. Proceedings of 2004 IEEE International Conference on Radar, Philadelphia, PA, United States,2004:71-78
[12]Fisher E, Haimovich A, Blum, R S, et al. Spatial diversity in radars models and detection performance. IEEE Transactions on Signal Processing,2006,54(3):823-838
[13]何子述,韩春林,刘波.MIMO雷达概念及其技术特点分析.电子学
报,2005,33(12A)：2441-2445
[14]Haimovich A M, Blum R S, Leonard J, et al, MIMO radar with widely separated antennas. IEEE Signal Processing Magazine,2008,25(1):116-129
[15]Fishler E, Haimovich A M, Blum R S, et al. Performance of MIMO radar systems: advantages of angular diversity. Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, United States,2004:305-309.
[16]Lehmann N H, Fisher E, Haimovich A M,et al. Evaluation of transmit diversity in MIMO radar direction finding. IEEE Transactions on Signal Processing,2007,55(5): 2215-2225
[17]Baumgarten D. Optimum detection and receiver performance for multistatic radar configurations. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Paris, France,1982:359-362.
[18]Chernyak V S. Fundamentals of multisite radar systems. New York: Gordon and Breach,1998.
[19]Johnsen T, Olsen K E, Johnsrud S, et al. Simultaneous use of multiple pseudo random noise codes in multistatic CW radar. Proceedings of IEEE International Conference on Radar, Philadelphia, PA, USA,2004:266-270
[20]张光斌.双／多基地雷达参数估计算法研究.西安电子科技大学博士学位论文,2006
[21]Papoutsis I, Baker C J, Griffiths H D. Fundamental performance limitations of radar networks. Proceedings of 1 st EMRS DTC Technical Conference, Edinburgh, England, 2004: A7
[22]Viswanathan R, Varshney P K. Distributed detection with multiple sensors I: Fundamentals. Proceedings of the IEEE,1997,85(1):54-63
[23]Blum R S, Kassam S A, Poor H V. Distributed detection with multiple sensors II: Advanced topics," Proceedings of the IEEE,1997,85(1):64-79
[24]Blum R S. Distributed detection for diversity reception of fading signals in noise. IEEE Transactions on Information Theory,1999,45(1):158-164
[25]Gorji A A, Tharmarasa R, Kirubarajan T. MIMO vs. multistatic radars for target localization. Proceedings of the SPIE,2009,7445(2009):744502-744502-12
[26]Lehmann N, Haimovich A M, Blum R S, et al. MIMO radar application to moving target detection in homogenous clutter. Waltham, MA, USA: Adaptive Sensor Array Processing Workshop at MIT Lincoln Laboratory,2006 [Online]. Available: http://www.ll.mit. edu/asap/asap_06/pdf/Presentations/05_Haimovich_P.pdf
[27]Sheikhi A, Zamani A, Norouzi Y. Model-based adaptive target detection in clutter using MIMO radar. Proceedings of 2006 International Conference on Radar(CIE'06), Shanghai, China,2006:57-60
[28]Sheikhi A, Zamani A. Adaptive target detection in clutter using MIMO radar. Proceedings of 2006 International Radar Symposium (IRS 2006), Krakow, Poland, 2006:1-4
[29]Sammartino P F, Baker C J, Griffiths H D. MIMO radar performance in clutter environment. Proceedings of 2006 International Conference on Radar (CIE '06), Shanghai, China,2006:32-37
[30]Akcakaya M, Hurtado M, NehoraiA. MIMO radar detection of targets in compound-gaussian clutter. Proceedings of 2008 42nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA,USA,2008:208-212
[31]Sheikhi A, Zamani A. Temporal coherent adaptive target detection for multi-input multi-output radars in clutter. IET Radar, Sonar & Navigation,2008,2(2):86-96
[32]Lehmann N H. Some contributions on MIMO radar [PhD Dissertation]. University Heights, Newark, NJ,2007
[33]Lehmann N H, Haimovich A M, Blum R S, et al. High resolution capabilities of MIMO radar. Proceedings of 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA,2006:25-30
[34]Godrich H, Haimovich A M, Blum R S. Target localization techniques and tools for MIMO radar. Proceedings of 2008 IEEE Radar Conference, Rome, Italy,2008:1-6
[35]Godrich H, Haimovich A M, Blum R S. Target localisation techniques and tools for multiple-input multiple-output radar. IET Radar, Sonar & Navigation, 2009,3(4):314-327
[36]Rabideau D J, Parker P. Ubiquitous MIMO multifunction digital array radar. Conference Record of the 37th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA,2003:1057-1064
[37]Li J, Stoica P. MIMO radar with colocated antennas, IEEE Signal Processing Magazine,2007,24(5):106-114
[38]Bekkerman I, Tabrikian J. Target detection and localization using MIMO radars and sonars. IEEE Transactions on Signal Processing,2006,54(10):3873-3883.
[39]Robey F C, Coutts S, Weikle D. MIMO radar theory and experimental results. Conference Record of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United states,2004:300-304
[40]曾建奎.MIMO雷达信号检测的若干问题研究.电子科技大学博士学位论文,2008.
[41]刘波.MIMO雷达正交波形设计及信号处理研究.电子科技大学博士学位论文,2007.
[42]Dorey J, Gamier G. RIAS, synthetic impulse and antenna radar.Proceedings of international conference on radar, Paris, France,1989:36-44
[43]保铮,张庆文.一种新型的米波雷达一综合脉冲与孔径雷达.现代雷达,1995,17(1)：1-13
[44]陈伯孝.四维跟踪及其长相干积累等技术研究.西安电子科技大学博士学位论文,1997
[45]陈伯孝,张守宏.稀布阵综合脉冲孔径雷达低距离旁瓣与距离高分辨技术.电子学报,1998,26(9)：29-33
[46]陈伯孝,张守宏.综合脉冲孔径雷达的主要特点及其“四抗”性能.西安电子科技大学学报(雷达信号处理专辑),1997,24：140-146
[47]赵光辉.基于SIAR体制的稀布阵米波雷达若干问题研究.西安电子科技大学博士学位论文,2008
[48]Bliss D W, Forsythe K W. Multiple-input multiple-output (MIMO) radar and imaging degrees of freedom and resolution. Conference Record of the 37th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United states,2003:54-59
[49]De Maio A, Lops M. Design principles of MIMO radar detectors. IEEE Transactions on Aerospace and Electronic Systems,2007,43(3):886-898
[50]Khan H A, Malik W Q, Edwards D J, et al. Ultra wideband multiple-input multiple-output radar. Conference Record of 2005 IEEE International Radar, Arlington, VA, USA,2005:900-904
[51]Tang J, Li N, Wu Y, et al. Diversity order and detection performance of MIMO radar a relative entropy based study. IEEE Signal Processing Letters,2009,16(3):184-187
[52]Tang J, Wu Y, Peng Y, et al. On detection performance and system configuration of MIMO radar. Science in China Series F: Information Sciences, 2009, 52(7):1250-1257.
[53]Tang J, Wu Y, Peng Y, et al. On detection performance of MIMO radar for Rician target. Science in China Series F:Information Sciences,2009,52(8):1456-1465
[54]Petillot Y, Du C, Thompson J S. Predicted detection performance of MIMO radar. IEEE Signal Processing Letters,2008,15:83-86
[55]Godrich H, Haimovich A M, Blum R S. A comparative study of target localization in MIMO radar systems. Proceedings of 2009 International Waveform Diversity and Design Conference, Kissimmee, FL, United states,2009:124-128
[56]Godrich H, Haimovich A M, Blum R S. Cramer Rao bound on target localization estimation in MIMO radar systems. Proceedings of The 42nd Annual Conference on Information Sciences and Systems, Princeton, NJ, United states,2008:134-139
[57]He Q, Blum R S, Godrich H. Cramer-Rao bound for target velocity estimation in MIMO radar with widely separated antennas. Proceedings of The 42nd Annual Conference on Information Sciences and Systems, Princeton, NJ, United states, 2008:123-127
[58]He Q, Blum R S. Cramer-Rao bound for MIMO radar target localization with phase errors. IEEE Signal Processing Letters,2010,17(1):83-86
[59]Tabrikian J. Barankin Bounds for Target localization by MIMO radars. Processing of Fourth IEEE Workshop on Sensor Array and Multichannel, Waltham, MA, USA, 2006:278-281
[60]Bekkerman I, Tabrikian J. Spatially coded transmission for active arrays. Processing of IEEE International Conference on Acoustics, Speech and Signal Processing, Montreal, Que, Canada,2004:209-212
[61]Tabrikian J, Bekkerman I. Transmission diversity smoothing for multi-target localization. Processing of IEEE International Conference on Acoustics. Speech, and Signal, Philadelphia, PA, United states,2005:1041-1044
[62]Frazer G J, Johnson B A, Abramovich Y. Orthogonal waveform support in MIMO HF OTH radars. Processing of 2007 International Waveform Diversity and Design Conference, Pisa, Italy,2007:423-427
[63]Frazer G J, Abramovich Y, Johnson B A. Spatially waveform diverse radar: Perspectives for high frequency OTHR. Processing of IEEE National Radar Conference, Waltham, MA, United states,2007:385-390
[64]Frazer G J, Abramovich Y I, Johnson B A recent results in MIMO over-the-horizon radar. Processing of 2008 IEEE Radar Conference, Rome, Italy,2008:1-6
[65]Xu L, Li J, Stoica P. Adaptive techniques for MIMO radar. Processing of 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop, Waltham, MA, United states,2006:258-262
[66]Li J, Stoica P, Xu L. On parameter identifiability of MIMO radar. IEEE Signal Processing Letters,2007,14(12):968-971
[67]Stoica P, Xu L, Li J. Parameter estimation and number detection of MIMO radar targets. Conference Record of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United states,2007:177-181
[68]Xu L, Li J. Iterative generalized-likelihood ratio test for MIMO radar. IEEE Transactions on Signal Processing,2007,55(6):2375-2385
[69]Romberg J. Imaging via compressive sampling:Introduction to compressive sampling and recovery via convex programming. IEEE Signal Processing Magazine, 2008, 25(2):14-20.
[70]Bajwa W, Haupt J. Sayeed A, et al. Compressive wireless sensing. Processing of the Fifth International Conference on Information Processing in Sensor Networks, Piscataway, NJ, USA,2006:134-142.
[71]Yu Y, Petropulu A P, Poor H V. Compressive sensing for MIMO radar. Processing of 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, Taipei, Taiwan.2009:3017-3020
[72]Petropulu A, Yu Y, Poor H V. Distributed MIMO radar using compressive sampling. Conference Record of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, United states,2008:203-207
[73]Chen C, Vaidyanathan P P. MIMO radar space-time adaptive processing using prolate spheroidal wave functions. IEEE Transactions on Signal Processing, 2008.56(2):623-635
[74]Chen C, Vaidyanathan P P. A subspace method for MIMO radar space-time adaptive processing. Processing of 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, Piscataway, NJ, USA,2007:Ⅱ925-Ⅱ928
[75]Rabideau D J. Non-adaptive multiple-input, multiple-output radar techniques for reducing clutter. IET Radar, Sonar and Navigation,2009,3(4):304-313.
[76]Zeng J, He Z, Liu B. Adaptive space-time-waveform processing for MIMO radar. Processing of 2007 International Conference on Communications, Circuits and Systems, Kokura, Japan,2008:641-643
[77]Wang G, Lu Y. Clutter rank of MIMO radar with a speical class of waveforms. Processing of 2009 International Waveform Diversity and Design Conference, Kissimmee, FL, United states,2009:108-112
[78]Deng H, Himed B. Detection of low-speed ground moving targets using MIMO radar. Processing of 2009 IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting, North Charleston, SC, United states, 2009:1-4
[79]Mecca V F, Ramakrishnan D, Krolik J. MIMO radar space-time adaptive processing for multipath clutter mitigation. Processing of 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop, Waltham, MA, United states, 2006:249-253
[80]Mecca V F, Krolik J L. MIMO enabled multipath clutter rank estimation. Processing of IEEE National Radar Conference, Pasadena, CA, United states,2009:1-6
[81]Bergin J, Techau P, Greenspan M. MIMO phased-array for airborne radar. Processing of 2008 IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting. San Diego, CA, United states, 2008:1-4
[82]Li J, Stoica P, Zheng X. Signal synthesis and receiver design for MIMO radar imaging. IEEE Transactions on Signal Processing,2008,56(8):3959-3968
[83]Wang D, Duan N, Xiao Y, et al. High-resolution imaging using a wideband MIMO radar system. Processing of 2009 IEEE International Conference on Information and Automation, Zhuhai, Macau, China,2009:1150-1155
[84]Ma X, Wang D, Su Y. High-resolution imaging using a narrowband MIMO radar system. Processing of International Conference on Signal Processing, Beijing, China,2008:2263-2266.
[85]Wang H, Su Y. Narrowband MIMO radar imaging with two orthogonal linear TR arrays Processing of International Conference on Signal Processing, Beijing, China.2008:2513-2516
[86]Roberts W, Li J, Stoica P, et al. MIMO radar angle-range-doppler imaging. Processing of IEEE National Radar Conference, Pasadena, CA, United states,2009:1-6
[87]Xue M, Zhu X, Li J, et al. MIMO radar angle-Doppler imaging via iterative space-time adaptive processing. Processing of 2009 International Waveform Diversity and Design Conference, Kissimmee, FL, United states,2009:129-133
[88]Zhu Q, Yuan Y. A method of MIMO system for synthetic aperture radar imaging. Processing of 2008 9th International Conference on Signal Processing, Piscataway, NJ, USA,2008:2404-2408.
[89]Deng H. Polyphase code design for orthogonal netted radar systems. IEEE Transactions on Signal Processing,2004,52(11):3126-3135
[90]Deng H, Wang B, Gu C, et al. Synthesis of binary sequences with good autocorrelation and cross-correlation properties by simulated annealing. Processing of 1998 International Conference on Communication Technology, Beijing, China,1998: PS051-PS055
[91]Deng H. Discrete frequency-coding waveform design for netted radar systems. IEEE Signal Processing Letters,2004,11(2):179-182
[92]Yang Y, Blum R S. Waveform design for MIMO radar based on mutual information and minimum mean-square error estimation. Processing of 2006 IEEE Conference on Information Sciences and Systems, Princeton, NJ, United states,2007:111-116
[93]戴喜增,彭应宁,汤俊.MIMO雷达检测性能.清华大学学报(自然科学版),2007,47(1)：88-91
[94]屈金佑,张剑云.MIMO雷达的相干脉冲串检测性能.电子与信息学报,2009,31(2):378-381
[95]关键,黄勇.Guass色噪声中MIMO分布孔径雷达检测性能分析.中国科学F辑：信息科学,2009,39(3)：363-369.
[96]Feng D, Li X, Lv H, et al. Two-sided minimum-variance distortionless response beamformer for MIMO radar. Signal Processing,2009,89(3):328-332.
[97]Qu Y, Liao G, Zhu S, et al. Performance analysis of beamforming for MIMO radar. Progress in Electromagnetics Research,2008,84:123-134
[98]Yan H, Li J, Liao G. Multitarget Identification and Localization Using Bistatic MIMO Radar Systems. EURASIP Journal on Advances in Signal Processing. 2008.2008(2008):Article ID 283483,8pp.
[99]Duofang C, Baixiao C, Guodong Q. Angle estimation using ESPRIT in MIMO radar. Electronics Letters,2008,44(12), 770-771.
[100]Jin M, Liao G, Li J. Joint DOD and DOA Estimation for Bistatic MIMO Radar. Elsevier Signal Processing,2009,89(2):244-251.
[101]Zhao G, Chen B, Zhu S. Direction synthesis in DOA estimation for monostatic multiple input multiple output (MIMO) radar based on synthetic impulse and aperture radar (SIAR) and its performance analysis. Science in China, Series E:Technological Sciences,2008,51(6):656-673
[102]Xia W, He Z. Multiple-target localization and estimation of MIMO radars using Capon and APES techniques. Processing of 2008 IEEE Radar Conference, Rome, Italy,2008: 6pp.
[103]Lv H, Feng D, Liu H, et al. Tri-iterative least-square method for bearing estimation in MIMO radar. Signal Processing,2009,89(12):2686-2691
[104]王怀军,粟毅,朱宇涛,等.基于空间谱域填充的MIMO雷达成像研究.电子学报,2009,37(6)：1242-1246
[105]杨明磊,陈伯孝,张守宏,等.多载频FMCW在MIMO雷达中的应用研究.电子学报,2008,36(12)：2351-2356
[106]Li J, Liu H, He Z, et al. Range migration compensation based on range-direction coupling in SFDLFM MIMO radar. WSEAS Transactions on Signal Processing,2009, 5(4):137-146
[107]Dai X, Xu J, Ye C, et al. Low-sidelobe HRR profiling based on the FDLFM-MIMO radar. Proceedings of 2007 1st Asian and Pacific Conference on Synthetic Aperture Radar, Huangshan, China,2007:132-135
[108]Haleem M A, Haimovich A M, Blum R S. Sidelobe Mitigation in MIMO Radar with Multiple Subcarriers. Proceedings of IEEE National Radar Conference, Pasadena, CA, United states,2009:6pp
[109]Wu Y, Tang J, Peng Y. Models and performance evaluation for multiple-input multiple-output space-time adaptive processing radar. IET Radar, Sonar and Navigation,2009,3(6):569-582
[110]张直中.雷达信号的选择与处理.北京：国防工业出版社,1979
[111]Liu G, Qian G,Yang G. Properties of noise code phase-modulated CW radar. Proceedings of ICSP'90, Beijing, China,1990:643-645.
[112]Liu G, Gu H, Su W. Development of random signal radar. IEEE Transactions on Aerospace and Electronic Systems,1999,35(3):770-777.
[113]Liu G, Gu H, Zhu X, et al. The present and the future of random signal radars. IEEE Aerospace and Electronic Systems Magazine,1997,12 (10):35-40
[114]张艳艳.雷达相位编码信号的研究和应用.西安电子科技大学硕士学位论文,2007
[115]盛建锋.相位编码雷达信号处理及其性能分析.南京理工大学硕士学位论文,2004
[116]Khan H A, Edwards D J. Doppler problems in orthogonal MIMO radars. Proceedings of 2006 IEEE Radar Conference, New York, United states,2006:244-247
[117]Chen X, Oksman J. A new algorithm to optimize Barker code sidelobe suppression filter. IEEE Transactions on Aerospace and Electronic Systems,1990,26(4):673-677
[118]金淑芳,顾红,盛剑锋,等.基于子空间投影的相位编码雷达旁瓣抑制方法.数据采集与处理,2004,19(4)：361-364
[119]张仕元,吴乐南.基于RLS的脉压雷达数字旁瓣抑制滤波器设计方法.测控技术,2006,25(7)：79-82
[120]熊张亮,张永胜,是湘全,等.一种大多普勒容限的伪码调相连续波雷达.南京理工大学学报,2005,29(5)：514-517,520
[121]赵菁菁,胡学成.巴克码多普勒容限带宽扩展的神经网络法研究.现代雷达,2004,26(8)：33-35.
[122]王毅鹰苏兮.基于m序列信号的多普勒补偿方法.现代雷达,2007,29(2)：48-51.
[123]祁玉生,邵世祥.现代移动通信系统.北京：人民邮电出版社,1999.
[124]樊昌信,张甫翊,徐炳祥,等.通信原理.第五版.北京：国防工业出版社,2002
[125]张永胜.伪码调相连续波雷达的性能与应用研究.南京理工大学硕士学位论文,2004.
[126]章潜五.随机信号分析.陕西：西北电讯工程学院出版社,1986
[127]Chen C. Signal processing algorithms for MIMO radar. California, USA:California Institute of Technology,Electrical Engineering/DSP Lab,2009[Online]. Available: http://www.systems.caltech.edu/cyc/presentations/Candidacy_new.ppt
[128]夏威.MIMO雷达模型与信号处理研究.电子科技大学博士学位论文,2008
[129]Liu N, Zhang L R, Zhang J, et al. Direction finding of MIMO radar through ESPRIT and Kalman filter. Electronics Letters,2009,45(17):908-910
[130]Chen J, Gu H, Su W. A new method for joint DOD and DOA estimation in bistatic MIMO radar. Signal Processing,2010,90(2):714-718
[131]Chen J, Gu H, Su W. Angle estimation using ESPRIT without pairing in MIMO radar. Electronics Letters,2008,44(24):1422-1423.
[132]Xia W, He Z, Liao Y. Subspace-based method for multiple-target localization using MIMO radars. Proceedings of IEEE International Symposium on Signal Processing and Information Technology, Giza, Egypt,2007:715-720
[133]Calvary P, Janer D. Spatio-temporal coding for radar array processing. Proceedings of 1998 IEEE International Conference on Acoustics, Speech, and Signal Processing, Seattle, WA, USA,1998:2509-2512
[134]杨振起,张永顺,骆永军.双(多)基地雷达系统.北京：国防工业出版社,1998
[135]王永良,陈辉,彭应宁,等.空间谱估计理论与算法.北京：清华大学出版社,2004
[136]张涛麟,刘颖,廖桂生.一种未知信源数的高分辨DOA估计算.电子与信息学报,2008,30(2)：375-378
[137]朱敏,游志胜,聂健荪.双(多)基地雷达系统中的若干关键技术研究.现代雷达,2002,24(6)：1-5
[138]Jao J K. Coherent multilateral radar processing for precise target geolocation. Proceedings of 2006 IEEE conference on radar, Piscataway, NJ, USA,2006:325-330.
[139]Krim H, Viberg M. Two decades of array signal processing research:The parametric approach. IEEE Signal Processing Magazine,1996,13(4):67-94
[140]任勋立,廖桂生,曾操.一种低复杂度的二维波达方向估计方法.电报科学学报,2005,20(4),526-530.
[141]唐明,王定江,冯鸣,等.线性代数.杭州：浙江大学出版社,2004
[142]Wu H T, Yang J F, Chen F K. Source number estimators using transformed gerschgorin radii. IEEE Transactions on Signal Processing,1995,43(6):1325-1333.
[143]刁鸣,缪善林.一种二维ESPRIT算法参数配对新方法.系统工程与电子技术,2007,29(8),1226-1229.
[144]Golub G H, VanLoan C F. Matrix Computations.3rd ed. Baltimore, MD:John Hopkins University Press,1996
[145]Golub G H, Reinsch C. Singular value decomposition and least squares solutions. Numerische Mathematik,1970,14(4):403-420.
[146]Zhou C G, Haber F, Jaggard D L. The resolution threshold of MUSIC with unknown spatially correlated noise. IEEE Transactions on Signal Processing,1993, 41(1):511-516.
[147]Sinath H, Reddy V U. Analysis of MUSIC algorithm with sensor gain and phase perturbations. Signal Processing,1991.23(3):245-256.
[148]Li F, Vaccaro R J. Performance degradation of DO A estimators due to unknown noise field. IEEE Transactions on Signal Processing,1992,40(3):656-690
[149]Qiang W, Kon M. UN-Music and UN-CLE:An application of generalized correlation analysis to the estimation of the direction of arrival of signal in unknown correlated noise, IEEE Transactions on Signal Processing,1994,42(9):2331-2343.
[150]陈校平,曾祥能.MIMO雷达在防空反导作战中的优势分析.电讯技术,2009,49(10)：53-57
[151]搜狐科学.NASA:空间站若受冲击宇航员将转至联盟号[Online].Available: http://news.cqnews.net/special/wxxz/wxxz_zxxx/200902/t20090213_2960995.htm
[152]Chen J J, Chen J, and Wang S L. Detection of ultra-high speed moving target based on matched Fourier transform. Proceedings of International conference on radar, Shanghai, China,2006:1-4.
[153]冯德军,王雪松,肖顺平,等.高速目标解调频处理的相位特性及其补偿.电子与信息学报,2008,30(4),916-920.
[154]莫力.雷达微弱目标长时间积累检测算法的研究.北京理工大学博士学位论文,2004.
[155]王俊.微弱目标信号积累检测的方法研究.西安电子科技大学博士学位论文,1999.
[156]陈远征,朱永锋,赵宏钟,等.基于包络插值移位补偿的高速运动目标的积累检测算法研究.信号处理,2004,20(4)：387-390.
[157]韩兴斌,胡卫东,郁文贤,等.分布式多通道雷达成像技术.电子与信息学报,2007,29(10)：2354-2358.
[158]孙立宏,王俊.高速运动雷达弱小目标检测方法研究.系统工程与电子技术,2008,30(2)：257-260.
[159]张顺生,曾涛.基于Keystone变换的微弱目标检测.电子学报,2005,33(9)：1675-1678.
[160]Gray D A and Capria A. MIMO noise radar-matched filters and coarrays. Proceedings of IEEE Radar Conference, Roma, Italy,2008:1-6.
[161]Liu B, He Z, and Zeng J. Receiving signal processing of MIMO radar based on transmitting diversity. Proceedings of 6th International Conference on ITS Telecommunications, Chengdu, China,2006:1224-1227.
[162]Liu G S, Gu H, and Su W M. The development of random signal radars. IEEE Transactions on Aerospace and Electronic Systems,1999,35(3):770-777.
[163]刘国岁,顾红,苏卫民.随机信号雷达.北京：国防工业出版社.2005.