基于RD-SRT的TR MIMO雷达DOA估计算法
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摘要
针对时间反转MIMO雷达多重信号分类算法计算量庞大的问题,提出一种基于降维子空间旋转变换技术的多目标波达角估计算法。首先,通过采用降维思想对TR MIMO回波信号进行降维处理,来减少计算量;然后,为构造旋转变换矩阵,对噪声子空间按行分块并取其逆矩阵;最后,利用该逆矩阵对噪声子空间矩阵旋转变换,得到低维子空间矩阵,对比导向矢量构造谱函数估计目标的角度信息。相对于传统的MUSIC算法,该算法降低了噪声子空间的维度,大大降低了计算量,而且具有更高的目标分辨率。
For the problem of huge computations of multiple signal classification(MUSIC)algorithm in the time reversal(TR)MIMO radar,a multi-target direction of arrival(DOA)estimation algorithm based on reduced dimension(RD)and subspace rotation technique(SRT)was proposed.Firstly,the proposed algorithm was applied to reduce the dimension for the echo signal of TR MIMO,and the computational complexity was reduced.To construct a rotation transformation matrix,the noise subspace matrix was divided into two sub-matrices along its row direction,and its inverse matrix was obtained.Finally,the rotation transformation of noise subspace matrix was carried out by the inverse matrix,and the lower-dimensional subspace matrix was obtained.According to the orthogonality of rotated sub-noise subspace and the signal subspace,a new spectral function was established to estimate angles.Compared with the conventional MUSIC algorithm,the proposed algorithm can reduce the computational complexity and greatly improve the resolution ratio by decreasing the dimension of noise subspace.
For the problem of huge computations of multiple signal classification(MUSIC)algorithm in the time reversal(TR)MIMO radar,a multi-target direction of arrival(DOA)estimation algorithm based on reduced dimension(RD)and subspace rotation technique(SRT)was proposed.Firstly,the proposed algorithm was applied to reduce the dimension for the echo signal of TR MIMO,and the computational complexity was reduced.To construct a rotation transformation matrix,the noise subspace matrix was divided into two sub-matrices along its row direction,and its inverse matrix was obtained.Finally,the rotation transformation of noise subspace matrix was carried out by the inverse matrix,and the lower-dimensional subspace matrix was obtained.According to the orthogonality of rotated sub-noise subspace and the signal subspace,a new spectral function was established to estimate angles.Compared with the conventional MUSIC algorithm,the proposed algorithm can reduce the computational complexity and greatly improve the resolution ratio by decreasing the dimension of noise subspace.
引文
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[11]LI J,ZHANG X.Closed-form blind 2D-DOD and 2D-DOA estimation for MIMO radar with arbitrary arrays[J].Wireless Personal Communications,2013,69(1):175-186.
[12]张秦,张林让,郑桂妹,等.任意阵列双基地MIMO雷达半实值MUSIC目标DOD和DOA联合估计[J].系统工程与电子技术,2016,38(3):532-538.ZHANG Qin,ZHANG Linrang,ZHENG Guimei,et al.Joint DOD and DOA estimation for bistatic MIMO radar with arbitrary array using semi-real-valued MUSIC[J].Systems Engineering and Electronics,2016,38(3):532-538.(in Chinese)
[13]党晓方,张辉.基于RD-RISR的单基地MIMO雷达DOA估计方法[J].火控雷达技术,2016,45(4):31-37.DANG Xiaofang,ZHANG Hui.RD-RISR based DOA estimation method of monostatic MIMO radar[J].Fire Control Radar Technology,2016,45(4):31-37.(in Chinese)
[14]闫锋刚,齐晓辉,刘帅,等.基于子空间旋转变换的低复杂度波达角估计算法[J].电子与信息学报,2016,38(3):629-634.YAN Fenggang,QI Xiaohui,LIU Shuai,et al.Low-complexity DOA estimation via subspace rotation technique[J].Journal of Electronics and Information Technology,2016,38(3):629-634.(in Chinese)
[15]GOLUB G H.Matrix computations[M].Baltimore,MD:The Johns Hopkins University Press,1996:238-246.
[16]XU G,KAILATH T.Fast subspace decomposition[J].IEEE Transactions on Signal Processing,1999,42(3):539-551.
[17]ZHANG Xiaofei,XU Lingyun,XU Dazhuan.Direction of departure(DOD)and direction of arrival(DOA)estimation in MIMO radar with reduced-dimension MUSIC[J].IEEE Commun Letters,2010,14(12):1161-1163.
[2]胡仁荣,童宁宁,何兴宇,等.基于模式耦合稀疏贝叶斯的MIMO雷达成像[J].空军工程大学学报,2018,19(4):51-56.HU Renrong,TONG Ningning,HE Xingyu,et al.MIMO radar imaging based on pattern-coupled sparse Bayesian learning[J].Journal of Air Force Engineering University,2018,19(4):51-56.(in Chinese)
[3]蒋艳英,欧阳缮,晋良念,等.时间反转在UWB-MIMO雷达中的应用[J].桂林电子科技大学学报,2013,33(3):173-176.JIANG Yanying,OU Yangshan,JIN Liangnian,et al.Time reversal detection in UWB MIMO radar[J].Journal of Guilin University of Electronic Technology,2013,33(3):173-176.(in Chinese)
[4]MOHAMMAD H,SAJJADIEH S,ASIF A.Compressive sensing time reversal MIMO radar:joint direction and doppler frequency estimation[J].IEEE Signal Processing Letters,2015,22(9):1283-1287.
[5]吴索路,欧阳缮,张海如.基于时间反转的探地雷达多目标成像算法研究[J].微波学报,2015,31(5):51-54.WU Suolu,OU Yangshan,ZHANG Hairu.Multi-target imaging algorithm based on time reversal for ground penetrating radar data[J].Journal of Microwaves,2015,31(5):51-54.(in Chinese)
[6]连振,白渭雄,付孝龙,等.SSC移频算法的改进型间歇采样转发干扰[J].空军工程大学学报,2018,19(1):60-64.LIAN Zhen,BAI Weixiong,FU Xiaolong,et al.Improved interrupted-sampling repeater jamming based on spectrum spread and compression algorithm[J].Journal of Air Force Engineering University,2018,19(1):60-64.(in Chinese)
[7]JIN Y,MOURA J,O’DONOUGHUE N.Time reversal adaptive waveform in MIMO radar[C]//Proceedings of 2010International Conference on Electromagnetics in Advanced Applications.Sydney:IEEE,2010:741-744.
[8]FOROOZAN F,ASIF A,JIN Y,et al.Direction finding algorithms for time reversal MIMO radars[C]//Proceedings of IEEE Statistical Signal Processing Workshop.Nice:IEEE,2011:433-436.
[9]FOROOZAN F,ASIF A.Time reversal MIMO radars for estimation of velocity and direction[C]//Proceedings of IEEE Statistical Signal Processing Workshop.Annarbor:IEEE,2012:860-863.
[10]FOROOZAN F,ASIF A,JIN Y.Cramér-rao bounds for time reversal MIMO radars with multipath[J].IEEE Trans Aerospace and Electronic System,2016,52(1):137-154.
[11]LI J,ZHANG X.Closed-form blind 2D-DOD and 2D-DOA estimation for MIMO radar with arbitrary arrays[J].Wireless Personal Communications,2013,69(1):175-186.
[12]张秦,张林让,郑桂妹,等.任意阵列双基地MIMO雷达半实值MUSIC目标DOD和DOA联合估计[J].系统工程与电子技术,2016,38(3):532-538.ZHANG Qin,ZHANG Linrang,ZHENG Guimei,et al.Joint DOD and DOA estimation for bistatic MIMO radar with arbitrary array using semi-real-valued MUSIC[J].Systems Engineering and Electronics,2016,38(3):532-538.(in Chinese)
[13]党晓方,张辉.基于RD-RISR的单基地MIMO雷达DOA估计方法[J].火控雷达技术,2016,45(4):31-37.DANG Xiaofang,ZHANG Hui.RD-RISR based DOA estimation method of monostatic MIMO radar[J].Fire Control Radar Technology,2016,45(4):31-37.(in Chinese)
[14]闫锋刚,齐晓辉,刘帅,等.基于子空间旋转变换的低复杂度波达角估计算法[J].电子与信息学报,2016,38(3):629-634.YAN Fenggang,QI Xiaohui,LIU Shuai,et al.Low-complexity DOA estimation via subspace rotation technique[J].Journal of Electronics and Information Technology,2016,38(3):629-634.(in Chinese)
[15]GOLUB G H.Matrix computations[M].Baltimore,MD:The Johns Hopkins University Press,1996:238-246.
[16]XU G,KAILATH T.Fast subspace decomposition[J].IEEE Transactions on Signal Processing,1999,42(3):539-551.
[17]ZHANG Xiaofei,XU Lingyun,XU Dazhuan.Direction of departure(DOD)and direction of arrival(DOA)estimation in MIMO radar with reduced-dimension MUSIC[J].IEEE Commun Letters,2010,14(12):1161-1163.