The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-...The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-MUSIC) algorithm is proposed.Conventional MUSIC algorithm for joint DOA and Doppler frequency estimation requires a large computational cost due to the two dimensional (2D) spectral peak searching.Aiming at this shortcoming,the proposed CE-MUSIC algorithm firstly uses a reduced-dimension transformation to reduce the subspace dimension and then obtains the estimates of DOA and Doppler frequency with only one-dimensional (1D) search.The proposed CE-MUSIC algorithm has much lower computational complexity and very close estimation performance when compared to conventional 2D-MUSIC algorithm.Furthermore,it outperforms estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm.Meanwhile,the mean squared error (MSE) and Cramer-Rao bound (CRB) of joint DOA and Doppler frequency estimation are derived.Detailed simulation results illustrate the validity and improvement of the proposed algorithm.展开更多
该文通过空域匹配滤波器,将阵元空间中的均匀圆阵转化为波束空间中的均匀线阵,并将时空匹配滤波器的输出转换到频域,利用 DOA Matrix方法解决了非周期扩频系统中均匀圆阵条件下多径信号的角度和时延的联合估计问题及常规空域处理方法中...该文通过空域匹配滤波器,将阵元空间中的均匀圆阵转化为波束空间中的均匀线阵,并将时空匹配滤波器的输出转换到频域,利用 DOA Matrix方法解决了非周期扩频系统中均匀圆阵条件下多径信号的角度和时延的联合估计问题及常规空域处理方法中多径数不能大于阵元数的问题。理论分析和仿真实验结果表明,该方法是一种无偏估计,且其估计精度远远高于滑动相关方法。展开更多
传统算法通常采取舍弃互质阵列的“差联合”阵列形成离散虚拟阵元,只利用其中连续虚拟阵元进行离波方向角(direction of departure,DOD)和波达方向角(direction of arrival,DOA)联合估计,存在自由度提升受限、估计性能不佳等问题。对此...传统算法通常采取舍弃互质阵列的“差联合”阵列形成离散虚拟阵元,只利用其中连续虚拟阵元进行离波方向角(direction of departure,DOD)和波达方向角(direction of arrival,DOA)联合估计,存在自由度提升受限、估计性能不佳等问题。对此,提出基于虚拟阵元内插的互质阵列目标DOD和DOA联合估计算法。首先,将两个互质子阵以零点为中心布列,分别构成双基地多输入多输出(multiple input multiple output,MIMO)雷达的发射阵列和接收阵列,该布阵结构将传统的虚拟阵元由阵列“差联合”结构形式变成“和联合”结构形式,降低了虚拟阵列的冗余度。其次,在形成的虚拟阵元基础上,通过在虚拟阵列孔洞位置内插虚拟阵元使其连续,对于内插的虚拟阵元无实际接收信号问题,基于最小化核范数优化理论,采用协方差矩阵Toeplitz化重建的方式恢复内插虚拟阵元的等价接收信号,利于所有虚拟阵元层面的角度联合估计。最后,针对因角度配对导致的高运算量问题,结合降维多重信号分类(reduced dimension multiple signal classification,RD-MUSIC)算法使角度自动配对,从而减小算法运算复杂度。有效提高了目标分辨力和角度联合估计性能,仿真实验验证了算法的有效性。展开更多
基金supported in part by the Funding for Outstanding Doctoral Dissertation in NUAA (No.BCXJ1503)the Funding of Jiangsu Innovation Program for Graduate Education(No.KYLX15_0281)the Fundamental Research Funds for the Central Universities
文摘The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-MUSIC) algorithm is proposed.Conventional MUSIC algorithm for joint DOA and Doppler frequency estimation requires a large computational cost due to the two dimensional (2D) spectral peak searching.Aiming at this shortcoming,the proposed CE-MUSIC algorithm firstly uses a reduced-dimension transformation to reduce the subspace dimension and then obtains the estimates of DOA and Doppler frequency with only one-dimensional (1D) search.The proposed CE-MUSIC algorithm has much lower computational complexity and very close estimation performance when compared to conventional 2D-MUSIC algorithm.Furthermore,it outperforms estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm.Meanwhile,the mean squared error (MSE) and Cramer-Rao bound (CRB) of joint DOA and Doppler frequency estimation are derived.Detailed simulation results illustrate the validity and improvement of the proposed algorithm.
文摘该文通过空域匹配滤波器,将阵元空间中的均匀圆阵转化为波束空间中的均匀线阵,并将时空匹配滤波器的输出转换到频域,利用 DOA Matrix方法解决了非周期扩频系统中均匀圆阵条件下多径信号的角度和时延的联合估计问题及常规空域处理方法中多径数不能大于阵元数的问题。理论分析和仿真实验结果表明,该方法是一种无偏估计,且其估计精度远远高于滑动相关方法。
文摘传统算法通常采取舍弃互质阵列的“差联合”阵列形成离散虚拟阵元,只利用其中连续虚拟阵元进行离波方向角(direction of departure,DOD)和波达方向角(direction of arrival,DOA)联合估计,存在自由度提升受限、估计性能不佳等问题。对此,提出基于虚拟阵元内插的互质阵列目标DOD和DOA联合估计算法。首先,将两个互质子阵以零点为中心布列,分别构成双基地多输入多输出(multiple input multiple output,MIMO)雷达的发射阵列和接收阵列,该布阵结构将传统的虚拟阵元由阵列“差联合”结构形式变成“和联合”结构形式,降低了虚拟阵列的冗余度。其次,在形成的虚拟阵元基础上,通过在虚拟阵列孔洞位置内插虚拟阵元使其连续,对于内插的虚拟阵元无实际接收信号问题,基于最小化核范数优化理论,采用协方差矩阵Toeplitz化重建的方式恢复内插虚拟阵元的等价接收信号,利于所有虚拟阵元层面的角度联合估计。最后,针对因角度配对导致的高运算量问题,结合降维多重信号分类(reduced dimension multiple signal classification,RD-MUSIC)算法使角度自动配对,从而减小算法运算复杂度。有效提高了目标分辨力和角度联合估计性能,仿真实验验证了算法的有效性。
