非圆实信号MIMO雷达中基于实值ESPRIT的角度估计
收稿日期: 2012-10-30
修回日期: 2013-05-12
网络出版日期: 2013-05-23
基金资助
国家自然科学基金(61071163,61071164,61271327);江苏高校优势学科建设工程资助项目
Angle Estimation in MIMO Radar with Non-circular Signals Based on Real-valued ESPRIT
Received date: 2012-10-30
Revised date: 2013-05-12
Online published: 2013-05-23
Supported by
National Natural Science Foundation of China (61071163, 61071164, 61271327);A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions
研究单基地多输入多输出(MIMO)雷达中的波达角(DOA)估计问题,提出了一种基于非圆(NC)实信号的实值旋转不变性信号参数估计(ESPRIT)算法。首先对接收信号进行降维变换,降低运算复杂度;之后根据非圆实信号特性构造中心Hermitian对称矩阵,通过酉(Unitary)变换将复数运算转为实数,进一步降低复杂度;最后根据ESPRIT得到角度估计。该算法无需谱峰搜索,运算复杂度较NC ESPRIT和Unitary ESPRIT大大降低,且该算法的角度估计性能优于后两种算法。论文分析了所提算法的复杂度,并推导了克拉美-罗界(CRB)。仿真结果验证了该算法的有效性。
胡彤 , 张弓 , 李建峰 , 张小飞 , 贲德 . 非圆实信号MIMO雷达中基于实值ESPRIT的角度估计[J]. 航空学报, 2013 , 34(8) : 1953 -1959 . DOI: 10.7527/S1000-6893.2013.0258
In this paper, the direction of arrival (DOA) estimation in a monostatic multiple-input multiple-output (MIMO) radar is studied, and a real-valued estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm for the estimation based on non-circular (NC) signals is proposed. Through a reduced-dimensional transformation, the received data is transformed to be low-dimensional, which lead to lower complexity. Thereafter, a center-Hermitian matrix is constructed based on the characteristics of the NC real-valued signals. Then a unitary matrix is used to transform the complex computations into real-valued ones, thus further reducing the complexity. Finally, ESPRIT is employed to estimate the angles. The proposed algorithm requires no peak searching, and has lower complexity but better angle estimation performance than the NC ESPRIT and Unitary ESPRIT. The complexity of the algorithm is analyzed, and the Cramer-Rao bound (CRB) for the angle estimation in MIMO radar is derived. In the simulation, these algorithms are compared, which verifies the effectiveness of our algorithm.
[1] Fishler E, Haimovich A, Blum R S, et al. MIMO radar: an idea whose time has come. Proceedings of IEEE Radar Conference, 2004: 71-78.
[2] Li J, Stoica P. MIMO radar—diversity means superiority. Proceedings of 14th Adaptive Sensor Array Processing Workshop (ASAP '06), 2006: 1-6.
[3] Li X R, Zhang Z, Mao W X, et al. A study of frequency diversity MIMO radar beamforming. IEEE 10th International Conference (ICSP2010), 2010: 352-356.
[4] Sharma R. Analysis of MIMO radar ambiguity functions and implications on clear region. IEEE Radar Conference, 2010: 544-548.
[5] Li J, Liao G, Griffiths H. Bistatic MIMO radar space-time adaptive processing. IEEE International Radar Conference, 2011: 498-502.
[6] Wu X H, Kishk A A, Glisson A W. MIMO-OFDM radar for direction estimation. IET Radar, Sonar & Navigation, 2010, 4(1): 28-36.
[7] Li J, Stoica P, Xu L, et al. On parameter identifiability of MIMO radar. IEEE Signal Processing Letters, 2007, 14(12): 968-971.
[8] Li J, Liao G, Ma K, et al. Waveform decorrelation for multitarget localization in bistatic MIMO radar systems. IEEE International Radar Conference, 2010: 21-24.
[9] Chen J L, Gu H, Su W M. Angle estimation using ESPRIT without pairing in MIMO radar. Electronic Letters, 2008, 44(24): 1422-1423.
[10] Zheng G, Chen B, Yang M. Unitary ESPRIT algorithm for bistatic MIMO radar. Electronic Letters, 2012, 48(3): 179-181.
[11] Yan H, Li J, Liao G. Multitarget identification and localization using bistatic MIMO radar systems. EURASIP Journal on Advances in Signal Processing, 2008: 1-8.
[12] Gao X, Zhang X, Feng G, et al. On the MUSIC-derived approaches of angle estimation for bistatic MIMO radar. Proceedings of International Conference on Wireless Networks and Information Systems, 2009: 343-346.
[13] Zhang X, Xu L, Xu L, et al. Direction of departure (DOD) and direction of arrival (DOA) estimation in MIMO radar with reduced-dimension MUSIC. IEEE Communications Letters, 14(12): 1161-1163.
[14] Zhang X, Xu Z, Xu L, et al. Trilinear decomposition-based transmit angle and receive angle estimation for multiple-input multiple-output radar. IET Radar, Sonar & Navigation, 2011, 5(6): 626-631.
[15] Nion D, Sidiropoulos N D. Adaptive algorithms to track the PARAFAC decomposition of a third-order tensor. IEEE Transactions on Signal Processing, 2009, 57(6): 2299-2310.
[16] Tayem N, Kwon H M. Conjugate ESPRIT(C-SPRIT). IEEE Transactions on Antennas Propagation, 2004, 52(10): 2618-2624.
[17] Charge P, Wang Y, Saillard J. A non-circular sources direction finding method using polynomial rooting. Signal Processing, 2001, 81(8): 1765-1770.
[18] Yang M L, Chen B X, Yang X Y. Conjugate ESPRIT algorithm for bistatic MIMO radar. Electronic Letters, 2010, 46(25): 2409-2411.
[19] Liu X, Sidiropoulos N D. Cramer-Rao lower bounds for low-rank decomposition of multidimensional arrays. IEEE Transactions on Signal Processing, 2001, 49(9):2074-2086.
[20] Stoica P, Nehorai A. Performance study of conditional and unconditional direction-of-arrival estimation. IEEE Transactions on Signal Processing, 1990, 38(10): 1783-1795.
/
〈 | 〉 |