一种用于单基地FDA-MIMO雷达的新型单一ESPRIT算法。
A Novel Unitary ESPRIT Algorithm for Monostatic FDA-MIMO Radar.
作者信息
Liu Feilong, Wang Xianpeng, Huang Mengxing, Wan Liangtian, Wang Huafei, Zhang Bin
机构信息
State Key Laboratory of Marine Resource Utilization in South China Sea and School of Information and Communication Engineering, Hainan University, Haikou 570228, China.
Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, Dalian 116620, China.
出版信息
Sensors (Basel). 2020 Feb 4;20(3):827. doi: 10.3390/s20030827.
A novel unitary estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm, for the joint direction of arrival (DOA) and range estimation in a monostatic multiple-input multiple-output (MIMO) radar with a frequency diverse array (FDA), is proposed. Firstly, by utilizing the property of Centro-Hermitian of the received data, the extended real-valued data is constructed to improve estimation accuracy and reduce computational complexity via unitary transformation. Then, to avoid the coupling between the angle and range in the transmitting array steering vector, the DOA is estimated by using the rotation invariance of the receiving subarrays. Thereafter, an automatic pairing method is applied to estimate the range of the target. Since phase ambiguity is caused by the phase periodicity of the transmitting array steering vector, a removal method of phase ambiguity is proposed. Finally, the expression of Cramér-Rao Bound (CRB) is derived and the computational complexity of the proposed algorithm is compared with the ESPRIT algorithm. The effectiveness of the proposed algorithm is verified by simulation results.
提出了一种新颖的通过旋转不变技术估计信号参数（ESPRIT）算法，用于具有频率分集阵列（FDA）的单基地多输入多输出（MIMO）雷达中的联合到达方向（DOA）和距离估计。首先，利用接收数据的中心厄米特性，通过酉变换构造扩展实值数据，以提高估计精度并降低计算复杂度。然后，为避免发射阵列导向矢量中角度和距离之间的耦合，利用接收子阵列的旋转不变性估计DOA。此后，应用一种自动配对方法估计目标的距离。由于发射阵列导向矢量的相位周期性会引起相位模糊，提出了一种相位模糊消除方法。最后，推导了克拉美罗界（CRB）的表达式，并将所提算法的计算复杂度与ESPRIT算法进行了比较。仿真结果验证了所提算法的有效性。
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