An (M, N)-coprime array comprises two well-organized subarrays: an M-element and an N-element. This sparse array configuration is capable of resolving a number of remote sources up to O(MN) solely with the use of an M + N - 1 sensors, which allows the identification of more targets with fewer transceivers while maintaining high resolution. In this way, the coprime array theory can significantly help to simplify the configuration of traditional transceiver systems. However, to date, the coprime array approaches reported in the literature rely strongly on far-field approximation, which is associated with significant error when dealing with the problem of short-range radar detection because the probed objects are nearby the sensors. To solve this problem, we extend the theory of the standard coprime array to short-range detection, whereby the probed object is located NOT far away from the sensors (either the transmitter or receiver). We demonstrate that the (M, N)-coprime array configuration can retrieve the object spectrum over [-2τk0, 2τk0] with a resolution of 4τk0/MN, where k0 denotes the free space wavenumber and τ is a scenario-dependent factor. As a consequence, the (M, N)-coprime array allows for the resolution of O(MN) objects nearby sensors, with a spatial resolution of λ/4τ. We also examined the performance of the coprime array with respect to the through-wall-imaging problem. Finally, we verified the usefulness of the coprime array for short-range radar detection with a selected number of numerical experiments.
The National Natural Science Foundation of China (61471006).
通讯作者:
Li Lianlin lianlin.li@pku.edu.cn
E-mail: lianlin.li@pku.edu.cn
作者简介: Wang Longgang was born in 1988. He received his B.Eng degree in communication engineering from the Tianjin University. He is currently working toward the Ph.D. degree in Peking University. His research interest is highresolution microwave imaging methods. E-mail: longgang.wang@pku.edu.cn;Li Lianlin was born in 1980. He received his Ph.D. degree from the Institute of Electronics, Chinese Academy of Sciences in 2006. He is currently a hundred talented program professor with Peking University. His research interests are super-resolution imaging, microwave imaging, sparse signal processing, and ultrawideband radar systems.
引用本文:
王龙刚, 李廉林. 基于互质阵列雷达技术的近距离目标探测方法(英文)[J]. 雷达学报, 2016, 5(3): 244-253.
Wang Longgang, Li Lianlin. Short-range Radar Detection with (M, N)-Coprime Array Configurations(in English). JOURNAL OF RADARS, 2016, 5(3): 244-253.
Vaidyanathan P P and Pal P. Sparse sensing with co-prime samples and arrays[J]. IEEE Transactions on Signal Processing, 2011, 59(2): 573-586.
[2]
Vaidyanathan P P and Pal P. Theory of sparse coprime sensing in multiple dimensions[J]. IEEE Transactions on Signal Processing, 2011, 59(8): 3592-3608.
[3]
Qin S, Zhang Y D, and Amin M G. Generalized coprime array configurations for direction-of-arrival estimation[J]. IEEE Transactions on Signal Processing, 2015, 63(6): 1377-1390.
[4]
Tan Z, Eldar Y C, and Nehorai A. Direction of arrival estimation using co-prime arrays: a super resolution viewpoint[J]. IEEE Transactions on Signal Processing, 2014, 62(21): 5565-5576.
[5]
Tan Z and Nehorai A. Sparse direction of arrival estimation using co-prime arrays with off-grid targets[J]. IEEE Signal Processing Letters, 2014, 21(1): 26-29.
[6]
Wang L and Li L. Through-the-wall target localization and tracking using co-prime array[C]. The 5th Asia-Pacific Conference on Synthetic Aperture Radar, Singapore, 2015.
[7]
Chew W C. Waves and Fields in Inhomogeneous Media[M]. Wiley-IEEE Press, 1995: 20-23.
[8]
Li L, Zhang W, and Li F. A novel autofocusing approach for real-time through-wall imaging under unknown wall characteristics[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(1): 423-431.
2016, Vol. 5 
