基于互质阵列雷达技术的近距离目标探测方法（英文）

Short-range Radar Detection with(M,N)-Coprime Array Configurations

一组(M,N)互质阵列由两组结构化排列的子阵列构成:一组包括M个天线单元,另一组包括N个天线单元。互质阵列稀疏天线仅需要M+N–1个收发天线单元就可实现对O(MN)个远距离目标的识别。在相同分辨条件下,互质阵列雷达技术可利用更少的收发单元来识别更多的雷达目标。因此互质阵列雷达技术能够极大地降低传统雷达收发系统的复杂度。但是,现有文献中所讨论的互质阵列雷达技术均基于远场近似假设,当探测近距离目标时,会由于目标邻近天线单元而产生严重的探测误差。为了解决上述问题,该文将标准的互质阵列雷达技术的适用范围扩展到用于解决近距离目标探测。该文论证了(M,N)互质阵列雷达技术能够以4tk0/MN空域分辨率恢复[–2tk0,2tk0]空域范围内的目标信息,其中k0表示自由空间波数,t是场景因子。由此可见(M,N)互质阵列能够以l/4t的方位向分辨率获得O(MN)个近距离目标方位向位置信息。该文进一步论证了互质阵列雷达技术在穿墙成像中的适用性。最后,该文提供了一组数值仿真实验结果,验证了互质阵列雷达技术对于近距离目标探测的有效性。

An （M,N）-coprime array comprises two well-organized subarrays： anM-element and anN-element. This sparse array configuration is capable of resolving a number of remote sources up toO（MN） solely with the use of anM ＋N – 1 sensors, which allows the identification of more targets with fewer transceivers while main-taining high resolution. In this way, the coprime array theory can significantly help to simplify the configura-tion of traditional transceiver systems. However, to date, the coprime array approaches reported in the literat-ure 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 prob-lem, 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 [–2tk0, 2tk0] with a resolution of 4tk0/MN, wherek0 denotes the free space wavenumber andt is a scenario-dependent factor. As a consequence, the （M, N）-coprime array allows for the resolution ofO（MN） objects nearby sensors, with a spatial resolution ofl/4t. We also examined the performance of the coprime array with respect to the through-wall-imaging problem. Fi-nally, we verified the usefulness of the coprime array for short-range radar detection with a selected number of numerical experiments.