基于卷积波束空间传播算子的FDA-MIMO雷达角度、距离估计算法

Angle Range Estimation Algorithm for FDA-MIMO Radar Based on Convolutional Beamspace Propagator Method

针对FDA-MIMO雷达接收数据维数高和工程实现复杂的问题,提出一种FDA-MIMO雷达卷积波束空间目标角度、距离估计算法。首先基于发射波形间的正交性,将对应各发射波形的回波信号通过一组满足奈奎斯特性质的滤波器组,然后对各滤波器的稳态卷积输出进行抽取处理以降低数据维数;对抽取数据应用传播算子法,再基于卷积滤波器的通带特性和FDA阵列角度、距离间的耦合关系,实现目标角度和距离参数的无模糊估计。仿真实验验证了该参数估计算法的有效性。

Addressing the issues of high dimensional received data and complex engineering implementation for FDA-MIMO(Frequency Diverse Array-Multiple Input Multiple Output)radar,this paper proposes an algorithm to estimate angle and range of target in the convolutional beamspace.Firstly,based on the orthogonality between the transmitted waveforms,the echo signal corresponding to each transmitted waveform is passed through a set of filters that satisfy the Nyquist property.Secondly,the output data of the convolutional steady state of each filter is decimated to reduce the data dimensionality.Then,an angle and range estimation algorithm using propagator method is developed.The unambiguous angle and range estimates are obtained based on the passband characteristics of the convolutional filters and the coupling relationship between the angle and range of FDA.Finally,numerical simulations are conducted to validate the effectiveness of the proposed convolutional beamspace algorithm.