The authors present a non-traditional, parametric method for velocity, angle, and range estimation in a frequency diverse array radar. Unlike the traditional beamforming techniques, the proposed scheme transmits an omni-directional sinusoid regardless of the target locations. They propose a simple sampling strategy, which eliminates the need for employing a bank of bandpass filters at the receiver. Under the proposed sampling scheme the received data follows a convenient low rank model. They exploit this model to design a fast and accurate parametric estimation algorithm. Their velocity and range estimation steps employ known spectral analysis techniques. For angle estimation, they propose a new grid-less sparse recovery algorithm. The resulting methods are applicable to any arbitrary array geometry. Furthermore, they propose an efficient method to mitigate jamming. They also provide necessary guidelines to avoid ambiguity and achieve the desired resolution performance. The Cramér-Rao lower bound for the estimation problem is derived. The utility of the proposed method is demonstrated via numerical simulation results.

中文翻译：

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频率分集阵列中的参数定位

作者提出了一种非传统的参数化方法，用于频率可变阵列雷达中的速度，角度和距离估计。与传统的波束成形技术不同，所提出的方案无论目标位置在哪里，都可以发送全方位正弦波。他们提出了一种简单的采样策略，从而消除了在接收机处使用一组带通滤波器的需求。在建议的采样方案下，接收到的数据遵循便利的低秩模型。他们利用该模型来设计一种快速，准确的参数估计算法。他们的速度和范围估计步骤采用已知的频谱分析技术。对于角度估计，他们提出了一种新的无网格稀疏恢复算法。所得方法适用于任何任意数组几何。此外，他们提出了一种有效的方法来减轻干扰。它们还提供了必要的指南，以避免歧义并实现所需的分辨率性能。得出估计问题的Cramér-Rao下界。通过数值仿真结果证明了该方法的实用性。