基于频控阵MIMO雷达的低复杂度稳健波束形成算法

频控阵(frequency diverse array, FDA)多输入多输出(multiple input multiple output, MIMO)雷达基于发射端调制而具备的距离维自由度为主瓣干扰提供了抑制方案。结合自适应波束形成算法, 频控阵MIMO雷达能有效抑制主瓣范围内欺骗干扰信号, 但存在的信号环境复杂、导向矢量失配、采样快拍不足等问题将使算法性能恶化。针对该问题，提出了一种基于频控阵的低复杂度的稳健自适应波束形成算法。仿真实验表明, 相比于其他自适应波束形成算法, 所提算法在低信噪比(signal to noise ratio, SNR)低采样快拍且存在导向矢量失配等非理想条件下形成的波束稳健性更强、计算复杂度更低, 有效实现了对目标的指示和对干扰的抑制, 克服了其他算法在非理想条件下性能恶化的问题。

Low-complexity and robust beamforming algorithm based on frequency diverse array MIMO radar

Frequency diverse array (FDA) multiple input multiple output (MIMO) radar provides a suppression scheme for mainlobe interference based on the range-dimensional freedom from the transmitter modulation. Combined with the adaptive beamforming algorithm, FDA-MIMO radar can effectively suppress deceptive interference signals within the mainlobe. However, the existing problems such as complex signal environment, steering vector mismatch and insufficient sampling snapshots will deteriorate the performance of the algorithm. To solve the problem, this paper proposes a low-complexity robust adaptive beamforming (RAB) algorithm based on FDA. Simulation experiments show that the proposed algorithm has stronger robustness and lower computational complexity under non-ideal conditions such as low signal-to-noise ratio, low-sampling snapshot and 5-degree steering vector mismatch. Meanwhile, the proposed algorithm effectively achieves the indication of the target and the suppression of interference, and overcomes the performance degradation of other algorithms under non-ideal conditions.