基于时域波束信号高阶谱的目标检测技术

Object detection technology based on high-order spectrum of time domain beamforming signal

为解决常规时域波束形成技术抗噪声能力弱、对弱目标检测能力差的问题,利用高斯噪声的高阶累积量(三阶及三阶以上)为零、非高斯信号的高阶累积量不为零这一性质,对常规时域波束形成后输出的波束信号进行后置处理。首先,对常规时域波束形成后输出的各预成波束信号,分别求其四阶累积量切片谱值;然后,再对各四阶累积量切片谱值分别进行能量累加,得到空间谱图;最后,通过对空间谱在时间上的累积,得到方位历程图。用仿真和海试数据对算法进行了验证:在低信噪比情况下,常规算法不能有效检测到弱目标时,经后置处理后可以有效检测到弱目标。结果表明,与常规时域波束形成算法相比,波束形成后再进行切片谱后置处理的算法增强了对噪声的抑制能力,提高了对弱目标的检测能力。

In order to solve the problem of low noise suppress ability and poor detection ability of the conventional beam-forming(CBF) technology in weak target detection, the theory that the high-order cumulants of Gauss noise(three order and three order above) is zero and the non-Gauss signal is not zero, is used to process the beamforming signals after the CBF has been done. First, the fourth-order cumulant slice spectrum values of the time domain beamforming signals are calculated, and their square sum(i.e. energy superposition) is taken to obtain the spatial spectrum. Then, by accumulating the spatial spectrum in time, the azimuth time record is obtained. In this paper, both simulation data and actual data are used to verify the validity of the algorithm. It is found that the conventional algorithm cannot detecet the weak target effectively when the SNR decreases to a certain value, but the post processing algorithm can. The results show that the post processing algorithm after beamforming improves the ability of detecting weak targets and suppressing background noise.