低信噪比线性调频信号目标的方位估计

线性调频(LFM)信号目标的方位估计是水声探测研究的重要内容,在进行方位估计时,若存在强干扰信号源与强背景噪声,阵元接收信号的信噪比会显著降低,严重影响LFM信号目标方位估计结果的准确性.针对该问题,提出了一种简明分数阶滤波方法,并将其与常规波束形成方法(CBF)相结合来实现低信噪比条件下LFM信号目标的方位估计.简明分数阶傅里叶变换能在正交角度上将LFM信号的能量聚集在特定频点处并形成明显的能量峰,利用该特性,可对阵列各阵元接收的低信噪比LFM信号在简明分数阶域聚集的能量峰进行最佳滤波,以滤除干扰信息及背景噪声.对滤波输出进行逆简明分数阶傅里叶变换可得到增强信干比和信噪比的阵元域信号,进一步用于目标方位估计,就能获得更加准确的目标方位。数值仿真结果和海试实验数据处理结果验证表明,本文所提出的方法可有效抑制干扰和背景噪声,并对低信噪比LFM信号进行准确、稳健的方位估计。 

Bearing estimation of low SNR linear frequency-modulated signal

The linear frequency-modulated (LFM) signal is a type of pulse compression signal widely used in the active sonar system. The bearing estimation of the LFM signal is important in the field of underwater acoustic signal processing. While there are strong interferences and background noise, the signal to noise ratio (SNR) of LFM signal may be so low that its bearing cannot be estimated correctly. Aiming to solve this problem, the concise fractional Fourier transform (CFRFT) filter is proposed to combine with the conventional beamforming (CBF) in this paper. The CFRFT can gather energy of the LFM signal in certain frequency as a pulse peak in specific angle. Thus, by transforming the signal received by sensors of horizontal array with CFRFT and filtering the pulse peak out of CFRFT spectrum in an extremely narrow bandwidth, the interference and the background noise can be dislodged partly. And then, the new time domain signal can be obtained after transforming the filtered pulse peak with inverse CFRFT. With this method, the SNR of target signal in the new time domain can be improved efficiently; therefore, the bearing estimation result of LFM signal can be more accurate. Numerical simulation and experimental results show that, the proposed method has better performance in eliminating the interference and the background noise mangled with the LFM signal so that the efficient bearing estimation result can be obtained.