水下小尺寸基阵的空域窄波束形成技术

Narrow Spatial Beamforming Method for Underwater Small Dimensional Arrays

在水下小尺寸无人平台的主动声呐目标探测中,无人平台体积限制了传感器阵列的物理孔径,影响接收波束的空域分辨能力。针对混响背景下小尺寸阵列波束分辨力差,抗干扰性不强的问题,提出一种水下小尺寸基阵的空域窄波束形成技术。上述算法根据已知传感器阵元的接收数据,采用卡尔曼滤波算法估计虚拟阵元数据,抑制预测信号的系统状态参数干扰,减小预测值的偏差,使阵列基阵孔径在虚拟的意义上得到扩展,实现阵的高指向性窄波束接收,提高对目标的分辨力。数据仿真结果表明,与传统线性预测(Linear Prediction, LP)方法相比,卡尔曼滤波算法能够减小波束形成主瓣宽度,有效地提高基阵的角度分辨力和抗干扰性能。

In the active sonar target detection of underwater small-sized unmanned platform, the volume of unmanned platform limits the physical aperture of the sensor array and affects the spatial resolution of the receiving beam. Aiming at the problems of poor resolving ability and low anti-interference performance of small-sized array beams in the reverberation background, this paper proposes a narrow beamforming technique for small underwater array. The algorithm uses the Kalman filter algorithm to estimate the virtual array data according to the received data of the known sensor array, suppresses the system state parameter interference of the predicted signal, reduces the deviation of the predicted value, makes the array aperture in the virtual sense, expand to achieve high directional narrow beam reception and improves the resolution of the target. The simulation results show that compared with the traditional Linear Prediction(LP) method, the Kalman filter algorithm can reduce the main beam width of beamforming, and effectively improve the lobe resolution and anti-interference performance of the array.