Greening Michael V, Perkins Jane E
Defence Science and Technology Organisation, Edinburgh Site, MOD Building 79, P.O. Box 1500, Edinburgh, S.A., 5111, Australia.
J Acoust Soc Am. 2002 Dec;112(6):2872-81. doi: 10.1121/1.1514931.
Adaptive beamformers automatically adjust to the input data on the sensors in an attempt to maximize the bearing resolution of a signal and minimize the effects of noise or interfering signals. To the author's knowledge, all adaptive beamformers currently available in the literature assume that the sensors are stationary over the time required to collect the data. This assumption is invalid on arrays of sensors mounted on nonstationary platforms, and results in poor beamforming performance. In this paper we present an adaptive beamformer that has been designed to operate on nonstationary arrays. The beamformer directly incorporates any changes in array shape or heading that may occur during the time required to collect the data. The output of the adaptive beamformer is shown for both synthetic data and for real data collected on a towed array. Results show that signal detection, bearing accuracy, bearing resolution, and interference suppression all increase when the array shape and track are incorporated into the beamformer if the sensor platform is not stationary.
自适应波束形成器会自动根据传感器上的输入数据进行调整,以尽量提高信号的方位分辨率,并将噪声或干扰信号的影响降至最低。据作者所知,目前文献中所有可用的自适应波束形成器都假定传感器在收集数据所需的时间内是静止的。对于安装在非静止平台上的传感器阵列,这一假设是无效的,会导致波束形成性能不佳。在本文中,我们提出了一种设计用于在非静止阵列上运行的自适应波束形成器。该波束形成器直接纳入了在收集数据所需时间内可能发生的阵列形状或航向的任何变化。给出了自适应波束形成器对合成数据以及在拖曳阵列上收集的真实数据的输出结果。结果表明,如果传感器平台不是静止的,将阵列形状和轨迹纳入波束形成器时,信号检测、方位精度、方位分辨率和干扰抑制都会提高。