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Cooperative Localization of an Acoustic Source using Towed Hydrophone Arrays

机译:使用牵引式水听器阵列的声学来源的协同定位

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We describe field experiments in which a team of autonomous underwater vehicles cooperatively localize an acoustic source. The team implements a data fusion algorithm to enhance the localization performance of each individual vehicle and implements a decentralized motion control algorithm so that each vehicle maneuvers to minimize the joint localization error of the acoustic source. Each autonomous underwater vehicle is equipped with a custom-designed towed hydrophone array that measures the bearing angle between the array and the acoustic source. The noise statistics of the hydrophone arrays are state-dependent, and a generalized Kalman filter that accounts for the state-dependant measurement noise is utilized for localization.
机译:我们描述了现场实验,其中一支自动水下车辆团队协同定位声学来源。该团队实现数据融合算法,以增强每个车辆的定位性能,并实现分散的运动控制算法,使得每个车辆操纵以最小化声学源的接合定位误差。每个自主水下车辆都配备了定制设计的牵引式室阵,可测量阵列和声学源之间的轴承角度。水听器阵列的噪声统计是具有国家依赖的,并且用于占据状态相关测量噪声的通用卡尔曼滤波器用于本地化。

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