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Tightly Coupled INS/GNSS Navigation Filter for the Automation of a River Ferry ?

机译：用于河流渡轮自动化的紧密耦合INS / GNSS导航滤波器 ？

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The automation of ships offers great potential in terms of safety and efficiency. A river ferry is automated for this reason in the research project AKOON. The performance of the ferry’s guidance, navigation and control (GNC) system highly depends on state estimates which act as a feedback signal and close the control loop. To estimate the ferry’s state in an accurate, precise and robust fashion, sophisticated navigation techniques are required. Therefore, this paper addresses the state estimation of the river ferry by providing a new navigation filter concept. The filter fuses quantities of an inertial measurement unit (IMU) and pseudo- and deltaranges of a dual antenna GNSS receiver. The estimation of heading of the ferry with slow dynamics poses a challenge due to bad observability. The filter is extended by a new correction step which integrates the heading estimates of a GNSS compass in a loosely-coupled manner to overcome this problem. The filter is implemented as unscented Kalman filter (UKF). For automatized operation, the UKF must achieve a maximum horizontal position accuracy of 1 m and a maximum heading accuracy of 1 deg in the river crossing and approach phase. Hence, the concept is evaluated with measurement data from real world tests with the river ferry during daily operation. Furthermore, the experimental setup is discussed in detail. During multiple river crossings, a maximum 2D position error of 52 cm and a maximum heading error of less than 1 deg are achieved.
机译：船舶的自动化在安全性和效率方面具有很大的潜力。河流渡轮在研究项目Akoon的原因是自动化的。 Ferry的指导，导航和控制（GNC）系统的性能高度取决于状态估计，作为反馈信号并关闭控制回路。为了以准确，准确和强大的方式估计渡轮的状态，需要复杂的导航技术。因此，本文通过提供新的导航滤波器概念来解决河流渡轮的状态估计。惯性测量单元（IMU）和双天线GNSS接收器的零件和Deltaranges的滤波器熔断量。由于可观察性差，具有缓慢动力学的渡轮标题的估计构成了挑战。通过新的校正步骤延伸过滤器，该校正步骤将GNSS罗盘的标题估计以松散耦合的方式集成，以克服该问题。过滤器实现为Unscented Kalman滤波器（UKF）。对于自动化操作，UKF必须在河流交叉和接近阶段获得1米的最大水平位置精度，最大的标题精度为1°。因此，在日常操作期间，通过与河流渡轮的真实世界测试的测量数据评估该概念。此外，详细讨论了实验装置。在多河流交叉期间，实现了52厘米的最大2D位置误差和小于1°的最大标题误差。

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