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GNSS/IMU/DVL 集成在真实海况干扰下的性能特征分析。

Performance Characterization of GNSS/IMU/DVL Integration under Real Maritime Jamming Conditions.

机构信息

German Aerospace Center (DLR), Institute of Communications and Navigation, Neustrelitz 17235, Germany.

BASELABS GmbH, Chemnitz 09126, Germany.

出版信息

Sensors (Basel). 2018 Sep 5;18(9):2954. doi: 10.3390/s18092954.

DOI:10.3390/s18092954
PMID:30189646
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6164504/
Abstract

Currently Global Navigation Satellite Systems (GNSSs) are the primary source for the determination of absolute position, navigation, and time (PNT) for merchant vessel navigation. Nevertheless, the performance of GNSSs can strongly degrade due to space weather events, jamming, and spoofing. Especially the increasing availability and adoption of low cost jammers lead to the question of how a continuous provision of PNT data can be realized in the vicinity of these devices. In general, three possible solutions for that challenge can be seen: (i) a jamming-resistant GNSS receiver; (ii) the usage of a terrestrial backup system; or (iii) the integration of GNSS with other onboard navigation sensors such as a speed log, a gyrocompass, and inertial sensors (inertial measurement unit-IMU). The present paper focuses on the third option by augmenting a classical IMU/GNSS sensor fusion scheme with a Doppler velocity log. Although the benefits of integrated IMU/GNSS navigation system have been already demonstrated for marine applications, a performance evaluation of such a multi-sensor system under real jamming conditions on a vessel seems to be still missing. The paper evaluates both loosely and tightly coupled fusion strategies implemented using an unscented Kalman filter (UKF). The performance of the proposed scheme is evaluated using the civilian maritime jamming testbed in the Baltic Sea.

摘要

目前,全球导航卫星系统(GNSS)是商船导航确定绝对位置、导航和时间(PNT)的主要来源。然而,由于空间天气事件、干扰和欺骗,GNSS 的性能会严重下降。特别是低成本干扰器的可用性和采用不断增加,导致了如何在这些设备附近实现 PNT 数据的连续提供的问题。一般来说,对于这一挑战有三种可能的解决方案:(i)抗干扰 GNSS 接收器;(ii)使用地面备份系统;或(iii)将 GNSS 与其他 onboard 导航传感器(如速度计、陀螺罗盘和惯性传感器(惯性测量单元-IMU))集成。本文通过在经典的 IMU/GNSS 传感器融合方案中增加多普勒速度计来关注第三种选择。尽管已经证明了集成的 IMU/GNSS 导航系统在海洋应用中的优势,但在船舶上的真实干扰条件下对这种多传感器系统的性能评估似乎仍然缺失。本文使用无迹卡尔曼滤波器(UKF)评估了松散和紧密耦合融合策略的实现。该方案的性能是使用波罗的海民用海事干扰测试台进行评估的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/d439dac6b059/sensors-18-02954-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/d439dac6b059/sensors-18-02954-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/99f4b0e5df42/sensors-18-02954-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/d7435724f68d/sensors-18-02954-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/6d8fbfe9603a/sensors-18-02954-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/726e777c6978/sensors-18-02954-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/2a311c67747f/sensors-18-02954-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/d5f11482832a/sensors-18-02954-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/8b260a639238/sensors-18-02954-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/464df7e70848/sensors-18-02954-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/c49e51cb9f65/sensors-18-02954-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/310a43170ab3/sensors-18-02954-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/419933f04ddb/sensors-18-02954-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c55c/6164504/d439dac6b059/sensors-18-02954-g012.jpg

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