Relatively-Integrated Ship Navigation by H¥ Fusion Filters

For the system with unknown statistical property noises, the property that the energies of the system noise and the observation noise are limited is utilized in this paper. On this basis, two novel fusion algorithms are proposed for ship integrated navigation with the relative navigation information, broadcasted by the Automatic Identification Systems (AISs) in the adjacent ships. Firstly, an H∞ fusion filtering algorithm is given to deal with the navigation observation messages, under the centralized fusion framework. The integrated navigation method based on this algorithm cannot deal with the asynchronous navigation messages in real time. Therefore, a sequential H∞ fusion filtering algorithm is also given to sequentially deal with the asynchronous navigation messages, secondly. Finally, a computer simulation is employed to illustrate the validity and feasibility of the sequential method.

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An INS/Geomagnetic Integrated Navigation Algorithm Based on Matching Strategy and Hierarchical Filtering

Electronics ◽

10.3390/electronics8040460 ◽

2019 ◽

Vol 8 (4) ◽

pp. 460

Author(s):

Xiusheng Duan ◽

Jing Xiao ◽

Xiaohui Qi ◽

Yifei Liu

Keyword(s):

Magnetic Measurements ◽

Inertial Navigation ◽

State Equation ◽

Integrated Navigation ◽

Matching Algorithm ◽

Filtering Algorithm ◽

Navigation Algorithm ◽

Physical Experiments ◽

Matching Strategy ◽

Navigation Information

To improve the positioning accuracy of an inertial/geomagnetic integrated navigation algorithm, a combined navigation method based on matching strategy and hierarchical filtering is proposed. First, the PDA-ICCP geomagnetic matching algorithm is improved. On basis of evaluating the distribution of magnetic measurements, a number of controllable magnetic values are regenerated to participate in the geomagnetic matching algorithm (GMA). As a result, accuracy of the matching algorithm is ensured and its efficiency is improved. Secondly, the integrated navigation filter is designed based on the hierarchical filtering strategy, in which the navigation information of the geomagnetic matching module and inertial navigation module are respectively filtered and fused in the main filter. In this way, the shortcoming that GMA is unable to provide continuous and real-time navigation information is overcome. Meanwhile, precision of the inertial/geomagnetic integrated navigation algorithm is improved. Finally, the feasibility and validity of the proposed algorithm are verified by simulation and physical experiments. Compared with the integrated filtering algorithm which directly uses the error equation of inertial navigation system (INS) as the state equation, the proposed hierarchical filtering algorithm can achieve higher positioning precision.

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Research on a Novel Federated Least Square Filter Based on Integrated Navigation

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.229-231.1239 ◽

2012 ◽

Vol 229-231 ◽

pp. 1239-1243

Author(s):

Hai Peng Liu ◽

Ke Zhang ◽

Heng Nian Li

Keyword(s):

Information Fusion ◽

Least Square ◽

Aviation Industry ◽

Integrated Navigation ◽

Integrated Navigation System ◽

Filtering Algorithm ◽

System Noise ◽

Fast Development ◽

Sensor Information ◽

Set Up

With the fast development of aviation industry, integrated navigation techniques must be improved quickly along with it. In order to overcome the limitation of classical Kalman filtering algorithm in multi-sensor information fusion, the regression memory factor is introduced while the statistic characteristic of the system noise and measurement noise are uncertain. Firstly, a novel federated least square filtering algorithm based on integrated navigation is offered, and this filtering algorithm’s practical criterion is deducted. Then, a simulation flat of integrated navigation system is set up, and the simulation is conducted. Finally, through the contrast between this filter and the classical federated filter, the adaptability and accuracy of this algorithm is approved.

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An Integrated Navigation Method Based on an Adaptive Federal Kalman Filter for a Rice Transplanter

Transactions of the ASABE ◽

10.13031/trans.13682 ◽

2021 ◽

Vol 64 (2) ◽

pp. 389-399

Author(s):

Juan Liao ◽

Yao Wang ◽

Junnan Yin ◽

Lingling Bi ◽

Shun Zhang ◽

...

Keyword(s):

Kalman Filter ◽

Navigation System ◽

Visual Navigation ◽

List Type ◽

Integrated Navigation ◽

Distribution Factor ◽

Information Distribution ◽

Navigation Accuracy ◽

Navigation Information ◽

Navigation Method

HighlightsAn integrated GPS/INS/VNS navigation system was developed to improve navigation accuracy.An adaptive federal Kalman filter with information distribution factors was used to fuse navigation information.Detection of seedling row lines was achieved based on subregional feature points clustering.A modified rice transplanter was developed as an experimental platform for automatic navigation.Abstract. In this article, an integrated global positioning system (GPS), inertial navigation system (INS), and visual navigation system (VNS) navigation method based on an adaptive federal Kalman filter (KF) is presented to improve positioning accuracy for a rice transplanter operating in a paddy field. The proposed method used GPS/VNS to aid the INS and reduce the influence of the accumulated error of the INS on navigation accuracy. An adaptive federal KF algorithm was designed to fuse navigation information from different sensors. The information distribution factor of each local filter was obtained adaptively on the basis of its own error covariance matrix. Computer simulation and transplanter tests were conducted to verify the proposed method. Results showed that the proposed method provided accurate and reliable navigation information outputs and achieved better navigation performance compared with single GPS navigation and an integrated method based on a conventional federal KF. Keywords: Federal Kalman filter, GPS/INS/VNS, Information distribution factor, Information fusion, Integrated navigation.

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Ship Security Relative Integrated Navigation with Injected Fault Measurement Attack and Unknown Statistical Property Noises

Journal of Marine Science and Engineering ◽

10.3390/jmse8050305 ◽

2020 ◽

Vol 8 (5) ◽

pp. 305 ◽

Cited By ~ 1

Author(s):

Yongjing Wang ◽

Yi Wang ◽

Xiaoliang Feng

Keyword(s):

Navigation Systems ◽

Integrated Navigation ◽

Chi Square ◽

Integrated Navigation System ◽

Statistical Property ◽

Estimate Error ◽

Chi Square Test ◽

Ship Security ◽

Navigation Method ◽

Energy Property

In this work, the ship relative integrated navigation approaches are studied for the navigation scenarios with the measurements disturbed by unknown statistical property noises and with the injected fault measurement attacks. On the basis of the limited energy property of system noises, the navigation states are estimated by the local finite horizon H∞ filter to satisfy the performance index function. Then, the local estimates are fused in the relative integrated navigation system with the weight fusion parameters obtained by using the local estimate error measurements. Further, the injected fault measurement attacks are considered in the relative integrated navigation systems. Due to the system noises and the measurement noises having unknown statistical property, the classical Chi-square test can hardly be utilized to detect the injected fault measurements. Therefore, a secure relative integrated navigation method is proposed with a distance-based clustering detector. The finial simulation results illustrate the effectiveness of the proposed relative integrated navigation approach and the proposed secure relative integrated navigation approach.

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Autonomous Navigation of Mars Probes by Single X-ray Pulsar Measurement and Optical Data of Viewing Martian Moons

Journal of Navigation ◽

10.1017/s0373463316000357 ◽

2016 ◽

Vol 70 (1) ◽

pp. 18-32 ◽

Cited By ~ 5

Author(s):

Pengbin Ma ◽

Tianshu Wang ◽

Fanghua Jiang ◽

Junshan Mu ◽

Hexi Baoyin

Keyword(s):

Kalman Filter ◽

Autonomous Navigation ◽

Unscented Kalman Filter ◽

Optical Data ◽

Optical Navigation ◽

Integrated Navigation ◽

X Ray ◽

Navigation Accuracy ◽

Navigation Information ◽

Navigation Method

In order to achieve high accuracy of autonomous navigation for Mars probes, an integrated navigation method using X-ray pulsar measurement and optical data of viewing Martian moons is proposed. For single X-ray pulsar measurement on board a Mars probe, navigation accuracy is low due to its poor observability. On the other hand, Phobos and Deimos, two natural moons of Mars, are important optical navigation information sources available for Mars missions. However, the Martian moons ephemeris bias and the differences between barycentre and centre of brightness of Martian moons will result in low navigation accuracy. The method of integrated navigation using X-ray pulsar measurement and optical data of viewing Martian moons can overcome the defect and achieve accurate navigation. Two sequential orbit determination algorithms, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), are compared. The simulation results show this method can obtain high autonomous navigation accuracy during the phase of a probe orbiting Mars.

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