Improving AUV Localization Accuracy by Combining Ultra-Short-Baseline and Long-Baseline Measurements Systems in a Post-Processing Extended Kalman Filter

2019 ◽  
Author(s):  
Eric Wolbrecht ◽  
David Pick ◽  
John Canning ◽  
Dean Edwards
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Post Processing ◽  
Short Baseline ◽  
Localization Accuracy ◽  
Long Baseline

scholarly journals Underwater Positioning Using Near Surface Long Baseline Transponder’s Induced by Wave Motion

2017 ◽  
Author(s):  
Stian S. Sandøy ◽  
Ingrid Schjølberg
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Wave Motion ◽  
Weather Conditions ◽  
Sea Surface ◽  
Positioning System ◽  
Motion Model ◽  
Near Surface ◽  
Long Baseline ◽  
Underwater Positioning

This paper presents a filter for underwater positioning in an aquaculture environment with demanding weather conditions. The positioning system is based on acoustic transponders mounted at a net pen on the sea surface. The transponders are exposed to oscillations due to wave disturbance. This will have an impact on the accuracy of the positioning system. An extended Kalman filter (EKF) solution has been proposed including a wave motion model integrated with the pseudo-range measurements from the transponders. Simulations show that the proposed filter compensates well for the disturbances.

Sensor Noise Compensation for a Remote Controlled Sprayer Using EKF

2013 ◽  
Vol 694-697 ◽  
pp. 1025-1029
Author(s):  
Juh Yun An ◽  
In Nam Lee ◽  
Ki Ho Kim ◽  
Kwan Ho You
Keyword(s):  
Kalman Filter ◽  
Dynamic Model ◽  
Extended Kalman Filter ◽  
State Equation ◽  
Sensor Noise ◽  
Localization Accuracy ◽  
Noise Compensation ◽  
Precision Tracking ◽  
Skid Steering

The dynamic model of a remote controlled sprayer using skid-steering method is presented as a state equation. The precision tracking of the remote controlled sprayer is difficult to realize due to sensor noise. In this paper, we propose the extended Kalman filter (EKF) algorithm to compensate for the odometric sensor noise. To demonstrate the performance of the proposed algorithm, simulations which represent a real working sprayer in a greenhouse are performed. The results show the improved localization accuracy obtained by using the proposed algorithm.

scholarly journals High-accuracy localization for indoor group users based on extended Kalman filter

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881272 ◽  
Author(s):  
Tian Wang ◽  
Yuzhu Liang ◽  
Yaxin Mei ◽  
Muhammad Arif ◽  
Chunsheng Zhu
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Indoor Localization ◽  
High Accuracy ◽  
Mutual Distance ◽  
Distance Information ◽  
Localization Accuracy ◽  
Accuracy Requirement ◽  
Time Operation ◽  
Real Time Operation

Indoor localization has attracted increasing research attentions in the recent years. However, many important issues still need to be further studied to keep pace with new requirements and technical progress, such as real-time operation, high accuracy, and energy efficiency. In order to meet the high localization accuracy requirement and the high localization dependable requirement in some scenarios, we take the users as a group to utilize the mutual distance information among them to get better localization performance. Moreover, we design a mobile group localization method based on extended kalman filter and believable factor of non-localized nodes, which can alleviate the influence caused by environmental noisy and unstable wireless signals to improve the localization accuracy. Besides, we implement a real system based on ZigBee technique and perform experiments on the campus of Huaqiao University. Experimental results and theoretical analysis validate the effectiveness of the proposed method.

Outdoor Localization for Quad-Rotor Using Extended Kalman Filter and Path Planning

2014 ◽  
Vol 11 (03) ◽  
pp. 1440001 ◽  
Author(s):  
Keon-Woo Jeong ◽  
Ki-Jung Kim ◽  
Yun-Ki Kim ◽  
Hyun-Woo Kim ◽  
Jangmyung Lee
Keyword(s):  
Kalman Filter ◽  
Path Planning ◽  
Extended Kalman Filter ◽  
Low Cost ◽  
Short Interval ◽  
Localization Accuracy ◽  
Location Data ◽  
Planning Algorithm ◽  
A New Technique ◽  
Path Planning Algorithm

This paper proposes a new technique that can be used to produce improved localization accuracy and to remove out the noises in sensing when the low-cost GPS/INS system has been used for a quad-rotor. The level of localization accuracy could be worse when the quad-rotor flies through the air by forming a curve. Also, the accuracy is influenced by the performance of GPS/INS system. The location data by the GPS/INS system include high frequency noises caused by various factors such as measurement noises and external disturbances. When the quad-rotor flies outdoor, it is possible to estimate the moving path for a short interval since the path can be assumed to be straight for a short interval. Therefore, the extended Kalman filter has been adopted to improve the localization accuracy. Also the global path can be more precisely estimated by fitting the location data obtained by the GPS/INS system to the planned path. Through the foregoing processes of the extended Kalman filter and path planning algorithm, the improved localization information can be obtained when the quad-rotor flies. Performance improvement of the proposed system has been verified based on various outdoor experiments.

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