scholarly journals Distributed State Estimation for Dynamic Positioning Systems with Uncertain Disturbances and Transmission Time Delays

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Li Liu ◽  
Tao Yao ◽  
Xin Hu ◽  
Chunjie Zhou ◽  
Dianli Hou ◽  
...  
Keyword(s):  
State Estimation ◽  
Time Delays ◽  
Transmission Time ◽  
Model Parameters ◽  
Dynamic Positioning ◽  
Positioning System ◽  
Selection Scheme ◽  
Positioning Systems ◽  
Uncertain Disturbances ◽  
Spatial Positioning

The dynamic positioning system of unmanned underwater vehicles (UUVs) is a complex and large-scale system mainly due to the nonlinear dynamics, uncertainty in model parameters, and external disturbances. With the aid of the bio-inspired computing (BIC) method, the designed three-dimensional (3D) spatial positioning system is used for enlarging communication constraints and increasing signal coordination processing. With the growing of measurement scales, the issue of the networked high-precision positioning has been developed rapidly. Then, an information fusion estimation approach is presented for the distributed networked systems with data random transmission time delays and lost and disordered packets. To reduce the communication burden, an adaptive signal selection scheme is employed to reorganize the measurement sequence, and the parameter uncertainties as well as cross-correlated noise are used to describe the uncertain disturbances. Moreover, a reoptimal weighted fusion state estimation is designed to alleviate the information redundancy and maintain higher measurement accuracy. An illustrative example obtained from the 3D spatial positioning system is given to validate the effectiveness of the proposed method.

scholarly journals Analysis of Impact of Ship Model Parameters on Changes of Control Quality Index in Ship Dynamic Positioning System

2019 ◽  
Vol 26 (1) ◽  
pp. 6-14 ◽  
Author(s):  
Tacjana Niksa Rynkiewicz ◽  
Anna Witkowska
Keyword(s):  
Quality Index ◽  
Adaptive Controller ◽  
Model Parameters ◽  
Dynamic Positioning ◽  
Positioning System ◽  
Integral Control ◽  
Dynamic Positioning System ◽  
Ship Model ◽  
Control Quality ◽  
The Impact

Abstract In this work there is presented an analysis of impact of ship model parameters on changes of control quality index in a ship dynamic positioning system designed with the use of a backstepping adaptive controller. Assessment of the impact of ship model parameters was performed on the basis of Pareto-Lorentz curves and ABC method in order to determine sets of the parameters which have either crucial, moderate or low impact on objective function. Simulation investigations were carried out with taking into account integral control quality indices.

Optimal Thrust Allocation in a Dynamic Positioning System

2008 ◽  
Author(s):  
J. A. Leavitt
Keyword(s):  
Dynamic Positioning ◽  
Positioning System ◽  
Positioning Systems ◽  
Dynamic Positioning System ◽  
Surface Vessels ◽  
Thrust Allocation

An existing approach to optimizing thrust allocation in surface vessels is considered for general use with dynamic positioning systems. A solution to the power limiting problem is presented, and the handling of azimuthing thrusters is significantly improved. Various other considerations related to thrust allocation are treated. A generalized algorithm is developed.

Dimensioning of a Dynamic Positioning System for a Shuttle Tanker

2002 ◽  
Author(s):  
Stefania Defilippo Rocha ◽  
Ricardo B. Portella
Keyword(s):  
First Generation ◽  
Critical Issue ◽  
Dynamic Positioning ◽  
Positioning System ◽  
Water Production ◽  
Positioning Systems ◽  
Dynamic Positioning System ◽  
Deep Waters ◽  
Under Construction ◽  
New Generation

The increase of the offshore deep water production activities in Brazil based on the growth of the FPSO/FSO fleet, became the offloading operations a critical issue related to the possibilities of platform downtime. In order to improve the actual operational behavior, a new generation of shuttle tankers equipped with dynamic positioning systems is now under construction. The intent of this paper is to present the work performed for the dimensioning of the first generation of the DP Shuttle Tankers specifically projected to operate on Brazilian deep waters [1]. The system is intended to be installed in existing ships converted to operate as DP shuttle tankers.

scholarly journals Modern Dynamic Positioning (DP) System of ORP ‘Kormoran’ — Class Mine Destroyer

2018 ◽  
Vol 215 (4) ◽  
pp. 143-155
Author(s):  
Paweł Zalewski ◽  
Roman Haberek ◽  
Mirosław Chmieliński
Keyword(s):  
Control System ◽  
Remote Control ◽  
Dynamic Positioning ◽  
Main Task ◽  
Positioning System ◽  
Allocation Model ◽  
Positioning Control ◽  
Positioning Systems ◽  
Dynamic Positioning System ◽  
The World

Abstract The paper presents the dynamic positioning system (DP), particularly its thruster allocation model, designed for ORP ‘Kormoran’, a Polish mine destroyer built for the Polish Navy in Remontowa Shipbuilding S.A. in Gdańsk. The ORP ‘Kormoran’ ship is the newest and best equipped minehunter ship in Europe. The main task of the new Polish mine destroyer is to search for, classify, identify and combat marine mines and improvised underwater explosives, recognize waterways, transport mines, deploy mines and provide remote control of self-propelled anti-mine platforms. The dynamic positioning control system of the ship presented in the article was constructed by Autocomp Management Ltd. from Szczecin, the only in Poland and one of the few producers of dynamic ship positioning systems in the world.

scholarly journals High-Precision RTT-Based Indoor Positioning System Using RCDN and RPN

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3701
Author(s):  
Ju-Hyeon Seong ◽  
Soo-Hwan Lee ◽  
Won-Yeol Kim ◽  
Dong-Hoan Seo
Keyword(s):  
High Precision ◽  
Distance Estimation ◽  
Sampling Period ◽  
Multipath Fading ◽  
Indoor Positioning ◽  
Positioning System ◽  
Positioning Systems ◽  
Positioning Errors ◽  
Location Determination ◽  
Indoor Positioning System

Wi-Fi round-trip timing (RTT) was applied to indoor positioning systems based on distance estimation. RTT has a higher reception instability than the received signal strength indicator (RSSI)-based fingerprint in non-line-of-sight (NLOS) environments with many obstacles, resulting in large positioning errors due to multipath fading. To solve these problems, in this paper, we propose high-precision RTT-based indoor positioning system using an RTT compensation distance network (RCDN) and a region proposal network (RPN). The proposed method consists of a CNN-based RCDN for improving the prediction accuracy and learning rate of the received distances and a recurrent neural network-based RPN for real-time positioning, implemented in an end-to-end manner. The proposed RCDN collects and corrects a stable and reliable distance prediction value from each RTT transmitter by applying a scanning step to increase the reception rate of the TOF-based RTT with unstable reception. In addition, the user location is derived using the fingerprint-based location determination method through the RPN in which division processing is applied to the distances of the RTT corrected in the RCDN using the characteristics of the fast-sampling period.

scholarly journals Consistency of the Empirical Distributions of Navigation Positioning System Errors with Theoretical Distributions—Comparative Analysis of the DGPS and EGNOS Systems in the Years 2006 and 2014

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 31
Author(s):  
Mariusz Specht
Keyword(s):  
Normal Distribution ◽  
Root Mean Square ◽  
Statistical Tests ◽  
Position Error ◽  
Positioning System ◽  
Navigation Systems ◽  
Mean Square ◽  
Positioning Systems ◽  
Position Errors ◽  
System Errors

Positioning systems are used to determine position coordinates in navigation (air, land and marine). The accuracy of an object’s position is described by the position error and a statistical analysis can determine its measures, which usually include: Root Mean Square (RMS), twice the Distance Root Mean Square (2DRMS), Circular Error Probable (CEP) and Spherical Probable Error (SEP). It is commonly assumed in navigation that position errors are random and that their distribution are consistent with the normal distribution. This assumption is based on the popularity of the Gauss distribution in science, the simplicity of calculating RMS values for 68% and 95% probabilities, as well as the intuitive perception of randomness in the statistics which this distribution reflects. It should be noted, however, that the necessary conditions for a random variable to be normally distributed include the independence of measurements and identical conditions of their realisation, which is not the case in the iterative method of determining successive positions, the filtration of coordinates or the dependence of the position error on meteorological conditions. In the preface to this publication, examples are provided which indicate that position errors in some navigation systems may not be consistent with the normal distribution. The subsequent section describes basic statistical tests for assessing the fit between the empirical and theoretical distributions (Anderson-Darling, chi-square and Kolmogorov-Smirnov). Next, statistical tests of the position error distributions of very long Differential Global Positioning System (DGPS) and European Geostationary Navigation Overlay Service (EGNOS) campaigns from different years (2006 and 2014) were performed with the number of measurements per session being 900’000 fixes. In addition, the paper discusses selected statistical distributions that fit the empirical measurement results better than the normal distribution. Research has shown that normal distribution is not the optimal statistical distribution to describe position errors of navigation systems. The distributions that describe navigation positioning system errors more accurately include: beta, gamma, logistic and lognormal distributions.

scholarly journals Sensing Framework for the Internet of Actors in the Value Co-Creation Process with a Beacon-Attachable Indoor Positioning System

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 83
Author(s):  
Keiichi Zempo ◽  
Taiga Arai ◽  
Takuya Aoki ◽  
Yukihiko Okada
Keyword(s):  
Radio Wave ◽  
Indoor Positioning ◽  
Measurement Range ◽  
Pulse Interval ◽  
Retail Stores ◽  
Positioning System ◽  
Radio Waves ◽  
Positioning Systems ◽  
Environment Recognition ◽  
Indoor Positioning System

To evaluate and improve the value of a service, it is important to measure not only the outcomes, but also the process of the service. Value co-creation (VCC) is not limited to outcomes, especially in interpersonal services based on interactions between actors. In this paper, a sensing framework for a VCC process in retail stores is proposed by improving an environment recognition based indoor positioning system with high positioning performance in a metal shelf environment. The conventional indoor positioning systems use radio waves; therefore, errors are caused by reflection, absorption, and interference from metal shelves. An improvement in positioning performance was achieved in the proposed method by using an IR (infrared) slit and IR light, which avoids such errors. The system was designed to recognize many and unspecified people based on the environment recognition method that the receivers had installed, in the service environment. In addition, sensor networking was also conducted by adding a function to transmit payload and identification simultaneously to the beacons that were attached to positioning objects. The effectiveness of the proposed method was verified by installing it not only in an experimental environment with ideal conditions, but posteriorly, the system was tested in real conditions, in a retail store. In our experimental setup, in a comparison with equal element numbers, positioning identification was possible within an error of 96.2 mm in a static environment in contrast to the radio wave based method where an average positioning error of approximately 648 mm was measured using the radio wave based method (Bluetooth low-energy fingerprinting technique). Moreover, when multiple beacons were used simultaneously in our system within the measurement range of one receiver, the appropriate setting of the pulse interval and jitter rate was implemented by simulation. Additionally, it was confirmed that, in a real scenario, it is possible to measure the changes in movement and positional relationships between people. This result shows the feasibility of measuring and evaluating the VCC process in retail stores, although it was difficult to measure the interaction between actors.

scholarly journals Hybrid Deep Learning Model Based Indoor Positioning Using Wi-Fi RSSI Heat Maps for Autonomous Applications

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 2
Author(s):  
Alwin Poulose ◽  
Dong Seog Han
Keyword(s):  
Deep Learning ◽  
Signal Strength ◽  
Indoor Positioning ◽  
Learning Model ◽  
Signal Interference ◽  
Positioning System ◽  
Heat Maps ◽  
Positioning Systems ◽  
Localization Performance ◽  
Deep Learning Model

Positioning using Wi-Fi received signal strength indication (RSSI) signals is an effective method for identifying the user positions in an indoor scenario. Wi-Fi RSSI signals in an autonomous system can be easily used for vehicle tracking in underground parking. In Wi-Fi RSSI signal based positioning, the positioning system estimates the signal strength of the access points (APs) to the receiver and identifies the user’s indoor positions. The existing Wi-Fi RSSI based positioning systems use raw RSSI signals obtained from APs and estimate the user positions. These raw RSSI signals can easily fluctuate and be interfered with by the indoor channel conditions. This signal interference in the indoor channel condition reduces localization performance of these existing Wi-Fi RSSI signal based positioning systems. To enhance their performance and reduce the positioning error, we propose a hybrid deep learning model (HDLM) based indoor positioning system. The proposed HDLM based positioning system uses RSSI heat maps instead of raw RSSI signals from APs. This results in better localization performance for Wi-Fi RSSI signal based positioning systems. When compared to the existing Wi-Fi RSSI based positioning technologies such as fingerprint, trilateration, and Wi-Fi fusion approaches, the proposed approach achieves reasonably better positioning results for indoor localization. The experiment results show that a combination of convolutional neural network and long short-term memory network (CNN-LSTM) used in the proposed HDLM outperforms other deep learning models and gives a smaller localization error than conventional Wi-Fi RSSI signal based localization approaches. From the experiment result analysis, the proposed system can be easily implemented for autonomous applications.

scholarly journals Research on Spatial Positioning System of Fruits to be Picked in Field Based on Binocular Vision and SSD Model

2021 ◽  
Vol 1748 ◽  
pp. 042011
Author(s):  
Xing Zhang ◽  
Qiaoming Gao ◽  
Dong Pan ◽  
Peng Cheng Cao ◽  
Dong Hui Huang
Keyword(s):  
Binocular Vision ◽  
Positioning System ◽  
Spatial Positioning
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