scholarly journals Analyzing of Cooperative Locating Error and Formation Configuration of AUV Based on Geometric Interpretation

2020 ◽  
Vol 38 (4) ◽  
pp. 755-765
Author(s):  
Lichuan Zhang ◽  
Junqi Qu ◽  
Guang Pan ◽  
Yongzhao Wang
Keyword(s):  
Performance Evaluation ◽  
Information Matrix ◽  
Geometric Interpretation ◽  
Measurement Information ◽  
Evaluation Function ◽  
Locating Error ◽  
Priori Information ◽  
Value Decomposition ◽  
Ellipse Area ◽  
Interpretation Method

Because the evaluation of the location performance of AUVs with the lower bound of the Cramer-Rao inequality is not intuitive, the geometric interpretation method is proposed based on geometric ellipse. The Fisher information matrix is used to replace the Cramer-Rao inequality. The priori information matrix and the measurement information matrix are synthesized into the posterior information matrix through singular value decomposition. The geometric ellipse is used to geometrically represent the posterior information matrix. The posterior information ellipse area is used to establish the location performance evaluation function. By analyzing the performance evaluation function, the optimal formation configurations of single-master, dual-master and three-master AUVs are designed. The implementation of the special formation configuration for the three-master AUV formation proposed in the paper is easier, while the location performance of the optimal formation configuration is not much inferior. The simulation results verify that the optimal formation configuration has a higher location accuracy and that the special formation configuration is effective.

scholarly journals AN INDOOR SLAM METHOD BASED ON KINECT AND MULTI-FEATURE EXTENDED INFORMATION FILTER

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 327-332
Author(s):  
M. Chang ◽  
Z. Kang
Keyword(s):  
Point Cloud ◽  
Information Matrix ◽  
Depth Image ◽  
Point Cloud Data ◽  
A Posteriori ◽  
Cloud Data ◽  
Information Filter ◽  
Error Accumulation ◽  
Priori Information ◽  
Information Vector

Based on the frame of ORB-SLAM in this paper the transformation parameters between adjacent Kinect image frames are computed using ORB keypoints, from which priori information matrix and information vector are calculated. The motion update of multi-feature extended information filter is then realized. According to the point cloud data formed by depth image, ICP algorithm was used to extract the point features of the point cloud data in the scene and built an observation model while calculating a-posteriori information matrix and information vector, and weakening the influences caused by the error accumulation in the positioning process. Furthermore, this paper applied ORB-SLAM frame to realize autonomous positioning in real time in interior unknown environment. In the end, Lidar was used to get data in the scene in order to estimate positioning accuracy put forward in this paper.

A New Algorithm to Compensate Ionosphere Phase Contamination

2014 ◽  
Vol 644-650 ◽  
pp. 4551-4554
Author(s):  
Hui Ai ◽  
Jin Feng Hu ◽  
Wan Ge Li ◽  
Zhi Rong Lin ◽  
Ya Xuan Zhang
Keyword(s):  
Fourier Transform ◽  
Singular Value Decomposition ◽  
Prior Information ◽  
Hankel Matrix ◽  
Singular Value ◽  
Echo Signal ◽  
Rank Reduction ◽  
Coherent Integration ◽  
Priori Information ◽  
Value Decomposition

The echo signals of sky-wave over-the-horizon radar involve ionospheric phase contamination with spectrum expansion. The bragg peaks expand and cover the frequency spectrum of low speed target. So ionospheric phase decontamination is necessary before coherent integration. The traditional Hankel Rank Reduction (HRR) phase decontamination method constructs the Hankel matrix by folding the echo signal, estimating instantaneous frequency through singular value decomposition. But HRR method requires the prior information of signal components. The estimation is invalid without priori information. The algorithm presented in this paper does not require the priori information. The algorithm based on matched fourier transform can accurately estimate the phase contamination function for the clutter noise ratio is high. Simulation shows that the proposed algorithm has better performance in phase decontamination.

ALGORITHM FOR SELECTION OF LAUNCH ELEMENTS IN THE PRESENCE OF A PRIORI INFORMATION ABOUT ITS COMPOSITION AND STRUCTURE

2018 ◽  
pp. 114-119
Author(s):  
O. I. Nemykin
Keyword(s):  
Decision Making ◽  
Loss Function ◽  
Selection Process ◽  
A Priori ◽  
Measurement Information ◽  
A Priori Information ◽  
Space Objects ◽  
Alternative Hypotheses ◽  
Priori Information ◽  
Selection Of

Traditional methods of the theory of statistical solutions are developed for cases of making single-valued two-alternative or multialternative solutions about the class of an object. Assuming the possibility of ambiguous multi-alternative (in the case of solving the problem of selection of space objects of three-alternative) decisions on the classification of of space objects at the stages of the selection process, a modification of the traditional statistical decision making algorithm is required. Such a modification of the algorithm can be carried out by appropriate selection of the loss function. In the framework of the Bayes approach, an additive loss function is proposed, the structure of which takes into account a priori information on the structure and composition of launch elements in relation to the classes «Launch vehicle» and «spacecraft». The algorithm of decision making is synthesized under the conditions of a priori certainty regarding the probabilistic description of the analyzed situation. It is shown that the problem of verifying three-alternative hypotheses can be reduced to an independent verification of three two-alternative hypotheses, which makes it possible to take particular solutions in the solution process and use a different set of the signs of selection for the formation of solutions for individual classes of space objects. The peculiarities of the implementation of the selection algorithm are discussed in the presence of a priori information and measurement information on starts of a limited volume. The synthesized Bayesian decision making algorithm has the properties necessary to solve the problem of selection of space objects at launch in real conditions in the presence of measuring information specified in the form of a training sample. Its architecture allows to form unambiguous and ambiguous decisions about each space object in the launch.

scholarly journals Optimal Sensor Formation for 3D Cooperative Localization of AUVs Using Time Difference of Arrival (TDOA) Method

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4442 ◽  
Author(s):  
Xu Bo ◽  
Asghar Razzaqi ◽  
Xiaoyu Wang
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Information Matrix ◽  
Three Dimensional ◽  
Time Difference ◽  
Cooperative Localization ◽  
Evaluation Function ◽  
Time Difference Of Arrival ◽  
Single Target ◽  
Novel Method ◽  
Localization Systems

The cooperative localization of submerged autonomous underwater vehicles (AUVs) using the Time Difference of Arrival (TDOA) measurements of surface AUV sensors is an effective method for many applications of AUVs. Proper positioning of the sensors to maximize the observability of the AUVs is very critical for cooperative localization. In this paper, a novel method for obtaining the optimal formation of sensor AUVs has been presented for the three-dimensional (3D) cooperative localization of targets using the TDOA technique. An evaluation function for estimating the optimal formation has been derived based on Fisher Information Matrix (FIM) theory for a single target as well as multiple-target cooperative localization systems. An iterative stepping algorithm has been followed to solve the evaluation function and obtain the optimal positions of the sensors. The algorithm ensured that the computation complexity should remain limited, even when the number of sensor AUVs is increased. Various simulation examples are then presented to calculate the optimal formation for different systems/situations. The effect of the position of the reference sensor and operating depth of the target AUVs on the optimal formation of the sensors has also been studied, and conclusions are drawn. For implementation of the proposed method for more practical scenarios, a simulation example is also presented for cases when the target’s position is only known with uncertainty.

scholarly journals Model and method development for determining the completeness of information for remote detection of landmarks for autonomous mobile robots

2021 ◽  
Vol 6 (2(62)) ◽  
pp. 37-41
Author(s):  
Oleksandr Poliarus ◽  
Andrii Lebedynskyi ◽  
Yevhenii Chepusenko ◽  
Nina Lyubymova
Keyword(s):  
Method Development ◽  
A Priori ◽  
Weather Conditions ◽  
Threshold Level ◽  
Remote Detection ◽  
Measurement Information ◽  
Priori Information ◽  
The Given ◽  
Physical Principles ◽  
Approach Unity

The object of research is the completeness of information for making a navigation decision by an autonomous mobile robot when it performs a task in an unfamiliar area without GPS. It is difficult to identify a landmark in the absence and abundance of information. One of the most problematic places is the mathematical description of the criterion according to which an autonomous robot makes a decision about the completeness of information. The paper substantiates a model and method for determining the completeness of information by a robot equipped with several landmarks detection tools operating on different physical principles. It is shown that the implementation of the method requires a priori information on the probability of detecting various landmarks by passive and active means against a continuous and discontinuous background at different illumination of objects, in day and night conditions under different weather conditions. The values of the probability of detecting a specific type of landmark obtained in such studies serve as the basis for constructing an information cadastre for a job performing tasks on the ground. Three formulas are proposed for determining the coefficient of completeness of information, taking into account a priori and a posteriori inventories, and recommended areas of application. The value of this coefficient depends on the threshold level of the probability of detecting a landmark. The reliability of a decision made by a robot is greatest when it is made under conditions of a certain level of completeness of information. The proposed method can be used for other technical objects from which the measurement information is received. Compared with the known methods, it expands the boundaries of application and reveals the possibility of assessing the completeness of information in constantly changing conditions. Along with a change in these conditions, the characteristics of the completeness of information also change. The coefficient of completeness of information can approach unity even in the absence of separate means of detecting landmarks, and then the method makes it possible to assess the need for their use in the given conditions.

scholarly journals INVERSION OF INTERVAL VELOCITIES: APPLICATION TO A GEOLOGICAL MODEL FROM A PRE-SALT AREA

2015 ◽  
Vol 33 (1) ◽  
pp. 19
Author(s):  
Thais Gomes Santana ◽  
Amin Bassrei
Keyword(s):  
Singular Value Decomposition ◽  
Relative Entropy ◽  
A Priori ◽  
Singular Value ◽  
A Priori Information ◽  
Minimum Relative Entropy ◽  
Priori Information ◽  
Interval Velocities ◽  
Value Decomposition

ABSTRACT. Seismic methods study the propagation of elastic wave fields inside the Earth, with the goal to provide subsurface images. In this work, the determination of the time interval velocity distribution is the main information provided. Several synthetic models were used, where one is based in a real situation, a dip section from the pre-salt region, central part of the Santos Basin, Brazil. Themethods used to determine interval velocities were based on the Dix transform, singular value decomposition (SVD) and minimum relative entropy (MRE). Dix transform showed excellent results when used in simple geological models, and was coincident to the other two methods. With the addition of a priori information, the SVD and MRE showed to be good methods for the determination of the interval velocities. When comparing SVD and MRE methods the latter showed the best results. When the a priori information is constant, the SVD and MRE methods give the same velocity estimate given from the direct application of the Dix transform.Keywords: inversion of interval velocities, singular value decomposition, minimum relative entropy, pre-salt.RESUMO. Os métodos sísmicos utilizam o campo de propagação de ondas elásticas no interior da Terra, com o objetivo de fornecer imagens da subsuperfície. Neste trabalho, a determinação do campo de velocidades intervalares é a principal informação a ser fornecida. Foram utilizados modelos sintéticos, sendo um deles baseado em uma situação real, no caso uma sessão dip , na região do pré-sal, parte central da Bacia de Santos. Os métodos usados para determinar as velocidades intervalares foram a transformada de Dix, a decomposição por valores singulares (SVD) e a entropia relativa mínima (MRE). A transformada de Dix, quando usada em modelos geológicos mais simples apresentou excelentes resultados coincidente aos outros dois métodos. Com a adição de estimativas a priori , o SVD e o MRE se mostraram como bons métodos para a determinação das velocidades intervalares, sendo que o MRE apresentou os melhores resultados. Quando a informação a priori é constante, os métodos do SVD e MRE fornecem a mesma estimativa de velocidade que é obtida pela transformada de Dix.Palavras-chave: inversão de velocidades intervalares, decomposição por valores singulares, entropia relativa mínima, pré-sal.

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