scholarly journals Angle of Arrival Passive Location Algorithm Based on Proximal Policy Optimization

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1558 ◽  
Author(s):  
Yao Zhang ◽  
Zhongliang Deng ◽  
Yuhui Gao
Keyword(s):  
Measurement Data ◽  
Gradient Methods ◽  
Least Square ◽  
Passive Location ◽  
Residential Areas ◽  
Angle Of Arrival ◽  
Data Set ◽  
Research Attention ◽  
Location Algorithm ◽  
Policy Optimization

Location technology is playing an increasingly important role in urban life. Various active and passive wireless positioning technologies for mobile terminals have attracted research attention. However, positioning signals experience serious interference in high-density residential areas or in the interior of large buildings. The main type of interference is that caused by non-line-of-sight (NLOS) propagation. In this paper, we present a new method for optimizing the angle of arrival (AOA) measurement to obtain high accuracy location results based on proximal policy optimization (PPO). PPO is a new family of policy gradient methods for reinforcement learning, which can be used to adjust the sampling data under different environments using stochastic gradient ascent. Therefore, PPO can correct the NLOS propagation errors to produce a clear AOA measurement data set without building an offline fingerprinting database. Then, we used the least square method to calculate the location. The simulation result shows that the AOA passive location algorithm based on PPO produced more accurate location information.

ERROR LEVELS OF THE PASSIVE GONIOMETRIC LOCATION OF RADIATION SOURCES WITH THE INCREASING AMOUNT OF PROCESSED INFORMATION

2019 ◽  
Author(s):  
В.Н. Юдин ◽  
А.М. Волков
Keyword(s):  
Least Square Method ◽  
Least Square ◽  
Passive Location ◽  
Aircraft Carrier ◽  
Location Errors ◽  
Radiation Sources ◽  
Aerial Reconnaissance ◽  
Location Algorithm

Рассмотрены варианты повышения точности угломерной пассивной локации источников излучения с использованием одиночного авиационного носителя и алгоритма местоопределения на основе метода наименьших квадратов. Оценены достижимые уровни ошибок локации применительно к различным условиям ведения воздушной разведки источников излучения. Options for improving the accuracy of the goniometric passive location of radiation sources using a single aircraft carrier and location algorithm based on the least square method are considered.The achievable levels of location errors were assessed for different conditions of aerial reconnaissance of radiation sources.

scholarly journals Correlation effect of transformed or corrected data inversion

2021 ◽  
Author(s):  
László Balázs
Keyword(s):  
Likelihood Function ◽  
Measurement Data ◽  
Least Square Method ◽  
Estimation Procedure ◽  
Correlation Effect ◽  
Least Square ◽  
Inversion Method ◽  
Data Set ◽  
Data Inversion ◽  
Fitting Procedure

AbstractBefore performing the inversion process, the original measured data set is often transformed (corrected, smoothed, Fourier-transformed, interpolated etc.). These preliminary transformations may make the original (statistically independent) noisy measurement data correlated. The noise correlation on transformed data must be taken into account in the parameter fitting procedure (inversion) by proper derivation of likelihood function. The covariance matrix of transformed data system is no longer diagonal, so the likelihood based metrics, which determines the fitting process is also changed as well as the results of inversion. In the practice, these changes are often neglected using the “customary” estimation procedure (simple least square method) resulting wrong uncertainty estimation and sometimes biased results. In this article the consequence of neglected correlation is studied and discussed by decomposing the inversion functional to “customary” and additional part which represents the effect of correlation. The ratio of two components demonstrates the importance and justification of the inversion method modification.

scholarly journals Localization of Scattering Objects Using Neural Networks

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 11
Author(s):  
Domonkos Haffner ◽  
Ferenc Izsák
Keyword(s):  
Neural Networks ◽  
Plane Waves ◽  
Measurement Data ◽  
Scattered Wave ◽  
Training Data ◽  
Data Set ◽  
Main Compound ◽  
Incident Plane ◽  
The Neural Networks ◽  
Simulation Package

The localization of multiple scattering objects is performed while using scattered waves. An up-to-date approach: neural networks are used to estimate the corresponding locations. In the scattering phenomenon under investigation, we assume known incident plane waves, fully reflecting balls with known diameters and measurement data of the scattered wave on one fixed segment. The training data are constructed while using the simulation package μ-diff in Matlab. The structure of the neural networks, which are widely used for similar purposes, is further developed. A complex locally connected layer is the main compound of the proposed setup. With this and an appropriate preprocessing of the training data set, the number of parameters can be kept at a relatively low level. As a result, using a relatively large training data set, the unknown locations of the objects can be estimated effectively.

Harmonic Analysis on Low Quality Tidal Data

2014 ◽  
Author(s):  
Joost den Haan
Keyword(s):  
Harmonic Analysis ◽  
Three Dimensional ◽  
Measurement Data ◽  
Tidal Energy ◽  
Energy Yield ◽  
Profile Measurement ◽  
Current Profile ◽  
Tidal Power ◽  
Data Set ◽  
Tidal Forcing

The aim of the study is to devise a method to conservatively predict a tidal power generation based on relatively short current profile measurement data sets. Harmonic analysis on a low quality tidal current profile measurement data set only allowed for the reliable estimation of a limited number of constituents leading to a poor prediction of tidal energy yield. Two novel, but very different approaches were taken: firstly a quasi response function is formulated which combines the currents profiles into a single current. Secondly, a three dimensional vectorial tidal forcing model was developed aiming to support the harmonic analysis with upfront knowledge of the actual constituents. The response based approach allowed for a reasonable prediction. The vectorial tidal forcing model proved to be a viable start for a full featuring numerical model; even in its initial simplified form it could provide more insight than the conventional tidal potential models.

scholarly journals Material parameter identification using finite elements with time-adaptive higher-order time integration and experimental full-field strain information

2021 ◽  
Author(s):  
Stefan Hartmann ◽  
Rose Rogin Gilbert
Keyword(s):  
Experimental Data ◽  
Finite Elements ◽  
Parameter Identification ◽  
Material Parameter ◽  
Measurement Data ◽  
Least Square ◽  
Image Correlation ◽  
Field Strain ◽  
Material Parameter Identification ◽  
Full Field

AbstractIn this article, we follow a thorough matrix presentation of material parameter identification using a least-square approach, where the model is given by non-linear finite elements, and the experimental data is provided by both force data as well as full-field strain measurement data based on digital image correlation. First, the rigorous concept of semi-discretization for the direct problem is chosen, where—in the first step—the spatial discretization yields a large system of differential-algebraic equation (DAE-system). This is solved using a time-adaptive, high-order, singly diagonally-implicit Runge–Kutta method. Second, to study the fully analytical versus fully numerical determination of the sensitivities, required in a gradient-based optimization scheme, the force determination using the Lagrange-multiplier method and the strain computation must be provided explicitly. The consideration of the strains is necessary to circumvent the influence of rigid body motions occurring in the experimental data. This is done by applying an external strain determination tool which is based on the nodal displacements of the finite element program. Third, we apply the concept of local identifiability on the entire parameter identification procedure and show its influence on the choice of the parameters of the rate-type constitutive model. As a test example, a finite strain viscoelasticity model and biaxial tensile tests applied to a rubber-like material are chosen.

An Improved Ant Colony Optimization Algorithm for Solving the TSP Problem

2010 ◽  
Vol 26-28 ◽  
pp. 620-624 ◽  
Author(s):  
Zhan Wei Du ◽  
Yong Jian Yang ◽  
Yong Xiong Sun ◽  
Chi Jun Zhang ◽  
Tuan Liang Li
Keyword(s):  
Genetic Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Convergence Time ◽  
Ant Colony Optimization Algorithm ◽  
Data Set ◽  
Research Attention ◽  
Simply Supported ◽  
Source Data

This paper presents a modified Ant Colony Algorithm(ACA) called route-update ant colony algorithm(RUACA). The research attention is focused on improving the computational efficiency in the TSP problem. A new impact factor is introduced and proved to be effective for reducing the convergence time in the RUACA performance. In order to assess the RUACA performance, a simply supported data set of cities, which was taken as the source data in previous research using traditional ACA and genetic algorithm(GA), is chosen as a benchmark case study. Comparing with the ACA and GA results, it is shown that the presented RUACA has successfully solved the TSP problem. The results of the proposed algorithm are found to be satisfactory.

A Comparative Study of Genetic Algorithms and Gradient Methods for RM12 Turbofan Engine Diagnostics and Performance Estimation

2004 ◽  
Author(s):  
Tomas Gro¨nstedt ◽  
Markus Wallin
Keyword(s):  
Gas Turbine ◽  
Performance Test ◽  
Gradient Methods ◽  
Performance Testing ◽  
Performance Estimation ◽  
Data Sets ◽  
Data Set ◽  
Turbofan Engine ◽  
Local Optima ◽  
Bypass Ratio

Recent work on gas turbine diagnostics based on optimisation techniques advocates two different approaches: 1) Stochastic optimisation, including Genetic Algorithm techniques, for its robustness when optimising objective functions with many local optima and 2) Gradient based methods mainly for their computational efficiency. For smooth and single optimum functions, gradient methods are known to provide superior numerical performance. This paper addresses the key issue for method selection, i.e. whether multiple local optima may occur when the optimisation approach is applied to real engine testing. Two performance test data sets for the RM12 low bypass ratio turbofan engine, powering the Swedish Fighter Gripen, have been analysed. One set of data was recorded during performance testing of a highly degraded engine. This engine has been subjected to Accelerated Mission Testing (AMT) cycles corresponding to more than 4000 hours of run time. The other data set was recorded for a development engine with less than 200 hours of operation. The search for multiple optima was performed starting from more than 100 extreme points. Not a single case of multi-modality was encountered, i.e. one unique solution for each of the two data sets was consistently obtained. The RM12 engine cycle is typical for a modern fighter engine, implying that the obtained results can be transferred to, at least, most low bypass ratio turbofan engines. The paper goes on to describe the numerical difficulties that had to be resolved to obtain efficient and robust performance by the gradient solvers. Ill conditioning and noise may, as illustrated on a model problem, introduce local optima without a correspondence in the gas turbine physics. Numerical methods exploiting the special problem structure represented by a non-linear least squares formulation is given special attention. Finally, a mixed norm allowing for both robustness and numerical efficiency is suggested.

From managing customers to joint venturing with customers: co-creating service value in the digital age

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Christine Falkenreck ◽  
Ralf Wagner
Keyword(s):  
Perceived Risk ◽  
Structural Equation ◽  
Business Models ◽  
Joint Venture ◽  
Digital Age ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Data Set ◽  
Content Type

Purpose Until today, scholars claim that the phenomenon of “co-creation” of value in an “interacted” economy and in the context of positive actor-to-actor relationships has not been adequately explored. This study aims to first to identify and separate the accessible values of internet of things (IoT)-based business models for business-to-business (B2B) and business-to-government (B2G) customer groups. It quantifies the drivers to successfully implement disruptive business models. Design/methodology/approach Data were gathered from 292 customers in Western Europe. The conceptual framework was tested using partial least square structural equation modeling. Findings Managing disruptions in the digital age is closely related to the fact that the existing trust in buyer-seller relationships is not enough to accept IoT projects. A company’s digitalization capabilities, satisfaction with the existing relationship and trust in the IoT credibility of the manufacturer drives the perceived value of IoT-based business models in B2B settings. Contrastingly, in B2G settings, money is less important. Research limitations/implications Research refers to one business field, the data set is of European origin only. Findings indicate that the drivers to engage in IoT-related projects differ significantly between the customer groups and therefore require different marketing management strategies. Saving time today is more important to B2G buyers than saving money. Practical implications The disparate nature of B2B and B2G buyers indicates that market segmentation and targeted marketing must be considered before joint-venturing in IoT business models. To joint venture supply chain partners co-creating value in the context of IoT-related business models, relationship management should be focused with buyers on the same footing, as active players and co-developers of a personalized experience in digital service projects. Originality/value Diverging from established studies focusing on the relationship within a network of actors, this study defines disruptive business models and identifies its drivers in B2B and B2G relationships. This study proposes joint venturing with B2B and B2G customers to overcome the perceived risk of these IoT-related business models. Including customers in platforms and networks may lead to the co-creation of value in joint IoT projects.

scholarly journals An Inverse Source Problem for Singular Parabolic Equations with Interior Degeneracy

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Khalid Atifi ◽  
Idriss Boutaayamou ◽  
Hamed Ould Sidi ◽  
Jawad Salhi
Keyword(s):  
Numerical Solution ◽  
Parabolic Equations ◽  
Measurement Data ◽  
Gradient Methods ◽  
Stability Estimate ◽  
Inverse Source Problem ◽  
Output Least Squares ◽  
Singular Parabolic Equations ◽  
Interior Degeneracy ◽  
Least Squares Approach

The main purpose of this work is to study an inverse source problem for degenerate/singular parabolic equations with degeneracy and singularity occurring in the interior of the spatial domain. Using Carleman estimates, we prove a Lipschitz stability estimate for the source term provided that additional measurement data are given on a suitable interior subdomain. For the numerical solution, the reconstruction is formulated as a minimization problem using the output least squares approach with the Tikhonov regularization. The Fréchet differentiability of the Tikhonov functional and the Lipschitz continuity of the Fréchet gradient are proved. These properties allow us to apply gradient methods for numerical solution of the considered inverse source problem.

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