Satellite and aerial imagery geo-referencing using ground features

2021 ◽  
Vol 975 (9) ◽  
pp. 21-29
Author(s):  
A.L. Aksenov ◽  
O.I. Kozlov
Keyword(s):  
Least Squares Method ◽  
Mathematical Formulation ◽  
Reference Points ◽  
Aerial Imagery ◽  
Approximation Technique ◽  
Linear Features ◽  
Non Linear ◽  
Parametric Description ◽  
Sequential Approximation ◽  
Terrain Features

The method of geo-referencing satellite- and aerial imagery using reference points, linear and non-linear features, and segments of geodetic tracks as elements of a plan-altitude basis is discussed in this article. The method can be used for any mathematical model of satellite- and aerial imagery. The parametric description of the features, that can be used for the geo-referencing and various mathematical models of the above-mentioned imagery are presented. The mathematical formulation of the matter of satellite and aerial imagery geo-referencing using terrain objects and reference points is presented. A list of linear and non-linear features that can be included in a high-raised basis along with reference points is made. A generalized algorithm for geo-referencing satellite and aerial imagery using reference points and terrain features is given. The algorithm includes making a nonlinear system of equations for reference points and items, linearizing the system and solving by the sequential approximation technique according to the least squares method. An example of clarifying the satellite RPC-model and aerial imagery using reference points, linear and non-linear features is given. The advantages of the proposed method of using features created according to the measurements on satellite and aerial imagery compared with method, when the model of the feature is created according to the measurements on the ground are described.

The minimum zone fitting and error evaluation for the logarithmic curve based on geometry optimization approximation algorithm

2019 ◽  
Vol 41 (15) ◽  
pp. 4380-4386
Author(s):  
Tu Xianping ◽  
Lei Xianqing ◽  
Ma Wensuo ◽  
Wang Xiaoyi ◽  
Hu Luqing ◽  
...  
Keyword(s):  
Approximation Algorithm ◽  
Evaluation Method ◽  
Geometry Optimization ◽  
Reference Points ◽  
Approximation Technique ◽  
Error Evaluation ◽  
Iterative Approximation ◽  
Logarithmic Curve ◽  
Normal Distance ◽  
Minimum Zone

The minimum zone fitting and error evaluation for the logarithmic curve has important applications. Based on geometry optimization approximation algorithm whilst considering geometric characteristics of logarithmic curves, a new fitting and error evaluation method for the logarithmic curve is presented. To this end, two feature points, to serve as reference, are chosen either from those located on the least squares logarithmic curve or from amongst measurement points. Four auxiliary points surrounding each of the two reference points are then arranged to resemble vertices of a square. Subsequently, based on these auxiliary points, a series of auxiliary logarithmic curves (16 curves) are constructed, and the normal distance and corresponding range of values between each measurement point and all auxiliary logarithmic curves are calculated. Finally, by means of an iterative approximation technique consisting of comparing, evaluating, and changing reference points; determining new auxiliary points; and constructing corresponding auxiliary logarithmic curves, minimum zone fitting and evaluation of logarithmic curve profile errors are implemented. The example results show that the logarithmic curve can be fitted, and its profile error can be evaluated effectively and precisely using the presented method.

scholarly journals Correction to: Emotion classification from speech signal based on empirical mode decomposition and non-linear features

2021 ◽  
Author(s):  
Palani Thanaraj Krishnan ◽  
Alex Noel Joseph Raj ◽  
Vijayarajan Rajangam
Keyword(s):  
Empirical Mode Decomposition ◽  
Speech Signal ◽  
Emotion Classification ◽  
Linear Features ◽  
Mode Decomposition ◽  
Non Linear

A correction to this paper has been published: https://doi.org/10.1007/s40747-021-00377-y

Relational asymmetry, trust, and innovation in supply chain management: a non-linear approach

2019 ◽  
Vol 30 (1) ◽  
pp. 303-328 ◽  
Author(s):  
Marek Michalski ◽  
Jose Luis Montes ◽  
Ram Narasimhan
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Institutional Environment ◽  
Least Squares Method ◽  
Cross Sectional ◽  
Chain Management ◽  
Content Type ◽  
Relationship Analysis ◽  
Novel Approach ◽  
Non Linear

PurposeThe purpose of this paper is to examine the non-linear aspects of the asymmetry-performance relationship under varying conditions of trust and innovation. Its novel approach is useful for addressing the strategic elements of supply chain management (SCM) relationships based on trust and innovation decisions.Design/methodology/approachResults are based on a study of 90 managers from small- and medium-sized firms in Spain. Instead of a classical linear relationship analysis, the authors performed a non-linear analysis, using polynomial modeling and Warp 3 partial least squares method, which provides a more nuanced view of the data and constitutes an original approach to empirical research in SCM.FindingsThis study adds a new viewpoint on SC relationships by suggesting that not all trust and innovation development leads directly to performance improvement. The principal finding is, in varying trust and innovation contexts, that the influences of asymmetry on performance have uneven characteristics and follow non-linear paths.Research limitations/implicationsThis study focuses on only one particular institutional environment in one country. The data are also cross-sectional, which makes it difficult to empirically test causality.Practical implicationsThe findings provide rational insights to managers on when it is appropriate to reduce (or not) asymmetric relationships with partners.Originality/valueTrust and innovation are important and ones of the key requirements of supply chain relationships in any environment, this study argues that the interactions of key SCM elements that drive members to better performance are more complex and non-linear.

scholarly journals The identification of a device based on a Peltier element by the least squares method

2020 ◽  
pp. 17-27
Author(s):  
Vladimir Grinkevich ◽  
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Control Object ◽  
Object Identification ◽  
Model Parameters ◽  
Peltier Element ◽  
Transport Delay ◽  
Non Linear ◽  
The Mathematical Model

The evaluation of the mathematical model parameters of a non-linear object with a transport delay is considered in this paper. A temperature controlled stage based on a Peltier element is an identification object in the paper. Several input signal implementations are applied to the input of the identification object. The least squares method is applied for the calculation of the non-linear differential equitation parameters which describe the identification object. The least squares method is used due to its simplicity and the possibility of identification non-linear objects. The parameters values obtained in the process of identification are provided. The plots of temperature changes in the temperature control system with a controller designed based on the mathematical model of the control object obtained as a result of identification are shown. It is found that the mathematical model obtained in the process of identification may be applied to design controllers for non-linear systems, in particular for a temperature stage based on a Peltier element, and for self-tuning controllers. However, the least square method proposed in the paper cannot estimate the transport delay time. Therefore it is required to evaluate the time delay by temperature transient processes. Dynamic object identification is applied when it is required to obtain a mathematical model structure and evaluate the parameters by an input and output control object signal. Also, identification is applied for auto tuning of controllers. A mathematical model of a control object is required to design the controller which is used to provide the required accuracy and stability of control systems. Peltier elements are applied to design low-power and small- size temperature stage . Hot benches based on a Peltier element can provide the desired temperature above and below ambient temperature.

A Sequential Approximation Method for Structural Optimization Using Logarithmic Barriers

1993 ◽  
Author(s):  
Ashok V. Kumar ◽  
David C. Gossard
Keyword(s):  
Structural Optimization ◽  
Objective Function ◽  
Line Search ◽  
Optimization Problems ◽  
Approximation Technique ◽  
Barrier Method ◽  
Non Linear Programming ◽  
Linearly Constrained ◽  
Sequential Approximation ◽  
And Function

Abstract A sequential approximation technique for non-linear programming is presented here that is particularly suited for problems in engineering design and structural optimization, where the number of variables are very large and function and sensitivity evaluations are computationally expensive. A sequence of sub-problems are iteratively generated using a linear approximation for the objective function and setting move limits on the variables using a barrier method. These sub-problems are strictly convex. Computation per iteration is significantly reduced by not solving the sub-problems exactly. Instead at each iteration, a few Newton-steps are taken for the sub-problem. A criteria for moving the move limit, is described that reduces or eliminates stepsize reduction during line search. The method was found to perform well for unconstrained and linearly constrained optimization problems. It requires very few function evaluations, does not require the hessian of the objective function and evaluates its gradient only once per iteration.

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