scholarly journals THE OPTIMIZATION METHOD OF FUZZY AUTOMATIC CLASSIFICATION IN THE PROBLEM OF COMBINING THE ASSESSMENTS OF TRAJECTOR MEASUREMENTS IN THE RADAR SYSTEM

Doklady BGUIR ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. 89-95
Author(s):  
A. V. Khizhniak

The paper describes the application of the optimization method of fuzzy automatic classification in the problem of combining estimates of trajectory measurements in a radar system. By a radiolocation system the author mean an automated hierarchical technical complex that combines, using communication tools, a set of asynchronously functioning radiolocation tools, as well as central and intermediate points that collect, process and issue trajectory radiolocation information. It must be borne in mind that in conditions of tracking tight groups of air targets, with relatively small intervals and distances, it is not always possible to obtain trajectory information of the required quality. The main reason for this is the difficulty in determining the values of the correlation matrices of errors in estimating the parameters of the state vector of air targets. The task becomes more complicated as the number of intermediate processing points increases when it is brought to the final consumer. The main goal of the article is to increase the accuracy of estimates of trajectory measurements in a radiolocation system. The research is done by means of the mathematical tool of fuzz-set theory, namely, by optimizing fuzzy automatic classification. The article demonstrates that using fuzzy automatic classification under a priori parametrical uncertainty in the law of trajectory measurement errors, when determining weight coefficients, can improve the accuracy of estimates in these conditions up to 30 % compared with methods based on the application of the probabilistic approach. The results obtained allow us to justify the prospects of using optimization methods of fuzzy automatic classification in the tasks of processing trajectory information. In addition, the advantage of the proposed method is its low computational complexity and ease of implementation, which is especially important while maintaining a large number of airborne objects.

2021 ◽  
Vol 13 (4) ◽  
pp. 707
Author(s):  
Yu’e Shao ◽  
Hui Ma ◽  
Shenghua Zhou ◽  
Xue Wang ◽  
Michail Antoniou ◽  
...  

To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively proposes two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algorithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To evaluate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.


2016 ◽  
Vol 33 (3) ◽  
Author(s):  
Danian Steinkirch de Oliveira ◽  
Milton José Porsani ◽  
Paulo Eduardo Miranda Cunha

ABSTRACT. We developed a strategy for automatic Semblance panels pick, that uses Genetic Algorithm optimization method. In conjunction with restrictions and penalties set from a priori information... RESUMO. Foi desenvolvida uma estratégia de pick automático dos painéis de Semblance , que usa método de otimização Algorítmo Genético. Em conjunto com restrições...


Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 609
Author(s):  
Roman Meshcheryakov ◽  
Andrey Iskhakov ◽  
Mark Mamchenko ◽  
Maria Romanova ◽  
Saygid Uvaysov ◽  
...  

The paper proposes an approach to assessing the allowed signal-to-noise ratio (SNR) for light detection and ranging (LiDAR) of unmanned autonomous vehicles based on the predetermined probability of false alarms under various intentional and unintentional influencing factors. The focus of this study is on the relevant issue of the safe use of LiDAR data and measurement systems within the “smart city” infrastructure. The research team analyzed and systematized various external impacts on the LiDAR systems, as well as the state-of-the-art approaches to improving their security and resilience. It has been established that the current works on the analysis of external influences on the LiDARs and methods for their mitigation focus mainly on physical (hardware) approaches (proposing most often other types of modulation and optical signal frequencies), and less often software approaches, through the use of additional anomaly detection techniques and data integrity verification systems, as well as improving the efficiency of data filtering in the cloud point. In addition, the sources analyzed in this paper do not offer methodological support for the design of the LiDAR in the very early stages of their creation, taking into account a priori assessment of the allowed SNR threshold and probability of detecting a reflected pulse and the requirements to minimize the probability of “missing” an object when scanning with no a priori assessments of the detection probability characteristics of the LiDAR. The authors propose a synthetic approach as a mathematical tool for designing a resilient LiDAR system. The approach is based on the physics of infrared radiation, the Bayesian theory, and the Neyman–Pearson criterion. It features the use of a predetermined threshold for false alarms, the probability of interference in the analytics, and the characteristics of the LiDAR’s receivers. The result is the analytical solution to the problem of calculating the allowed SNR while stabilizing the level of “false alarms” in terms of background noise caused by a given type of interference. The work presents modelling results for the “false alarm” probability values depending on the selected optimality criterion. The efficiency of the proposed approach has been proven by the simulation results of the received optical power of the LiDAR’s signal based on the calculated SNR threshold and noise values.


2021 ◽  
Vol 10 (6) ◽  
pp. 420
Author(s):  
Jun Wang ◽  
Lili Jiang ◽  
Qingwen Qi ◽  
Yongji Wang

Image segmentation is of significance because it can provide objects that are the minimum analysis units for geographic object-based image analysis (GEOBIA). Most segmentation methods usually set parameters to identify geo-objects, and different parameter settings lead to different segmentation results; thus, parameter optimization is critical to obtain satisfactory segmentation results. Currently, many parameter optimization methods have been developed and successfully applied to the identification of single geo-objects. However, few studies have focused on the recognition of the union of different types of geo-objects (semantic geo-objects), such as a park. The recognition of semantic geo-objects is likely more crucial than that of single geo-objects because the former type of recognition is more correlated with the human perception. This paper proposes an approach to recognize semantic geo-objects. The key concept is that a single geo-object is the smallest component unit of a semantic geo-object, and semantic geo-objects are recognized by iteratively merging single geo-objects. Thus, the optimal scale of the semantic geo-objects is determined by iteratively recognizing the optimal scales of single geo-objects and using them as the initiation point of the reset scale parameter optimization interval. In this paper, we adopt the multiresolution segmentation (MRS) method to segment Gaofen-1 images and tested three scale parameter optimization methods to validate the proposed approach. The results show that the proposed approach can determine the scale parameters, which can produce semantic geo-objects.


2013 ◽  
Vol 726-731 ◽  
pp. 3811-3817
Author(s):  
Yuan Feng ◽  
Ji Xian Wang

The analysis of the slope stability is important in soil conservation. To analyze the slope stability, optimization methods were coded and compared with the traditional experience-based methods. Furthermore, the results were visualized in the program, so that the user can easily check the results and can designate an area, in which the program seeks the center and radius of the most hazardous slide arc. Moreover, the graphic interaction function was implemented in the program. In addition, the Standard Model One, recommended by ACAD (The Association for Computer Aided Design), was calculated by the program, of which the results (safety factor Ks=0.95~0.96) were smaller than the official recommend value (Ks=1). It is because that the traditional slice method, which neglects the normal stress and shear stress between the slices, was applied for calculation of Ks.


2021 ◽  
Author(s):  
Spyros A. Kinnas ◽  
Kyungjung Cha ◽  
Seungnam Kim

A comprehensive method which determines the most efficient propeller blade shapes for a given axisymmetric hull to travel at a desired speed, is presented. A nonlinear optimization method is used to design the blade, the shape of which is defined by a 3-D B-spline polygon, with the coordinates of the B-spline control points being the parameters to be optimized for maximum propeller efficiency, for given effective wake and propeller thrust. The performance of the propeller within the optimization scheme is assessed by a vortex-lattice method (VLM). To account fully for the hull/propeller interaction, the effective wake to the propeller and the hull resistance are determined by analyzing the designed propeller geometry by the VLM, coupled with a Reynolds-Averaged Navier-Stokes (RANS) solver. The optimization method re-designs the optimum blade with the updated effective wake and propeller thrust (taken to be equal to the updated hull resistance), and the procedure continues until convergence of the propeller performance. The current approach does not require knowledge of the wake fraction or the thrust deduction factor, both of which must be estimated a priori in traditional propeller design. The method is applied for a given hull to travel at a desired speed, and the optimum blades are designed for various combinations of propeller diameter and RPM, in the case of open and ducted propellers with provided duct shapes. The effects of the propeller diameter and RPM on the designed propeller thrust, torque, propeller efficiency, and required power are presented and compared with each other in the case of open and ducted propellers. The present approach is shown to provide guidance on the design of propulsors for underwater vehicles, and is applicable to the design of propulsors for surface ships.


Author(s):  
Kazufumi Ito ◽  
Karl Kunisch

Abstract In this paper we discuss applications of the numerical optimization methods for nonsmooth optimization, developed in [IK1] for the variational formulation of image restoration problems involving bounded variation type energy criterion. The Uzawa’s algorithm, first order augmented Lagrangian methods and Newton-like update using the active set strategy are described.


2021 ◽  
Author(s):  
Sebastian F. Riebl ◽  
Christian Wakelam ◽  
Reinhard Niehuis

Abstract Turbine Vane Frames (TVF) are a way to realize more compact jet engine designs. Located between the high pressure turbine (HPT) and the low pressure turbine (LPT), they fulfill structural and aerodynamic tasks. When used as an integrated concept with splitters located between the structural load-bearing vanes, the TVF configuration contains more than one type of airfoil with sometimes pronouncedly different properties. This system of multidisciplinary demands and mixed blading poses an interesting opportunity for optimization. Within the scope of the present work, a full geometric parameterization of a TVF with splitters is presented. The parameterization is chosen as to minimize the number of parameters required to automatically and flexibly represent all blade types involved in a TVF row in all three dimensions. Typical blade design parameters are linked to the fourth order Bézier-curve controlled camber line-thickness parameterization. Based on conventional design rules, a procedure is presented, which sets the parameters within their permissible ranges according to the imposed constraints, using a proprietary developed code. The presented workflow relies on subsequent three dimensional geometry generation by transfer of the proposed parameter set to a commercially available CAD package. The interdependencies of parameters are discussed and their respective significance for the adjustment process is detailed. Furthermore, the capability of the chosen parameterization and adjustment process to rebuild an exemplary reference TVF geometry is demonstrated. The results are verified by comparing not only geometrical profile data, but also validated CFD simulation results between the rebuilt and original geometries. Measures taken to ensure the robustness of the method are highlighted and evaluated by exploring extremes in the permissible design space. Finally, the embedding of the proposed method within the framework of an automated, gradient free numerical optimization is discussed. Herein, implications of the proposed method on response surface modeling in combination with the optimization method are highlighted. The method promises to be an option for improvement of optimization efficiency in gradient free optimization of interdependent blade geometries, by a-priori excluding unsuitable blade combinations, yet keeping restrictions to the design space as limited as possible.


Author(s):  
Ozan G. Erol ◽  
Hakan Gurocak ◽  
Berk Gonenc

MR-brakes work by varying viscosity of a magnetorheological (MR) fluid inside the brake. This electronically controllable viscosity leads to variable friction torque generated by the actuator. A properly designed MR-brake can have a high torque-to-volume ratio which is quite desirable for an actuator. However, designing an MR-brake is a complex process as there are many parameters involved in the design which can affect the size and torque output significantly. The contribution of this study is a new design approach that combines the Taguchi design of experiments method with parameterized finite element analysis for optimization. Unlike the typical multivariate optimization methods, this approach can identify the dominant parameters of the design and allows the designer to only explore their interactions during the optimization process. This unique feature reduces the size of the search space and the time it takes to find an optimal solution. It normally takes about a week to design an MR-brake manually. Our interactive method allows the designer to finish the design in about two minutes. In this paper, we first present the details of the MR-brake design problem. This is followed by the details of our new approach. Next, we show how to design an MR-brake using this method. Prototype of a new brake was fabricated. Results of experiments with the prototype brake are very encouraging and are in close agreement with the theoretical performance predictions.


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