M. S. E. Abadi Articles List

List of Articles M. S. E. Abadi

Open Access Article
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1 - Multipath Error Mitigation of Low-Cost GPS Receiver Using PSO-SVM and GA-SVM Hybrid Methods
Mohammad S. E. Abadi M. H. Refan A. Dameshghi
20.1001.1.16823745.1397.16.2.9.7

One of the major errors that affect GPS accurately is the multi-path effect of each receiver. Multi-paths is receiving an antenna signal from more than one path, multi-path effect is a major source of unknown error in positioning and is not eliminated by differential me More

One of the major errors that affect GPS accurately is the multi-path effect of each receiver. Multi-paths is receiving an antenna signal from more than one path, multi-path effect is a major source of unknown error in positioning and is not eliminated by differential methods. This effect is largely dependent on the environment specific to each receiver and it is low-frequency effect. The geometry between GPS satellites and the specific location of each receiver is repeated on astronomical days, the multi-path effects tend to behave similarly on consecutive days. In this paper, a method for extracting the multi-path effects behavior was applied to the GPS-code observations, multi-path error mitigation increases the accuracy of positioning. In the proposed method, the residual signal is generated based on the dual difference (DD) and is used as the input of the proposed algorithm. Support Vector Machine (SVM) is used for multi-path approximation. To determine the basic parameters of SVM and its kernel function, particle optimization algorithms (PSO) and genetic algorithm (GA) were used. In order to evaluate the accuracy of the proposed method, simulation and experimental based on two stations (reference and user) and two low-cost receivers were designed. The proposed methods were tested based on practical data. The experiments showed that the multi-path error of the receiver of the user's station decreased by 70% in the static test based on the RMS criterion. Models of this paper have been compared with some recent models presented in the context of multi-path error reduction. The results showed that the proposed model had better performance than other methods. The result is high accuracy and stability in positioning results. Three-dimensional position accuracy improved by about 56% after using the proposed method, reaching 1.60 m. Manuscript profile
Open Access Article
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2 - Performance Analysis of Subband Adaptive Algorithms over Distributed Networks Based on Incremental Strategy
Mohammad S. E. Abadi A. R. Danaee M. S. Shafiee
20.1001.1.16823745.1397.16.3.2.2

This paper presents the problem of distributed estimation in an incremental network based on the family of normalized subband adaptive algorithms (NSAAs). The distributed NSAA (dNSAA), the distributed selective partial update NSAA (dSPU-NSAA), the distributed dynamic se More

This paper presents the problem of distributed estimation in an incremental network based on the family of normalized subband adaptive algorithms (NSAAs). The distributed NSAA (dNSAA), the distributed selective partial update NSAA (dSPU-NSAA), the distributed dynamic selection NSAA (dDS-NSAA), and the dSPU-DS-NSAA are introduced in a unified way. The dNSAAs have better convergence speed than distributed normalized least mean square (dNLMS) algorithm especially for colored Gaussian input of the nodes. In comparison with dNSAA, the dSPU-NSAA, and dDS-NSAA have lower computational complexity and close performance to dNSAA. Also by combination of these algorithms, the dSPU-DS-NSAA is established which is computationally efficient. In addition, a unified approach for mean-square performance analysis of each individual node is presented. This approach can be used to establish a performance analysis of classical distributed adaptive algorithms as well. The theoretical expressions for transient, and steady-state performance analysis of the various dNSAAs are introduced. The validity of the theoretical results, and the good performance of these algorithms are demonstrated by several computer simulations. Manuscript profile
Open Access Article
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3 - Family of Variable Step-Size Affine Projection Adaptive Algorithms in Diffusion Distributed Networks
Mohammad S. E. Abadi E. Heydari
20.1001.1.16823745.1398.17.3.12.9

Distributed processing uses local computations at each node and communications among neighboring nodes to solve the problems over the entire network. Diffusion is one of the methods for performing distributed networks. This paper presents a novel Variable Step-Size Diff More

Distributed processing uses local computations at each node and communications among neighboring nodes to solve the problems over the entire network. Diffusion is one of the methods for performing distributed networks. This paper presents a novel Variable Step-Size Diffusion Affine Projection Algorithm (VSS-DAPA) to improve the performance of the Diffusion Affine Projection Algorithm (DAPA) in distributed networks. The variable step-size of each node is obtained by minimizing the Mean-Square Deviation (MSD) in that node. In comparison with Diffusion Affine Projection Algorithm (DAPA), the VSS-DAPA algorithm has faster convergence speed and lower steady-state error. To reduce the computational complexity of VSS-DAPA, the Variable Step-Size Selective Regressors Diffusion Affine Projection Algorithm (VSS-SR-DAPA), the Variable Step-Size Dynamic Selection of Diffusion Affine Projection Algorithm (VSS-DS-DAPA) and Variable Step-Size Selective Partial Update Diffusion Affine Projection Algorithm (VSS-SPU-DAPA) are proposed. Simulation results show the good performance of proposed algorithms in convergence speed and steady-state error. Manuscript profile

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List of Articles M. S. E. Abadi