scholarly journals Genetic Algorithm based Optimization of Uniform Circular Array

2020 ◽  
Vol 10 (6) ◽  
pp. 6403-6409
Author(s):  
V. Kumar ◽  
S. K. Dhull
Keyword(s):  
Genetic Algorithm ◽  
Signal Classification ◽  
Circular Array ◽  
Signal Parameter ◽  
Multiple Signal Classification ◽  
First Order ◽  
Forward Prediction ◽  
Array Structure ◽  
Esprit Algorithm ◽  
Better Than

Signal estimation at the antenna is a major challenge of the antenna array structure because the received signals have different directions. Therefore, in this paper, a Genetic Algorithm (GA) is applied to the uniform circular array for the optimization of array structure in regard to its geometry. On the optimized array structure, four different algorithms (Estimation of Signal Parameter via Rotational Invariance Technique – ESPRIT, First Order Forward Prediction - FOFP, Beamscan, and Multiple Signal Classification - MUSIC) have been implemented in order to estimate the signal direction accurately with quick estimation time. The accuracy has been calculated with Root Mean Square Error (RMSE) indices. From the experimental analysis, it has been found that the performance of the ESPRIT algorithm is better than the others in terms of accuracy and estimation time.

A Developed ESPRIT Algorithm for DOA Estimation

Frequenz ◽  
2015 ◽  
Vol 69 (5-6) ◽  
Author(s):  
Youssef Fayad ◽  
Caiyun Wang ◽  
Qunsheng Cao ◽  
Alaa El-Din Sayed Hafez
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Performance Enhancement ◽  
Doa Estimation ◽  
Signal Parameter ◽  
Nonlinearity Effect ◽  
Esprit Algorithm ◽  
Cramer Rao Bound ◽  
Novel Algorithm ◽  
Better Than

AbstractA novel algorithm for estimating direction of arrival (DOAE) for target, which aspires to contribute to increase the estimation process accuracy and decrease the calculation costs, has been carried out. It has introduced time and space multiresolution in Estimation of Signal Parameter via Rotation Invariance Techniques (ESPRIT) method (TS-ESPRIT) to realize subspace approach that decreases errors caused by the model’s nonlinearity effect. The efficacy of the proposed algorithm is verified by using Monte Carlo simulation, the DOAE accuracy has evaluated by closed-form Cramér–Rao bound (CRB) which reveals that the proposed algorithm’s estimated results are better than those of the normal ESPRIT methods leading to the estimator performance enhancement.

scholarly journals Direction of Arrival Using Uniform Circular Array based on 2-D MUSIC Algorithm

2018 ◽  
Vol 12 (1) ◽  
pp. 30
Author(s):  
Mohammed Amine Ihedrane ◽  
Seddik Bri
Keyword(s):  
Dielectric Permittivity ◽  
Patch Antenna ◽  
Direction Of Arrival ◽  
Dielectric Substrate ◽  
Signal Classification ◽  
Circular Array ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Linear Arrays ◽  
Circular Arrays

<p>This study presents the conception, simulation, realisation and characterisation of a patch antenna for Wi-Fi. The antenna is designed at the frequency of 2.45 GHz; the dielectric substrate used is FR4_epoxy which has a dielectric permittivity of 4.4.this patch antenna is used to estimate the direction of arrival (DOA) using 2-D Multiple Signal Classification (2-D MUSIC) the case of the proposed  uniform circular arrays (UCA). The comparison between Uniform circular arrays and Uniform Linear arrays (ULA) demonstrate that the proposed structure give better angles resolutions compared to ULAs.</p>

scholarly journals Two-Dimensional Direction-of-Arrivals Estimation Based on One-Dimensional Search Using Rank Deficiency Principle

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Feng-Gang Yan ◽  
Zhi-Kun Chen ◽  
Ming-Jian Sun ◽  
Yi Shen ◽  
Ming Jin
Keyword(s):  
Computational Complexity ◽  
Signal Classification ◽  
Two Dimensional ◽  
Music Algorithm ◽  
Signal Parameter ◽  
Rank Deficiency ◽  
Multiple Signal Classification ◽  
One Dimensional ◽  
Pair Matching ◽  
Improved Accuracy

A novel efficient method for two-dimensional (2D) direction-of-arrivals (DOAs) estimation is proposed to reduce the computational complexity of conventional 2D multiple signal classification (2D-MUSIC) algorithm with uniform rectangular arrays (URAs). By introducing two electrical DOAs, the formula of 2D-MUSIC is transformed into a new one-dimensional (1D) quadratic optimal problem. This 1D quadratic optimal problem is further proved equivalent to finding the conditions of noise subspace rank deficiency (NSRD), which can be solved by an efficient 1D spectral search, leading to a novel NSRD-MUSIC estimator accordingly. Unlike 2D-MUSIC with exhaustive 2D search, the proposed technique requires only an efficient 1D one. Compared with the estimation of signal parameter via rotation invariance techniques (ESPRIT), NSRD-MUSIC has a significantly improved accuracy. Moreover, the new algorithm requires no pair matching. Numerical simulations are conducted to verify the efficiency of the new estimator.

2D-DOA Estimation for MIMO Radar on Monostatic L-Shaped Minimum-Redundancy Linear Arrays

2014 ◽  
Vol 926-930 ◽  
pp. 2871-2875
Author(s):  
Ying Li ◽  
Gong Zhang
Keyword(s):  
High Efficiency ◽  
Linear Array ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Radar System ◽  
Signal Classification ◽  
Multiple Signal Classification ◽  
Linear Arrays ◽  
2D Doa Estimation ◽  
Better Than

This paper discussed the problem of two dimensional (2D) direction of arrival (DOA) estimation for multi-input multi-output (MIMO) radar. The minimum-redundancy linear array (MLRA) is introduced into the transmitting array and receiving array, which enables the high efficiency of the radar system. By utilizing the algorithm of multiple signal classification (MUSIC), we illustrate that the proposed scheme performs better than the uniform linear arrays (ULA) configuration under the same conditions. Simulation results verify the effectiveness of our scheme.

scholarly journals A Building-Block-Based Genetic Algorithm for Solving the Robots Allocation Problem in a Robotic Mobile Fulfilment System

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Jingtian Zhang ◽  
Fuxing Yang ◽  
Xun Weng
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Scheduling ◽  
Building Blocks ◽  
Allocation Problem ◽  
Accurate Analysis ◽  
Allocation Problems ◽  
Scheduling Method ◽  
Project Scheduling Problem ◽  
Block Based ◽  
Better Than

Robotic mobile fulfilment system (RMFS) is an efficient and flexible order picking system where robots ship the movable shelves with items to the picking stations. This innovative parts-to-picker system, known as Kiva system, is especially suited for e-commerce fulfilment centres and has been widely used in practice. However, there are lots of resource allocation problems in RMFS. The robots allocation problem of deciding which robot will be allocated to a delivery task has a significant impact on the productivity of the whole system. We model this problem as a resource-constrained project scheduling problem with transfer times (RCPSPTT) based on the accurate analysis of driving and delivering behaviour of robots. A dedicated serial schedule generation scheme and a genetic algorithm using building-blocks-based crossover (BBX) operator are proposed to solve this problem. The designed algorithm can be combined into a dynamic scheduling structure or used as the basis of calculation for other allocation problems. Experiment instances are generated based on the characteristics of RMFS, and the computation results show that the proposed algorithm outperforms the traditional rule-based scheduling method. The BBX operator is rapid and efficient which performs better than several classic and competitive crossover operators.

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