scholarly journals DOA Estimation in Low SNR Environment through Coprime Antenna Arrays: An Innovative Approach by Applying Flower Pollination Algorithm

2021 ◽  
Vol 11 (17) ◽  
pp. 7985
Author(s):  
Khurram Hameed ◽  
Shanshan Tu ◽  
Nauman Ahmed ◽  
Wasim Khan ◽  
Ammar Armghan ◽  
...  
Keyword(s):  
Antenna Arrays ◽  
Signal To Noise Ratio ◽  
Sensor Arrays ◽  
Doa Estimation ◽  
Cumulative Distribution ◽  
Estimation Accuracy ◽  
Noise Robustness ◽  
Flower Pollination Algorithm ◽  
Flower Pollination ◽  
Highly Nonlinear

The design of the modern computing paradigm of heuristics is an innovative development for parameter estimation of direction of arrival (DOA) using sparse antenna arrays. In this study, the optimization strength of the flower pollination algorithm (FPA) is exploited for the DOA estimation in a low signal to noise ratio (SNR) regime by applying coprime sensor arrays (CSA). The enhanced degree of freedom (DOF) is achieved with FPA by investigating the global minima of highly nonlinear cost function with multiple local minimas. The sparse structure of CSA demonstrates that the DOF up to O(MN) is achieved by employing M+N CSA elements, where M and N are the numbers of antenna elements used to construct the CSA . Performance analysis is conducted for estimation accuracy, robustness against noise, robustness against snapshots, frequency distribution of root mean square error (RMSE), variability analysis of RMSE, cumulative distribution function (CDF) of RMSE over Monte Carlo runs and the comparative studies of particle swarm optimization (PSO). These reveal the worth of the proposed methodology for estimating DOA.

scholarly journals High-Resolution Direction-of-Arrival Estimation via Concentric Circular Arrays

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Serdar Ozgur Ata ◽  
Cevdet Isik
Keyword(s):  
Antenna Arrays ◽  
Linear Array ◽  
Signal To Noise Ratio ◽  
Sensor Arrays ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Circular Array ◽  
Multiple Signal Classification ◽  
Circular Arrays ◽  
Source Signals

Estimating the direction of arrival (DOA) of source signals is an important research interest in application areas including radar, sonar, and wireless communications. In this paper, the problem of DOA estimation is addressed on concentric circular antenna arrays (CCA) in detail as an alternative to the well-known geometries of the uniform linear array (ULA) and uniform circular array (UCA). We define the steering matrix of the CCA geometry and investigate the performance analysis of the array in the DOA-estimation problem by simulations that are realized through varying the parameters of signal-to-noise ratio, number of sensors, and resolution angle of sensor arrays by using the MUSIC (Multiple Signal Classification) algorithm. The results present that CCA geometries provide higher angle resolutions compared to UCA geometries and require less physical area for the same number of sensor elements. However, as a cost-increasing effect, higher computational power is needed to estimate the DOA of source signals in CCAs compared to ULAs.

scholarly journals DOA Estimation Method in Multipath Environment for Passive Bistatic Radar

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Panhe Hu ◽  
Qinglong Bao ◽  
Zengping Chen
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Bistatic Radar ◽  
Spatial Difference ◽  
Coherent Signals ◽  
Vhf Radar ◽  
Multipath Environment ◽  
Passive Bistatic Radar

Direction-of-arrival (DOA) estimation in multipath environment is an important issue for passive bistatic radar (PBR) using frequency agile phased array VHF radar as illuminator of opportunity. Under such scenario, the main focus of this paper is to cope with the closely spaced uncorrelated and coherent signals in low signal-to-noise ratio and limited snapshots. Making full use of the characteristics of moduli of eigenvalues, the DOAs of the uncorrelated signals are firstly estimated. Afterwards, their contributions are eliminated by means of spatial difference technique. Finally, in order to improve resolution and accuracy DOA estimation of remaining coherent signals while avoiding the cross-terms effect, a new beamforming solution based iterative adaptive approach (IAA) is proposed to deal with a reconstructed covariance matrix. The proposed method combines the advantages of both spatial difference method and the IAA algorithm while avoiding their shortcomings. Simulation results validate its effectiveness; meanwhile, the good performances of the proposed method in terms of resolution probability, detection probability, and estimation accuracy are demonstrated by comparison with the existing methods.

Flower Pollination Algorithm for Software Effort Coefficients Optimization to Improve Effort Estimation Accuracy

2021 ◽  
Vol 9 (2) ◽  
pp. 139
Author(s):  
Alifia Puspaningrum ◽  
Fachrul Pralienka Bani Muhammad ◽  
Esti Mulyani
Keyword(s):  
Search Algorithm ◽  
Cost Model ◽  
Cuckoo Search ◽  
Estimation Accuracy ◽  
Flower Pollination Algorithm ◽  
Metaheuristic Algorithm ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Flower Pollination ◽  
Cocomo Ii

Software effort estimation is one of important area in project management which used to predict effort for each person to develop an application. Besides, Constructive Cost Model (COCOMO) II is a common model used to estimate effort estimation. There are two coefficients in estimating effort of COCOMO II which highly affect the estimation accuracy. Several methods have been conducted to estimate those coefficients which can predict a closer value between actual effort and predicted value.  In this paper, a new metaheuristic algorithm which is known as Flower Pollination Algorithm (FPA) is proposed in several scenario of iteration. Besides, FPA is also compared to several metaheuristic algorithm, namely Cuckoo Search Algorithm and Particle Swarm Optimization. After evaluated by using Mean Magnitude of Relative Error (MMRE), experimental results show that FPA obtains the best result in estimating effort compared to other algorithms by reached 52.48% of MMRE in 500 iterations.

scholarly journals Pattern Synthesis of Linear Antenna Arrays Using Enhanced Flower Pollination Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Urvinder Singh ◽  
Rohit Salgotra
Keyword(s):  
Antenna Arrays ◽  
Flower Pollination Algorithm ◽  
Benchmark Problems ◽  
Linear Antenna ◽  
Exploration And Exploitation ◽  
Pattern Synthesis ◽  
Flower Pollination ◽  
New Variant ◽  
Cauchy Mutation ◽  
Linear Antenna Arrays

In this paper, a new variant of flower pollination algorithm (FPA), namely, enhanced flower pollination algorithm (EFPA), has been proposed for the pattern synthesis of nonuniform linear antenna arrays (LAA). The proposed algorithm uses the concept of Cauchy mutation in global pollination and enhanced local search to improve the exploration and exploitation tendencies of FPA. It also uses dynamic switching to control the rate of exploration and exploitation. The algorithm is tested on standard benchmark problems and has been compared statistically with state of the art to prove its worthiness. LAA design is a tricky and difficult electromagnetic problem. Hence to check the efficacy of the proposed algorithm it has been used for synthesis of four different LAA with different sizes. Experimental results show that EFPA algorithm provides enhanced performance in terms of side lobe suppression and null control compared to FPA and other popular algorithms.

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