Analysis of Estimation of Direction of Arrival by Comparative Study

Khedekar, Sachin; Mukhopadhyay, Mainak

doi:10.1016/j.matpr.2017.11.266

Cited by 4 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a study conducted by Khedekar and Mukhopadhyay [13], a three-dimensional approach was used to compare and analyze the three algorithms estimation of signal parameters via rotational invariance technique (ESPRIT), multiple signal classification (MUSIC), and mechanical alteration of direction of arrival (DOA). The results showed that the mechanical algorithm is better than other algorithms in terms of accuracy and durability.…”

Section: Literarure Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Comparative and analysis of evaluation of several direction of arrival estimation methods

2021

View full text Add to dashboard Cite

Modern-day, global, and clever array systems have several distinguished approaches with regard to a wireless device. In this paper, a comparative analysis has been carried out amongst nine direction of arrival (DOA) algorithms: Capon, multiple signal classification (MUSIC), Bartlett, Pisarenko, linear prediction, maximum entropies, and min-norm, root-MUSIC, and estimation of signal parameters via rotational invariance technique (ESPRIT). in this paper reduces the number of antennas and snaps necessary to observe six target swithout interference for several DOA estimation methods. After comparing and analyzing all the algorithms, it has been shown that the music algorithm is the best algorithm that reduces interference and detects the desired sources. MATLAB R2019b was used in the simulation process.

show abstract

Section: Literarure Reviewmentioning

confidence: 99%

“…This method was proposed in the seventies and aims to analyse and estimate arrival angel and signal strength interferes with white noise [13]. Pisarenko harmonic decomposition (PHD) pseudospectrum is given by (6).…”

Section: Pisarenko Harmonic Aoa Estimatementioning

confidence: 99%

Comparative and analysis of evaluation of several direction of arrival estimation methods

2021

View full text Add to dashboard Cite

show abstract

“…On the general topic of estimation in signal processing, Zoubir et al [23] presented a tutorial which includes valuable information on DoA estimation, but does not describe specific array geometries. There are also less related comparison studies by Kiani and Pezeshk [24], Khedekar and Mukhopadhyay [25], Ahmed et al [26], Adhikari and Drozdenko [27], and reviews in other areas related to DoA estimation [28,29].…”

Section: Introductionmentioning

confidence: 99%

A Review of Sparse Sensor Arrays for Two-Dimensional Direction-of-Arrival Estimation

et al. 2021

View full text Add to dashboard Cite

arrays are fundamental to localization applications. Specifically spares arrays can provide superior direction-of-arrival (DoA) estimation performance with limited number of sensors. There has been increased interest in the research community in designing 2D sparse arrays with performance improvement and complexity reduction. The research efforts are uncoordinated resulting in some repetitions and sometimes conflicting claims. After introducing 2D sparse arrays and their importance, this paper establishes the 2D-DoA estimation model and consolidates the performance metrics. An extensive literature overview of sparse arrays for 2D-DoA estimation is presented with an attempt to categorize existing works. The examined arrays include parallel arrays, L-shaped, V-shaped, hourglass, thermos, nested planer, and coprime planner, to name a few. Existing designs are compared in terms of required number of sensors, degrees of freedom (DOF), algorithm used, associated complexity and aperture size. The focus is on describing the sparse arrays, yet some specific details on DoA estimation algorithms are provided for selected array geometries. Fundamental problems of 2D-DoA estimation are outlined and existing solutions to alleviate these problems are discussed. This should be useful in predicting the estimation performance and required complexity; thus, aiding the decision of selecting a sensor geometry for DoA estimation. This review serves as a starting point for researchers interested in exploring or designing new 2D sparse arrays. It also helps to identify the gaps in the field and avoids unnecessary minor design modifications.

show abstract

Sparse Sensor Arrays for Two‐dimensional Direction‐of‐arrival Estimation

Muqaibel,

Alawsh

2023

Sparse Arrays for Radar, Sonar, and Communications

View full text Add to dashboard Cite

Analysis of Estimation of Direction of Arrival by Comparative Study

Cited by 4 publications

References 13 publications

Comparative and analysis of evaluation of several direction of arrival estimation methods

Comparative and analysis of evaluation of several direction of arrival estimation methods

A Review of Sparse Sensor Arrays for Two-Dimensional Direction-of-Arrival Estimation

Sparse Sensor Arrays for Two‐dimensional Direction‐of‐arrival Estimation

Contact Info

Product

Resources

About