scholarly journals Performance evaluation of direction-finding techniques of an acoustic source with uniform linear array

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Farid Uddin ◽  
Ayan Alam Khan ◽  
Mohd Wajid ◽  
Mahima Singh ◽  
Faisal Alam

PurposeThe purpose of this paper is to show a comparative study of different direction-of-arrival (DOA) estimation techniques, namely, multiple signal classification (MUSIC) algorithm, delay-and-sum (DAS) beamforming, support vector regression (SVR), multivariate linear regression (MLR) and multivariate curvilinear regression (MCR).Design/methodology/approachThe relative delay between the microphone signals is the key attribute for the implementation of any of these techniques. The machine-learning models SVR, MLR and MCR have been trained using correlation coefficient as the feature set. However, MUSIC uses noise subspace of the covariance-matrix of the signals recorded with the microphone, whereas DAS uses the constructive and destructive interference of the microphone signals.FindingsVariations in root mean square angular error (RMSAE) values are plotted using different DOA estimation techniques at different signal-to-noise-ratio (SNR) values as 10, 14, 18, 22 and 26dB. The RMSAE curve for DAS seems to be smooth as compared to PR1, PR2 and RR but it shows a relatively higher RMSAE at higher SNR. As compared to (DAS, PR1, PR2 and RR), SVR has the lowest RMSAE such that the graph is more suppressed towards the bottom.Originality/valueDAS has a smooth curve but has higher RMSAE at higher SNR values. All the techniques show a higher RMSAE at the end-fire, i.e. angles near 90°, but comparatively, MUSIC has the lowest RMSAE near the end-fire, supporting the claim that MUSIC outperforms all other algorithms considered.

2018 ◽  
Vol 7 (4.36) ◽  
pp. 398
Author(s):  
S. Venkata Rama Rao ◽  
A. Mallikarjuna Prasad ◽  
Ch. Santhi Rani

In this paper, Root-MUSIC algorithm for direction of arrival (DOA) estimation of uncorrelated signals is explored both for uniform linear and uniform circular arrays. The basic problem in Uniform Linear Arrays (ULAs) is Mutual coupling between the individual elements of the antenna array. This problem is reduced in Uniform Circular Arrays (UCAs) because of its symmetric structure. The DOA estimation of uncorrelated signals that have different power levels is simulated on a MATLAB environment. And the noise consider is white across all the array elements. The factors considered for simulation are number of number of snapshots, array elements, radius of circular array, array length, and signal to noise ratio. 


2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Yuguan Hou ◽  
Qingguo Jin ◽  
Shaochuan Wu ◽  
Zhuoming Li

Due to the fluctuation of the signal-to-noise ratio (SNR) and the single snapshot case in the MIMO HF sky-wave radar system, the accuracy of the online estimation of the mutual coupling coefficients matrix of the uniform rectangle array (URA) might be degraded by the classical approach, especially in the case of low SNR. In this paper, an Online Particle Mean-Shift Approach (OPMA) is proposed, which is to get a relatively more effective estimation of the mutual coupling coefficients matrix with the low SNR. Firstly, the spatial smoothing technique combined with the MUSIC algorithm of URA is introduced for the DOA estimation of the multiple targets in the case of single snapshot which are taken as coherent sources. Then, based on the idea of the particle filter, the online particles with a moderate computational complexity are used to generate some different estimation results. Finally, the mean-shift algorithm is applied to get a more robust estimate of the equivalent mutual coupling coefficients matrix. The simulation results demonstrate the validity of the proposed approach in terms of the success probability, the statistics of bias, and the variance. The proposed approach is more robust and more accurate than the other two approaches.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Lin Li ◽  
Fangfang Chen ◽  
Jisheng Dai

A novel MUSIC-type algorithm is derived in this paper for the direction of departure (DOD) and direction of arrival (DOA) estimation in a bistatic MIMO radar. Through rearranging the received signal matrix, we illustrate that the DOD and the DOA can be separately estimated. Compared with conventional MUSIC-type algorithms, the proposed separate MUSIC algorithm can avoid the interference between DOD and DOA estimations effectively. Therefore, it is expected to give a better angle estimation performance and have a much lower computational complexity. Meanwhile, we demonstrate that our method is also effective for coherent targets in MIMO radar. Simulation results verify the efficiency of the proposed method, particularly when the signal-to-noise ratio (SNR) is low and/or the number of snapshots is small.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yusniliyana Yusof ◽  
Kaliappa Kalirajan

PurposeThe study contributes to the aim of regional development policy in reducing regional disparities, by examining the spatial balance in socioeconomic development across the states of Malaysia based on composite development index (CDI). Besides, the study has attempted to understand the issues in the development gaps across Malaysian states by evaluating the factors that explain the variation in economic growthDesign/methodology/approachThis study uses three-stage least squares (3SLS) and bootstrap sampling and estimation techniques to examine the factors that explain the variations in the growth of development across the states in Malaysia. The analysis involves 13 states in Malaysia (Johor, Melaka, Negeri Sembilan, Pulau Pinang, Perak, Perlis, Selangor, Kedah, Kelantan, Pahang, Terengganu, Sabah and Sarawak) from 2005 to 2015.FindingsThe pattern in the spatial socioeconomic imbalance demonstrates a decreasing trend. However, the development index reveals that the performance of less developed states remained behind that of the developed states. The significant factors in explaining the variation in growth across the Malaysian states are relating to agriculture, manufacturing, human capital, population growth, Chinese ethnicity, institutional factors and natural resources.Research limitations/implicationsThe authors focused on Malaysian states over the period between 2005 and 2015. The authors encountered some limitations in obtaining relevant data such as international factors and technological change that might also explain the variation in economic growth as the data on these variables are not reported at the state level. Moreover, the data on GSDP by sector was only available from the year 2005. Second, the study is based on secondary data. Future studies might examine the factors that contribute to the development gap across Malaysian states through interviews or questionnaires and compare the findings with the existing results. Despite its limitations, this study contributes to the existing literature that emphasizes on spatial balance of socioeconomic in a developing country, focusing on Malaysian states.Practical implicationsThese findings provide guidance for policymakers by understanding key potential areas to reduce the disparity in economic growth across Malaysian states by understanding their impact on the growth.Originality/valueThis study employs different method of 3SLS and bootstrap sampling and estimation techniques in examining the factors that explain the variations in the growth of development across the states in Malaysia.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
M. A. B. Abbasi ◽  
V. F. Fusco ◽  
O. Yurduseven ◽  
T. Fromenteze

AbstractThis paper presents a physical frequency-diverse multimode lens-loaded cavity, designed and used for the purpose of the direction of arrival (DoA) estimation in millimetre-wave frequency bands for 5G and beyond. The multi-mode mechanism is realized using an electrically-large cavity, generating spatio-temporally incoherent radiation masks leveraging the frequency-diversity principle. It has been shown for the first time that by placing a spherical constant dielectric lens (constant-ϵr) in front of the radiating aperture of the cavity, the spatial incoherence of the radiation modes can be enhanced. The lens-loaded cavity requires only a single lens and output port, making the hardware development much simpler and cost-effective compared to conventional DoA estimators where multiple antennas and receivers are classically required. Using the lens-loaded architecture, an increase of up to 6 dB is achieved in the peak gain of the synthesized quasi-random sampling bases from the frequency-diverse cavity. Despite the fact that the practical frequency-diverse cavity uses a limited subset of quasi-orthogonal modes below the upper bound limit of the number of theoretical modes, it is shown that the proposed lens-loaded cavity is capable of accurate DoA estimation. This is achieved thanks to the sufficient orthogonality of the leveraged modes and to the presence of the spherical constant-ϵr lens which increases the signal-to-noise ratio (SNR) of the received signal. Experimental results are shown to verify the proposed approach.


Author(s):  
Xueli Wang ◽  
Yufeng Zhang ◽  
Hongxin Zhang ◽  
Xiaofeng Wei ◽  
Guangyuan Wang

Abstract For wireless transmission, radio-frequency device anti-cloning has become a major security issue. Radio-frequency distinct native attribute (RF-DNA) fingerprint is a developing technology to find the difference among RF devices and identify them. Comparing with previous research, (1) this paper proposed that mean (μ) feature should be added into RF-DNA fingerprint. Thus, totally four statistics (mean, standard deviation, skewness, and kurtosis) were calculated on instantaneous amplitude, phase, and frequency generated by Hilbert transform. (2) We first proposed using the logistic regression (LR) and support vector machine (SVM) to recognize such extracted fingerprint at different signal-to-noise ratio (SNR) environment. We compared their performance with traditional multiple discriminant analysis (MDA). (3) In addition, this paper also proposed to extract three sub-features (amplitude, phase, and frequency) separately to recognize extracted fingerprint under MDA. In order to make our results more universal, additive white Gaussian noise was adopted to simulate the real environment. The results show that (1) mean feature conducts an improvement in the classification accuracy, especially in low SNR environment. (2) MDA and SVM could successfully identify these RF devices, and the classification accuracy could reach 94%. Although the classification accuracy of LR is 89.2%, it could get the probability of each class. After adding a different noise, the recognition accuracy is more than 80% when SNR≥5 dB using MDA or SVM. (3) Frequency feature has more discriminant information. Phase and amplitude play an auxiliary but also pivotal role in classification recognition.


Sensor Review ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 304-311 ◽  
Author(s):  
Pengfei Jia ◽  
Fengchun Tian ◽  
Shu Fan ◽  
Qinghua He ◽  
Jingwei Feng ◽  
...  

Purpose – The purpose of the paper is to propose a new optimization algorithm to realize a synchronous optimization of sensor array and classifier, to improve the performance of E-nose in the detection of wound infection. When an electronic nose (E-nose) is used to detect the wound infection, sensor array’s optimization and parameters’ setting of classifier have a strong impact on the classification accuracy. Design/methodology/approach – An enhanced quantum-behaved particle swarm optimization based on genetic algorithm, genetic quantum-behaved particle swarm optimization (G-QPSO), is proposed to realize a synchronous optimization of sensor array and classifier. The importance-factor (I-F) method is used to weight the sensors of E-nose by its degree of importance in classification. Both radical basis function network and support vector machine are used for classification. Findings – The classification accuracy of E-nose is the highest when the weighting coefficients of the I-F method and classifier’s parameters are optimized by G-QPSO. All results make it clear that the proposed method is an ideal optimization method of E-nose in the detection of wound infection. Research limitations/implications – To make the proposed optimization method more effective, the key point of further research is to enhance the classifier of E-nose. Practical implications – In this paper, E-nose is used to distinguish the class of wound infection; meanwhile, G-QPSO is used to realize a synchronous optimization of sensor array and classifier of E-nose. These are all important for E-nose to realize its clinical application in wound monitoring. Originality/value – The innovative concept improves the performance of E-nose in wound monitoring and paves the way for the clinical detection of E-nose.


2014 ◽  
Vol 610 ◽  
pp. 339-344
Author(s):  
Qiang Guo ◽  
Yun Fei An

A UCA-Root-MUSIC algorithm for direction-of-arrival (DOA) estimation is proposed in this paper which is based on UCA-RB-MUSIC [1]. The method utilizes not only a unitary transformation matrix different from UCA-RB-MUSIC but also the multi-stage Wiener filter (MSWF) to estimate the signal subspace and the number of sources, so that the new method has lower computational complexity and is more conducive to the real-time implementation. The computer simulation results demonstrate the improvement with the proposed method.


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