The effectiveness of JADE based minimum variance distortionless response algorithm for DOA estimation and adaptive beamforming in multipath smart antenna application

2014 ◽  
Author(s):  
Ahmad Aminu ◽  
Mustafa Secmen ◽  
Munir Aminu Husein
Keyword(s):  
Smart Antenna ◽  
Doa Estimation ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Minimum Variance Distortionless Response

scholarly journals Evaluation of Minimum Variance Distortionless Response Beamforming Algorithm Based Circular Antenna Arrays

2016 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Suhail Najm Shahab ◽  
Ayib Rosdi Zainun ◽  
Balasim S. S. ◽  
Nurul Hazlina Noordin ◽  
Izzeldin Ibrahim Mohamed
Keyword(s):  
Antenna Arrays ◽  
Smart Antenna ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Antenna System ◽  
Noise Power ◽  
Noise Mitigation ◽  
Lte Networks ◽  
Continuous Growth ◽  
Minimum Variance Distortionless Response

Wireless data traffic is in a continuous growth, and there are increasing demands for wireless systems that provide deep interference suppression and noise mitigation. In this paper, adaptive beamforming (ABF) technique for Smart Antenna System (SAS) based on Minimum Variance Distortionless Response (MVDR) algorithm connected toCircular Antenna Array (CAA) is discussed and analyzed. The MVDR performance is evaluated by varying various parameters; namely the number of antenna elements, space separation between the elements, the number of interference sources, noise power label, and a number of snapshots. LTE networks allocate a spectrum band of 2.6 GHz is used for evaluating the MVDR performance. The MVDR performance is evaluated with two important metrics; beampattern and SINR. Simulation results demonstrate that as the antenna elements increase, the performance of the MVDR improves dramatically. This means the performance of MVDR greatly relies upon the number of the elements. Half of the wavelength is considered the best interelement spacing, the performance degraded as noise power increased, and more accurately resolution occurred when the number of snapshots increased. The proposed method was found to be performed better than some existing techniques. According to the result, the beampattern relies on the number of element and the separation between array elements. Also, the SINR strongly depends on noise power label and the number of snapshots.

PARALLEL ALGORITHMS FOR ADAPTIVE MATCHED-FIELD PROCESSING ON DISTRIBUTED ARRAY SYSTEMS

2004 ◽  
Vol 12 (02) ◽  
pp. 149-174 ◽  
Author(s):  
KILSEOK CHO ◽  
ALAN D. GEORGE ◽  
RAJ SUBRAMANIYAN ◽  
KEONWOOK KIM
Keyword(s):  
Parallel Algorithms ◽  
Real Time ◽  
Digital Signal Processor ◽  
High Performance ◽  
Digital Signal ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Matched Field Processing ◽  
Minimum Variance Distortionless Response ◽  
Distributed Array

Matched-field processing (MFP) localizes sources more accurately than plane-wave beamforming by employing full-wave acoustic propagation models for the cluttered ocean environment. The minimum variance distortionless response MFP (MVDR–MFP) algorithm incorporates the MVDR technique into the MFP algorithm to enhance beamforming performance. Such an adaptive MFP algorithm involves intensive computational and memory requirements due to its complex acoustic model and environmental adaptation. The real-time implementation of adaptive MFP algorithms for large surveillance areas presents a serious computational challenge where high-performance embedded computing and parallel processing may be required to meet real-time constraints. In this paper, three parallel algorithms based on domain decomposition techniques are presented for the MVDR–MFP algorithm on distributed array systems. The parallel performance factors in terms of execution times, communication times, parallel efficiencies, and memory capacities are examined on three potential distributed systems including two types of digital signal processor arrays and a cluster of personal computers. The performance results demonstrate that these parallel algorithms provide a feasible solution for real-time, scalable, and cost-effective adaptive beamforming on embedded, distributed array systems.

DISTRIBUTED PARALLEL PROCESSING TECHNIQUES FOR ADAPTIVE SONAR BEAMFORMING

2002 ◽  
Vol 10 (01) ◽  
pp. 1-23 ◽  
Author(s):  
ALAN D. GEORGE ◽  
JESUS GARCIA ◽  
KEONWOOK KIM ◽  
PRIYABRATA SINHA
Keyword(s):  
Parallel Processing ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Autonomous Operation ◽  
Minimum Variance Distortionless Response ◽  
Efficiency And Effectiveness ◽  
Execution Speed ◽  
Processing Techniques ◽  
Performance Results ◽  
Communication Demands

Quiet submarine threats and high clutter in the littoral environment increase computation and communication demands on beamforming arrays, particularly for applications that require in-array autonomous operation. By coupling each transducer node in a distributed array with a microprocessor, and networking them together, embedded parallel processing for adaptive beamformers can glean advantages in execution speed, fault tolerance, scalability, power, and cost. In this paper, a novel set of techniques for the parallelization of adaptive beamforming algorithms is introduced for in-array sonar signal processing. A narrowband, unconstrained, Minimum Variance Distortionless Response (MVDR) beamformer is used as a baseline to investigate the efficiency and effectiveness of this method in an experimental fashion. Performance results are also included, among them execution times, parallel efficiencies, and memory requirements, using a distributed system testbed comprised of a cluster of workstations connected by a conventional network.

scholarly journals An Efficient DOA Estimation Algorithm Based on Diagonal-Symmetric Loading

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yangyang Xie ◽  
Biao Wang ◽  
Feng Chen
Keyword(s):  
Super Resolution ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Minimum Variance ◽  
Spatial Spectrum ◽  
Estimation Accuracy ◽  
Minimum Variance Distortionless Response ◽  
Symmetric Loading ◽  
Subspace Processing ◽  
Source Number

In order to solve the problem that the subspace-like direction of arrival (DOA) estimation performs poor due to the error of sources number, this paper proposes a new super-resolution DOA estimation algorithm based on the diagonal-symmetric loading (DSL). Specifically, orthogonality principle of the minimum eigenvector of the specific covariance matrix and the source number estimation based on the improved K-means method were adopted to construct the spatial spectrum. Then, by considering the signal-to-interference-to-noise ratio (SINR), the theoretical basis for selecting parameters was given and verified by numerical experiment. To evaluate the effectiveness of the proposed algorithm, this paper compared it with the methods of minimum variance distortionless response (MVDR) and new signal subspace processing (NSSP). Experimental results prove that the proposed DSL has higher resolution and better estimation accuracy than the MVDR and NSSP.

scholarly journals Improved Linearly Constrained Minimum Variance Algorithm for 5G Communications System

2021 ◽  
Author(s):  
Kaviya K R ◽  
Deepa S
Keyword(s):  
Comparative Analysis ◽  
Smart Antenna ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Key Technology ◽  
The Core ◽  
Linearly Constrained ◽  
Communications System ◽  
Beam Patterns ◽  
Minimum Interference

Beamforming is a process formulated to produce the radiated beam patterns of the antennas by completely building up the processed signals in the direction of the desired terminals and cancelling beams of interfering signals. Adaptive beamforming is a key technology of smart antenna. The core is to obtain optimum weights of the antenna array by some adaptive beamforming algorithms and finally adjust the main lobe to focus on the arriving direction of the desired signal as well as suppressing the interfering signal. There are several beamforming algorithms that includes Linearly Constrained Minimum Variance (LCMV) algorithm in which Self Nulling Issue is further reduced by adding multiplier to the MCMV algorithm and it is referred as Improved LCMV (IMPLCMV). A Comparative analysis is done for different multipliers and it is found that w=0.15 gives best result with minimum interference of flat response and also self-nulling issues can be reduced.

Robust Algorithms for DOA Estimation and Adaptive Beamforming in Wireless Mobile Communications

2009 ◽  
pp. 558-564
Author(s):  
R.M. Shubair ◽  
K.O. AlMidfa ◽  
A. Al-Marri ◽  
M. Al-Nuaimi
Keyword(s):  
Mobile Communications ◽  
Antenna Arrays ◽  
Communication Systems ◽  
Smart Antenna ◽  
Doa Estimation ◽  
Adaptive Beamforming ◽  
Lms Algorithm ◽  
Robust Algorithms ◽  
Wireless Mobile Communications ◽  
Wireless Mobile

This paper presents a tool for the modelling, analysis and simulation of direction-of-arrival (DOA) estimation and adaptive beamforming needed in the design of smart antenna arrays for wireless mobile communications. The developed tool implements the Minimum Variance Distortionless Response (MVDR) algorithm for DOA estimation and the Least Mean Squares (LMS) algorithm for adaptive beamforming. Performance of each algorithm is investigated with respect to the variation of a number of parameters that related to the signal environment and sensor array. Results of numerical simulation are useful for the design of smart antennas systems with optimal performance. Hence, the developed simulation tool can be used to improve and accelerate the design of wireless networks. It can also be used for computeraided learning of modern communication systems utilizing smart antenna arrays.

Robust Algorithms for DOA Estimation and Adaptive Beamforming in Wireless Mobile Communications

2011 ◽  
pp. 1036-1047
Author(s):  
R. M. Shubair ◽  
K. O. AlMidfa ◽  
A. Al-Marri ◽  
M. Al-Nuaimi
Keyword(s):  
Mobile Communications ◽  
Antenna Arrays ◽  
Communication Systems ◽  
Smart Antenna ◽  
Doa Estimation ◽  
Adaptive Beamforming ◽  
Lms Algorithm ◽  
Robust Algorithms ◽  
Wireless Mobile Communications ◽  
Wireless Mobile

This paper presents a tool for the modelling, analysis and simulation of direction-of-arrival (DOA) estimation and adaptive beamforming needed in the design of smart antenna arrays for wireless mobile communications. The developed tool implements the Minimum Variance Distortionless Response (MVDR) algorithm for DOA estimation and the Least Mean Squares (LMS) algorithm for adaptive beamforming. Performance of each algorithm is investigated with respect to the variation of a number of parameters that related to the signal environment and sensor array. Results of numerical simulation are useful for the design of smart antennas systems with optimal performance. Hence, the developed simulation tool can be used to improve and accelerate the design of wireless networks. It can also be used for computer-aided learning of modern communication systems utilizing smart antenna arrays.

scholarly journals Performance analysis of direction of arrival algorithms for Smart Antenna

2019 ◽  
Vol 9 (6) ◽  
pp. 4873
Author(s):  
Btissam Boustani ◽  
Abdennaceur Baghdad ◽  
Aicha Sahel ◽  
Abdelmajid Badri
Keyword(s):  
Performance Analysis ◽  
Smart Antenna ◽  
Direction Of Arrival ◽  
Minimum Variance ◽  
Antenna System ◽  
Estimation Algorithms ◽  
Minimum Variance Distortionless Response ◽  
Subspace Fitting ◽  
Arrival Angles ◽  
Smart Antenna System

<p>This paper presents the performance analysis of the direction of arrival estimation algorithms such as Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Multiple Signal Classification (MUSIC), Weighted Subspace Fitting (WSF), The Minimum Variance Distortionless Response (MVDR or capon) and beamspace. These algorithms are necessary to overcome the problem of detecting the arrival angles of the received signals in wireless communication. Therefore, these algorithms are evaluated and compared according to several constraints required in smart antenna system parameters, as the number of array elements, number of samples (snapshots), and number of the received signals. The main purpose of this study is to obtain the best estimation of the direction of arrival, which can be perfectly implemented in a smart antenna system. In this context, the ROOT-Weighted Subspace Fitting algorithm provides the most accurate detection of arrival angles in each of the proposed scenarios.</p>

Sign in / Sign up

Export Citation Format

Share Document