scholarly journals Fundamentals of Narrowband Array Signal Processing

2021 ◽  
Author(s):  
Zeeshan Ahmad
Keyword(s):  
Signal Processing ◽  
Array Signal Processing ◽  
Technological Development ◽  
Optimization Theory ◽  
Doa Estimation ◽  
Research Area ◽  
Adaptive Arrays ◽  
Vector Solution ◽  
Second Order Statistics ◽  
Estimation Algorithms

Array signal processing is an actively developing research area connected to the progress in optimization theory, and remains the key technological development that attracts prevalent attention in signal processing. This chapter provides an overview of the fundamental concepts and essential terminologies employed in narrowband array signal processing. We first develop a general signal model for narrowband adaptive arrays and discuss the beamforming operation. We next introduce the basic performance parameters of adaptive arrays and the second order statistics of the array data. We then formulate various optimal weigh vector solution criteria. Finally, we discuss various types of adaptive filtering algorithms. Besides, this chapter emphasizes the theory of narrowband array signal processing employed in narrowband beamforming and direction-of-arrival (DOA) estimation algorithms.

Unified analysis for DOA estimation algorithms in array signal processing

1991 ◽  
Vol 25 (2) ◽  
pp. 147-169 ◽  
Author(s):  
Fu Li ◽  
Richard J. Vaccaro
Keyword(s):  
Signal Processing ◽  
Array Signal Processing ◽  
Doa Estimation ◽  
Estimation Algorithms

A Broadband Array Signal Processing Method Based on Joint Sparsity of Signal Spatial Domain

2019 ◽  
Author(s):  
Daqian He ◽  
Dahai Zhang ◽  
Congying Wang ◽  
Xirui Peng
Keyword(s):  
Signal Processing ◽  
Frequency Domain ◽  
Acoustic Signal ◽  
Array Signal Processing ◽  
Doa Estimation ◽  
Spatial Domain ◽  
Processing Method ◽  
Arrival Angle ◽  
Joint Sparsity ◽  
Signal Processing Method

Abstract Broadband underwater acoustic signal direction of arrival (DOA) estimation method is an important part of underwater array signal processing. The commonly used array signal DOA estimation algorithms due to the restriction of algorithm principles, are unable to process broadband array signal effectively, at the case of the arriving signals have strong correlation, small sampling snapshots or small arrival angle. Therefore, we need a new efficient algorithm to meet the increasing demand of broadband under water acoustic signal processing method. This paper makes use of the broadband acoustic signal similarity of joint sparsity in signal spatial domain received by underwater sonar arrays, establishes the whole space grid covering all broadband frequency domain slices. On the basis, the global sparsity of each frequency domain slice is combined with sparse element extraction class algorithm. By integrating the energy of signal on each slice, the spatial sparsity of each slice is obtained, from which we can get the directions of the arriving broadband wave signals. Through the simulation analysis and experimental verification on lake, we can be see that: The SDJS algorithm improves the performance and signal processing capability of the algorithm compared with the traditional algorithms. Therefore SDJS algorithm has a widely range of research value and application space.

scholarly journals Investigations on antenna array calibration algorithms for direction-of-arrival estimation

2016 ◽  
Vol 14 ◽  
pp. 181-190 ◽  
Author(s):  
Michael Eberhardt ◽  
Philipp Eschlwech ◽  
Erwin Biebl
Keyword(s):  
Antenna Array ◽  
Array Signal Processing ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Calibration Procedure ◽  
Estimation Algorithms ◽  
Modeling Errors ◽  
Array Calibration ◽  
History Of ◽  
The Common

Abstract. Direction-of-arrival (DOA) estimation algorithms deliver very precise results based on good and extensive antenna array calibration. The better the array manifold including all disturbances is known, the better the DOA estimation result. A simplification or ideally an omission of the calibration procedure has been a long pursued goal in the history of array signal processing. This paper investigates the practicability of some well known calibration algorithms and gives a deeper insight into existing obstacles. Further analysis on the validity of the common used data model is presented. A new effect in modeling errors is revealed and simulation results substantiate this theory.

Method to Estimate and Promote SNR of Covariance Matrix in Array Signal Processing

2013 ◽  
Vol 397-400 ◽  
pp. 2156-2160
Author(s):  
Yi Ran Shi ◽  
Yan Tao Tian ◽  
Hong Wei Shi ◽  
Lan Xiang Zhu
Keyword(s):  
Signal Processing ◽  
Covariance Matrix ◽  
Array Signal Processing ◽  
Doa Estimation ◽  
Accurate Estimation ◽  
Music Algorithm ◽  
Important Work ◽  
Variance Matrix ◽  
Eigen Value ◽  
The Difference

Estimation for direction of arrival (DOA) is an important work in array signal processing, and subspace method such as MUSIC algorithm is basic and important in DOA estimation. This paper analyzes the structure of eigen value of variance matrix, and proposes a method to estimate the signal noise ratio (SNR) of the data received by sensor array. With the accurate estimation for SNR, we can estimate the work environment and decide detect threshold for many algorithm. The paper also proposes a method to promote the SNR of covariance matrix with moving the covariance slice to do DOA estimation. It can efficiently widen the difference of signal eigen value and noise eigen value.

scholarly journals Direction of Arrival Estimation using Conventional Subspace Algorithms

2019 ◽  
Vol 8 (9) ◽  
pp. 815-819
Keyword(s):  
Array Signal Processing ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Research Area ◽  
Minimum Variance ◽  
Spatial Spectrum ◽  
Basic Knowledge ◽  
Main Beam ◽  
Spectrum Estimation ◽  
Minimum Variance Distortionless Response

In recent times, Direction of Arrival (DOA) Estimation study earns attention in array signal processing and it develops rapidly in several application such as sonar, radar, communication, biomedicine and seismology measurements. The self adaption and spatial spectrum are the broad research area in array processing. The spatial spectrum estimation focused on the signal distribution in the space is received from all direction to receiver. To maintain accuracy in DOA estimation for the antenna array the basic knowledge is required for main beam, and side lobes pattern must be small to suppress signal from other direction. This paper discussed the overview of the Direction of Arrival (DOA) estimation based on classical Sum and delay beamformer, Minimum Variance Distortionless Response (MVDR) technique, Min Norm technique and Multiple Signal Classification(MUSIC) by using the spatial spectrum parameters.

Two DOA estimation algorithms based on the theory of sparse representation

2014 ◽  
Author(s):  
Z. Luo ◽  
W. Zhao ◽  
F. Yu ◽  
Y. Liu
Keyword(s):  
Sparse Representation ◽  
Doa Estimation ◽  
Estimation Algorithms
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