Collaborative Direction of Arrival estimation by using Alternating Direction Method of Multipliers in distributed sensor array networks employing Sparse Bayesian Learning framework

Nurbas, Ekin
Onat, Emrah
Tuncer, Temel Engin
In this paper, we present a new method for Direction of Arrival (DoA) estimation in distributed sensor array networks by using Alternating Direction Method of Multipliers (ADMM) in Sparse Bayesian Learning (SBL) framework. Our proposed method, CDoAE, has certain advantages compared to previous distributed DoA estimation methods. It does not require any special array geometry and there is no need for inter -array frequency and phase matching. CDoAE uses the distributed ADMM to update the parameter set extracted by the SBL frameworks in the local arrays to minimize a common objective function. This update process is implemented in the master-node and the result is distributed back to the slave nodes. It is shown that the performance of the local arrays can be improved significantly in this distributed DOA estimation framework. Moreover, we present a method, CDoAE-TVR, to reduce the number of parameters transmitted from the local arrays to the master array which is important for the networks with limited bandwidth and energy. Several simulations have been performed including the cases with coherent sources. It is shown that the use of ADMM in a distributed fashion improves the SBL output efficiently and effectively. In addition, proposed CDoAE-TVR method reduces the transmitted parameters in the network with a small sacrifice on the DoA estimation performance.(c) 2022 Elsevier Inc. All rights reserved.


Direction of Arrival estimation by using Alternating Direction Method of Multipliers in distributed sensor array networks
Nurbaş, Ekin; Tuncer, Temel Engin; Onat, Emrah; Department of Electrical and Electronics Engineering (2022-8-26)
In recent years, developments in microprocessor and wireless communication technologies have benefited a variety of distributed sensor network applications, including array signal processing. Researchers have been investigating distributed implementations of array signal processing algorithms, such as Direction of Arrival Estimation, for a variety of applications. Performance and practical implementations of those algorithms are affected by a variety of factors, such as inter-array phase and frequency match...
Fine resolution frequency estimation from three DFT samples: Case of windowed data
Candan, Çağatay (2015-09-01)
An efficient and low complexity frequency estimation method based on the discrete Fourier transform (DFT) samples is described. The suggested method can operate with an arbitrary window function in the absence or presence of zero-padding. The frequency estimation performance of the suggested method is shown to follow the Cramer-Rao bound closely without any error floor due to estimator bias, even at exceptionally high signal-to-noise-ratio (SNR) values.
Sparse linear sensor arrays: analysis of recent coarray based arrays and array design for nonlinear processing
Epçaçan, Erdal; Çiloğlu, Tolga; Department of Electrical and Electronics Engineering (2021-9-09)
In this thesis, sparse linear sensor arrays have been studied. The study of sparse arrays in this work can be considered under two main headings: Analysis and comparison of recently proposed coarray based arrays, and the adaptation of the nonlinear apodization method for linear arrays and its use in sparse linear array design. Recently proposed coarray-based sparse arrays are designed with closed form structures without the need for any optimization and have much higher degrees of freedom (DOF) than a unif...
Cooperative terrain based navigation and coverage identification using consensus
Kasebzadeh, Parinaz; Fritsche, Carsten; Özkan, Emre; Gunnarsson, Fredrik; Gustafsson, Fredrik ( Institute of Electrical and Electronics Engineers Inc.; 2015-07-06)
This paper presents a distributed online method for joint state and parameter estimation in a Jump Markov NonLinear System based on a distributed recursive Expectation Maximization algorithm. State inference is enabled via the use of Rao-Blackwellized Particle Filter and, for the parameter estimation, the E-step is performed independently at each sensor with the calculation of local sufficient statistics. An average consensus algorithm is used to diffuse local sufficient statistics to neighbors and approxim...
Implicit monolithic parallel solution algorithm for seismic analysis of dam-reservoir systems
Özmen, Semih; Kurç, Özgür; Department of Civil Engineering (2016)
This research mainly focuses on developing a computationally scalable and efficient solution algorithm that can handle linear dynamic analysis of dam-reservoir interaction problem. Lagrangian fluid finite elements are utilized and compressibility and viscosity of the fluid are taken into consideration during the reservoir modeling. In order to provide computational scalability and efficiency, domain decomposition methods implemented with parallel computing approaches such as Finite Element Tearing and Inter...
Citation Formats
E. Nurbas, E. Onat, and T. E. Tuncer, “Collaborative Direction of Arrival estimation by using Alternating Direction Method of Multipliers in distributed sensor array networks employing Sparse Bayesian Learning framework,” DIGITAL SIGNAL PROCESSING, vol. 130, pp. 0–0, 2022, Accessed: 00, 2022. [Online]. Available: