Browsing by Subject "Direction of arrival estimation"

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Open Access
Adaptive measurement matrix design in compressed sensing based direction of arrival estimation
(IEEE, 2021) Kılıç, Berkan; Güngör, Alper; Kalfa, Mert; Arıkan, Orhan
Design of measurement matrices is an important aspect of compressed sensing (CS) based direction of arrival (DoA) applications that enables reduction in the analog channels to be processed in sparse target environments. Here, a novel measurement matrix design methodology for CS based DoA estimation is proposed and its superior performance over alternative measurement matrix design methodologies is demonstrated. The proposed method uses prior probability distribution of the targets to improve performance. Compared to the state-of-the-art techniques, it is quantitatively demonstrated that the proposed measurement matrix design approach enables significant reduction in the number of analog channels to be processed and adapts to a priori information on the target scene.
Open Access
Adaptive measurement matrix design in direction of arrival estimation
(IEEE, 2022-09-26) Kılıç, Berkan; Güngör, Alper; Kalfa, Mert; Arıkan, Orhan
Advances in compressed sensing (CS) theory have brought new perspectives to encoding and decoding of signals with sparse representations. The encoding strategies are determined by measurement matrices whose design is a critical aspect of the CS applications. In this study, we propose a novel measurement matrix design methodology for direction of arrival estimation that adapts to the prior probability distribution on the source scene, and we compare its performance over alternative approaches using both on-grid and gridless reconstruction methods. The proposed technique is derived in closed-form and shown to provide improved compression rates compared to the state-of-the-art. This technique is also robust to the uncertainty in the prior source information. In the presence of significant mutual coupling between antenna elements, the proposed technique is adapted to mitigate these mutual coupling effects.
Open Access
Adaptive techniques in compressed sensing based direction of arrival estimation
(2021-07) Kılıç, Berkan
Direction of arrival (DOA) estimation is an important research area having exten-sive applications including radar, sonar, wireless communications, and electronic warfare systems. Development and popularization of the compressed sensing (CS) theory has led to a vast literature on the use of the CS techniques in DOA esti-mation which has been shown to be superior over the classical techniques under various scenarios. In the CS based techniques, measurement matrices determine the received information while sparsity promoting reconstruction algorithms are used to estimate the unknown DOAs. Hence, design of measurement matrices and sparse reconstruction algorithms are among the most important aspects of the CS theory. In this thesis, both aspects are investigated and novel techniques are proposed for improved performance. Following a brief explanation of the classical and the CS based DOA estimation techniques, a new optimization perspective is introduced on the Capon’s beam-former by using the minimum mean square error criterion. After that, a mea-surement matrix design methodology exploiting prior information on the source environment is introduced. Hardware and sofware implementation constraints of the introduced method are investigated and more eﬃcient alternatives are pro-posed. Additionally, an adaptive dictionary design algorithm is introduced for more eﬀective use of the prior information. Lastly, the Cramer-Rao Lower Bound expression for the compressed DOA signal models is derived and its implications on the measurement matrix design are investigated leading to a sector based mea-surement matrix design technique along with a novel reconstruction algorithm.
Open Access
Efficient heterogeneous parallel programming for compressed sensing based direction of arrival estimation
(John Wiley & Sons Ltd., 2021-07) Fişne, A.; Kılıç, Berkan; Güngör, Alper; Özsoy, A.
In the direction of arrival (DoA) estimation, typically sensor arrays are used where the number of required sensors can be large depending on the application. With the help of compressed sensing (CS), hardware complexity of the sensor array system can be reduced since reliable estimations are possible by using the compressed measurements where the compression is done by measurement matrices. After the compression, DoAs are reconstructed by using sparsity promoting algorithms such as alternating direction method of multipliers (ADMM). For the given procedure, both the measurement matrix design and the reconstruction algorithm may include computationally intensive operations, which are addressed in this study. The presented simulation results imply the feasibility of the system in real-time processing with energy efficient implementations. We propose employing parallel programming to satisfy the real-time processing requirements. While the measurement matrix design has been accelerated 16urn:x-wiley:cpe:media:cpe6490:cpe6490-math-0001 with CPU based parallel version with respect to the fastest serial implementation, ADMM based DoA estimation has been improved 1.1urn:x-wiley:cpe:media:cpe6490:cpe6490-math-0002 with GPU based parallel version compared to the fastest CPU parallel implementation. In addition, we achieved, to the best of our knowledge, the first energy-efficient real-time DoA estimation on embedded Jetson GPGPUs in 15 W power consumption without affecting the DoA accuracy performance.
Open Access
Mode separation and direction of arrival estimation in HF links
(Wiley-Blackwell Publishing, 2003) Arikan, F.; Yilmaz, N.; Arıkan, Orhan; Miled, M. K. B. H.
Estimation of arrival angles and incoming signals is a challenging problem for HF channels where the signals are correlated and the separation between the signals can be as low as a couple of degrees. In this paper, a new algorithm, Multipath Separation- Direction of Arrival (MS-DOA), is developed to estimate both the arrival angles in elevation and azimuth and the incoming signals at the output of the reference antenna with very high accuracy. The MS-DOA algorithm provides reliable angle and signal estimates even with small separation of arrival angles and for low SNRs. The minimum number of antennas that are required by the algorithm is only one more than the number of incoming signals. In a narrowed down region of interest and for a few incoming signals, the computational search time for MS-DOA is only a couple of minutes in a Standard PC.