Browsing by Subject "Measurement matrix design"

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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.