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Conical localization from angle measurements: an approximate convex solution

Alamdari, E ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1109/LSENS.2022.3163186
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2022
  4. Abstract:
  5. For several years, a substantial effort has been devoted to the study of 3-D source localization based on 2-D arrays by measuring the well-known azimuth and elevation angles. However, studies on 3-D source localization performed by 1-D arrays are still lacking. Perhaps, the most important drawback in the deployment of a 2-D array structure lies in the fact that it needs a planar space, which might not be available in some applications. This letter concentrates on the problem of 3-D source localization based on 1-D angle measurement provided by a linear array. Different from the traditional 2-D structures where each measurement induces a straight line, each measurement in the 1-D array results in a conic surface originating at the array location. The localization problem is formulated as a constrained weighted least squares optimization problem and the semidefinite relaxation technique has been utilized to recast it as a convex optimization problem. Numerical simulation indicates that the performance of the proposed method outperforms the existing estimator and can reach the Cramer-Rao lower bound under mild Gaussian noise conditions. © 2017 IEEE
  6. Keywords:
  7. 1-D angle of arrival (AOA) ; Cramer Rao lower bound (CRLB) ; Semidefinite programming (SDP) ; Sensor signal processing ; Angle measurement ; Constrained optimization ; Convex optimization ; Direction of arrival ; Gaussian noise (electronic) ; Numerical methods ; 1-D AOA ; 3-D localization ; Azimuth ; Conical localization ; Crame-rao lowe bound ; Cramer-rao ; Localisation ; Location awareness ; Maximum-likelihood estimation ; Optimisations ; Semi-definite programming ; Semidefinite programming ; Sensors array ; Maximum likelihood estimation
  8. Source: IEEE Sensors Letters ; Volume 6, Issue 5 , 2022 ; 24751472 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/9744522