Urban source localization based on time of arrival measurement and street information
Enyang Xu, Zhi Ding, Soura Dasgupta
Abstract
Enyang Xu, Zhi Ding, Soura Dasgupta
Abstract
In this work, we study the localization of mobile signal emitters using time of arrival (TOA) measurement and additional urban street information. Two algorithms are proposed to improve the localization performance by integrating street information with the TOA measurement. The first algorithm exhaustively searches of all possible road paths. For each possible path, the source location is estimated based a semidefinite programming (SDP) algorithm by minimizing the maximum error measurement between the observed propagation time and the modeled propagation time. Only location on a street that satisfies the minimum mean square error yields estimation output. To reduce complexity, our second joint optimization algorithm combines the two steps together and jointly optimizes the path selection and source location. Numerical results show that both algorithms can improve the localization performance. Our proposed joint optimization approach is more suitable for practical use because of lower complexity and good performance.
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In this work, we study the localization of mobile signal emitters using time of arrival (TOA) measurement and additional urban street information. Two algorithms are proposed to improve the localization performance by integrating street information with the TOA measurement. The first algorithm exhaustively searches of all possible road paths. For each possible path, the source location is estimated based a semidefinite programming (SDP) algorithm by minimizing the maximum error measurement between the observed propagation time and the modeled propagation time. Only location on a street that satisfies the minimum mean square error yields estimation output. To reduce complexity, our second joint optimization algorithm combines the two steps together and jointly optimizes the path selection and source location. Numerical results show that both algorithms can improve the localization performance. Our proposed joint optimization approach is more suitable for practical use because of lower complexity and good performance.
Key concepts: Computer science, Semidefinite programming, Time of arrival, Algorithm, Path (computing), Mathematical optimization, Direction of arrival, Joint (building)