Emitter source localization using time-of-arrival measurements from single moving receiver

In this paper, we consider using time-of-arrival (TOA) measurements from single moving receiver to locate a stationary source which emits periodical signal. First, we give the TOA measurements model and deduce the Cramér-Rao lower bounds (CRLB). Then, we formulated the maximum likelihood estimation...

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Bibliographic Details
Main Authors: Yanbin Zou, Qun Wan
Format: Conference Proceeding
Language:English
Subjects:
Intelligent sensors
Maximum likelihood estimation
Programming
Receivers
Robustness
Semidefinite programming (SDP)
Signal processing algorithms
single moving receiver
source localization
Symmetric matrices
time-of-arrival (TOA)
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Summary:In this paper, we consider using time-of-arrival (TOA) measurements from single moving receiver to locate a stationary source which emits periodical signal. First, we give the TOA measurements model and deduce the Cramér-Rao lower bounds (CRLB). Then, we formulated the maximum likelihood estimation (MLE) problem. We use the semidefinite programming (SDP) method to relax the nonconvex MLE problem into convex problem. It is shown that the original SDP algorithm can not provide a high-quality solution. We jointly add second-order-cone (SOC) constraints and penalty term to improve the tightness of the original SDP algorithm. Besides, we also consider the presence of receiver position errors, and develop the robust localization algorithm. Numerical simulations are conducted to demonstrate the localization performance of the proposed algorithms by comparing with the CRLB.
ISSN:2379-190X
DOI:10.1109/ICASSP.2017.7952796