A Spatio-Temporal Array Processing for Passive Localization of Radio Transmitters

The problem of passive geographical localization is commonly solved by independently measuring intermediate parameters such as angles of arrival (AOA), times of arrival (TOA) or frequencies of arrival (FOA) on different separated multiple-sensors base stations on a first step. These intermediate par...

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Bibliographic Details
Published inIEEE transactions on signal processing Vol. 61; no. 22; pp. 5485 - 5494
Main Authors Bosse, Jonathan, Ferreol, Anne, Larzabal, Pascal
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.11.2013
Institute of Electrical and Electronics Engineers
Subjects
AOA estimation
Applied sciences
Array processing
Arrays
Base stations
Context
Detection, estimation, filtering, equalization, prediction
Engineering Sciences
Exact sciences and technology
Information, signal and communications theory
Miscellaneous
Sensors
Signal and communications theory
Signal and Image processing
Signal processing
Signal, noise
Telecommunications and information theory
transmitter geolocalization
Transmitters
Vectors
Wideband
Performance evaluation
Line of sight propagation
transmitter geolocalization
Multisensor
Array signal processing
Geolocation
Radio transmitters
Array processing
Base station
Signal estimation
Space time
Temporal logic
Arrival time
Simulation
AOA estimation
Arrival angle
Signal processing
Localization
Cramer Rao inequality
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Summary:The problem of passive geographical localization is commonly solved by independently measuring intermediate parameters such as angles of arrival (AOA), times of arrival (TOA) or frequencies of arrival (FOA) on different separated multiple-sensors base stations on a first step. These intermediate parameters are then used to estimate the emitter's coordinates on a second step. Such approach is suboptimal. This is why, recently, under line-of-sight conditions, some approaches (sometimes called one-step procedures) exploiting directly all signals collected on all base stations were investigated. Based on a space time observation vector we investigate here a new one-step localization technique called LOST that is spectrum adaptive contrary to the existing one-step approach. Simulations shows that the proposed technique outperforms existing techniques and lies close to the corresponding Cramer-Rao bound.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2013.2278515