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dc.contributor.authorEngebråten, Sondre
dc.contributor.authorMoen, Hans Jonas Fossum
dc.contributor.authorGlette, Kyrre
dc.date.accessioned2017-09-29T07:12:36Z
dc.date.accessioned2017-10-02T08:06:22Z
dc.date.available2017-09-29T07:12:36Z
dc.date.available2017-10-02T08:06:22Z
dc.date.issued2017
dc.identifier.citationEngebråten SA, Moen HJM, Glette K. Meta-heuristics for improved RF emitter localization. Lecture Notes in Computer Science. 2017;10200 LNCS(Part II):207-223en_GB
dc.identifier.urihttp://hdl.handle.net/20.500.12242/652
dc.identifier.urihttps://ffi-publikasjoner.archive.knowledgearc.net/handle/20.500.12242/652
dc.descriptionEngebråten, Sondre; Moen, Hans Jonas Fossum; Glette, Kyrre. Meta-heuristics for improved RF emitter localization. Lecture Notes in Computer Science 2017 ;Volum 10200 LNCS.(Part II) s. 207-223en_GB
dc.description.abstractLocating Radio Frequency (RF) emitters can be done with a number of methods, but cheap and widely available sensors make the Power Difference of Arrival (PDOA) technique a prominent choice. Predicting the location of an unknown RF emitter can be seen as a continuous optimization problem, minimizing the error w.r.t. the sensor measurements gathered. Most instances of this problem feature multi-modality, making these challenging to solve. This paper presents an analysis of the performance of evolutionary computation and other meta-heuristic methods on this real-world problem. We applied the Nelder-Mead method, Genetic Algorithm, Covariance Matrix Adaptation Evolutionary Strategies, Particle Swarm Optimization and Differential Evolution. The use of meta-heuristics solved the minimization problem more efficiently and precisely, compared to brute force search, potentially allowing for a more widespread use of the PDOA method. To compare algorithms two different metrics were proposed: average distance miss and median distance miss, giving insight into the algorithms’ performance. Finally, the use of an adaptive mutation step proved important.en_GB
dc.language.isoenen_GB
dc.titleMeta-heuristics for improved RF emitter localizationen_GB
dc.typeArticleen_GB
dc.date.updated2017-09-29T07:12:36Z
dc.identifier.cristinID1491181
dc.identifier.cristinID1491181
dc.identifier.doi10.1007/978-3-319-55792-2_14
dc.source.issn0302-9743
dc.source.issn1611-3349
dc.type.documentJournal article
dc.relation.journalLecture Notes in Computer Science


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