dc.contributor.author | Engebråten, Sondre | |
dc.contributor.author | Moen, Hans Jonas Fossum | |
dc.contributor.author | Glette, Kyrre | |
dc.date.accessioned | 2017-09-29T07:12:36Z | |
dc.date.accessioned | 2017-10-02T08:06:22Z | |
dc.date.available | 2017-09-29T07:12:36Z | |
dc.date.available | 2017-10-02T08:06:22Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Engebråten SA, Moen HJM, Glette K. Meta-heuristics for improved RF emitter localization. Lecture Notes in Computer Science. 2017;10200 LNCS(Part II):207-223 | en_GB |
dc.identifier.uri | http://hdl.handle.net/20.500.12242/652 | |
dc.identifier.uri | https://ffi-publikasjoner.archive.knowledgearc.net/handle/20.500.12242/652 | |
dc.description | Engebråten, 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. 207-223 | en_GB |
dc.description.abstract | Locating 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.iso | en | en_GB |
dc.title | Meta-heuristics for improved RF emitter localization | en_GB |
dc.type | Article | en_GB |
dc.date.updated | 2017-09-29T07:12:36Z | |
dc.identifier.cristinID | 1491181 | |
dc.identifier.cristinID | 1491181 | |
dc.identifier.doi | 10.1007/978-3-319-55792-2_14 | |
dc.source.issn | 0302-9743 | |
dc.source.issn | 1611-3349 | |
dc.type.document | Journal article | |
dc.relation.journal | Lecture Notes in Computer Science | |