Eckrich, Christian ; Schroth, Christian A. ; Jamali, Vahid ; Zoubir, Abdelhak M. (2023)
Radar Based Humans Localization with Compressed Sensing and Sparse Reconstruction.
24th International Conference on Digital Signal Processing. Rhodes, Greece (11.-13.06.2023)
doi: 10.1109/DSP58604.2023.10167990
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Localization and detection is a vital task in emergency rescue operations. Devastating natural disasters can create environments that are inaccessible or dangerous for human rescuers. Contaminated areas or buildings in danger of collapsing can be searched by rescue robots which are equipped with diverse sensors such as optical and radar sensors. In scenarios where the line of sight is blocked, e.g., by a wall, a door or heavy smoke or dust, sensors like LiDAR or cameras are not able to provide sufficient information. The usage of radar in these kinds of situations can drastically improve situational awareness and hence the likelihood of rescue. In this paper, we present a method that is used for radar imaging behind obstacles by utilizing a signal model that includes the floor reflection propagation path in addition to the direct path of the radar signal. Additionally, compressed sensing methods are presented and applied to real world radar data that was recorded by a Stepped Frequency Continuous Wave (SFCW) radar mounted on a semi-autonomous robot. The results show an improved radar image that allows the clear identification of persons behind obstacles.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Eckrich, Christian ; Schroth, Christian A. ; Jamali, Vahid ; Zoubir, Abdelhak M. |
| Art des Eintrags: | Bibliographie |
| Titel: | Radar Based Humans Localization with Compressed Sensing and Sparse Reconstruction |
| Sprache: | Englisch |
| Publikationsjahr: | 5 Juli 2023 |
| Verlag: | IEEE |
| Buchtitel: | 24th DSP 2023: 2023 24th International Conference on Digital Signal Processing |
| Veranstaltungstitel: | 24th International Conference on Digital Signal Processing |
| Veranstaltungsort: | Rhodes, Greece |
| Veranstaltungsdatum: | 11.-13.06.2023 |
| DOI: | 10.1109/DSP58604.2023.10167990 |
| Kurzbeschreibung (Abstract): | Localization and detection is a vital task in emergency rescue operations. Devastating natural disasters can create environments that are inaccessible or dangerous for human rescuers. Contaminated areas or buildings in danger of collapsing can be searched by rescue robots which are equipped with diverse sensors such as optical and radar sensors. In scenarios where the line of sight is blocked, e.g., by a wall, a door or heavy smoke or dust, sensors like LiDAR or cameras are not able to provide sufficient information. The usage of radar in these kinds of situations can drastically improve situational awareness and hence the likelihood of rescue. In this paper, we present a method that is used for radar imaging behind obstacles by utilizing a signal model that includes the floor reflection propagation path in addition to the direct path of the radar signal. Additionally, compressed sensing methods are presented and applied to real world radar data that was recorded by a Stepped Frequency Continuous Wave (SFCW) radar mounted on a semi-autonomous robot. The results show an improved radar image that allows the clear identification of persons behind obstacles. |
| Freie Schlagworte: | emergenCITY_CPS, emergenCITY_KOM, emergenCITY |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Signalverarbeitung LOEWE LOEWE > LOEWE-Zentren LOEWE > LOEWE-Zentren > emergenCITY |
| Hinterlegungsdatum: | 10 Jul 2023 10:19 |
| Letzte Änderung: | 10 Jul 2023 10:19 |
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