{"ID":2875792,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.01223","arxiv_id":"2509.01223","title":"SMDS-based Rigid Body Localization","abstract":"We consider a novel rigid body localization (RBL) method, based only on a set of measurements of the distances, as well as the angles between sensors of the vehicle to the anchor landmark points. A key point of the proposed method is to use a variation of the super multidimensional scaling (SMDS) algorithm, where only a minor part of the complex edge kernel is used, based on the available information, which in the case of RBL is anchor-to-anchor and target-to-target information. Simulation results illustrate the good performance of the proposed technique in terms of mean square error (MSE) of the estimates, compared also to the corresponding Cramér-Rao Lower Bound (CRLB).","short_abstract":"We consider a novel rigid body localization (RBL) method, based only on a set of measurements of the distances, as well as the angles between sensors of the vehicle to the anchor landmark points. A key point of the proposed method is to use a variation of the super multidimensional scaling (SMDS) algorithm, where only...","url_abs":"https://arxiv.org/abs/2509.01223","url_pdf":"https://arxiv.org/pdf/2509.01223v1","authors":"[\"Niclas Führling\",\"Giuseppe Abreu\",\"David González G.\",\"Osvaldo Gonsa\"]","published":"2025-09-01T08:09:01Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}