{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T06:37:43Z","timestamp":1774507063351,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2020,9,26]],"date-time":"2020-09-26T00:00:00Z","timestamp":1601078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["Finance Code 001."],"award-info":[{"award-number":["Finance Code 001."]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Methods for autonomous navigation systems using sonars in air traditionally use the time-of-flight technique for obstacle detection and environment mapping. However, this technique suffers from constructive and destructive interference of ultrasonic reflections from multiple obstacles in the environment, requiring several acquisitions for proper mapping. This paper presents a novel approach for obstacle detection and localisation using inverse problems and compressed sensing concepts. Experiments were conducted with multiple obstacles present in a controlled environment using a hardware platform with four transducers, which was specially designed for sending, receiving and acquiring raw ultrasonic signals. A comparison between the performance of compressed sensing using Orthogonal Matching Pursuit and two traditional image reconstruction methods was conducted. The reconstructed 2D images representing the cross-section of the sensed environment were quantitatively assessed, showing promising results for robotic mapping tasks using compressed sensing.<\/jats:p>","DOI":"10.3390\/s20195511","type":"journal-article","created":{"date-parts":[[2020,9,28]],"date-time":"2020-09-28T08:02:58Z","timestamp":1601280178000},"page":"5511","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Compressed Sensing Approach for Multiple Obstacle Localisation Using Sonar Sensors in Air"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7010-0774","authenticated-orcid":false,"given":"Eduardo","family":"Tondin Ferreira Dias","sequence":"first","affiliation":[{"name":"Graduate Program in Electrical and Computer Engineering (CPGEI), Federal University of Technology-Paran\u00e1 (UTFPR), Curitiba-PR 80230-901, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3138-5639","authenticated-orcid":false,"given":"Hugo","family":"Vieira Neto","sequence":"additional","affiliation":[{"name":"Graduate Program in Electrical and Computer Engineering (CPGEI), Federal University of Technology-Paran\u00e1 (UTFPR), Curitiba-PR 80230-901, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6916-1361","authenticated-orcid":false,"given":"F\u00e1bio Kurt","family":"Schneider","sequence":"additional","affiliation":[{"name":"Graduate Program in Electrical and Computer Engineering (CPGEI), Federal University of Technology-Paran\u00e1 (UTFPR), Curitiba-PR 80230-901, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,26]]},"reference":[{"key":"ref_1","unstructured":"Siegwart, R., Nourbakhsh, I.R., and Scaramuzza, D. 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