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PubMed · 17036794

High reliability outdoor sonar prototype based on efficient signal coding.

Fernando J Alvarez·Jesús Ureña·Manuel Mazo·Alvaro Hernández·Juan J García·Carlos de Marziani
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Abstract

Many mobile robots and autonomous vehicles designed for outdoor operation have incorporated ultrasonic sensors in their navigation systems, whose function is mainly to avoid possible collisions with very close obstacles. The use of these systems in more precise tasks requires signal encoding and the incorporation of pulse compression techniques that have already been used with success in the design of high-performance indoor sonars. However, the transmission of ultrasonic encoded signals outdoors entails a new challenge because of the effects of atmospheric turbulence. This phenomenon causes random fluctuations in the phase and amplitude of traveling acoustic waves, a fact that can make the encoded signal completely unrecognizable by its matched receiver. Atmospheric turbulence is investigated in this work, with the aim of determining the conditions under which it is possible to assure the reliable outdoor operation of an ultrasonic pulse compression system. As a result of this analysis, a novel sonar prototype based on complementary sequences coding is developed and experimentally tested. This encoding scheme provides the system with very useful additional features, namely, high robustness to noise, multi-mode operation capability (simultaneous emissions with minimum cross talk interference), and the possibility of applying an efficient detection algorithm that notably decreases the hardware resource requirements.

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Data CompressionEquipment DesignEquipment Failure AnalysisReproducibility of ResultsRoboticsSensitivity and SpecificitySignal Processing, Computer-AssistedUltrasonographyEvaluation StudyJournal ArticleResearch Support, Non-U.S. Gov't

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Fernando J Alvarez, Jesús Ureña, Manuel Mazo, Alvaro Hernández, Juan J García, Carlos de Marziani. 2006. High reliability outdoor sonar prototype based on efficient signal coding.. https://pubmed.ncbi.nlm.nih.gov/17036794/

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