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An optimized embedded target detection system using acoustic and seismic sensors

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication25th European Signal Processing Conference, EUSIPCO 2017
PublisherIEEE
Pages986-990
Number of pages5
ISBN (Electronic)9780992862671
DOIs
Publication statusPublished - 23 Oct 2017
Publication typeA4 Article in a conference publication
EventEuropean Signal Processing Conference -
Duration: 1 Jan 1900 → …

Publication series

Name
ISSN (Electronic)2076-1465

Conference

ConferenceEuropean Signal Processing Conference
Period1/01/00 → …

Abstract

Detection of targets using low power embedded devices has important applications in border security and surveillance. In this paper, we build on recent algorithmic advances in sensor fusion, and present the design and implementation of a novel, multi-mode embedded signal processing system for detection of people and vehicles using acoustic and seismic sensors. Here, by "multi-mode", we mean that the system has available a complementary set of configurations that are optimized for different trade-offs. The multimode capability delivered by the proposed system is useful to supporting long lifetime (long term, energy-efficient "standby" operation), while also supporting optimized accuracy during critical time periods (e.g., when a potential threat is detected). In our target detection system, we apply a strategically-configured suite of single-and dual-modality signal processing techniques together with dataflow-based design optimization for energyefficient, real-time implementation. Through experiments using a Raspberry Pi platform, we demonstrate the capability of our target detection system to provide efficient operational tradeoffs among detection accuracy, energy efficiency, and processing speed.

ASJC Scopus subject areas

Publication forum classification

Field of science, Statistics Finland