DBPIA-NURIMEDIA

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1 Journal of Institute of Control, Robotics and Systems (2012) 18(8): ISSN: eissn: Infrastructure-based Localization System using Underwater Wireless Sensor Network,,, * (Daegil Park 1, Kyungmin Kwak 2, Wan Kyun Chung 1, and Jinhyun Kim 2 ) 1 Pohang University of Science and Technology 2 Seoul National University of Science and Technology Abstract: In this paper, an infrastructure-based localization method using underwater wireless sensor network (UWSN) is addressed. A localization using the UWSN is necessary to widen the usage of underwater applications, however it is very difficult to establish the UWSN due to the restrictions of water. In this paper, to extend the usage of UWSN at the infrastructure, we propose a sophisticated UWSN localization method using the Received Signal Strength Indicator (RSSI) of the electromagnetic waves. During the electromagnetic waves propagating in underwater, there arises a lot of attenuation according to the distance, while the attenuation shows uniformity according to the distance. Using this characteristics, the localization system in underwater infrastructure is proposed and the experimental results show the effectiveness. Keywords: UWSN (Underwater Wireless Sensor Network), underwater localization, RSSI (Received Signal Strength Indicator), infrastructure-based localization I. 서론현재지상에서의위치추정(localization) 은 GPS, 레이저, 소나등의다양한센서및정보를이용하여비교적정확한위치를추정함으로서우리삶속에서유비쿼터스 (ubiquitous) 환경조성에기여하고있다. 그렇기때문에, 지상에서의위치추정은어떻게정확한위치추정방법에대한연구뿐만아니라, 얼마나작고저렴한가격으로높은성능을보이는지에대한연구가활발히진행되고있다[1,2]. 하지만수중위치추정(underwater localization) 은수중자원개발, 수중생태계및환경모니터링, 군수분야등에서의위치추정 (localization) 을요구하는영역이증가하고있는데반하여, 사용할수있는센서가적으며, 수중환경에서사용이불가능하거나센서작동범위가매우짧기때문에실제로위치 * 책임저자 (Corresponding Author) 논문접수: , 수정: , 채택확정: 박대길, 정완균: 포항공과대학교기계공학과 (daegilpark@postech.ac.kr/wkchung@postech.ac.kr) 곽경민, 서울과학기술대학교 : 기계공학과 (supermaxx@seoultech.ac.kr/jinhyun@seoultech.ac.kr) 본연구는교육과학기술부와한국연구재단의선도연구센터지원사업(NO ), 지식경제부 ' 산업원천기술개발사업' 의일환인 노약자를위한감성교감및이동보조서비스로봇개발 과제( ), 교육과학기술부와한국연구재단의 < 실감교류인체감응솔루션> 글로벌프런티어연구개발사업( 한국연구재단 -M1AXA ), 교육과학기술부와한국연구재단의도약연구지원프로그램(R ), 한국연구재단 (No ), 한국과학기술원국방무인화기술특화연구센터를통한방위사업청과국방과학연구소의연구비지원으로수행되었음. 추정을위해서수중음파센서만이주로사용되고있다. 하지만음파센서의경우가격이매우비싸고동적인환경에서사용하기힘들다는단점을가지고있다. 본논문에서는이러한문제를극복하기위한방법으로전자기파의수신된신호의세기 (RSSI: Received Signal Strength Indicator) 를이용하여수중센서네트워크(UWSN: Underwater Wireless Sensor Network) 를구성할것을제안한다. 그림 1 은동일한대역(420 MHz) 에서전자기파(EM: Electromagnetic) 의거리에따른신호세기를보여준다. 그림 1에서볼수있듯이공기중에서의전자기파는거리에따른신호감쇠는미미한데반하여불규칙적인외부영향에따른감쇠가큰특징을보이며, 물속에서는신호의세기가급속하게감소하여넓은영역을위치추정하기어려울것으로보인다. 하지만 RSSI 를이용하여수중에서위치추정을하는경우이는반대로장점이될수있다. 그림 1에서공기중에서의수신신호세기는앞서언급한바와같이거리에따른신호세기의변화보다그외의환경에따른신호세기의변화가크다. 이때문에수신신호세기를이용하여위치추정이힘들며거리에따른감쇠가적기때문에분해능(resolution) 이떨어진다. 반면에수중에서는거리에따른신호의감쇠가크지만균일하게일어나기때문에공기중보다좋은분해능을가지며위치추정정확도역시높다. 이를이용하면기존의공기중에서 RSSI 를이용한위치추정방법보다더욱좋은성능의센서로사용이가능할수있다[3-5]. 다만, 물에서의감쇠때문에위치추정이가능한영역이매우작기때문에이러한한계를극복하기위하여송신전자기파의세기를강하게하거나통신 Copyright ICROS 2012

2 700 박대길, 곽경민, 정완균, 그림 1. 거리에따른 (a) 공기와 (b) 수중에서의 RSSI 값의비교. Fig. 1. Value of RSSI according to the distance: (a) in air, and (b) in underwater. 대역의주파수를낮추는방법을사용할수있다. 그럼에도불구하고공기중과비교하여극히짧은센서간의통신가능거리때문에실제로수중위치추정은매우어려운일이며, 이를극복하기위하여센서의작동범위를고려한 UWSN 을구성함으로서, 보다넓은영역에서위치추정을하려한다. 본논문에서는이러한 UWSN 을이용한위치추정을위하여 UWSN 방법중하나인구조화된영역에서의위치추정 (Infrastructure-based localization) 을수조에구성함으로서, UWSN 을이용한위치추정이가능한지를실험으로확인하고자한다. 먼저 II 장에서는구조화된영역에서의위치추정방법및관련이론을설명하고거리추정기법중하나인 RSSI 를이용한위치추정방법을소개하며, 또한 UWSN을구성하기위한센서모델, 다중주파수채널사용및노드구성방법에대해서설명한다. III 장에서는실제수조에서알루미늄프레임을이용하여실험환경을구성하고실험을통하여실험환경에서의위치추정실험및실험결과에대해고찰한다. 마지막으로 IV 장에서는결론및앞으로의연구방향에대해설명하고자한다. II. 본론 1. UWSN을이용한위치추정방법기존의 UWSN 을이용한위치추정을하는방법에는크게센서사이의거리(range) 와방향(bearing) 을측정하여위치추정에이용하는 Range-based method와거리및방향을이용하지않는 Range-free method 으로나눌수있다. Range-based method 는노드(node) 간의정확한거리또는 각도를측정하여 UWSN 에서의노드사이의위치를추정하는방법이다. 이방법은정교한위치추정을할수있으나, 방법이 range-free method에비하여복잡하고더많은정보가요구된다는단점이있다. 노드사이의거리및각도를측정하기위해서는 Time of Arrival(ToA), Time Difference of Arrival(TDoA), Angle of Arrival(AoA), RSSI 등이사용된다. Range-based method는노드들의자유도및절대위치를알고있는노드의수에따라서구조화된영역에서의위치추정(infrastructure based localization), 분배된노드에서의위치추정(distributed positioning localization), 모바일노드에서의위치추정(localization that use mobile beacons) 으로분류할수있다 [5]. 이와반대로 Range-free method는노드사이의거리또는각도를사용하지않고, 위상학(topological) 이나기하학 (geometric) 등을이용하여위치추정을하는방법이다. 이방법은거리나방향정보를요구하지않으며매우간단하다는장점이있으나, 정밀한위치추정이어렵다는단점이있다. 대표적인기법으로 Centroid localization [6], DV-Hop [7], Density aware Hop-count localization [8] 등이있다. Range-free method 는크게홉수(hop-count) 를이용하여위치추정을하는홉수기반위치추정방법 (hop-count based localization) 과주어지는정보로영역을나누어위치추정을하는영역기반위치추정(area-based localization) 으로분류할수있다 [9]. 2. 구조화된영역에서의위치추정본논문에서사용한위치추정방법은구조화된영역에서의위치추정이다. 이는 range-based method 중하나로서, 고정된노드(fixed node) 들의위치를정확히알고있을때, 움직이는모바일노드(mobile node) 와고정된노드간의 RSSI 정보를가지고삼각측량법을사용하여위치를추정한다. 2.1 RSSI 를이용한거리추정기법 RSSI을이용한거리추정기법은송신노드에서송신된전자기파가거리에따라매질에흡수및산란되어신호세기가감쇠되는현상을이용하여거리를추정하는방법이다. RSSI 기법은크게센서모델을세워거리를추정하는방법과학습을통해 Radio map [8] 을만들어거리추정에이용하는방법으로나눌수있다. 그림 1에서볼수있듯이, 공기중( 그림 1(a)) 에서는거리에따른감쇠보다환경에의한불확실성이크기때문에 Radio map을이용한방법을많이사용한다. 하지만수중에서는그림 1(b) 와같이불확실성이적기때문에다항식을이용한센서모델로표현할수있다. 수중에서의센서모델은 3.1.1에서다룰것이다 [4,12]. 2.2 삼각측량법삼각측량방법은다수의거리센서들로부터얻어지는거리값을이용해위치추정을하는방법이다. 그림 2 와같이, 고정된노드와모바일노드사이의거리값을얻을수있을때, 고정된노드에서얻어진하나의거리값으로부터알수있는모바일노드의평면상의위치는거리 d만큼떨어진원의형태로나타난다. 이때고정된노드 와모바일노드 사이의거리모델은

3 구조화된공간에서의수중무선센서네트워크를이용한위치추정시스템 701 그림 2. 삼각측량법. Fig. 2. Triangulation. (1) 와같이나타낼수있다. 이때실제노드로부터얻어지는거리값 d 에는에러가포함되어있는경우가많은데, 이경우최소자승법(least square method) 을이용하여각노드간의거리값 d 의에러를최소화시키는위치를추정한다. 이때타깃의위치를추정하기위해서는 3개이상의고정된노드가필요하며, 3차원공간상에서는 4개이상의고정된노드가필요하다. 3. RSSI방식의위치추정을위한 UWSN의구성 RSSI 방식위치추정을위해서신호의세기를이용하여두노드사이의거리를추정할수있도록거리추정기법을제시해야하며, 각다중노드에서송신된신호의세기를수신노드에서구분할수있도록신호의세기가중첩되지않아야한다. 이를위해서우리는매질을고려한센서모델을사용하고다중주파수채널을이용하여신호가중첩되지 않도록 UWSN 을구성하였다. 3.1 센서모델 RSSI 값은두노드사이의거리뿐만이아니라매질및안테나의특성과주파수의영향을받는다. 공기중의센서모델은 Friis Transmission Formula [11] 을사용하나, 이는매질이공기이고, 무지향성안테나일경우에만적용이가능하기때문에수중환경에서적용하기부적절하다. 따라서본논문에서는매질에따른감쇠특성이고려된센서모델을사용하였다[12]. 송신노드에서송신된신호세기 (dbm) 에따른수신노드에서의신호세기 (dbm) 은식 (1), (2) 와같이나타낼수있다. 그림 3. 실험데이터와제시된센서모델의비교 [12]. Fig. 3. Comparison between Experiment and Sensor model [12]. 는미소에러변수이다. 그림 3은제시한센서모델과실험데이터를비교한그래프이다[12]. 이그림에서센서모델은실험데이터와비슷한감쇠경향을가지는것을확인할수있었다. 3.2 무지향성안테나를이용한 UWSN 노드구성무지향성안테나(omnidirectional antenna) 는그림 4와같이기본적으로앙각에대해서는지향성을가지고있으나방위에대해서는원형에가까운무지향성을나타내는안테나를말하며, 대표적으로다이폴안테나가있다. 무지향성안테나는이러한특성때문에평면상의같은거리에있는노드로부터같은세기의 RSSI 값을얻을수있다. 하지만, log (2) log log log (3) 여기서, 은각각송신및수신안테나게인 (db),,, 는각각주파수, 매질의굴절률, 빛의속도를나타내며 그림 4. 무지향성안테나의전파특성. Fig. 4. Propagation property of omnidirectional antenna [12].

4 702 박대길, 곽경민, 정완균, 송신노드와수신노드사이에평행이이루어지지않으면두노드사이의각의크기에따라수신신호의세기가감소한다. 이경우 RSSI을이용한거리추정오차가커지기때문에각노드의안테나들이평행을유지하도록해야한다. 3.3 다중주파수채널을이용한 RSSI 측정평면상의위치추정을위해서는 3개이상의고정된노드에서송신된신호를하나의모바일노드에서수신해야한다. 이때각노드의송신주파수가같을경우, 신호가중첩되어송신노드를알수없을뿐만아니라신호의중첩으로인하여추정거리의오차가생기게된다. 이러한신호의중첩을방지하고다중노드로부터거리를추정하기위하여각노드마다다른주파수의채널을할당하였다. 그림 5는다른채널을이용한두개의노드로부터송신된신호를받았을때의 RSSI 그래프이다. 이렇게수신된신호의세기를제시한주파수채널에따라센서모델에각각대입하여고정노드와모바일노드간의거리를추정하고, 얻어진노드사이의거리를이용하여삼각측량법으로모바일노드의위치를추정한다 [13]. 분석기(NI5660 signal analyzer) 를사용하였다. 실험시의송신전력은 10 mw 이며, 이때의송신주파수는 420 MHz 이다. 각노드들의배치는그림 6(b) 와같다. 시험대가장자리의노드들은지정된위치에고정시켰으며, 고정된노드들은전자기파생성기로부터각기다른주파수의전자기파를송신한다. 각노드간의거리는알고있다고가정하였다. 시험대의가운데에는위치를알고자하는모바일노드를배치하였으며, 모바일노드는전자기파분석기와연결되어수신된전자기파의세기를측정한다. 이때실험결과와비교하기위하여모바일노드의위치를측정하였다. 실험에사용된안테나와물의특성값은표 1 과같다. III. 실험및결과 1. 구조화된환경의설치구조화된수중센서네트워크를구성하기위하여, 가로 12 m, 세로 8 m, 깊이 6 m 의한국로봇융합연구원(KIRO) 지하공학수조에실험공간을설치하였다 ( 그림 6(a)). 수중센서네트워크환경은알루미늄프레임을사용하여구성하였으며, 시험대의너비 2.5 m, 길이 6 m 로제작하였다. 안테나의경우물에서사용하기위해서방수처리를하였으며, 무지향성안테나로부터안정된 RSSI 값을얻기위해그림 7과같이알루미늄을이용한안테나프레임을제작하였다. 안테나프레임은시험대위에서자유롭게이동이가능하도록제작하였으며, 안테나는프레임의중앙에고정될수있도록설계하였다. 이때수면으로부터안테나의끝단까지의깊이는 150 cm 이다. 또한전자기파의생성및전자기파의세기를측정하기위하여전자기파생성기 (NI5670 signal generator) 와전자기파 (a) (b) 그림 6. 구조화된환경의설치. Fig. 6. Setup the infrastructure-based localization. 그림 5. 동일한거리에서수신한다중주파수채널의신호강도. Fig. 5. Received signal strength of multi frequency channel at same distance. 표 1. 실험환경에서의환경특성. Table 1. Characteristics of experiment environment. 변수 변수값 안테나의송신게인 안테나 안테나의수신게인 송신파워 송신주파수 실험수조특성( 민물) 전기전도도투자율유전율굴절률

5 구조화된 공간에서의 수중 무선 센서 네트워크를 이용한 위치 추정 시스템 2. 실험과정 실험 과정은 송신 노드와 수신 노드를 원하는 위치에 배 치한 후, 각 안테나간의 거리와 시험대와의 거리를 정밀한 도구로 측정하여 각 안테나의 실제 위치를 기록한다. 그 후, 시험대 가장자리의 4개의 고정된 노드에서 동일한 세기 의 전자기파를 송신하였으며, 모바일 노드에서는 안테나를 통해 각 노드에서 송신된 신호의 RSSI 값을 측정하여 센서 모델을 통해 거리 정보를 얻고, 거리 정보를 이용하여 최소 자승법으로 모바일 노드의 위치 추정을 한다. 마지막으로 추정된 위치와 실제 위치간의 비교를 통하여 UWSN의 가 능성을 확인하였다. 3. 실험결과 및 고찰 총 4번에 걸쳐 모바일 노드의 위치를 변경하며 실험하였 으며, 각 실험 조건 및 실험결과는 그림 8 및 표 2와 같다. 표 2에서 최대 오차와 최소 오차란 각각 실제 위치와 추정 위치간 거리가 가장 클 때와 가장 작을 때의 오차 거리를 나타낸다. 또한 RMS 오차(root mean square error)란 추정된 위치와 실제 위치간의 오차를 제곱하여 더한 제곱근의 평 균을 말하며, 추정 위치와 실제 위치의 평균적인 오차를 표 현한다. 표 2에서 볼 수 있듯이 4번의 실험 모두에서 추정 된 위치가 실제 위치와 거의 비슷한 결과 값을 얻는 것을 확인할 수 있었으며, RMS 오차 및 최대-최소 오차 역시 만 족할만한 결과를 얻는 것을 확인할 수 있었다. 다만, 그림 8을 보면, 실험 1~3에서는 공분산이 추정위치를 기준으로 정규분포를 따르는 것을 확인할 수 있으나, 실험 4에서는 공분산 값이 추정위치를 기준으로 2개의 부분으로 나누어 지는 것을 확인할 수 있었다. 이는 그림 3에서 나타나는 센 서 모델과 실제 실험 데이터간의 차이로 인하여 나타나는 바이어스 에러가 심하게 나타나는 경우로 볼 수 있다. 그림 7. 안테나 및 안테나 프레임 설계. Fig. 7. Antenna and Antenna frame design. 표 2. 실험 조건 및 결과. Table 2. Experiment condition and result. 실제위치 추정위치 최대오차 최소오차 RMS오차 실험 m m m 실험 m m m 실험 m 0.005m m 실험 m m m 그림 8. 위치 추정 실험 결과. Fig. 8. Localization experiment result. 703

6 704 박대길, 곽경민, 정완균, IV. 결론본논문에서는수중센서네트워크를이용한수중위치추정가능성에대해서알아보고, RSSI 방식의위치추정을위한 UWSN 구성방법에대해서설명하였다. 또한, 실제로구성한센서네트워크를이용하여수중위치추정을실험하였으며, 실험을통해구조화된영역에서 UWSN 을이용한만족스러운위치추정결과를얻을수있었다. 추후 3차원공간에서위치추정이가능하도록안테나특성을고려한 UWSN 기법에대한연구를지속적으로수행할계획이다. 참고문헌 [1] T. K. Yang, W. Y. Choi, and J. M. Lee, Localization of multiple robots in a wide area Journal of Institute of Control, Robotics and Systems (in Korean), vol 16, no. 3, pp , Mar [2] Y.-H. Kim, U. K. Song, and B. K. Kim, Development of precise localization system for autonomous mobile robots using multiple ultrasonic transmitters and receivers in indoor environments Journal of Institute of Control, Robotics and Systems (in Korean), vol 17, no. 4, pp , Apr [3] K. Yedavalli, B. Krishnamachari, S. Ravula, and B. Srinivasan, Ecolocation: a sequence based technique for rf localization in wireless sensor networks, in Proc. of 4th International Symposium on Information Processing in Sensor Networks, New Jersey, USA, no. 38, pp , [4] S.-J. Lee, K. M. Kwak, and J. Kim, Development of two dimensional underwater localization system using rf sensors, in Proc. The 7th International Conference on Ubiquitous Robots and Ambient Intelligence 2010, Busan, Korea, pp , Oct [5] V. Chandrasekhar, W. K. G. Seah, Y. S. Choo, and H. V. Ee, Localization in underwater sensor networkssurvey and challenges, in Proc. The 1st ACM international workshop on Underwater network 2006, New York, USA, pp , [6] N. Bulusu, J. Heidemann, and D. Estrin, GPS-less low cost outdoor localization for very small devices, IEEE Personal Communications Magazine, vol. 7, no. 5, pp , Oct [7] D. Niculescu and B. Nath, DV based positioning in Ad Hoc networks, Telecommunication Systems, vol. 22, no. 1-4, pp , [8] S. Y. Wong, J. G. Lim, S. V. Rao, and W. K. G. Seah, Multihop localization with density and path length awareness in non-uniform wireless sensor networks, Proceedings of the 61st IEEE Vehicular Technology Conference, Stockholm, Sweden, May 30-Jun 1, [9] J. Heidemann, Y. Li, A. Syed, J. Wills, and W. Ye, Research challenges and applications for underwater sensor networking, Proc. of the IEEE Wireless Communications and Networking Conference (WCNC 2006), Las Vegas, USA, April 3-6, [10] P. Bahl and V. N. Padmanabhan, RADAR: An in-building RF-based user location and tracking system, IEEE INFOCOM, vol. 2, pp , Mar [11] D. C. Hogg, Fun with the friis free-space transmission formula, IEEE Antennas Propagat. Mag., vol. 35, no. 4, pp , [12] D. Park, K. Kwak, W. K. Chung, and J. Kim, Development of underwater distance sensor using EM wave attenuation, IROS 2012 Submitted. [13] K. M. Kwak and J. Kim, Feasibility of obtaining multi channel sensor nodes' distance data using RSSI, Proc. of the KAMES 2011 Joint Symposium, Daegu, Korea, pp , Nov 박대길 2011년서울과학기술대학교기계공학 과학사 년~ 현재포항공과대학교 기계공학과석박통합과정재학중. 관 심분야는 Underwater Sensors, SLAM, Underwater Localization, Underwater Robots. 곽경민 2011년서울과학기술대학교기계공학과학사 년~ 현재서울과학기술대학교기계공학과석사과정재학중. 관심분야는 Underwater Localization with RSSI, Underwater Robots. 정완균 1981 년서울대학교기계설계학과학사 년한국과학기술원기계공학석사 년한국과학기술원로봇공학박사 년~1993년 POSTECH 기계공학과조교수. 1988년 CMU 방문교수 년 U.C.Berkeley visiting scholar 년~2000년 POSTECH 기계공학과부교수 년~ 현재 POSTECH 기계공학과정교수 년~ 현재 IEEE Transactions on Robotics Editor. 관심분야는 SLAM, Navigation, Underwater robots, Medical Robotics, Minimally Invasive Surgery, Robust Controller.

7 구조화된공간에서의수중무선센서네트워크를이용한위치추정시스템 년포항공과대학교기계공학과학사. 2000년포항공과대학교기계공학과석사. 2005년포항공과대학교기계공학과공학박사 년~2007년한국생산기술연구원선임연구원 년~ 현재서울과학기술대학교기계공학과조교수. 관심분야는 Redundant Manipulator, Underwater robots, Hovering robots, Neuro Robotics.

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