Collaborative In-Network Processing for Target Tracking Export

@article{liu-etal-eurasip02, abstract = {This paper presents a class of signal processing techniques for collaborative signal processing in ad hoc sensor networks, focusing on a vehicle tracking application. In particular, we study two types of commonly used sensors-- acoustic-amplitude sensors for target distance estima-tion and direction-of-arrival sensors for bearing estimation-- and investigate how networks of such sensors can collaborate to extract useful information with minimal resource usage. The information-driven sensor collaboration has several advantages: the tracking is distributed; the network is energy-efficient, and is activated only on a when-needed basis. We demonstrate the effectiveness of the approach to target tracking using both simulation and field data.}, author = {Liu, Juan and Reich, James and Feng}, citeulike-article-id = {3680373}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.3649}, journal = {EURASIP Journal on Applied Signal Processing}, keywords = {networks, sensor, tracking}, pages = {378--391}, posted-at = {2008-11-24 08:31:27}, priority = {2}, title = {Collaborative In-Network Processing for Target Tracking}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.3649}, volume = {4}, year = {2003} }

TY - JOUR ID - liu-etal-eurasip02 L3 - citeulike-article-id:3680373 N2 - This paper presents a class of signal processing techniques for collaborative signal processing in ad hoc sensor networks, focusing on a vehicle tracking application. In particular, we study two types of commonly used sensors-- acoustic-amplitude sensors for target distance estima-tion and direction-of-arrival sensors for bearing estimation-- and investigate how networks of such sensors can collaborate to extract useful information with minimal resource usage. The information-driven sensor collaboration has several advantages: the tracking is distributed; the network is energy-efficient, and is activated only on a when-needed basis. We demonstrate the effectiveness of the approach to target tracking using both simulation and field data. JF - EURASIP Journal on Applied Signal Processing EP - 391 TI - Collaborative In-Network Processing for Target Tracking VL - 4 SP - 378 KW - networks KW - sensor KW - tracking AU - Liu, Juan AU - Reich, James AU - Feng PY - 2003/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.3649 ER -