Detection, classification, and tracking of targets

Networks of small, densely distributed wireless sensor nodes are being envisioned and developed for a variety of applications involving monitoring and the physical world in a tetherless fashion. Typically, each individual node can sense in multiple modalities but has limited communication and computation capabilities. Many challenges must be overcome before the concept of sensor networks In particular, there are two critical problems underlying successful operation of sensor networks: (1) efficient methods for exchanging information between the nodes and (2) collaborative signal processing (CSP) between the nodes to gather useful information about the physical world. This article describes the key ideas behind the CSP algorithms for distributed sensor networks being developed at the University of Wisconsin (UW). We also describe the basic ideas on how the CSP algorithms interface with the networking/routing algorithms being developed at Wisconsin (UW-API). We motivate the framework via the problem of detecting and tracking a single maneuvering target. This example illustrates the essential ideas behind the integration between UW-API and UW-CSP algorithms and also highlights the key aspects of detection and localization algorithms. We then build on these ideas to present our approach to tracking multiple targets that necessarily requires classification techniques becomes a reality.

[1]  Douglas L. Jones,et al.  Optimal detection using bilinear time-frequency and time-scale representations , 1995, IEEE Trans. Signal Process..

[2]  Arogyaswami Paulraj,et al.  Space-time processing for wireless communications , 1997 .

[3]  Akbar M. Sayeed Data-driven time-frequency and time-scale detectors , 1997, Optics & Photonics.

[4]  Kung Yao,et al.  Blind beamforming on a randomly distributed sensor array system , 1998, IEEE J. Sel. Areas Commun..

[5]  James F. Scholl,et al.  Seismic Attenuation Characterization Using Tracked Vehicles , 1999 .

[6]  Kung Yao,et al.  Direct joint source localization and propagation speed estimation , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[7]  Gregory J. Pottie,et al.  Self-organizing distributed sensor networks , 1999, Defense, Security, and Sensing.

[8]  James F. Scholl,et al.  Low-power impulse signal classifier using the Haar wavelet transform , 1999, Other Conferences.

[9]  Akbar M. Sayeed,et al.  Canonical space-time processing for wireless communications , 2000, IEEE Trans. Commun..

[10]  Jonathan R. Agre,et al.  An Integrated Architecture for Cooperative Sensing Networks , 2000, Computer.

[11]  Gregory J. Pottie,et al.  Instrumenting the world with wireless sensor networks , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[12]  Jeff Sherman,et al.  A Distributed Time-Difference of Arrival Algorithm for Acoustic Bearing Estimation , 2001 .

[13]  Péter Molnár,et al.  Maximum likelihood methods for bearings-only target localization , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[14]  Randolph L. Moses,et al.  SELF-CALIBRATION OF UNATTENDED GROUND SENSOR NETWORKS , 2001 .

[15]  Kung Yao,et al.  A maximum-likelihood parametric approach to source localizations , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[16]  S. Phoha,et al.  Semantic Information Fusion for Coordinated Signal Processing in Mobile Sensor Networks , 2002, Int. J. High Perform. Comput. Appl..

[17]  Richard R. Brooks,et al.  Self-Organized Distributed Sensor Network Entity Tracking , 2002, Int. J. High Perform. Comput. Appl..

[18]  Feng Zhao,et al.  Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks , 2002, Int. J. High Perform. Comput. Appl..

[19]  Richard R. Brooks,et al.  Traffic Model Evaluation of Ad Hoc Target Tracking Algorithms , 2002, Int. J. High Perform. Comput. Appl..