Quantizer Design for Energy-Based Source Localization in Sensor Networks

We consider energy-based source localization applications, where distributed sensors quantize acoustic signal energy readings and transmit quantized data to a fusion node, which then produces an estimate of the source location. We propose an iterative quantizer design algorithm that allows us to take into account localization accuracy for quantizer design in the framework of the generalized Lloyd algorithm. Since source coding methodologies based on the Lloyd algorithm suffer from the presence of numerous poor local optima depending on initialization of quantizers, we introduce an efficient initialization, the equally distance-divided quantizer (EDQ), designed so that quantizer partitions correspond to a uniform partitioning in terms of distance. Our simulations demonstrate that improved performance over traditional quantizer designs can be achieved by using our proposed application specific strategy.

[1]  Peter Willett,et al.  Asymptotic Design of Quantizers for Decentralized MMSE Estimation , 2007, IEEE Transactions on Signal Processing.

[2]  Pramod K. Varshney,et al.  Target Location Estimation in Wireless Sensor Networks Using Binary Data , 2004 .

[3]  G. Pottie,et al.  Entropy-based sensor selection heuristic for target localization , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[4]  Antonio Ortega,et al.  Maximum a Posteriori (MAP)-Based Algorithm For Distributed Source Localization Using Quantized Acoustic Sensor Readings , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[5]  Robert M. Gray.  Quantization in Task-Driven Sensing and Distributed Processing , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[6]  Kenneth Rose,et al.  Robust Distributed Source Coder Design by Deterministic Annealing , 2010, IEEE Transactions on Signal Processing.

[7]  Feng Zhao,et al.  Information-driven dynamic sensor collaboration , 2002, IEEE Signal Process. Mag..

[8]  Kung Yao,et al.  Source localization and beamforming , 2002, IEEE Signal Process. Mag..

[9]  Vivek K. Goyal,et al.  High-Resolution Functional Quantization , 2008, Data Compression Conference (dcc 2008).

[10]  P.K. Varshney,et al.  Target Location Estimation in Sensor Networks With Quantized Data , 2006, IEEE Transactions on Signal Processing.

[11]  Maurizio Longo,et al.  Quantization for decentralized hypothesis testing under communication constraints , 1990, IEEE Trans. Inf. Theory.

[12]  G.B. Giannakis,et al.  Distributed compression-estimation using wireless sensor networks , 2006, IEEE Signal Processing Magazine.

[13]  Antonio Ortega,et al.  Quantizer design for source localization in sensor networks , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[14]  Pramod K. Varshney,et al.  Near-optimum quantization for signal detection , 1996, IEEE Trans. Commun..

[15]  ZhaoFeng,et al.  Collaborative in-network processing for target tracking , 2003 .

[16]  Urbashi Mitra,et al.  Application-specific compression for time delay estimation in sensor networks , 2003, SenSys '03.

[17]  Mikael Skoglund,et al.  Distributed quantization over noisy channels , 2009, IEEE Transactions on Communications.

[18]  Antonio Ortega,et al.  Joint compression-classification with quantizer/classifier dimension mismatch , 2000, IS&T/SPIE Electronic Imaging.

[19]  Antonio Ortega,et al.  Entropy- and complexity-constrained classified quantizer design for distributed image classification , 2002, 2002 IEEE Workshop on Multimedia Signal Processing..

[20]  Yu Hen Hu,et al.  Detection, classification, and tracking of targets , 2002, IEEE Signal Process. Mag..

[21]  Yunmin Zhu,et al.  An efficient sensor quantization algorithm for decentralized estimation fusion , 2011, Autom..

[22]  Amy R. Reibman,et al.  Design of quantizers for decentralized estimation systems , 1993, IEEE Trans. Commun..

[23]  Robert M. Gray,et al.  Encoding of correlated observations , 1987, IEEE Trans. Inf. Theory.

[24]  Ruzena Bajcsy,et al.  The Sensor Selection Problem for Bounded Uncertainty Sensing Models , 2005, IEEE Transactions on Automation Science and Engineering.

[25]  Deepak S. Turaga,et al.  QUANTization for Adapted GMM-Based Speaker Verification , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[26]  Antonio Ortega,et al.  Distributed Encoding Algorithm for Source Localization in Sensor Networks , 2010, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[27]  Antonio Ortega,et al.  Quantizer design and distributed encoding algorithm for source localization in sensor networks , 2005, IPSN.

[28]  Pascal Frossard,et al.  Signal Processing Challenges in Distributed Stream Processing Systems , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[29]  Yu Hen Hu,et al.  Energy-Based Collaborative Source Localization Using Acoustic Microsensor Array , 2003, EURASIP J. Adv. Signal Process..

[30]  Antonio Ortega,et al.  Efficient scalable encoding for distributed speech recognition , 2006, Speech Commun..

[31]  Feng Zhao,et al.  Collaborative In-Network Processing for Target Tracking , 2003, EURASIP J. Adv. Signal Process..

[32]  Kannan Ramchandran,et al.  Distributed source coding using syndromes (DISCUS): design and construction , 2003, IEEE Trans. Inf. Theory.

[33]  Biplab Sikdar,et al.  A protocol for tracking mobile targets using sensor networks , 2003, Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, 2003..

[34]  R. Ladner.  Entropy-constrained Vector Quantization , 2000 .

[35]  Antonio Ortega,et al.  Distributed algorithms for source localization using quantized sensor readings , 2007 .

[36]  Sanjit K. Mitra,et al.  Optimal variable-rate mean-gain-shape vector quantization for image coding , 1996, IEEE Trans. Circuits Syst. Video Technol..