A scheme for robust distributed sensor fusion based on average consensus Export

@proceedings{XiaoBoydLall_05, abstract = {We consider a network of distributed sensors, where where each sensor takes a linear measurement of some unknown parameters, corrupted by independent Gaussian noises. We propose a simple distributed iterative scheme, based on distributed average consensus in the network, to compute the maximum-likelihood estimate of the parameters. This scheme doesn't involve explicit point-to-point message passing or routing; instead, it diffuses information across the network by updating each node's data with a weighted average of its neighbors' data (they maintain the same data structure). At each step, every node can compute a local weighted least-squares estimate, which converges to the global maximum-likelihood solution. This scheme is robust to unreliable communication links. We show that it works in a network with dynamically changing topology, provided that the infinitely occurring communication graphs are jointly connected.}, author = {Xiao, L. and Boyd, S. and Lall, S.}, booktitle = {Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on}, citeulike-article-id = {3431167}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/IPSN.2005.1440896}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1440896}, doi = {10.1109/IPSN.2005.1440896}, journal = {Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on}, keywords = {consensus, distributed\_sensor\_fusion, stochastic\_consensus}, pages = {63--70}, posted-at = {2008-10-20 16:29:12}, priority = {2}, title = {A scheme for robust distributed sensor fusion based on average consensus}, url = {http://dx.doi.org/10.1109/IPSN.2005.1440896}, year = {2005} }

TY - CONF ID - XiaoBoydLall_05 L3 - citeulike-article-id:3431167 N2 - We consider a network of distributed sensors, where where each sensor takes a linear measurement of some unknown parameters, corrupted by independent Gaussian noises. We propose a simple distributed iterative scheme, based on distributed average consensus in the network, to compute the maximum-likelihood estimate of the parameters. This scheme doesn't involve explicit point-to-point message passing or routing; instead, it diffuses information across the network by updating each node's data with a weighted average of its neighbors' data (they maintain the same data structure). At each step, every node can compute a local weighted least-squares estimate, which converges to the global maximum-likelihood solution. This scheme is robust to unreliable communication links. We show that it works in a network with dynamically changing topology, provided that the infinitely occurring communication graphs are jointly connected. JF - Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on EP - 70 TI - A scheme for robust distributed sensor fusion based on average consensus T2 - Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on SP - 63 KW - consensus KW - distributed_sensor_fusion KW - stochastic_consensus AU - Xiao, L AU - Boyd, S AU - Lall, S PY - 2005/// UR - http://dx.doi.org/10.1109/IPSN.2005.1440896 ER -