Channel Aware Target Localization in Multi-hop Wireless Sensor Networks
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摘要: 针对资源有限、存在信道退化的无线传感器网络(Wireless sensor network, WSN),基于最大似然估计(Maximum-likelihood estimation, MLE)提出一种信道感知的目标定位方法. 把传感器观测数据量化为M位二进制序列,经过衰落信道多跳中继到达融合中心. 中继节点采用二元解码-前向中继策略,中继输出是被信道污染的中继信号的估计值. 在Rayleigh信道衰落和高斯信道噪声假设下,结合无线信道衰落的统计知识和解码策略, 推导了观测数据的似然函数,得到目标位置的最大似然估计. 此外,还推导了估计器性能的后验克拉美-罗下界(Cramr-Rao lower bounds, CRLB). 仿真结果表明,信道感知的方法能够减缓由于信道衰落和噪声所带来的定位性能的退化.Abstract: In this paper, a novel channel aware target localization approach is proposed for channel-faded and resource-constrained wireless sensor network (WSN) based on maximum-likelihood estimation (MLE). The measurements from local sensor are quantized and coded to an M-bit data, then relayed through multi-hop fading channels to reach a fusion center. Each relay node employs a binary decode-and-forward relay scheme where the relay output is inferred from the channel impaired observation received from its source node. The observation likelihood function is derived which incorporates wireless channel statistics as well as decoding scheme characteristics. The target location is estimated based on maximum-likelihood method. Furthermore, we derive the Cramr-Rao lower bound (CRLB) for our proposed channel-aware localization method. Simulation results are presented to show that the channel-aware approach can mitigate the performance degradation caused by the channel imperfection.
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[1] Yao K. Sensor networking: concepts, applications, and challenges. Acta Automatica Sinica, 2006, 32(6): 839-845 [2] Chong C Y, Kumar S P. Sensor networks: evolution, opportunities, and challenges. Proceedings of the IEEE, 2003, 91(8): 1247-1256 [3] Sayeed A, Estrin D, Pottie G, Ramchandran K, Pursley M B. Guest editorial self-organizing distributed collaborative sensor networks. IEEE Journal on Selected Areas in Communication, 2005, 23(4): 689-692 [4] Oshman Y, Davidson P. Optimization of observer trajectories for bearings-only target localization. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(3): 892-902 [5] Kaplan L M, Le Q, Molnar N. Maximum likelihood methods for bearings-only target localization. In: Proceedings of the 2001 IEEE International Conference on Acoustics, Speech, and Signal (ICASSP 2001), Salt Lake City, USA: IEEE, 2001 [6] Dvorkind T G, Gannot S. Time difference of arrival estimation of speech source in a noisy and reverberant environment. Signal Processing, 2005, 85(1): 177-204 [7] Doclo S, Moonen M. Robust adaptive time delay estimation for speaker localization in noisy and reverberant acoustic environments. EURASIP Journal on Advances in Signal Processing, 2003, 2003(11): 1110-1124 [8] Sheng X H, Hu Y H. Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks. IEEE Transactions on Signal Processing, 2005, 53(1): 44-53 [9] Niu R X, Varshney P K. Target location estimation in sensor networks with quantized data. IEEE Transactions on Signal Processing, 2006, 54(12): 4519-4528 [10] Meesookho C, Mitra U, Narayanan S. On energy-based acoustic source localization for Sensor networks. IEEE Transactions on Signal Processing, 2008, 56(1): 365-377 [11] Katenka N, Levina E, Michailidis G. Robust Target Localization from Binary Decisions in Wireless Sensor Networks, Technical Report 452, Department of Statistics, University of Michigan, USA, 2007 [12] Masazade E, Niu R X, Varshney P K, Keskinoz M. Energy aware iterative source localization for wireless sensor networks. IEEE Transactions on Signal Processing, 2010, 58(9): 4824-4835 [13] Chen B, Jiang R X, Kasetkasem T, Varshney P K. Channel aware decision fusion in wireless sensor networks. IEEE Transactions on Signal Processing, 2004, 52(12): 3454-3458 [14] Niu R X, Chen B, Varshney P K. Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks. IEEE Transactions on Signal Processing, 2006, 54(3): 1018-1027 [15] Chen B, Tong L, Varshney P K. Channel-aware distributed detection in wireless sensor networks. IEEE Signal Processing Magazine, 2006, 23(4): 16-26 [16] Ozdemir O, Niu R X, Varshney P K. Tracking in wireless sensor networks using particle filtering: physical layer considerations. IEEE Transactions on Signal Processing, 2009, 57(5): 1987-199 [17] Ozdemir O, Niu R X, Varshney P K. Channel aware target localization with quantized data in wireless sensor networks. IEEE Transactions on Signal Processing, 2009, 57(3): 1190-1202 [18] Lin Y, Chen B, Varshney P K. Decision fusion rules in multi-hop wireless sensor networks. IEEE Transactions on Aerospace and Electronic Systems, 2005, 41(2): 475-488 [19] Tian Q J, Coyle E J. Optimal distributed detection in clustered wireless sensor networks. IEEE Transactions on Signal Processing, 2007, 55(7): 3892-3904 [20] Rahman R, Alanyali M, Saligrama V. Distributed tracking in multihop sensor networks with communication delays. IEEE Transactions on Signal Processing, 2007, 55(9): 4656-4668 [21] Yang Xiao-Jun, Xing Ke-Yi. Channel fault tolerant target tracking in multi-hop wireless sensor networks based on particle filtering. Acta Automatica Sinica, 2011, 37(4): 440-448 (杨小军, 邢科义. 无线多跳传感器网络下基于粒子滤波的信道容错的目标跟踪方法. 自动化学报, 2011, 37(4): 440-448) [22] Yang X J, Niu R X, Masazade E, Varshney P K. Channel aware target tracking in multi-hop wireless sensor networks. In: Proceedingss of the 14th International Conference on Information Fusion (FUSION 2011). Chicago, USA: IEEE, 2011. 1-8 [23] Yang X J, Niu R X, Masazade E, Varshney P K. Channel-aware tracking in multi-hop wireless sensor networks with quantized measurements. IEEE Transactions on Aerospace and Electronic Systems, to be published [24] Al-Karaki J N, Kamal A E. Routing techniques in wireless sensor networks: a survey. IEEE Wireless Communications, 2004, 11(6): 6-28 [25] Liu J, Feng Z, Petrovic D. Information-directed routing in ad hoc sensor networks. IEEE Journal on Selected Areas in Communications, 2005, 23(4): 851-861 [26] Wu X B, Chen G H, Das S K. Avoiding energy holes in wireless sensor networks with nonuniform node distribution. IEEE Transactions on Parallel and Distributed Systems, 2008, 19(5): 710-720 [27] Nowak R D. Distributed EM algorithms for density estimation and clustering in sensor networks. IEEE Transactions on Signal Processing, 2003, 51(8): 2245-2253 [28] Tong Z, Nehorai A. Information-driven distributed maximum likelihood estimation based on Gauss-Newton method in wireless sensor networks. IEEE Transactions on Signal Processing, 2007, 55(9): 4669-4682
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