基于粒子群优化和M-H抽样粒子滤波的传感器网络目标跟踪方法

doi:10.3969/j.issn.1000-436x.2013.11.002

Abstract

Abstract:

For the characteristic of the nonlinear relationship between the observation information of sensor nodes and the target dynamic parameters under the real application conditions, a target tracking algorithm for wireless sensor networks based on particle swarm optimization and Metropolis-Hasting sampling particle filter was proposed. Distributed archi-tecture is adopted in this target tracking scheme. And under the dynamic network topology, particle swarm optimization and Metropolis-Hasting sampling are introduced into the resampling period to reduce sample degeneracy. In order to achieve the goal of high-precision tracking performance, the history information is shared among the particles to reduce the correlation between the history states of a single particle, so that the particles can rapidly converge to an optimal dis-tribution. The simulations corroborate that compared with currently existing target tracking schemes based on the tech-nology of information particle filter and parallel particle filter, the proposed scheme can reduce the total energy consump-tion, while ensuring the accuracy of target tracking.

Key words: particle swarm optimization, metropolis-hasting sampling, particle filter, target tracking

Peng JIANG,Hua-hua SONG,Guang LIN. Target tracking algorithm for wireless sensor networks based on particle swarm optimization and metropolis-hasting sampling particle filter[J]. Journal on Communications, 2013, 34(11): 8-17.

Figures/Tables 11

操作	能量消耗
发送电路E_Tx?elec
接收电路E_Rx?elec	50nJ/bit
E_Tx?elec=E_Rx?elec=E_elec
发送放大器E_amp	100pJ/bit/m²
程序执行器E_Rf	N_c×C× $V_{d d}^{2}$

参数名称	符号	取值	参数名称	符号	取值
监测区域	m×n	400m×400m	方差	$s_{0}^{2}$	1
节点数目	N	256	增益因子	g	±30%
感知半径	Rs	60m	衰减因子	x	2.2
通信半径	Rc	75m	传感器抽样次数	N_sam	1 000
初始状态	x₀	[-45 -20 -50 -35]^T	非线性常量	c	1.5
参数	a	180	粒子总数	N_p	400
步长	T	0.04	系统参量	j₁	2
控制参数	c₁	0.75	系统参量	j₂	2
控制参数	c₂	1	Burn-in period	B	20
控制常量	q	0.002	MCMC迭代次数	J	50

References 16

[1]	MUSICKI D , KAUNE R , KOCH W . Mobile emitter geolocation and tracking using TDOA and FDOA measurements[J]. IEEE Tra ions on Signal Processing, 2010,58 (3): 1863-1874.
[2]	CHEN J , SALIM M B , MATSUMOTO M . A single mobile target tracking in voronoi-based clustered wireless sensor network[J]. Journal of Information Processing Systems, 2011,7 (1): 17-28.
[3]	SCHMID J , BEUTLER F , NOACK B , et al. An Experimental Evalua-tion of Position Estimation Methods for Person Localization in Wire-less Sensor Networks[M]. Bonn:Springer Berlin Heidelberg, 2011.
[4]	KUMAR S , PRAKASH J , KANAGASABAPATHY P . A Critical Evaluation and Experimental Verification of Extended Kalman Filter, Unscented Kalman Filter and Neural State Filter for State Estimation of Three Phase Induction Motor[J]. Applied Soft Computing, 2011,11 (3): 3199-3208.
[5]	OKA A , LAMPE L . Distributed target tracking using signal strength measurements by a wireless sensor network[J]. IEEE Jou l on Se-lected Areas in Communications, 2010,28 (7): 1006-1015.
[6]	USTEBAY D , COATES M , RABBAT M . Distributed auxiliary par-ticle filters using selective gossip[A]. IEEE Internatio l Conference on Acoustics, Speech and Signal Processing[C]. Prague, Czech Re-public, 2011.3296-3299.
[7]	MURANGIRA A , MUSSO C , DAHIA K , et al. Robust regularized particle filter for terrain navigation[A]. The 14th International Confe-rence on Information Fusion[C]. Chicago, USA, 2011.1-8.
[8]	CARLONE L , NG M K , DU J , et al. Simultaneous localization and mapping using rao-blackwellized particle filters in multi-robot sys-tems[J]. Journal of Intelligent ＆ Robotic Systems, 2011,63 (2): 283-307.
[9]	邹冈，石章松，刘忠 . 传感器网络中的分布式粒子滤波被动跟踪算法比较研究[J]. 传感技术学报, 2007,20 (6): 1344-1348. ZOU G , SHI Z S , LIU Z . Comparison of decentralized particle filter algorithms in sensor networks for passive tracking[J]. Chinese Journal of Sensors and Actuators, 2007,20 (6): 1344-1348.
[10]	OLFATI-SABER R , SANDELL N F . Distributed tracking in sensor networks with limited sensing range[A]. American Control Confe-rence[C]. Washington, USA, 2008.3157-3162.
[11]	AHMED N , RUTTEN M , BESSELL T , et al. Detection and tracking using particle-filter-based wireless sensor networks[J]. IEEE Transac-tions on Mobile Computing, 2010,9 (9): 1332-1345.
[12]	JIANG P , LI S Q . A data compression algorithm for wireless sensor networks based on an optimal order estimation model and distributed coding[J]. Sensors, 2010,10 (10): 9065-9083.
[3]	CABALLERO F , MERINO L , MAZA I , et al. A particle filtering method for wireless sensor network localization with an aerial robot beacon[A]. IEEE International Conference on Robotics and Automation[C]. Pasadena, USA, 2008.596-601.
[14]	OZDEMIR O , NIU R , VARSHNEY P K . Tracking in wireless sensor networks using particle filtering: physical layer cons tions[J]. IEEE Transactions on Signal Processing, 2009,57 (5): 1987-1999.
[15]	ALRASHIDI M R , EI-HAWARY M E . A survey of particle swarm optimization applications in electric power systems[J]. IEEE Transac-tions on Evolutionary Computation, 2009,13 (4): 913-918.
[16]	HOLDEN L , HAUGE R , HOLDEN M . Adaptive independent metro-polis-hastings[J]. The Annals of Applied Probability, 2009,19 (1): 395-413.

Metrics

Recommended 0

No Suggested Reading articles found!

[1]	Hao ZENG, Wangqiang MU, Shunping YANG. High maneuvering target tracking ATPM-IMM algorithm [J]. Journal on Communications, 2022, 43(7): 93-101.
[2]	Cuiran LI, Xuejie WANG, Jianli XIE, Anqi LYU. Routing algorithm for railway monitoring linear WSN based on improved PSO [J]. Journal on Communications, 2022, 43(5): 155-165.
[3]	Yang CAO, Ye ZHONG, Chunling PENG, Xiaofeng PENG. Energy efficiency optimization algorithm of heterogeneous networks based on hybrid energy supply and energy cooperation [J]. Journal on Communications, 2022, 43(3): 135-147.
[4]	Hongyan WANG, Libin ZHANG, Guoqiang CHEN, Zumin WANG, Zhiyuan GUAN. Approach of target tracking combining particle filter and metric learning [J]. Journal on Communications, 2021, 42(5): 98-110.
[5]	Xin SU, Haoyang XUE, Yiqing ZHOU, Jinxiu ZHU. Research on computing offloading method for maritime observation monitoring sensor network [J]. Journal on Communications, 2021, 42(5): 149-163.
[6]	Aijing SUN, Shichang LI, Yicai ZHANG. WSN clustering routing algorithm based on PSO optimized fuzzy C-means [J]. Journal on Communications, 2021, 42(3): 91-99.
[7]	Jiazheng PEI,Yong HUANG,Yunlong DONG,Xiaolong CHEN. Improved SMC cardinality-balanced multi-Bernoulli forwardbackward smoothing track-before-detect algorithm [J]. Journal on Communications, 2019, 40(8): 102-113.
[8]	Cuiqin DAI,Huang TANG,Linfeng GUO. Contact plan design based on bi-directional particle swarm optimization in satellite network [J]. Journal on Communications, 2019, 40(8): 189-199.
[9]	Gang LI,Zhijun WU. Task scheduling algorithm for system-wide information management based on multiple QoS constraints [J]. Journal on Communications, 2019, 40(7): 27-37.
[10]	Chao LIU,Zhiguo ZHANG,Jinping SUN. Amplitude information based robust tracking method for multiple marine targets [J]. Journal on Communications, 2019, 40(2): 60-69.
[11]	Xiaonian WU,Chuyun ZHANG,Runlian ZHANG,Yaping SUN. Clustering routing protocol based on improved PSO algorithm in WSN [J]. Journal on Communications, 2019, 40(12): 114-123.
[12]	Yuanhua FU,Zhiming HE. Distance criterion-based quantizer design for cooperative spectrum sensing [J]. Journal on Communications, 2018, 39(9): 49-56.
[13]	Zhen ZHANG,Peng WEI,Yufeng LI,Julong LAN,Ping XU,Bo CHEN. Feature selection algorithm based on improved particle swarm joint taboo search [J]. Journal on Communications, 2018, 39(12): 60-68.
[14]	Xing ZHANG,Ye WANG,Yi YANG,Qin-yu ZHANG. Cooperative spectrum sensing scheduling scheme based on discrete particle swarm optimization algorithm [J]. Journal on Communications, 2017, 38(7): 175-185.
[15]	Chun-hui ZHAO,Xue-yuan LI,Ying CUI. Image cluster algorithm of hybrid encoding method [J]. Journal on Communications, 2017, 38(2): 1-9.

Target tracking algorithm for wireless sensor networks based on particle swarm optimization and metropolis-hasting sampling particle filter

RichHTML

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 11

References 16

Related Articles 15

Metrics

Recommended 0