TDOA Passive Location Based on Cuckoo Search Algorithm

doi:10.1007/s12204-018-1952-7

Abstract

Abstract: Abstract: This paper formulates a new framework to estimate the target position by adopting cuckoo search (CS) positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time di?erence of arrival (TDOA). With the application of the Levy °ight mechanism, the preferential selection mechanism and the elimination mechanism, the proposed approach prevents positioning results from falling into local optimum. These intelligent mechanisms are useful to ensure the population diversity and improve the convergence speed. Simulation results demonstrate that the cuckoo localization algorithm has higher locating precision and better performance than the conventional methods. Compared with particle swarm optimization (PSO) algorithm and Newton iteration algorithm, the proposed method can obtain the Cram?er-Rao lower bound (CRLB) and quickly achieve the global optimal solutions.

Key words: time difference of arrival (TDOA)| passive location| cuckoo search (CS) algorithm| station layout

摘要： Abstract: This paper formulates a new framework to estimate the target position by adopting cuckoo search (CS) positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time di?erence of arrival (TDOA). With the application of the Levy °ight mechanism, the preferential selection mechanism and the elimination mechanism, the proposed approach prevents positioning results from falling into local optimum. These intelligent mechanisms are useful to ensure the population diversity and improve the convergence speed. Simulation results demonstrate that the cuckoo localization algorithm has higher locating precision and better performance than the conventional methods. Compared with particle swarm optimization (PSO) algorithm and Newton iteration algorithm, the proposed method can obtain the Cram?er-Rao lower bound (CRLB) and quickly achieve the global optimal solutions.

关键词: time difference of arrival (TDOA)| passive location| cuckoo search (CS) algorithm| station layout

CLC Number:

TN 974

JIANG Yilin (蒋伊琳), LIU Mengnan (刘梦楠), CHEN Tao (陈涛), GAO Lipeng (郜丽鹏). TDOA Passive Location Based on Cuckoo Search Algorithm[J]. Journal of Shanghai Jiao Tong University (Science), 2018, 23(3): 368-.

References 20

[1]	SUN M, HO K C. An asymptotically e±cient estimatorfor TDOA and FDOA positioning of multiple disjointsources in the presence of sensor location uncertain-ties [J]. IEEE Transactions on Signal Processing, 2011,59(7): 3434-3440.
[2]	HO K C, SUN M. Passive source localization usingtime di?erences of arrival and gain ratios of arrival [J].IEEE Transactions on Signal Processing, 2008, 56(2):464-477.
[3]	HE S. Asynchronous time di?erence of arrival position-ing system and implementation [D]. Victoria, Canada:Department of Electrical and Computer Engineering,University of Victoria, 2016.
[4]	YANG X J, LIU G, GUO J K, et al. The robust passivelocation algorithm for maneuvering target tracking [J].Mathematical Problems in Engineering, 2015, 2015:404986.
[5]	RENVET O, JAULIN L, CHABERT G. RobustTDOA passive location using interval analysis and con-tractor programming [C]//2009 International RadarConference on Surveillance for a Safer World. [s.l.]:IEEE, 2009: 1-6.
[6]	KABIR H, KANESAN J, REAZ A W, et al. Amathematical algorithm of locomotive source localiza-tion based on hyperbolic technique [J]. InternationalJournal of Distributed Sensor Networks, 2015, 2015:384180.
[7]	ZHU G, FENG D, JIN L I, et al. TDOA location algo-rithm based on modiˉed Newton iterations [J]. Jour-nal of Xidian University, 2014, 84(18): 343-363 (inChinese).
[8]	CAKIR O, KAYA I, YAZAGAN A, et al. Emitter lo-cation ˉnding using particle swarm optimization [J].Radioengineering, 2014, 23(1): 252-258.
[9]	MANSOURI M, NOUNOU H, NOUNOU M. Ge-netic algorithm-based adaptive optimization for tar-get tracking in wireless sensor networks [J]. Journal ofSignal Processing Systems, 2014, 74(2): 189-202.
[10]	VANKAYALAPATI, KAY S, DING Q. TDOA baseddirect positioning maximum likelihood estimator andthe Cramer-Rao bound [J]. IEEE Transactions onAerospace and Electronic Systems, 2014, 50(3): 1616-1635.
[11]	LUI K W K, ZHENG J, SO H C. Particle swarm op-timization for time-di?erence-of-arrival based localiza-tion [C]//15th European Signal Processing Conference(EUSIPCO 2007). Poznan, Poland: IEEE, 2007: 414-417.
[12]	WEN M, LI H, ZHENG Y F, et al. TDOA-based Sybilattack detection scheme for wireless sensor networks[J]. Journal of Shanghai University (English Edition),2008, 12(1): 66-70.
[13]	HO K C, XU W W. An accurate algebraic solutionfor moving source location using TDOA and FDOAmeasurements [J]. IEEE Transactions on Signal Pro-cessing, 2004, 52(9): 2453-2463.
[14]	ZHU G H, FENG D Z, XIE H, et al. An approxi-mately e±cient bi-iterative method for source positionand velocity estimation using TDOA and FDOA mea-surements [J]. Signal Processing, 2016, 125: 110-121.
[15]	WEI H W, PENG R, WAN Q, et al. Multidimen-sional scaling analysis for passive moving target lo-calization with TDOA and FDOA measurements [J].IEEE Transactions on Signal Processing, 2010, 58(3):1677-1688.
[16]	HO K C, LU X N, KOVAVISARUCH L. Source lo-calization using TDOA and FDOA measurements inthe presence of receiver location errors: Analysis andsolution [J]. IEEE Transactions on Signal Processing,2007, 55(2): 684-696.
[17]	LI X T, YIN M H. Modiˉed cuckoo search algorithmwith self adaptive parameter method [J]. InformationSciences, 2015, 298: 80-97.
[18]	ADAN M A, RAZZAQUE M A. A comparative studyof particle swarm optimization and cuckoo searchtechniques through problem-speciˉc distance func-tion [C]//2013 International Conference of Informa-tion and Communication Technology (ICOICT). [s.l.]:IEEE, 2013: 88-92.
[19]	YANG X S, DEB S. Multiobjective cuckoo search fordesign optimization [J]. Computers & Operations Re-search, 2013, 40(6): 1616-1624.
[20]	AZIZ M A E. Source localization using TDOA and FDOA measurements based on modiˉed cuckoosearch algorithm [J]. Wireless Networks, 2015.https://doi.org/10.1007/s11276-015-1158-y (publishedonline).