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.
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 Jiaotong University(Science), 2018
, 23(3)
: 368
.
DOI: 10.1007/s12204-018-1952-7
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