Time Difference of Arrival Passive Location Based on Salp Swarm Algorithm

CHEN Tao; WANG Mengxin; HUANG Xiangsong

doi:10.11999/JEIT170979

Volume 40 Issue 7

Jul. 2018

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CHEN Tao, WANG Mengxin, HUANG Xiangsong. Time Difference of Arrival Passive Location Based on Salp Swarm Algorithm[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1591-1597. doi: 10.11999/JEIT170979

Citation:

CHEN Tao, WANG Mengxin, HUANG Xiangsong. Time Difference of Arrival Passive Location Based on Salp Swarm Algorithm[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1591-1597. doi: 10.11999/JEIT170979

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Time Difference of Arrival Passive Location Based on Salp Swarm Algorithm

doi: 10.11999/JEIT170979

CHEN Tao WANG Mengxin HUANG Xiangsong

Funds:

The National Natural Science Foundation of China (61571146), The Fundamental Research Funds for the Central Universities (HEUCFP201769)

Received Date: 2017-10-20
Rev Recd Date: 2018-03-30
Publish Date: 2018-07-19

Abstract

Abstract

To solve the nonlinear equation problems of Time-Difference-Of-Arrival (TDOA) passive location, a new swarm intelligence optimization algorithm called Salp-Swarm-Algorithm (SSA) is used. Firstly, a new renewal model of salps is proposed to balance exploration and exploitation properly during iteration in SSA. SSA not only ensures the wholeness of searching and the diversity of individuals, but also improves the problem that other intelligent optimization algorithms fall into local optima easily. Besides, there are few parameters to be adjusted, therefor, the computation speed is obviously improved. Moreover, the convergence performance of the proposed algorithm is very stable and the accuracy of location is higher. Simulation results show that the proposed algorithm can converge to the position of emitters fast and stably in 3D TDOA location. Comparing with Particle-Swarm- Optimization (PSO) and Improved-Particle-Swarm-Optimization (IPSO), the proposed algorithm has lower mean square error.
- Passive location、Time-Difference-Of-Arrival (TDOA)、Intelligence optimization algorithm、Salp- Swarm-Algorithm (SSA),

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References(16)

References

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