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Volume 8
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Article

Optimal Configuration and Path Planning for UAV Swarms Using a Novel Localization Approach

by
Weijia Wang
1,
Peng Bai
1,
Hao Li
1,2,* and
Xiaolong Liang
1
1
Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, China
2
Air Force Early Warning Academy, Wuhan 430065, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2018, 8(6), 1001; https://doi.org/10.3390/app8061001
Submission received: 18 April 2018 / Revised: 28 May 2018 / Accepted: 11 June 2018 / Published: 19 June 2018
(This article belongs to the Special Issue Swarm Robotics)
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Abstract

In localization estimation systems, it is well known that the sensor-emitter geometry can seriously impact the accuracy of the location estimate. In this paper, time-difference-of-arrival (TDOA) localization is applied to locate the emitter using unmanned aerial vehicle (UAV) swarms equipped with TDOA-based sensors. Different from existing studies where the variance of measurement noises is assumed to be independent and changeless, we consider a more realistic model where the variance is sensor-emitter distance-dependent. First, the measurements model and variance model based on signal-to-noise ratio (SNR) are considered. Then the Cramer–Rao low bound (CRLB) is calculated and the optimal configuration is analyzed via the distance rule and angle rule. The sensor management problem of optimizing UAVs trajectories is studied by generating a sequence of waypoints based on CRLB. Simulation results show that path optimization enhances the localization accuracy and stability.
Keywords: time-difference-of-arrival (TDOA); Cramer–Rao low bound (CRLB); optimal configuration; UAV swarms; path optimization time-difference-of-arrival (TDOA); Cramer–Rao low bound (CRLB); optimal configuration; UAV swarms; path optimization
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MDPI and ACS Style

Wang, W.; Bai, P.; Li, H.; Liang, X. Optimal Configuration and Path Planning for UAV Swarms Using a Novel Localization Approach. Appl. Sci. 2018, 8, 1001. https://doi.org/10.3390/app8061001

AMA Style

Wang W, Bai P, Li H, Liang X. Optimal Configuration and Path Planning for UAV Swarms Using a Novel Localization Approach. Applied Sciences. 2018; 8(6):1001. https://doi.org/10.3390/app8061001

Chicago/Turabian Style

Wang, Weijia, Peng Bai, Hao Li, and Xiaolong Liang. 2018. "Optimal Configuration and Path Planning for UAV Swarms Using a Novel Localization Approach" Applied Sciences 8, no. 6: 1001. https://doi.org/10.3390/app8061001

APA Style

Wang, W., Bai, P., Li, H., & Liang, X. (2018). Optimal Configuration and Path Planning for UAV Swarms Using a Novel Localization Approach. Applied Sciences, 8(6), 1001. https://doi.org/10.3390/app8061001

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