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Appl. Sci. 2018, 8(6), 899; https://doi.org/10.3390/app8060899

Co-Optimization of Communication and Sensing for Multiple Unmanned Aerial Vehicles in Cooperative Target Tracking

School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
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Received: 24 March 2018 / Revised: 22 May 2018 / Accepted: 29 May 2018 / Published: 30 May 2018
(This article belongs to the Special Issue UAV Assisted Wireless Communications)

Abstract

In this paper, we consider motion-planning for multiple unmanned aerial vehicles (UAVs) that oversee cooperative target tracking in realistic communication environments. We present a novel multi-UAVs cooperative target tracking algorithm based on co-optimization of communication and sensing strategy, which can generate information-gathering trajectories considering the multi-hops communication reliability. Firstly, a packet-erasure channel model is used to describe the realistic wireless communication links, in which the probability of a successful information transmission is modeled as a function of the signal-to-noise ratio (SNR). Secondly, the Fisher information matrix (FIM) is used to quantify the information gained in target tracking. Thirdly, a scalar metric is used for trajectories panning over a finite time horizon. This scalar metric is a utility function of the expected information gain and the probability of a successful information transmission. With the combining of the sensing and communication into a utility function, the co-optimization of communication and sensing is reflected in the tradeoffs between maximizing information gained and improving communication reliability. The results of comparison simulations show that the proposed algorithm effectively improved estimation performance compared to the method that does not consider communication reliability. View Full-Text
Keywords: multi-UAVs; cooperative target tracking; information filter; radio frequency communication; Fisher information matrix; receding horizon optimizing multi-UAVs; cooperative target tracking; information filter; radio frequency communication; Fisher information matrix; receding horizon optimizing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Liu, Z.; Fu, X.; Gao, X. Co-Optimization of Communication and Sensing for Multiple Unmanned Aerial Vehicles in Cooperative Target Tracking. Appl. Sci. 2018, 8, 899.

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