A Closed-Form Method for Simultaneous Target Localization and UAV Trajectory Optimization

Dongzhen Wang,Cheng Xu,Daqing Huang,Wei Han

doi:10.3390/app11010114

Abstract

Unmanned aerial vehicles (UAVs) play a key role in modern surveillance-related missions. A major task for performing these missions is to find the precise location of a moving target in real-time, for which the main challenge is to estimate the target position to high precision using the noisy measurements from the airborne sensors. In this paper, we present a closed-form on-line simultaneous target localization and UAV trajectory optimization method based on the visual platform, which can effectively minimize the localization uncertainty to the target. The proposed method can be elucidated explicitly using two phases, of which, in the target localization phase, the expended information filtering (EIF) is exploited, which can express the predicted Fisher information matrix (FIM) of the target explicitly and iteratively, and in the UAV trajectory optimization phase, the property of the predicted FIM is exploited to establish the UAV waypoint optimization objective by taking account of the UAV motion limit. Compared with existing methods of the same class, the proposed method not only estimates the next target position more correctly, but also takes the error of the target motion into consideration, thus improving the effectiveness of the optimized UAV trajectory. Both simulations and field experiments were conducted, which show that the proposed method outperformed the existing methods.

Highlights

Target localization based on unmanned aerial vehicles (UAVs) has played an important role in many modern applications such as intelligence, reconnaissance, and surveillance missions (ISR) [1,2]
The simulations were conducted based on the full measurement of the UAV target localization system
This paper presents a closed-form method for simultaneous target localization and the the UAV

Summary

Introduction

Target localization based on unmanned aerial vehicles (UAVs) has played an important role in many modern applications such as intelligence, reconnaissance, and surveillance missions (ISR) [1,2]. A common ISR mission for UAV is to track and localize a target detected by airborne sensors. In order to position the target with a high accuracy given the fixed noise levels, a feasible and effective solution is to choose the observation stations so that the optimal sensor-target geometry can be formed, which can minimize the estimate uncertainty. As the task is to localize a moving target, the optimized sequential UAV observation stations form a desired UAV trajectory through which the target can be observed with the minimized uncertainty

Objectives

Results

Conclusion