Dual-UAV Collaborative High-Precision Passive Localization Method Based on Optoelectronic Platform

IF 4.4 2区 地球科学 Q1 REMOTE SENSING Drones Pub Date : 2023-10-25 DOI:10.3390/drones7110646
Xu Kang, Yu Shao, Guanbing Bai, He Sun, Tao Zhang, Dejiang Wang
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Abstract

Utilizing the optical characteristics of the target for detection and localization does not require actively emitting signals and has the advantage of strong concealment. Once the optoelectronic platform mounted on the unmanned aerial vehicle (UAV) detects the target, the vector pointing to the target in the camera coordinate system can estimate the angle of arrival (AOA) of the target relative to the UAV in the Earth-centered Earth-fixed (ECEF) coordinate system through a series of rotation transformations. By employing two UAVs and the corresponding AOA measurements, passive localization of an unknown target is possible. To achieve high-precision target localization, this paper investigates the following three aspects. Firstly, two error transfer models are established to estimate the noise distributions of the AOA and the UAV position in the ECEF coordinate system. Next, to reduce estimation errors, a weighted least squares (WLS) estimator is designed. Theoretical analysis proves that the mean squared error (MSE) of the target position estimation can reach the Cramér–Rao lower bound (CRLB) under the condition of small noise. Finally, we study the optimal placement problem of two coplanar UAVs relative to the target based on the D-optimality criterion and provide explicit conclusions. Simulation experiments validate the effectiveness of the localization method.
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基于光电平台的双无人机协同高精度无源定位方法
利用目标的光学特性进行探测和定位,不需要主动发射信号,具有隐蔽性强的优点。一旦安装在无人机(UAV)上的光电平台检测到目标,在相机坐标系中指向目标的矢量,通过一系列的旋转变换,可以估计出目标相对于无人机在地心定地(ECEF)坐标系中的到达角(AOA)。通过使用两架无人机和相应的AOA测量,可以对未知目标进行被动定位。为了实现高精度的目标定位,本文从以下三个方面进行了研究。首先,建立了两种误差传递模型来估计AOA和无人机在ECEF坐标系下的位置噪声分布;其次,为了减小估计误差,设计了加权最小二乘估计器。理论分析证明,在噪声较小的条件下,目标位置估计的均方误差(MSE)可以达到cram - rao下界(CRLB)。最后,基于d -最优准则研究了两架共面无人机相对于目标的最优布置问题,并给出了明确的结论。仿真实验验证了该定位方法的有效性。
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来源期刊
Drones
Drones Engineering-Aerospace Engineering
CiteScore
5.60
自引率
18.80%
发文量
331
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