Ground target three-dimensional positions measured from optical remote-sensing images taken by an unmanned aerial vehicle play an important role in related military and civil applications. The weakness of this system lies in its localization accuracy being unstable and its efficiency being low when using a single unmanned aerial vehicle. In this paper, a novel multi–unmanned aerial vehicle cooperative target localization measurement method is proposed to overcome these issues. In the target localization measurement stage, three or more unmanned aerial vehicles simultaneously observe the same ground target and acquire multiple remote-sensing images. According to the principle of perspective projection, the target point, its image point, and the camera’s optic center are collinear, and nonlinear observation equations are established. These equations are then converted to linear equations using a Taylor expansion. Robust weighted least-squares estimation is used to solve the equations with the objective function of minimizing the weighted square sum of re-projection errors from target points to multiple pairs of images, which can make the best use of the effective information and avoid interference from the observation data. An automatic calculation strategy using a weight matrix is designed, and the weight matrix and target-position coordinate value are updated in each iteration until the iteration stopping condition is satisfied. Compared with the stereo-image-pair cross-target localization method, the multi–unmanned aerial vehicle cooperative target localization method can use more observation information, which results in higher rendezvous accuracy and improved performance. Finally, the effectiveness and robustness of this method is verified by numerical simulation and flight testing. The results show that the proposed method can effectively improve the precision of the target’s localization and demonstrates great potential for providing more accurate target localization in engineering applications.

The heating and impact of arc and droplet acting on the weld pool lead to the transfer of mass, heat, and momentum, which affects the dynamic behavior of the weld pool and the microstructure in the P-GMAW process. In this paper, an image processing program is used to extract the dynamic behavior characteristics of the droplet transition and the weld pool in high-speed photography. The influence of the current waveform on the arc pressure and the impact of the droplet is quantitatively analyzed with different parameters. The dynamic behavior of the weld pool and the microstructure under different current waveform conditions are further studied. The internal relation of current waveform parameters to weld pool behavior and weld microstructure was expounded. The results show that the droplet impact is positively correlated with the pulse peak current. The rectangular wave pulse has a more significant droplet impact than the exponential wave with the same waveform parameters. The impact of droplet transition on the weld pool enhances the convective intensity of the weld pool. It slows down the cooling rate of the solidified weld microstructure below the tail of the weld pool, increasing the grain size of the weld microstructure.

Multichannel communication has great potential in environments with unknown interference patterns. However, existing link quality metrics and models are generally established and verified under a single-channel scenario, which does not consider the impacts of radio interference and channel change. Therefore, it is hard to directly judge whether these metrics and models are still valid under a multichannel scenario. This paper empirically analyzes the applicability of popular link quality metrics and models in multiple channels with different interference levels. Results show that the link quality estimation (LQE) capability of traditional metrics will be affected by the interference level of the channel, which makes the conclusions obtained under a single-channel scenario no longer valid. Meanwhile, traditional LQE models are basically not adaptive to radio interference and channel change. They are only valid for channels with similar interference under which they are modeled. If these models are directly used under a multichannel scenario, the link quality will be overestimated inevitably. In other words, traditional LQE metrics and models cannot be directly used in the multichannel scenario. It is necessary to deeply analyze the statistical characteristics of popular link quality metrics in multiple typical channels and design channel and interference adaptive metrics and models to support effective multichannel communication.

Accurate wireless channel modeling is essential for unmanned aerial vehicle (UAV) assisted wireless sensor networks (WSNs). However, existing path loss models suitable for UAV assisted WSNs are not accurate enough and usually can only characterize the channel under specific flight trajectories. In this letter, by introducing the impact of radio irregularity, a novel channel modeling methodology is proposed, which attempts to determine the bounds of path loss for UAV assisted WSNs. Experimental results show that the bounds of path loss estimated by the proposed modeling methodology are capable of covering 94.7% of the measured points in average under different UAV trajectories and environments. This means that the proposed methodology can be applied to various different scenarios, which could provide more general design and analysis tools for UAV assisted WSNs.

Most existing unmanned aerial vehicle (UAV) assisted wireless sensor network (WSN) studies usually assume that using a large SNR or a short distance can ensure good link quality. However, they don't consider the actual characteristics of UAV assisted WSN. In this paper, spatial characteristics of wireless links, link quality indicating capabilities of physical layer metrics and symmetry of uplink and downlink are analyzed by comparing the measured data of UAV assisted WSN and traditional WSN. The results show that link characteristics of UAV assisted WSN have changed significantly compared with those of traditional WSN. Firstly, connected region of the three traditional communication regions (connected region, transitional region, and disconnected region) is significantly compressed and even no longer exists, which makes that short distance can no longer guarantee reliable communication. Secondly, traditional physical layer metrics such as RSSI, SNR and LQI are no longer valid and even become deceptive, which may lead to wrong judgment of link quality. Finally, there is obvious overall asymmetry between uplink and downlink of UAV assisted WSN, and the quality of downlink is significantly higher than that of the uplink. The discovery of these new features would have great significance on guiding the design of UAV assisted WSN.