Layout of Detection Array Based on Multi-Strategy Fusion Improved Adaptive Mayfly Algorithm in Bearing-Only Sensor Network.

The various applications of bearing-only sensor networks for detection and localization are becoming increasingly widespread and important. The array layout of the bearing-only sensor network seriously impacts the detection performance. This paper proposes a multi-strategy fusion improved adaptive mayfly algorithm (MIAMA) in a bearing-only sensor network to perform layout planning on the geometric configuration of the optimal detection.

Distributed Cubature Information Filtering Method for State Estimation in Bearing-Only Sensor Network.

The problem of state estimation based on bearing-only sensors is increasingly important while existing research on distributed filtering solutions is rather limited. Therefore, this paper proposed the novel distributed cubature information filtering (DCIF) method for addressing the state estimation challenge in bearing-only sensor networks. Firstly, the system model of the bearing-only sensor network was constructed, and the observability of the system was analyzed.

[Elucidating the Impacts of Meteorology and Emission Changes on Concentrations of Major Air Pollutants in Major Cities in the Yangtze River Delta Region Using a Machine Learning De-weather Method].

This study applied a de-weather method based on a machine learning technique to quantify the contribution of meteorology and emission changes to air quality from 2015 to 2021 in four cities in the Yangtze River Delta Region. The results showed that the significant reductions in PM, NO, and SO emissions(57.2%-68.

Modeling particulate nitrate in China: Current findings and future directions.

Particulate nitrate (pNO) is now becoming the principal component of PM during severe winter haze episodes in many cities of China. To gain a comprehensive understanding of the key factors controlling pNO formation and driving its trends, we reviewed the recent pNO modeling studies which mainly focused on the formation mechanism and recent trends of pNO as well as its responses to emission controls in China. The results indicate that although recent chemical transport models (CTMs) can reasonably capture the spatial-temporal variations of pNO, model-observation biases still exist due to large uncertainties in the parameterization of dinitrogen pentoxide (NO) uptake and ammonia (NH) emissions, insufficient heterogeneous reaction mechanism, and the predicted low sulfate concentrations in current CTMs.

Prescribed-time cooperative guidance law against maneuvering target based on leader-following strategy.

This paper proposes a prescribed-time cooperative guidance law (PTCGL) against maneuvering target with variable line-of-sight (LOS) angle constraint for leader-following missiles, where the convergence times of the state errors can be arbitrarily set. The leader missile against the maneuvering target is provided as the modified proportional navigation (MPN) guidance law. The proposed PTCGL for follower missiles consist of two parts, in LOS direction, the range-to-go (Rgo) is selected as a co-variable, avoiding the estimation of time-to-go (Tgo), and a novel second-order nonlinear consensus protocol is developed to design the PTCGL; in normal LOS direction, considering the variable LOS angle constraint, the cooperative guidance law is designed with the proposed prescribed-time sliding model control (PTSMC) method.

Geometric calibration for LiDAR-camera system fusing 3D-2D and 3D-3D point correspondences.

Calibrating the extrinsic parameters on a system of 3D Light Detection And Ranging (LiDAR) and the monocular camera is a challenging task, because accurate 3D-2D or 3D-3D point correspondences are hard to establish from the sparse LiDAR point clouds in the calibration procedure. In this paper, we propose a geometric calibration method for estimating the extrinsic parameters of the LiDAR-camera system. In this method, a novel combination of planar boards with chessboard patterns and auxiliary calibration objects are proposed.

Transflective spin-orbital angular momentum conversion device by three-dimensional multilayer liquid crystalline materials.

In this paper, a liquid crystal device for generating transflected optical vortices with high efficiency based on Pancharatnam-Berry phase is devised and demonstrated experimentally. In the experiment, both photo-alignment material and polymer-alignment material are used for assembling three-dimensional distributed liquid crystal polymer and cholesteric liquid crystal. Through the interaction between the incident light and the device, both transmitted light and reflected light get spin-orbital angular momentum conversion.

Bio-Inspired Neural Adaptive Control of a Small Unmanned Aerial Vehicle Based on Airflow Sensors.

Inspired by the exceptional flight ability of birds and insects, a bio-inspired neural adaptive flight control structure of a small unmanned aerial vehicle was presented. Eight pressure sensors were elaborately installed in the leading-edge area of the forward wing. A back propagation neural network was trained to predict the aerodynamic moment based on pressure measurements.

Scene distance measurement method based on light field imaging.

Because a light field camera first takes an image and then refocuses it, we propose a scene distance measurement method based on light field imaging spatial refocusing principles, which was used to generate sequences of refocused images from raw spatial scene images taken by a Lytro1 light field camera. We selected the window of the object whose scene distance needed to be measured, used image-resolution evaluation functions to choose one of the clearest images among the refocused image sequences, and employed Gaussian formula to deduce the scene distance measurement formula. Finally, we used the scene distance measurement method to measure an object on the scene and theoretically analyzed its measurement range and accuracy.