For the problem that it is difficult to effectively cluster lidar point clouds with irregular shapes and uneven densities, a Neighborhood Effective Line Density (NELD)-based Euclidean Clustering (NELD-EC) algorithm proposed in this paper. The NELD-EC first eliminates interfering points within neighborhood of data by utilizing distance relationship calculates NELD using effective set without point. taken as local density Then, conducts clustering processing all uses reciprocal harmonic...

To address the deficiency of aircraft point cloud training data for low-altitude environment perception systems, a method termed APCG (aircraft generation) is proposed. can generate in single photon counting Lidar (SPC-Lidar) system based on information such as type, position, and attitude. The core depth image generator, which obtained through adversarial an improved conditional generative network (cGAN). cGAN are composed images formed by spatial sampling transformation fine clouds 76...

The growth of unmanned aerial vehicle applications in the low-altitude economy demand advanced multi-target tracking systems. Unlike traditional approaches that assume independent measurements, distributed systems generate coupled measurements containing additional target relationship information. This paper proposes a novel particle filtering algorithm through introducing measurement into conventional method. In proposed method, we fuse direct and via optimization then build cost function...

Few-shot scene classification methods aim to obtain discriminative ability from few labeled samples and has recently seen substantial advancements. However, the current few-shot learning approaches still suffer overfitting due scarcity of samples. To this end, a semi-supervised method is proposed address issue. Specifically, used increase target domain samples; then we train multiple models using augmented Finally, perform decision fusion results obtained accomplish image task. According...

Curvilinear synthetic aperture radar (SAR), as a more practicable 3-D SAR imaging system, utilizes parametric target feature estimates extracted from the received data to reconstruct image. The reconstructed image quality is then impacted by estimation accuracy of features. In this letter, through discussing correlation between system parameters and performance curvilinear SAR, conclusion can be drawn on how overall location determined azimuth elevation coordinates flight path, compactly...

Discovering fraud user behaviors is vital to keeping online websites healthy. Fraudsters usually exhibit grouping behaviors, and researchers have effectively leveraged this behavior design unsupervised algorithms detect groups. In work, we propose a visualization system, FraudVis, visually analyze the detection from temporal, intra-group correlation, inter-group feature selection, individual perspectives. FraudVis helps domain experts better understand algorithm output detected behaviors....

The clutter suppression effect of ground objects significantly impacts the detection and tracking performance avian lidar on low-altitude bird flock targets. It is imperative to simulate point cloud data in explore effective methods for suppressing caused by lidar. traditional ray-tracing method enhanced this paper efficiently obtain simulation results objects. By incorporating a beam constraint light-energy constraint, screening efficiency rays improved, making them more suitable simulating...

In order to satisfy the requirements of International Civil Aviation Organization (ICAO) for aircraft taxi route planning in Advanced Surface Movement Guidance and Control System (A-SMGCS), an airport surface operation modelling simulation approach based on timed coloured Petri net is presented. According layout features units, a static model established. On this basis, line with taxiing velocity ICAO DOC 9830, dynamic established by adding time attribute model. Additionally, method defining...

With the growing integration of drones into various civilian applications, demand for effective automatic drone identification (ADI) technology has become essential to monitor malicious flights and mitigate potential threats. While numerous convolutional neural network (CNN)-based methods have been proposed ADI tasks, inherent local connectivity convolution operator in CNN models severely constrains RF signal performance. In this paper, we propose an innovative hybrid transformer model...

In this paper, a blind adaptive beamforming algorithm for Global Positioning System (GPS) is proposed, which combines the cyclic (CAB) with subspace technique. Compared CAB algorithm, new can generate high gain toward satellite direction and form nulls in directions of jammers by constraining both weight vector control to orthogonal space steering vectors jammers. The proposed has advantages such as no requirement any knowledge transmitted signals locations, fast convergence speed, low...

For airborne radar detecting ground moving target, the range migration of target was often ignored. However, for cases high relative speed between and should be considered, especially resolution (HRR) radar. Since can dramatically reduce performance radar, effect must removed. In this paper, data model with is discussed, a STAP method proposed migration. Simulation results show that remove all targets simultaneously, improve detection capability (4 pages)

Wideband array signal processing is applied in many fields such as underwater acoustics, acoustic imaging, and comunication. So the design of wideband constant-beamwidth beamformer more important. Focused based on focusing approach an efficient method. It transforms spaces at different frequencies to common one using a matrix. has some advantages requiring only array, computational efficiency ability operate multipath environments. However, approaches have higher requirement knowledge...

Wind shear is recognized by a major hazard during takeoff and landing of aircraft, which can be detected airborne forward-looking weather radar. A high-fidelity wind model constructed the Computational Fluid Dynamics software has been implemented in this study. The reasonably representative downward falling to ground mature phase microburst shear. results radar echo signal simulation based on above show that distribution velocities an obvious horizontal "S" shape. simulated demonstrate...

To enhance the detection capability of weak targets and reduce dependence single-photon lidar target on number time-correlated counting cycles, a convolutional neural network (CNN) based point cloud (CNN-PC) method is proposed in this paper for detecting lidar. This approach utilizes exceptional feature extraction capabilities offered by CNN. The CNN-PC module trained CNN to simultaneously extract features from two-dimensional slices. Subsequently, it combines these feeds them into...

Global Positioning System (GPS) has found wide application in many areas. However, due to the low power of received signal, GPS is susceptible a variety interferences and multipath. In this paper, two stage anti-jamming processor based on adaptive arrays proposed. Firstly, array signals are projected onto orthogonal subspace corresponding interference suppress interferences. Then free further processed by conventional data-independent beamforming enhance direct-path signal mitigate multipath...

Smart jammer is one of the most threat interferences for GPS receiver, so a smart suppression algorithm proposed in this paper, which combines spatial amplitude and phase estimation(APES) method high resolution coherent subspace estimation method. The new can resolve problem that APES unable to cancel multiple interferences, also provide accurate signal estimate. Simulation results show feasible

In this paper, an iterative algorithm, which is based on support vector machine (SVM), proposed for synthetic aperture radar (SAR) image segmentation. The method considers the SAR segmentation as pixel classification. pixels of previous segmented are regarded training samples SVM, used to re-segment image. These iterations repeated until convergence, determined by checking relative change entropy between two consecutive images. Experimental results show that compared with, algorithm can...

Though curvilinear synthetic aperture radar (CLSAR) has the three-dimensional (3-D) imaging capability, images obtained by non-parametric methods are of little practical use because data collected CLSAR is not full volume but sparse in 3-D frequency space. In this paper, a fast non-iterative (FNII) method proposed for extracting scatterer's features CLSAR. Based on loose coupling between range and cross-range parameters, new algorithm first obtains estimates via subspace techniques, then...

The modal analysis and seismic time history were performed of cathead transmission towers with different tower legs heights by the software Open SEES, material nonlinearity geometrical considered in model. results show that increase height tower, fundamental period increases linearly, top maximum displacement bottom main member peak axial force are reducing, higher have better cushioning effect.

A relaxation-based sequential optimizing (RESO) method is proposed for three-dimensional (3-D) target, feature extraction via the curvilinear synthetic aperture radar (CLSAR) system. Compared with similarly structured algorithm RELAX, RESO obtains scatterer's 3-D position estimate one-dimensional (1-D) and two-dimensional (2-D) FFTs instead of FFT employed by former. Due to utilization these lower dimensional FFTs, new more efficient. Simulation results show that RELAX have similar...