Aerial image target detection is essential for urban planning, traffic monitoring, and disaster assessment. However, existing algorithms struggle with small recognition accuracy in complex environments. To address this issue, paper proposes an improved model based on YOLOv8, named MPE-YOLO. Initially, a multilevel feature integrator (MFI) module employed to enhance the representation of features, which meticulously moderates information loss during fusion process. For backbone network model,...

High-resolution sea-surface surveillance radars are designed to find two classes of small targets, low-velocity and floating targets on the sea surface low-altitude over surface. Existing feature-based detectors using amplitude Doppler spectra features returns can fast detect first class targets. But they often fail second due their radar cross sections low signal-to-clutter ratios (SCR). This paper proposes a dual tri-feature-based detector At detector, existing is used high-velocity new by...

Object detection and recognition in high-resolution remote sensing images captured by satellite optical sensors from a bird's-eye view perspective has been challenging task with considerable practical value. Unlike natural scenes, several inherent characteristics of scenes including irregular scale variations orientation, intricate contextual textures diverse ground materials domain gaps, dense distribution tiny fuzzy objects have severely hampered the development accuracy for geospatial...

<title>Abstract</title> Aerial image target detection is crucial for urban planning, traffic monitoring, and disaster assessment, but existing algorithms face challenges in small recognition accuracy within complex environments. To address this issue, paper proposes an improved model based on YOLOv8, named MPE-YOLO. Initially, a multilevel feature integrator (MFI) module employed to enhance the representation of features, which meticulously moderates information loss during fusion process....

Water body extraction can help eco-environmental policymakers to intuitively grasp surface water resources. Remote sensing technology accurately and quickly extract information, which is of great significance for monitoring changes. Fengyun satellite images have the advantages high time resolution multispectral bands. This provides important image data suitable high-frequency monitoring. Based on 3 medium spectral imager (FY-3/MERSI) data, 7 methods were applied in this study, include...

Aiming at the low observable target detection under sea clutter backgrounds, this paper emphasizes exploration of distinguishable full-polarization features between and echoes. To overcome shortcomings existing polarization feature-based methods, are modeled analyzed in detail by using Van Zyl decomposition. Then, three polarimetric (the relative surface scattering energy, dihedral energy diffuse energy) extracted from fully radar echoes, which improve feature differences targets. And a...

Object detection in drone aerial images is challenging due to the difficulty of small object and complex backgrounds. To address these issues, this paper proposes an improved model, perception target capture detector (PTCDet), increase accuracy robustness scenes. Specifically, proposed multiple feature extraction attention (MFEA) module significantly enhances ability model detect objects through multidimensional map augmentation. The weighted perceptive field augmentation (WPFA) designed...

In agricultural remote sensing monitoring, the quality of optical image data acquisition is often affected by climate, and acquired satellite imagery results usually contain cloud information, which can lead to a lack ground information.Unlike thick clouds, semi-transparent nature thin clouds prevents from completely obscuring scene.In order remove in cultivated land restore real information as much possible, we proposed removal method spatial fusion self-attention generative adversarial...

Detection of small objects in Unmanned Aerial Vehicle (UAV) images, which contain a large number with extremely pixels, has been major challenge over the last few decades. Owing to lack sufficiently detailed representation object features, conventional detectors based on deep learning are unsatisfactory when detecting objects. Meanwhile, flight altitude and shooting angle drone always changing, leads an uneven dispersion multiple varying density In response issues mentioned above, novel...

Abstract The study of short-term forecasting satellite clock bias (SCB) is important to promote the development real-time precise point positioning, and Kalman filter model has certain advantages over other models in single forecast model. However, filtering performance will be degraded by bias, a fading factor constructed control effect brought bias. Considering that may cause covariance matrix abnormally inflated or even invalid when observed information unreliable, chi-square test...

An accurate inversion of the fraction absorbed photosynthetically active radiation (FPAR) based on remote sensing data is particularly important for understanding global climate change. At present, there are relatively few studies focusing FPAR using Chinese autonomous satellites. This work intends to investigate obtained from FengYun-3C (FY-3C) domestic satellites by PROSAIL model and look-up table (LUT) algorithm different vegetation types various places in China. After analyzing...

The generalized Pareto (GP) distribution model is often used to describe the amplitude statistical feature of sea clutter. Generally, parameters GP are estimated by moments estimators. However, when state high, appearance spikes will increase echo anomalous scattering units, which leads a decrease in parameter estimation accuracy and target detection performance. To improve accuracy, this paper proposes novel method based on variable intervals. Considering local properties clutter, we take...

Due to unfavorable factors such as cluttered spatial and temporal distribution of multiple types targets, occlusion background objects different shapes, blurring feature information by inclement weather, the low detection accuracy in complex traffic scenarios has been a troubling issue. Regarding above-mentioned issues, paper proposes lightweight real-time network augment multi-scale object perception capabilities while ensuring speed. First, we construct novel global extraction (GFE)...

Driven by improvements in satellite internet and Low Earth Orbit (LEO) navigation augmentation, the integration of communication has become increasingly common, further improving capabilities based on constellations a significant challenge. In context existing Orthogonal Frequency Division Multiplexing (OFDM) systems, this paper proposes new ranging signal design method an LEO constellation. The Satellite Communication Constellation Block-type Pilot (LSCC-BPR) is superimposed block-type form...

The wide application of automotive radars significantly increases the possibility mutual interference. Interference can lead to false detections such as ghost objects and missed detections, with serious threats vehicle pedestrian safety. In this paper, we build an end-to-end interference suppression model using 2D UNet. UNet takes input through encoder down-sampling get a feature smaller than initial data, then inputs into decoder reduces it clean signal, thus achieving suppression. By...

Radio frequency interference (RFI) is a critical issue that leads to image degradation of spaceborne synthetic aperture radar (SAR) systems. In addition the ground terrestrial radiation sources, there an emerging type called mutual terrain scattered (MTSI), which becoming more and severe with deployment multiple satellite constellations. this paper, we investigated mechanism MTSI, analyzed signal characteristics, discussed boundary conditions from time, space perspectives. Simulation results...

Distributed operations have become a promising concept in the future of information and intelligent warfare. Conventional single multi-functional jammer has limited coverage due to beamwidth. In order further improve jamming performance, this paper analyzed UAV-based distributive model, simulated radar detection performance under line formation arch formation. The effect is evaluated with an effective assessment indicator. Experimental results show superiority formation, manifesting more...