An Optimization Algorithm for Forward-Scatter Radar Network Node Deployment Based on BFGS and Improved NSGA-II by Yuqing Zheng, Xiaofeng Ai, Zhiming Xu, Jing Wu, Feng Zhao

“…The radar system enables aerial target surveillance by deploying multiple receiving nodes on the ground. …”
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Respiration Signal Pattern Analysis for Doppler Radar Sensor with Passive Node and Its Application in Occupancy Sensing of a Stationary Subject by Chenyan Song, Ehsan Yavari, Xiaomeng Gao, Victor M. Lubecke, Olga Boric-Lubecke

“…Doppler radar node occupancy sensors are promising for applications in smart buildings due to their simple circuits and price advantage compared to quadrature radar sensors. …”
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Coherent Detection Method for Moving Platform Based Distributed Aperture Radar and Experimental Verification by Yuanhao WANG, Hongqiang WANG, Qi YANG

“…As one of the most promising next-generation radars, Moving platform based Distributed Aperture Radar (MDAR) cannot only coherently combining distributed apertures to obtain the same detection performance of a large aperture, but also enhance the detection and anti-damage capabilities through mobility and flexible deployment. …”
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A belief propagation algorithm based on track‐before‐detect for tracking low‐observable and manoeuvering targets using multiple sensors by Chenghu Cao, Haisheng Huang, Xin Li, Yongbo Zhao

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Acoustic Signal Reconstruction Across Water–Air Interface Through Millimeter-Wave Radar Micro-Vibration Detection by Yuchen Du, Xiaolong Cao, Yiguang Yang, Tongchang Zhang, Jiaqi Yuan, Tengyuan Cui, Jianquan Yao

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FED-GEM-CN: A federated dual-CNN architecture with contrastive cross-attention for maritime radar intrusion detection by Md. Alamgir Hossain

“…To enhance feature discriminability, a supervised contrastive learning paradigm is incorporated, while a gradient episodic memory (GEM) buffer strategically retains challenging instances to bolster model robustness against hard-to-detect intrusions. Operating under a federated learning scheme, FED-GEM-CN facilitates collaborative model optimization across distributed radar nodes, preserving data locality and mitigating privacy risks inherent in centralized approaches. …”
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A Three-Dimensional FDTD(2,4) Subgridding Algorithm for the Airborne Ground-Penetrating Radar Detection of Landslide Models by Lifeng Mao, Xuben Wang, Yuelong Chi, Su Pang, Xiangpeng Wang, Qilin Huang

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The Internet-of-Things-based Fishpond Security System Using NodeMCU ESP32-CAM Microcontroller by Arwin Datumaya Wahyudi Sumari, Ilyas Annurroni, Astika Ayuningtyas

“…This research aims to design and implement an Internet of Things (IoT)-based fishpond security system using NodeMCU ESP32-CAM Microcontroller equipped with HB100 Radar Sensor to detect human entity movement with NodeMCU ESP32-CAM to take pictures of the approaching human entity, as well as Arduino Uno R3 to control system inputs and outputs. …”
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A receive-coherent detector for airborne distributed coherent aperture radar under heterogeneous clutter and random phase errors by Xiaochuan Liu, Dongming Zhou, Hongwei Gao, Yaobing Lu

“…Abstract Airborne distributed coherent aperture radar (ADCAR) obtain target coherent parameters (TCPs) and improve target detection performance significantly in the receive-coherent (RC) stage by multiple physically isolated airborne radars with orthogonal waveforms. …”
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SIMULATION RESULTS OF SPECKLE SUPPRESSION IN RADAR WITH SYNTHETIC APERTURE by R. N. Akinshin, V. L. Rumyantzev, A. V. Peteshov

“…The disadvantage of (RLI) radar images obtained with a single-channel radar station is the presence of speckle that leads to intensity flashes increasing the number of false alarms when detecting point targets. …”
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Automatic dependent surveillance-broadcast (ADS-B) anomalous messages and attack type detection: deep learning-based architecture by Waqas Ahmed, Ammar Masood, Jawad Manzoor, Sedat Akleylek

“…Third, the study proposes a robust and accurate Intrusion Detection System (IDS) using three advanced deep learning models—TabNet, Neural Oblivious Decision Ensembles (NODE), and DeepGBM—to classify ADS-B messages and detect specific attack types. …”
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Characterisation and synchronisation of a netted software defined radio radar by Ferran Valdes Crespi, Angel Slavov, Matthias Weiß, Peter Knott, Daniel O’Hagan

“…The Universal software radio peripheral model X310 with two different daughterboard models as RF front‐end was used as SDR on either radar node. A network combining data and synchronisation purposes allowed the radar nodes under test to operate synchronously. …”
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Distributed multi‐target tracking via consensus‐based Arithmetic Average fusion by Xin Guan, Yu Lu

“…Abstract This paper proposes a multi‐target tracking fusion algorithm based on consensus arithmetic averaging to address the limitations of the sensor detection field of view and information fusion difficulty when tracking multiple targets in a distributed Airborne passive bistatic radar (APBR) network. …”
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Vehicles detection through wireless sensors networks and optical fiber sensors by Hacen Khlaifi, Amira Zrelli, Tahar Ezzedine

“…In our case, we apply WSN, radar and optical fiber sensors to detect vehicles in the border area. …”
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A model-based design strategy to engineer miRNA-regulated detection systems by Renske J. Verkuijlen, Robert W. Smith

“…These small RNA molecules are always present in the human body but become dysregulated when a person develops certain diseases. Although the detection of these biomarkers in cell-free tests is ongoing work, current systems often focus solely on detecting the presence or absence of a specific miRNA, rather than the miRNAs concentration. …”
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Weight-Based Clustering Decision Fusion Algorithm for Distributed Target Detection in Wireless Sensor Networks by Haiping Huang, Lei Chen, Xiao Cao, Ruchuan Wang, Qianyi Wang

“…We use a great deal of wireless sensor nodes to detect target signal that is more accurate than the traditional single radar detection method. …”
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Land-sea Clutter Classification Method Based on Multi-channel Graph Convolutional Networks by Can LI, Zengfu WANG, Xiaoxuan ZHANG, Quan PAN

“…For validation, RD maps from various seasons, times, and detection areas were selected. Based on radar parameters, data characteristics, and sample proportions, we construct a land-sea clutter original dataset containing 12 different scenes and a land-sea clutter scarce dataset containing 36 different configurations. …”
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Performance Enhancement of UWB Material Characterization and Object Recognition for Security Robots by Rahmi Salman, Thorsten Schultze, Ingolf Willms

“…The object recognition task is performed using bistatic sensor nodes on the basis of Radar measurements. The simulation-based performance evaluations show a very robust behavior due to suitable preprocessing of Radar data. …”
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Preoperative Localization for Non-Palpable Breast Lesions by Sang Yull Kang, Hyeong Eun Jeong, Ha Rim Ahn, Hyun Jo Youn

“…However, due to the several limitations of this method, alternative techniques, such as Intraoperative ultrasound localization, Breast biopsy marker localization, Radioactive localization (including Radioguided Occult Lesion Localization, Sentinel Node and Occult Lesion Localization, Radioactive Seed Localization, and Radioguided Occult Lesion Localization using Iodine-125 Seeds), Magnetic seed localization, Radar reflector localization, and Radiofrequency-based localization, have been developed. …”
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IoT-Edge Hybrid Architecture with Cross-Modal Transformer and Federated Manifold Learning for Safety-Critical Gesture Control in Adaptive Mobility Platforms by Xinmin Jin, Jian Teng, Jiaji Chen

“…The system architecture establishes a three-tier IoT network: a perception layer with 60 GHz FMCW radar and TOF infrared arrays (12-node mesh topology, 15 cm baseline spacing) for real-time motion tracking; an edge intelligence layer deploying a time-aware neural network via NVIDIA Jetson Nano to achieve up to 99.1% recognition accuracy with latency as low as 48 ms under optimal conditions (typical performance: 97.8% ± 1.4% accuracy, 68.7 ms ± 15.3 ms latency); and a federated cloud layer enabling distributed model synchronization across 32 edge nodes via LoRaWAN-optimized protocols (κ = 0.912 consensus). …”
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