Tao Shan

CVGD: Cross-View Guided Disentangler for Multi-View Radar Semantic Segmentation

Yaoyu He, Yuan Feng, Tao Shan, Nan Wang

Neural networks continue to face challenges in effectively extracting information from the high-dimensional and sparse range-azimuth-Doppler (RAD) tensor. While multi-view architectures using three-axis projections of the RAD tensor improve efficiency and maintain accuracy, existing designs suffer from inefficient inter-view information interaction. To …

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Multi-OFDM Waveform Design for Joint Radar and Communications via Hybrid Modulations: Achieving Good ISL and PMEPR Performances

Xiaonan Xu, Yongzhe Li, Ran Tao, Tao Shan

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A novel alphavirus-based saRNA platform for enhanced vaccination efficacy and organ-specific targeting

Zhen Feng Sun, Yuxiao Liu, Haoyi Zhang, Ting Ge et autres

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Centralized Multi-Sensor GLMB Smoother for Multi-Target Tracking

Qinchen Wu, Jinping Sun, Yanping Wang, Tao Shan

Aiming to improve the accuracy of multi-target tracking in multi-sensor scenarios, this paper proposes a centralized multi-sensor (MS) generalized labeled multi-Bernoulli (GLMB) smoother, abbreviated as MS-GLMB-S. The developed smoother is built on the multi-target forward–backward Bayesian smoothing framework, which uses an MS-GLMB …

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Joint Spatial-Temporal Transmission with OFDM Waveforms and Receive Adaptive Filter Design for MIMO Radar-Communications

Xiaonan Xu, Yongzhe Li, Ran Tao, Tao Shan

This paper focuses on the joint transmit and receive design for MIMO radar-communications with orthogonal frequency division multiplexing (OFDM) waveforms. The main objective of this joint design is to seek a maximum signal-to-interference-plus-noise ratio (SINR) at receiver from the radar side, and …

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Integrated detection of weak drone signals: From parameter estimation to sensitive classification

Tao Shan, Haoran Dong

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Multi-Information-Assisted Joint Detection and Tracking of Ground Moving Target for Airborne Radar

Ran Liu, Xiangqian Li, Jinping Sun, Tao Shan

Airborne radar-based ground moving target tracking faces challenges such as low detection rates and high clutter density. While lowering the detection threshold can improve detection performance, it introduces significant false alarms, thereby degrading tracking performance. To address these challenges, this paper proposes …

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An Efficient Sparse Representation Method for Passive Radar

Quande Sun, Yuan Feng, Tao Shan, Juan Zhao et autres

Passive radar (PR) commonly estimates target parameters by calculating the cross ambiguity function (CAF), which is prone to generating a wider main lobe and higher side lobes, leading to issues such as weak targets being masked and adjacent targets being difficult to …

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Joint Angle-Doppler Estimation for Passive Radar Based on Compressed Sensing

Lijing Ni, Yuan Feng, Juan Zhao, Tao Shan

In this paper, a fast target angle and Doppler joint estimation method based on compressed sensing is proposed for passive radar. The joint estimation of multi-dimensional parameters enables improved resolution without introducing additional matching overhead. However, the dimension of the over-complete dictionary …

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Next-Generation saRNA Platforms: Systematic Screening and Engineering Enhances Superior Protein Expression and Organ-Specific Targeting for RNA Therapeutics

Zhen Feng Sun, Yuxiao Liu, Haoyi Zhang, Ting Ge et autres

Abstract Self-amplifying RNA (saRNA), derived from alphaviruses, encodes nonstructural proteins (NSP1-4) that form a replicase complex, enabling prolonged and amplified protein expression at lower doses than conventional mRNA. However, its high immunogenicity and limited replication efficiency require optimization for improved protein expression. …

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Beam pattern optimization using Pareto-enhanced particle swarm with cross-variance optimization (PPS-CVO) algorithm

Lu Fang, Xiaobin Wang, yizhou sun, Peng Liang et autres

In this paper, a novel metaheuristic optimization algorithm, the Pareto-Enhanced Particle Swarm with Cross-Variance Optimization (PPS-CVO) Algorithm, is proposed for the task of underwater acoustic beam pattern optimization. The proposed method introduces several ideas: (1) the incorporation of a Crossover Variational Operator, …

Tracking Multiple Resolvable Group Targets With Coordinated Motion via Labeled Random Finite Sets

Qinchen Wu, Jinping Sun, Tao Shan, Yanping Wang

The standard multi-target transition density assumes that, conditional on the current multi-target state, targets survive and move independently of each other. Although this assumption is followed by most multi-target tracking (MTT) algorithms, it may not be applicable for tracking group targets exhibiting …

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