arXiv subjects

Lincong Han

Publications and source records attributed to Lincong Han.

7 recordsLinked to original sources

arXiv2026

Cram\'{e}r-Rao Bound Optimization for Near-Field ISAC with Extended Targets

Near-field integrated sensing and communication (ISAC) requires target models beyond the point-target abstraction when the target has a non-negligible spatial extent. In this letter, a geometry-aware transmit design is developed for a parametric extended target (ET) described by its center, orientation, and size under spherical-wave propagation. The CRB for the geometric parameters is formulated around a nominal ET state, an exact ET-aware reduced subspace is identified for the lifted covariance formulation, and a reduced-dimensional semidefinite relaxation (SDR) is developed under signal-to-interference-plus-noise ratio (SINR) and power constraints. Simulation results show lower CRB values than point-target and geometry-agnostic baselines together with substantially reduced runtime for large arrays.

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arXiv2026

Extended-Target Classification and Localization for Near-Field ISAC

Near-field integrated sensing and communication (ISAC) enables object-level sensing from distance-dependent array responses, yet most existing near-field methods still rely on point-target models and realistic extended targets remain largely unexplored. In this paper, joint target classification and range-azimuth localization are studied from channel responses of realistic extended targets. A dual-branch inference framework is proposed. Semantic and geometric branches are used for classification and localization, respectively. Cross-task attention is introduced after task-specific encoding so that complementary cues can be exchanged without forcing full feature sharing from the input stage. To improve localization on the same backbone, uncertainty-aware regression and a physics-guided structured objective are adopted, including planar consistency, peak-response regularization, and geometry-coupling constraints. Training and evaluation data are generated from full-wave electromagnetic scattering simulations of voxelized vehicle targets with randomized heading angles, material contrasts, and placements. The compared variants show that cross-task attention mainly benefits classification, while uncertainty-aware and structured supervision are needed to recover strong localization performance on the same backbone. Under the adopted shared-OFDM benchmark, the proposed framework reaches the best joint operating point with fewer sensing tones for the same target performance region.

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arXiv2026

A Spatio-Temporal-Frequency Transformer Framework for Near-Field Target Recognition

A target recognition framework relying on near-field integrated sensing and communication (ISAC) systems is proposed. By exploiting the distance-dependent spatial signatures provided by the near-field spherical wavefront, high-accuracy sensing is realized in a bandwidth-efficient manner. A spatio--temporal--frequency (STF) transformer framework is introduced for target recognition using electromagnetic features found in the wireless channel response. In particular, a lightweight spatial encoder is employed to extract features from the antenna array for each frame and subcarrier. These features are then fused by a time-frequency transformer head with positional embeddings to model temporal dynamics and cross-subcarrier correlations. Simulation results demonstrate that strong target recognition performance can be achieved even with limited bandwidth resources.

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arXiv2023

Multistatic Integrated Sensing and Communication System in Cellular Networks

A novel multistatic multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system in cellular networks is proposed. It can make use of widespread base stations (BSs) to perform cooperative sensing in wide area. This system is important since the deployment of sensing function can be achieved based on the existing mobile communication networks at a low cost. In this system, orthogonal frequency division multiplexing (OFDM) signals transmitted from the central BS are received and processed by each of the neighboring BSs to estimate sensing object parameters. A joint data processing method is then introduced to derive the closed-form solution of objects position and velocity. Numerical simulation shows that the proposed multistatic system can improve the position and velocity estimation accuracy compared with monostatic and bistatic system, demonstrating the effectiveness and promise of implementing ISAC in the upcoming fifth generation advanced (5G-A) and sixth generation (6G) mobile networks.

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arXiv2021

QoS-Oriented Sensing-Communication-Control Co-Design for UAV-Enabled Positioning

Unmanned aerial vehicle (UAV)-enabled positioning that uses UAVs as aerial anchor nodes is a promising solution for providing positioning services in harsh environments. In previous research, the state sensing and control of UAVs were either ignored or simply set to be performed continuously, resulting in system instability or waste of wireless resources. Therefore, in this article, we propose a quality-of-service (QoS)-oriented UAV-enabled positioning system based on the concept of sensing-communication-control (SCC) co-design. We first establish the mathematical models of UAV state sensing and control. Then, the influence of sensing scheduling and transmission failure on UAV stability, as well as the performance of positioning services in the presence of UAV control error, are analyzed. Based on these models and analysis results, we further study the problem of minimizing the amount of data transmitted by optimizing the sensing scheduling and blocklength allocation under the condition of satisfying each user's demand. Finally, an efficient scheme is developed to solve this mixed-integer nonlinear problem. Numerical results show that the proposed system could work efficiently and meet users' requirements. In addition, compared with two benchmark schemes, our scheme reduces the failure rate or resource consumption of positioning services by more than 76.2% or 82.7%.

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arXiv2020

Feasibility Study of UAV-Assisted Anti-Jamming Positioning

As the cost and technical difficulty of jamming devices continue to decrease, jamming has become one of the major threats to positioning service. Unfortunately, most conventional technologies are vulnerable to jamming attacks due to their inherent shortcomings like weak signal strength and unfavorable anchor geometry. Thanks to the high operational flexibility, unmanned aerial vehicle (UAV) could fly close to users to enhance signal strength while maintaining a satisfactory geometry, making it a potential solution to the above challenges. In this article, we propose a UAV-assisted anti-jamming positioning system, in which multiple UAVs first utilize time-difference-of-arrival (TDoA) measurements from ground reference stations and double-response two-way ranging (DR-TWR) measurements from UAV-to-UAV links to perform self-localization as well as clock synchronization, and then act as anchor nodes to provide TDoA positioning service for ground users in the presence of jamming. To evaluate the feasibility and performance of the proposed system, we first derive the Cramer-Rao lower bound (CRLB) of UAV self-localization. Then, the impacts of UAV position uncertainty and synchronization errors caused by jamming on positioning service are modeled, and the theoretical root-mean-square error (RMSE) of user position estimate is further derived. Numerical results demonstrate that the proposed system is a promising alternative to existing positioning systems when their services are disrupted by jamming. The most notable advantage of the proposed system is that it is fully compatible with existing user equipment (UE) and positioning methods.

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arXiv2020

Towards Reliable UAV-Enabled Positioning in Mountainous Environments: System Design and Preliminary Results

Reliable positioning services are extremely important for users and devices in mountainous environments as it enables a variety of location-based applications. However, in such environments, the service reliability of conventional wireless positioning technologies is often disappointing. Frequent non-line-of-sight (NLoS) propagation and poor geometry of available anchor nodes are two significant challenges. Due to the high maneuverability and flexible deployment of unmanned aerial vehicles (UAVs), UAV-enabled positioning could be a promising solution to these challenges. Compared with satellites and terrestrial base stations, UAVs are capable of flying to places where both the propagation conditions and geometry are favorable for positioning. The eventual aim of this research project is to design a novel UAV-enabled positioning system that uses a low-altitude UAV platform to provide highly reliable services for ground users in mountainous environments. In this article, we introduce the recent progress made in the first phase of our project, including the following. First, the structure of the proposed system and the positioning method used are determined after comprehensive consideration of various factors. Utilizing the digital elevation model of the realistic terrain, we then establish a geometry-based NLoS probability model so that the NLoS propagation can be treated as a type of fault during the reliability analysis. Most importantly, a reliability prediction method and the corresponding metric are developed to evaluate the system's ability to provide reliable positioning services. At the end of this article, we also propose a voting-based method for improving the service reliability. Numerical results demonstrate the tremendous potential of the proposed system in reliable positioning.

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