arXiv subjects

Haohan Li

Publications and source records attributed to Haohan Li.

9 recordsLinked to original sources

arXiv2026

Sensing the Variation of Wireless Propagation Environment Based on Channel Knowledge Map

With the evolution of sixth-generation (6G) wireless systems, integrated sensing and communication (ISAC) has raised the demand for high-precision environmental perception. To address the limited capability of existing techniques in sensing environmental variations, this work proposes a novel channel knowledge map (CKM)-based sensing framework that enables structural change sensing in the wireless propagation environment. By leveraging historical CKM data and real?time user channel, a mathematical model is formulated to infer the changing reflectors which represents the environment variations. Specifically, we propose the Information Aggregation Based Robust Two-Stage Reflection Point Refinement (IA-TS-RPR) scheme for reflection point (RP) estimation, which first uses block coordinate descent (BCD) and Riemannian manifold optimization (RMO) for initial estimation, then applies virtual base station (VBS) clustering for information aggregation in the sensitive area (SA) to refine the estimation. Furthermore, we propose an Environment Variation Sensing scheme based on the Hausdorff-Nearest Neighbor Criterion and Time-Window Voting (EVS-HC-TWV). Specifically, the Hausdorff distance is used to match each user to its most relevant CKM grid point (GP), and a time-window-based multi-user voting mechanism is further employed to improve robustness against positional deviations. Simulation results demonstrate that the proposed IA-TS-RPR scheme maintains sub-meter RP position estimation accuracy under user positioning errors, significantly outperforming the scheme based on time of arrival (ToA), linear minimum mean square error (LMMSE) and least squares (LS). The proposed scheme successfully senses and localizes dynamic reflectors, showing strong generalizability and robustness.

eess.SP↗

arXiv2026

Autonomous Orbit Determination Analysis of a Conceptual Cislunar Navigation Constellation based on Inter-Satellite Range Measurement

With the community's increasing interest in the cislunar space, building a navigation constellation servicing the whole cislunar space has become a pressing need. Previous studies mainly focus on constellations using orbits close to the Moon, which limits the servicing volume of the constellation. In this work, a four-satellite constellation using one L3 orbit, one L4 orbit, one L5 orbit and an orbit close to the Moon is proposed. The orbit determination accuracy is an important factor to be considered when designing parameters of the constellation. In this study, the mode of autonomous orbit determination (AOD) based on inter-satellite range data is considered. With such a model, the out-of-plane design parameters are identified as the main parameters influencing the AOD accuracy. For the AOD based on short arcs, we find that the increase of the out-of-plane amplitude can improve the AOD accuracy, and the out-of-plane initial phases have a more complex influence. A novel relative planarity factor (RPF) $P_\text{r}$, which has negative correlation with the AOD accuracy, is proposed as the metric to evaluate the variation of AOD performance. Using $P_\text{r}$, we demonstrate that the coplanarity of the constellation can significantly reduce the AOD accuracy. For the long arc AOD, the influence of different parameters is insignificant.

astro-ph.EP↗

arXiv2026

Contact Plan Design for Cross-Linked GNSSs: An ILP Approach for Extended Applications

Global Navigation Satellite Systems (GNSS) employ inter-satellite links (ISLs) to reduce dependency on ground stations, enabling precise ranging and communication across satellites. Beyond their traditional role, ISLs can support extended applications, including providing navigation and communication services to external entities. However, designing effective contact plan design (CPD) schemes for these multifaceted ISLs, operating under a polling time-division duplex (PTDD) framework, remains a critical challenge. Existing CPD approaches focus solely on meeting GNSS satellites' internal ranging and communication demands, neglecting their extended applications. This paper introduces the first CPD scheme capable of supporting extended GNSS ISLs. By modeling GNSS requirements and designing a tailored service process, our approach ensures the allocation of essential resources for internal operations while accommodating external user demands. Based on the BeiDou constellation, simulation results demonstrate the proposed scheme's efficacy in maintaining core GNSS functionality while providing extended ISLs on a best-effort basis. Additionally, the results highlight the significant impact of GNSS ISLs in enhancing orbit determination and clock synchronization for the Earth-Moon libration point constellation, underscoring the importance of extended GNSS ISL applications.

eess.SY↗

arXiv2026

A new solar radiation pressure model for some orbit types in the cislunar space

For satellites in the cislunar space, solar radiation pressure (SRP) is the third largest perturbation, which is only less significant than the lunisolar gravity perturbations. It is the primary factor limiting the accuracy of orbit determination for such satellites. Up to now, numerous SRP models have been proposed for artificial satellites close to the Earth, but these models have their shortcomings when applied to satellites in the cislunar space. In this study, we concentrate on various scenarios of cislunar satellites in periodic or quasi-periodic orbits. We first employ the box-wing model to simulate the SRP effects and then propose an appropriate general SRP model based on these simulations, termed Empirical NJU Cislunar Model (ENCM). Additionally, several scenario-specific sub-models suited to different mission profiles are developed. Furthermore, the proposed model is verified in the orbit determination process. Comparisons with the conventional cannonball and ECOM models demonstrate that the ENCM model yields a significant improvement in orbit determination accuracy, showing promising potential for future cislunar missions.

astro-ph.EP↗

arXiv2025

Joint Contact Planning for Navigation and Communication in GNSS-Libration Point Systems

Deploying satellites at Earth-Moon Libration Points (LPs) addresses the inherent deep-space coverage gaps of low-altitude GNSS constellations. Integrating LP satellites with GNSS into a joint constellation enables a more robust and comprehensive Positioning, Navigation, and Timing (PNT) system, while also extending navigation and communication services to spacecraft operating in cislunar space (i.e., users). However, the long propagation delays between LP satellites, users, and GNSS satellites result in significantly different link durations compared to those within the GNSS constellation. Scheduling inter-satellite links (ISLs) is a core task of Contact Plan Design (CPD). Existing CPD approaches focus exclusively on GNSS constellations, assuming uniform link durations, and thus cannot accommodate the heterogeneous link timescales present in a joint GNSS-LP system. To overcome this limitation, we introduce a Joint CPD (J-CPD) scheme tailored to handle ISLs with differing duration units across integrated constellations. The key contributions of J-CPD are: (i):introduction of LongSlots (Earth-Moon scale links) and ShortSlots (GNSS-scale links); (ii):a hierarchical and crossed CPD process for scheduling LongSlots and ShortSlots ISLs; (iii):an energy-driven link scheduling algorithm adapted to the CPD process. Simulations on a joint BeiDou-LP constellation demonstrate that J-CPD surpasses the baseline FCP method in both delay and ranging coverage, while maintaining high user satisfaction and enabling tunable trade-offs through adjustable potential-energy parameters. To our knowledge, this is the first CPD framework to jointly optimize navigation and communication in GNSS-LP systems, representing a key step toward unified and resilient deep-space PNT architectures.

eess.SY↗

arXiv2025

Mazzaroth: A High-Throughput DAG Consensus with State Root

Nakamoto Consensus achieves a decentralized ledger through a single-chain blockchain, assuming a maximum network delay, which limits block generation speed, resulting in low throughput. \cite{pg2018} (PG) enhances throughput using a blockDAG structure, but its probabilistic confirmation restricts smart contract applications. To address this, Mazzaroth proposes a Pow-based blockDAG consensus, employing a linear ordering algorithm to compute the \cite{eth} and achieve state finality, thereby supporting smart contracts. Its dynamic difficulty adjustment, independent of the assumption, adapts to network and hashrate fluctuations, ensuring state consistency via a head chain while maximizing throughput. Simulations validate Mazzaroth's efficient consensus performance. This paper presents the Mazzaroth ordering algorithm, the difficulty adjustment mechanism, and performance evaluation.

cs.DC↗

arXiv2024

MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning

In recent years, multimodal benchmarks for general domains have guided the rapid development of multimodal models on general tasks. However, the financial field has its peculiarities. It features unique graphical images (e.g., candlestick charts, technical indicator charts) and possesses a wealth of specialized financial knowledge (e.g., futures, turnover rate). Therefore, benchmarks from general fields often fail to measure the performance of multimodal models in the financial domain, and thus cannot effectively guide the rapid development of large financial models. To promote the development of large financial multimodal models, we propose MME-Finance, an bilingual open-ended and practical usage-oriented Visual Question Answering (VQA) benchmark. The characteristics of our benchmark are finance and expertise, which include constructing charts that reflect the actual usage needs of users (e.g., computer screenshots and mobile photography), creating questions according to the preferences in financial domain inquiries, and annotating questions by experts with 10+ years of experience in the financial industry. Additionally, we have developed a custom-designed financial evaluation system in which visual information is first introduced in the multi-modal evaluation process. Extensive experimental evaluations of 19 mainstream MLLMs are conducted to test their perception, reasoning, and cognition capabilities. The results indicate that models performing well on general benchmarks cannot do well on MME-Finance; for instance, the top-performing open-source and closed-source models obtain 65.69 (Qwen2VL-72B) and 63.18 (GPT-4o), respectively. Their performance is particularly poor in categories most relevant to finance, such as candlestick charts and technical indicator charts. In addition, we propose a Chinese version, which helps compare performance of MLLMs under a Chinese context.

cs.CV↗

arXiv2018

Weighted Nonlocal Total Variation in Image Processing

In this paper, a novel weighted nonlocal total variation (WNTV) method is proposed. Compared to the classical nonlocal total variation methods, our method modifies the energy functional to introduce a weight to balance between the labeled sets and unlabeled sets. With extensive numerical examples in semi-supervised clustering, image inpainting and image colorization, we demonstrate that WNTV provides an effective and efficient method in many image processing and machine learning problems.

cs.CV↗

arXiv2016

An efficient iterative thresholding method for image segmentation

We proposed an efficient iterative thresholding method for multi-phase image segmentation. The algorithm is based on minimizing piecewise constant Mumford-Shah functional in which the contour length (or perimeter) is approximated by a non-local multi-phase energy. The minimization problem is solved by an iterative method. Each iteration consists of computing simple convolutions followed by a thresholding step. The algorithm is easy to implement and has the optimal complexity $O(N \log N)$ per iteration. We also show that the iterative algorithm has the total energy decaying property. We present some numerical results to show the efficiency of our method.

cs.CV↗