Genshe Chen

Genshe Chen
Intelligent Fusion Technology, Inc.

Ph. D.

About

384
Publications
127,201
Reads
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5,234
Citations
Additional affiliations
September 2012 - present
Intelligent Fusion Technology, Inc.
Position
  • CTO
Description
  • Directs the research and development activities for the Government Services and Commercial Solutions.
January 2008 - September 2010
DCM Research Resources, LLC
Position
  • CTO
Description
  • Directed the research and development activities for the Government Services and Commercial Solutions.
February 2004 - January 2008
Intelligent Automation, Inc.
Position
  • Program Manager in Networks, Systems and Control
Description
  • Developed a team working on target tracking, adversarial intent inference, situation awareness, cooperative control, and resource management in air-space-cyber system.
Education
May 1985 - July 1994
Northwestern Polytechnical University
Field of study
  • Engineering (Aerospace, Electrical)

Publications

Publications (384)
Conference Paper
Full-text available
Distributed sparse arrays, consisting of multiple subarrays, facilitate a higher number of degrees of freedom and enhanced direction-of-arrival (DOA) estimation performance beyond what is offered by single uniform linear arrays. When the array elements in each subarray are sparsely located, the covariance matrix is sparse with missing entries. Cova...
Conference Paper
Given the significant technological advances over the past few years, autonomous vehicles are gradually entering the industrialization stage. Light detection and ranging (LiDAR) sensors are seeing increased use in autonomous vehicles. However, the final implementation of the technology remains undetermined because major automotive manufacturers hav...
Article
Light detection and ranging (Lidar) imaging systems are being increasingly used in autonomous vehicles. However, the final technology implementation is still undetermined as major automotive manufacturers are only starting to select providers for data collection units that can be introduced in commercial vehicles. Currently, testing for autonomous...
Article
The capability accurately and timely detect a resident space object (RSO) maneuver is a critical task for monitoring space activities. This paper presents a data-driven Gaussian Binary RSO Maneuver Detection (GaBRSOMD) method to detect whether or not there is a maneuver between two tracks of the same RSO on different orbital paths. Using an in-hous...
Conference Paper
Full-text available
Mobile Edge Computing (MEC) is a key technology to support the emerging low-latency Internet of Things (IoT) applications. With computing servers deployed at the network edge, the computational tasks generated by mobile users can be offloaded to these MEC servers and executed there with low latency. Meanwhile, with the ever-increasing number of mob...
Chapter
Full-text available
Current Artificial Intelligence (AI) machine learning approaches perform well with similar sensors for data collection, training, and testing. The ability to learn and analyze data from multiple sources would enhance capabilities for Artificial Intelligence (AI) systems. This paper presents a deep learning-based multi-source self-correcting approac...
Chapter
Motion imagery interpretability is commonly represented by the Video National Imagery Interpretability Rating Scale (VNIIRS), which is a subjective metric based on human analysts’ visual assessment. Therefore, VNIIRS is a very time-consuming task. This paper presents the development of a fully automated motion imagery interpretability prediction, c...
Conference Paper
Full-text available
Space situational awareness (SSA) is needed to control satellite movement and space pervasiveness, which relies on quick and precise space object behavioral classification and discovery. Perhaps the biggest obstacle in adopting machine learning (ML) techniques and evaluating their performance in SSA applications is the lack of large, labeled datase...
Chapter
Full-text available
The chapter presents a game theoretic training model enabling a deep learning solution for rapid discovery of satellite behaviors from collected sensor data. The solution has two parts, namely, Part 1 and Part 2. Part 1 is a PE game model that enables data augmentation method, and Part 2 uses convolutional neural networks (CNNs) for satellite behav...
Conference Paper
Full-text available
Advancement in artificial intelligence (AI) and machine learning (ML), dynamic data driven application systems (DDDAS), and hierarchical cloud-fog-edge computing paradigm provide opportunities for enhancing multi-domain systems performance. As one example that represents multi-domain scenario, a ``fly-by-feel'' system utilizes DDDAS framework to su...
Preprint
Advancement in artificial intelligence (AI) and machine learning (ML), dynamic data driven application systems (DDDAS), and hierarchical cloud-fog-edge computing paradigm provide opportunities for enhancing multi-domain systems performance. As one example that represents multi-domain scenario, a "fly-by-feel" system utilizes DDDAS framework to supp...
Article
Full-text available
Recent research has demonstrated improved performance of a brain-computer interface (BCI) using fusion based approaches. This paper proposes a novel decision-making selector (DMS) to integrate classification decisions of different frequency recognition methods based on canonical correlation analysis (CCA) which were used in decoding steady state vi...
Article
Full-text available
Among the Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), the phase-tagged SSVEP (p-SSVEP) has been proved a reliable paradigm to extend the number of available targets, especially for high-frequency SSVEP-based BCIs. However, the recognition efficiency of the high-frequency p-SSVEP still remains relatively low....
Preprint
Blockchain is a popular method to ensure security for trusted systems. The benefits include an auditable method to provide decentralized security without a trusted third party, but the drawback is the large computational resources needed to process and store the ever-expanding chain of security blocks. The promise of blockchain for edge devices (e....
Preprint
A blockchain and smart contract enabled security mechanism for IoT applications has been reported recently for urban, financial, and network services. However, due to the power-intensive and a low-throughput consensus mechanism in existing blockchain, like Bitcoin and Ethereum, there are still challenges in integrating blockchain technology into re...
Article
Full-text available
A hardware-in-loop control framework with robot dynamic models, pursuit–evasion game models, sensor and information solutions, and entity tracking algorithms is designed and developed to demonstrate discrete-time robotic pursuit–evasion games for real-world conditions. A parameter estimator is implemented to learn the unknown parameters in the robo...
Conference Paper
Imaging studies are one of the leading drivers of modern medical decision making, and thus, their accessibility to healthcare providers and patients is of critical importance. However, current techniques for storage and transferring medical imaging data are inconvenient and sometimes wholly inadequate. In this paper, we propose a decentralized auto...
Preprint
With the development of modern information technology (IT), a smart grid has become one of the major components of smart cities. To take full advantage of the smart grid, the capability of intelligent scheduling and planning of electricity delivery is essential. In practice, many factors have an impact on electricity consumption, which necessitates...
Article
Full-text available
Space situation awareness (SSA) includes tracking of active and inactive resident space objects and assessing the space environment through sensor data collection and processing. To enhance SSA, the dynamic data-driven application systems framework couples online data with offline models to enhance performance by using feedback control, sensor mana...
Article
We propose the diffusion-based enhanced covariance intersection cooperative space object tracking (DeCiSpOT) filter. The main advantage of the proposed DeCiSpOT algorithm is that it can balance the computational complexity and communication requirements between different sensors as well as improve track accuracy when measurements do not exist or ar...
Preprint
Space situation awareness (SSA) includes tracking of active and inactive resident space objects (RSOs) and space weather assessment through space environmental data collection and processing. To enhance SSA, the dynamic data-driven applications systems (DDDAS) framework couples on-line data with off-line models to enhance system performance. For in...
Conference Paper
Pursuit-evasion (PE) games are mathematical tools to model the space situational awareness (SSA) problems, such as satellite interception, collision avoidance, and space sensor management. Early work in pursuit-evasion games took place before the wide availability of computers and software packages. Consequently, the application of PE game theory t...
Article
A joint manifold learning fusion (JMLF) approach is proposed for nonlinear or mixed sensor modalities with large streams of data. The multimodal sensor data are stacked to form joint manifolds, from which the embedded low intrinsic dimensionalities are discovered for moving targets. The intrinsic low dimensionalities are mapped to resolve the targe...