公开(公告)号：US20220014347A1

公开(公告)日：2022-01-13

申请号：US16924853

申请日：2020-07-09

Applicant: INTELLIGENT FUSION TECHNOLOGY, INC.

Inventor： Xin TIAN ,  Genshe CHEN ,  Khanh PHAM ,  Erik BLASCH

IPC: H04L5/14 ,  H04L25/02 ,  H04L25/03 ,  H04B17/391 ,  H04B17/373

Abstract: A method for emulating a communication system with fast changing link condition, applied to a testbed system including an interference emulator, a transmitter, and a receiver, includes: by the transmitter, generating code-word symbols, in an initial symbol sequence, according to information bits; evaluating an interference condition and a time duration for each code-word symbol; reordering the code-word symbols to a reordered symbol sequence based on interference conditions; evaluating a total time duration of code-word symbols under each interference condition; and transmitting the code-word symbols in the reordered symbol sequence. The method also includes: by the interference emulator, obtaining the total time duration of code-word symbols under each interference condition from the transmitter; and providing an emulated interference environment by ordering the time durations of different interference conditions. The start time for transmitting code-word symbols with an interference condition is synchronized with the start time for emulating the interference condition.

公开(公告)号：US20210134046A1

公开(公告)日：2021-05-06

申请号：US16674929

申请日：2019-11-05

Applicant: INTELLIGENT FUSION TECHNOLOGY, INC.

Inventor： Jingyang LU ,  Yiran XU ,  Dan SHEN ,  Nichole SULLIVAN ,  Genshe CHEN ,  Khanh PHAM ,  Erik BLASCH

IPC: G06T15/06 ,  G06N20/00 ,  G06N5/04

Abstract: The present disclosure provides a method for wave propagation prediction based on a 3D ray tracing engine and machine-learning based dominant ray selection. The method includes receiving, integrating, and processing input data. Integrating and processing the input data includes dividing a cone of the original millimeter wave (mmWave) into a plurality of sub cones; determining a contribution weight of rays coming from each sub cone to the received signal strength (RSS) at a receiving end of interest; and determining rays coming from one or more sub cones that have a total contribution weight to the RSS larger than a preset threshold value as dominant rays using a neural network obtained through a machine learning approach. The method further includes performing ray tracing based on the input data and the dominant rays to predict wave propagation.

公开(公告)号：US20190219706A1

公开(公告)日：2019-07-18

申请号：US15874526

申请日：2018-01-18

Applicant: Intelligent Fusion Technology, Inc

Inventor： Zhonghai WANG ,  Bin JIA ,  Xingping LIN ,  Tao WANG ,  Xingyu XIANG ,  Genshe CHEN ,  Dan SHEN ,  Khanh PHAM ,  Erik BLASCH

IPC: G01S19/23

Abstract: A method for testing satellite signal receiver antenna is provided. The method includes: determining a satellite constellation state indicating status of a plurality of satellites in a satellite constellation; calculating, based on the determined satellite constellation state, initial positions of a plurality of satellite antennas that are used for emulating the satellite constellation; moving the plurality of satellite antennas to the initial positions of the plurality of satellite antennas; calibrating a phase delay of each of the plurality of satellite antennas; broadcasting, by the plurality of satellite antennas, satellite signals to test a satellite signal receiver antenna; determining a movement plan for the plurality of satellite antennas based on the satellite constellation state; and moving the plurality of satellite antennas based on the movement plan to emulate a propagation of the satellite constellation.

公开(公告)号：US20240403117A1

公开(公告)日：2024-12-05

申请号：US18806392

申请日：2024-08-15

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Qi ZHAO ,  Genshe CHEN ,  Khanh PHAM ,  Erik BLASCH

IPC: G06F9/48 ,  G06F9/54 ,  G06N20/00

Abstract: The present disclosure provides a machine-learning-based real-time task scheduling method. The method includes, for a worker node, executing a training task distributed by a master node; collecting latency time lengths of each machine learning model under different CPU utilization and memory usage; calculating a mean squared error of the latency time lengths of each machine learning model; comparing machine learning models according to mean squared errors of latency time lengths to select a desirable machine learning model installing on the worker node; providing an API for the worker node; when receiving a task by the master node, requesting the worker node to predict a latency time length; and returning the predicted latency time length to the master node; and after the master node collects predicted latency time lengths of worker nodes, assigning the task to a corresponding worker node with a lowest predicted latency time length.

公开(公告)号：US20240305551A1

公开(公告)日：2024-09-12

申请号：US18197330

申请日：2023-05-15

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Xin TIAN ,  Genshe CHEN ,  Khanh PHAM ,  Erik BLASCH

IPC: H04L43/0888 ,  H04L43/106 ,  H04L43/12

CPC classification number: H04L43/0888 ,  H04L43/106 ,  H04L43/12

Abstract: Embodiments of the present disclosure provide a method of a burst-based route discovery process. The method includes sending a probing interest packet to an NDN network; when one NDN forwarder receives the probing interest packet from a corresponding face, sending the probing interest packet to neighboring NDN forwarders; after anyone NDN forwarder receives the probing interest packet, sending back a burst of K probing data packets; as the burst of K probing data packets being received by an NDN forwarder, evaluating gaps between arrival times of the burst of K probing data packets; determining an available network throughput level of a face of the NDN forwarder; and if determined available network throughput level indicates a predefined increase in network throughput, setting the face of the NDN forwarder as a face for forwarding interest packets; and sending the burst of K probing data packets to neighboring NDN forwarders.

公开(公告)号：US20230179265A1

公开(公告)日：2023-06-08

申请号：US16813250

申请日：2020-03-09

Applicant: INTELLIGENT FUSION TECHNOLOGY, INC.

Inventor： Zhonghai WANG ,  Xingping LIN ,  Genshe CHEN ,  Khanh PHAM ,  Erik BLASCH

IPC: G01S13/90 ,  G01S13/88 ,  G01S7/35

CPC classification number: G01S13/9017 ,  G01S7/354 ,  G01S13/888

Abstract: A hidden chamber detector includes a linear frequency modulated continuous wave (LFMCW) radar, a synthetic aperture radar (SAR) imaging processor, and a time division multiple access (TDMA) multiple input multiple output (MIMO) antenna array, including a plurality of transmitting and receiving (Tx-Rx) antenna pairs. A Tx-Rx antenna pair is selected, in a time division manner, as a Tx antenna and an Rx antenna for the LFMCW radar. The LFMCW radar is configured to transmit an illumination signal, receive an echo signal, convert the echo signal to a baseband signal, collect baseband samples, and send the collected samples to the SAR imaging processor. The SAR imaging processor is configured to receive the collected samples, collect structure/configuration of the antenna array and scanning information, and form an SAR image based on the collected samples, the structure/configuration of the antenna array, and the scanning information.

公开(公告)号：US20220375134A1

公开(公告)日：2022-11-24

申请号：US17734858

申请日：2022-05-02

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Qi ZHAO ,  Yi LI ,  Xin TIAN ,  Genshe CHEN ,  Erik BLASCH ,  Khanh PHAM

IPC: G06T9/00 ,  G06T3/00 ,  G06V10/25 ,  G01S17/89

Abstract: A method for point cloud compression of an intelligent cooperative perception (iCOOPER) for autonomous air vehicles (AAVs) includes: receiving a sequence of consecutive point clouds; identifying a key point cloud (K-frame) from the sequence of consecutive point clouds; transforming each of the other consecutive point clouds (P-frames) to have the same coordinate system as the K-frame; converting each of the K-frame and P-frames into a corresponding range image; spatially encoding the range image of the K-frame by fitting planes; and temporally encoding each of the range images of the P-frames using the fitting planes.

公开(公告)号：US20220172122A1

公开(公告)日：2022-06-02

申请号：US17563014

申请日：2021-12-27

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Dan SHEN ,  Peter ZULCH ,  Marcello DISASIO ,  Erik BLASCH ,  Genshe CHEN

IPC: G06N20/00 ,  H04N5/33 ,  G06K9/62

Abstract: The present disclosure provide a system, a method, and a storage medium for distributed joint manifold learning (DJML) based heterogeneous sensor data fusion. The system includes a plurality of nodes; and each node includes at least one camera; one or more sensors; at least one memory configured to store program instructions; and at least one processor, when executing the program instructions, configured to obtain heterogeneous sensor data from the one or more sensors to form a joint manifold; determine one or more optimum manifold learning algorithms by evaluating a plurality of manifold learning algorithms based on the joint manifold; compute a contribution of the node based on the one or more optimum manifold learning algorithms; update a contribution table based on the contribution of the node and contributions received from one or more neighboring nodes; and broadcast the updated contribution table to the one or more neighboring nodes.

公开(公告)号：US20220092420A1

公开(公告)日：2022-03-24

申请号：US17480999

申请日：2021-09-21

Applicant: Intelligent Fusion Technology, Inc.

Inventor： Jingyang LU ,  Erik BLASCH ,  Roman ILIN ,  Hua-mei CHEN ,  Dan SHEN ,  Nichole SULLIVAN ,  Genshe CHEN

IPC: G06N3/08 ,  G06K9/62 ,  G06K9/00

Abstract: Embodiments of the present disclosure provide a method, a device, and a storage medium for domain adaptation for efficient learning fusion (DAELF). The method includes acquiring data from a plurality of data sources of a plurality of sensors; for each of the plurality of sensors, training an auxiliary classifier generative adversarial network (AC-GAN) by a hardware processor with data from each data source of the plurality of data sources, thereby obtaining a trained feature extraction network and a trained label prediction network for each data source; forming a decision-level fusion network or a feature-level fusion network; and training the decision-level fusion network or the feature-level fusion network with a source-only mode or a generate to adapt (GTA) mode; and applying the trained decision-level fusion network or the trained feature-level fusion network to detect a target of interest.

公开(公告)号：US20190356053A1

公开(公告)日：2019-11-21

申请号：US15983266

申请日：2018-05-18

Applicant: Intelligent Fusion Technology, Inc

Inventor： Xingping LIN ,  Zhonghai WANG ,  Genshe CHEN ,  Erik BLASCH ,  Khanh PHAM

IPC: H01Q9/28 ,  H01Q5/378 ,  H01Q1/38

Abstract: A cone-based multi-layer wide band antenna is provided, including a cone-based member having a multi-layer structure. The multi-layer structure includes a first layer conical structure, and the first layer conical structure has a height and a base radius configured to provide a desired impedance of the antenna.