Intelligent Fusion Technology, Inc.

United States of America as Represented by the Secretary of the Air Force

Genshe Chen

Khanh D Pham

Erik Philip Blasch

Dan Shen

Xin Tian

Zhonghai Wang

Bin Jia

Yi Li

Jingyang Lu

Xingping Lin

Nichole Sullivan

Sixiao Wei

Gang Wang

Lun Li

Wenhao Xiong

Kui Liu

Qi Zhao

Xingyu Xiang

Tien M Nguyen

Zhijiang Chen

Carolyn Sheaff

Hua-mei Chen

Haibin Ling

Weifeng Su

Jiaoyue Liu

Yiran Xu

Yajie Bao

Kuo-Chu Chang

Tao Wang

Biao Chen

Mingjie Feng

Huamei Chen

Li Li

Bora Sul

Roman Ilin

Ashley Diehl

Hui Huang

Peng Cheng

Zhengyang Fan

Tien Nguyen

Huong Ngoc Dang

John Nguyen

Bingwei Liu

Zhi Tian

Zijian Mo

Zhihui Shu

Thomas M Clemons, Iii

Cailing Dong

Hua-Mei Harry Chen

Peter Zulch

Marcello Disasio

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.

Method, device and system of point cloud compression for intelligent cooperative perception system

The present disclosure provides a method, a system and a storage medium of resilient human-on-the-loop range-only cooperative positioning of a plurality of unmanned aerial vehicles (UAVs). The method includes computing an initial exploitability using an initial distribution and an initial policy; performing a forward updating of a distribution of a portion of the plurality of UAVs, and performing a backward updating of a Q function of each UAV of the plurality of UAVs; for each time step, calculating a dual variable at an (i+1)-th iteration and calculating a policy at an (i+1)-th iteration; computing a ratio of an exploitability at the (i+1)-th iteration over the initial exploitability; and if the ratio is less than or equal to a pre-defined tolerance value, maintaining a policy at the i-th iteration; and if the ratio is greater than the pre-defined tolerance value, using the policy at the (i+1)-th iteration.

Method, system and storage medium of resilient human-on-the-loop range-only cooperative positioning of plurality of unmanned aerial vehicles

A global navigation satellite system (GNSS) is disclosed comprising a transmitter. The transmitter is configured to: receive a plurality of frequencies; determine a minimum frequency from the plurality of frequencies; determine a maximum frequency from the plurality of frequencies; determine a carrier from the minimum frequency and the maximum frequency; determine a set of subcarriers from the carrier and the plurality of frequencies; identify optimal radius of desired phase points to select optimal subcarriers from the set of subcarriers; determine inter-modulation terms with a minimal energy based on the optimal subcarriers; and generate multi-carrier constant envelope waveforms based on the inter-modulation terms.

Method, device and system of multi-carrier constant envelope GNSS waveforms compatible with existing user equipment

A method for detecting GPS spoofing attacks includes providing a trained deep learning (DL) model based on neural networks, feeding GPS signals into the trained DL model, using asymmetric Shapley values (ASVs) to calculate feature contributions, using the ASVs to assign a non-uniform distribution over an ordering of features, obtaining causal structures among the features, applying the ASVs to causal Shapley additive explanation to obtain Shapley attributions, incorporating the Shapley attributions and the causal structures, and detecting GPS spoofing attacks by running the trained DL model and using the causal structures, non-uniform distribution, feature contributions, and Shapley attributions.

Systems and methods to detect GPS spoofing attacks

The present disclosure provides a cross-correlation based method, a system and a storage medium for blind electromagnetic interference Doppler estimation from a single satellite geolocation system. The method includes at a first time, calculating a power spectral density (PSD) of a received signal; smoothing the PSD of the received signal using moving window average, and saving the smoothed PSD of the received signal as PSD0; at a next time, calculating a PSD of another received signal; smoothing the PSD of the another received signal using moving window average, and saving the smoothed PSD of the another received signal as PSD1; performing cross correlation between PSD0 and PSD1 to obtain a cross-correlation result; determining a peak position from the cross-correlation result; and obtaining a Doppler estimation based on a peak position shift between the peak position and a reference position.

System, method, and storage medium for design and use reference emitters to enhance passive single satellite geolocation of EMI sources

A method for recognizing a low-probability-of-interception (LPI) radar signal waveform includes: obtaining, by a radar signal receiver, an LPI radar signal s(t), s(t) varying with time t; extracting, by a radar signal processor, an adaptive feature and a pre-defined analytical feature from the LPI radar signal s(t); combining, by the radar signal processor, the adaptive feature with the pre-defined analytical feature to generate a constructed adaptive feature; and applying, by the radar signal processor, a convolutional neural network (CNN) model to classify the constructed adaptive feature to recognize the LPI radar signal waveform.

Method and system for low-probability-of-intercept radar signal waveform recognition

A method for detecting fake images includes: obtaining an image for authentication, and hand-crafting a multi-attribute classifier to determine whether the image is authentic. Hand-crafting the multi-attribute classifier includes fusing at least an image classifier, an image spectrum classifier, a co-occurrence matrix classifier, and a one-dimensional (1D) power spectrum density (PSD) classifier. The multi-attribute classifier is trained by pre-processing training images to generate an attribute-specific training dataset to train each of the image classifier, the image spectrum classifier, the co-occurrence matrix classifier, and the 1D PSD classifier.

Method and system of multi-attribute network based fake imagery detection (MANFID)

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.

Method, device, and storage medium for deep learning based domain adaptation with data fusion for aerial image data analysis

The present disclosure provides a method, a system and a storage medium of PID-based automatic gain control for a satellite transponder system. The method includes receiving a sequence of sample signals; determining two different block sizes where a block size of a first block is greater than a block size of a second block; using the block size of the first block to compute a first signal-amplitude-ratio (SAR)-based gain value and using the block size of the second block to compute a second signal-amplitude-ratio (SAR)-based gain value by the AGC processor through the sequence of sample signals; calculating a to-be-applied gain control value of an m-th transmitted symbol at a n-th time step; and calculating a new AGC gain at the n-th time step according to the to-be-applied gain control value at the n-th time step and a corresponding AGC gain at the (n−1)-th time step.

Method, system and storage medium of proportional-integral-derivative based automatic gain control for satellite transponder system under partial-time partial-band additive white gaussian noise jamming

An edge network computing system includes: a plurality of terminal devices; a plurality of edge servers connected to the terminal device through an access network; and a plurality of cloud servers connected to the plurality of edge servers through a core network. Each edge server is configured to: receive a plurality of computing tasks originated from one of the plurality of terminal devices; use a deep Q-learning neural network (DQN) with experience replay to select one of the plurality of could servers to offload a portion of the plurality of computing tasks; and send the portion of the plurality of computing tasks to the selected cloud server and forward results of the portion of the plurality of computing tasks received from the selected cloud server to the originating terminal device.

Edge network computing system with deep reinforcement learning based task scheduling

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.

Method, device, and storage medium for NDN based data transfer in multi-path networking environments

Embodiments of the present disclosure provide a method, a device, and a storage medium for targeted adversarial discriminative domain adaptation (T-ADDA). The method includes pre-training a source model including a source feature encoder and a source classifier, adapting a target feature encoder, and generating a target model by concatenating the adapted target feature encoder with the pre-trained source classifier. Adapting the target feature encoder includes configuring the pre-trained source feature encoder to be an initial target feature encoder for generating target feature vectors in each target class; adjusting a domain discriminator according to an adversarial domain discrimination loss; adjusting the initial target feature encoder according to a generative adversarial network (GAN) loss; and further adjusting the initial target feature encoder to generate the target feature encoder according to a feature class matching loss using labeled target feature vectors and corresponding source feature class centers.

Method, device, and storage medium for targeted adversarial discriminative domain adaptation

Embodiments of the present disclosure provide a method, a device, and a storage medium for hybrid automatic gain control in a communication system. The method includes amplifying an input signal to generate an amplified signal which is converted into a plurality of output signals; obtaining a moving average amplitude of a plurality of output signals of a current input signal; and calculating a signal amplitude difference according to the moving average amplitude and a desired output signal amplitude level; calculating a signal amplitude ratio according to a plurality of output signals of two previous output signal blocks and AGC gains corresponding to the plurality of output signals of the two previous output signal blocks; obtaining a step size according to the signal amplitude difference and the signal amplitude ratio; and calculating an AGC gain of the current input signal according to the step size and a corresponding previous AGC gain.

Method, device, and storage medium for hybrid automatic gain control in communication system

A system includes: a named data networking (NDN) based Spark distributed computing network including a Spark distributed computing network including a master computer node and a plurality of slave computer nodes, and a named data networking (NDN) protocol installed on the Spark distributed computing network, and a coded distributed computing (CDC) target recognition model deployed on the NDN-based Spark distributed computing network. The NDN-based Spark distributed computing network is configured to: receive one or more batches of input images; generate a parity image from each batch of the input images; predict a label for each image of the batch of the input images; process the generated parity image; upon a label prediction of one image of the batch of the input images being unavailable, reconstruct the unavailable label prediction; and classify labels for the input images.

Methods and systems of resilient mobile distributed computing

A system and method are provided for enhanced multi-way time transfer for time synchronization between at least one slave node and one master node. A slave node sends a first message to the master node to launch a time synchronization between the slave node and the master node. Upon receiving the first message, the master node adds a receiving time on a master clock to the first message to form a second message. The master node sends the second message back to the slave node and the slave node adds a receiving time on the slave clock to the second message to form an updated message. The slave node performs a time adjustment to the slave clock based on the updated message, thereby synchronizing time between the slave node and the master node.

Methods and systems for time synchronization among unmanned aerial systems

Growing community of inventors

Germantown, MD, United States of America

Genshe Chen