Nec Corporation

Nec Laboratories America, Inc.

Nec C Orporation

Karthikeyan Sundaresan

Sampath Rangarajan

Mohammad Ali Khojastepour

Eugene Chai

Mustafa Arslan

Rajesh Mahindra

Ayon Chakraborty

Ramanujan Sheshadri

Xiaodong Wang

Narayan Prasad

Mohammad Madihian

Xinyu Zhang

Jongwon Yoon

Sriram Lakshmanan

Md Shaifur Rahman

Krishna Garikipati

Ashutosh Dhekne

Mohammad Rostami

Xiufeng Xie

Ravindranath Kokku

Meilong Jiang

Honghai Zhang

Kishore Ramachandran

Mehrdad Moradi

Yuanxi Jiang

Swadhin Pradhan

Junguk Cho

Mallesham Dasari

Timothy Woodford

Arijit Banerjee

Rajarajan Sivaraj

Hariharasudhan Viswanathan

MdShaifur Rahman

Ahmed O F Atya

Jie Xiong

Sanaz Barghi

Cheng Liu

Mohammad Khojastepour

Systems and methods for automatically constructing a 3-dimensional (3D) model of a feature using a drone. The method includes generating a reconnaissance flight path that minimizes battery usage by the drone, and conducting a discovery flight that uses the reconnaissance flight path. The method further includes transmitting reconnaissance laser sensor data from the drone to a processing system for target identification, and selecting a target feature for 3D model construction based on the reconnaissance laser sensor data. The method further includes scanning the target feature using a laser sensor, transmitting laser sensor data for the target feature having a minimum point density from the drone to the processing system for 3D model construction, and constructing the 3D model from the minimum point density laser sensor data.

Near real-time reconstruction using drones

A method is provided for beam management. The method includes obtaining, by a Light Detection and Radar (LiDAR) sensor having one or more LiDAR cameras performing ray-tracing, out-of-band infrared measurements of a surrounding environment. The method further includes selecting, by a base station, a transmission and reception beam pair for use in the surrounding environment from a plurality of available transmission and reception beam pairs responsive to the out-of-band measurements of the surrounding environment.

LiDAR-driven mmWave beam management

Methods and systems for identifying device positions include measuring radio signal strength information between devices. Inertial information is measured for the devices. The radio signal strength information and the inertial information are fused to determine relative locations between the devices. The relative locations are oriented to a fixed anchor node. Elevation is estimated for the plurality of devices using pressure sensor information.

Device tracking with radio ranging and sensor functions

Methods and systems for determining a device position include determining a first position estimate using radio-based range information. A second position estimate is determined using visual odometry information. The first position estimate and the second position estimate are fused based on radio environmental conditions and visual environmental conditions to determine a final position estimate. Resources are deployed based on the final position estimate.

Visual and RF sensor fusion for multi-agent tracking

A product locating system is provided. The system includes at least one Radio Frequency (RF) backscatter transmitter configured to emit a main carrier RF signal that forms an excitation signal. The system further includes a passive RF backscatter tag associated with a product and configured to generate an Ultra-Wideband (UWB) signal from the excitation signal. The system also includes at least one RF backscatter receiver configured to simultaneously receive both the excitation signal from the at least one RF backscatter transmitter and the UWB signal from the passive RF backscatter tag, and compute the time-difference-of-arrival (TDoA) therebetween. TDoA information from multiple RF backscatter receivers, including the at least one RF backscatter receiver, is aggregated to compute the location of the product to which the passive RF backscatter tag is attached.

Locating objects in indoor spaces using radio frequency backscatter tags

A method for product tagging is presented including emitting, by at least one RF backscatter transmitter, a dual-tone Radio Frequency (RF) signal embedded within a standardized RF signal on a frequency channel, reflecting and frequency shifting, by a passive RF backscatter tag associated with a product, the dual-tone RF signal to a different frequency channel, and reading, by at least one RF backscatter receiver, the product on the different frequency channel by detecting a distributed ambient backscatter signal generated by a reflection and frequency shifting of the dual-tone RF signal by the passive RF backscatter tag.

Reading passive wireless tags using commodity devices

Methods and systems for localization within an environment include determining a topology estimate of nodes located in a dynamic indoor environment, based on distances measured between the nodes. Rigid k-core sub-graphs of the topology estimate are generated to determine relative localizations of the nodes. Relative localizations are transformed into absolute localizations to generate a map of positions of the nodes within the environment. A feature of the map is deployed to a device in the environment.

Infrastructure-free tracking and response

Aspects of the present disclosure describe systems, methods, and structures infrastructure-free RF tracking in dynamic indoor environments.

Infrastructure-free RF tracking in dynamic indoor environments

Systems and methods implementing a multi-unmanned aerial vehicle (UAV) wireless communication network are provided. The system includes application UAVs that wirelessly provide applications. The system includes relay UAVs that connect the application UAVs to a ground station. The ground station connects to a wireless backhaul network. Processor devices determine mobility for the application UAVs based on application-specific objectives. The processor devices also determine mobility for the relay UAVs based on forming and maintaining the wireless backhaul network.

Unmanned aerial vehicle network

Systems and methods for localizing and tracking mobile objects are provided. A method includes determining an initial location of a node in a multi-hop network based on multi-lateration from an unmanned aerial vehicle. The method also includes applying an adaptive aperture to address a non-uniform velocity of the node based on the turn and a velocity vector. A determination whether localization for the node can be implemented using first hop nodes in the multi-hop network is made. In response to a determination that localization cannot be implemented using the first hop nodes, inertial sensor measurements associated with the node are accessed and the inertial sensor measurements are integrated with the adaptive aperture to improve localization accuracy.

Tracking indoor objects with inertial sensor measurements

Systems and methods for localizing and tracking mobile objects are provided. The method includes determining an initial location of a node based on multi-lateration from an unmanned aerial vehicle and determining a velocity vector associated with the node based on multi-lateration. The method also includes detecting when the node turns. An adaptive aperture is applied to address a non-uniform velocity of the node based on the turn and the velocity vector.

Tracking indoor objects from an unmanned aerial vehicle

A computer-implemented method, system, and computer program product are provided for positioning an unmanned autonomous vehicle (UAV) in a long term evolution radio access network. The method includes acquiring, by a processor-device, a position of the UAV with a global position system. The method also includes determining, by the processor-device, physical distances from the UAV to each of a plurality of user equipment (UE) responsive to a time-of-flight from the UAV to each of the plurality of UE. The method additionally includes generating, by the processor-device, radio environment maps for each of the plurality of UE with signal-to-noise ratios (SNR) from each of the plurality of UEs to the UAV. The method further includes selecting, by the processor-device, a determined position for the UAV as a position with a minimum SNR in the REMs. The method also includes commanding the UAV to move to the determined position.

Self-configuring long term evolution radio access network on unmanned autonomous vehicles

A product tagging system is provided. The product tagging system includes at least one RF backscatter transmitter configured to emit (i) a main carrier RF signal, and (ii) Radio Frequency (RF) signals on two frequencies whose summation forms a twin carrier RF signal. The product tagging system further includes a passive RF backscatter tag associated with a product and configured to reflect and frequency shift the main carrier RF signal to a different frequency using the twin carrier RF signal. The product tagging system also includes at least one RF backscatter receiver configured to read the product on the different frequency by detecting a distributed ambient backscatter signal generated by a reflection and frequency shifting of the main carrier RF signal by the passive RF backscatter tag.

Tagging objects in indoor spaces using ambient, distributed backscatter

A navigation assistance system is provided. At least one RF backscatter transmitter, hosted on a device, is configured to emit a RF signal on a frequency. A set of passive RF backscatter tags, each associated with a respective one of a plurality of navigation markers in a given venue, is configured to reflect the RF signal and frequency shift the RF signal to a different frequency. At least one RF backscatter receiver is configured to read the navigation markers on the different frequency by detecting a distributed ambient backscatter signal generated by a reflection and frequency shifting of the RF signal by the passive RF backscatter tag. At least one of the device hosting the at least one RF backscatter transmitter and the other device hosting the at least one RF backscatter receiver is configured to maintain an inventory of locations of the navigation markers in the given venue.

Backscatter-aided navigation system

An in-home inventory and location system is provided. At least one RF backscatter transmitter, hosted on a device, is configured to emit a RF signal on a frequency. A set of passive RF backscatter tags, each associated with a respective one of a plurality of products in a given area, is configured to reflect and frequency shift the RF signal to a different frequency. At least one RF backscatter receiver, hosted on another device, is configured to read the products on the different frequency by detecting a distributed ambient backscatter signal generated by a reflection and frequency shifting of the RF signal by the passive RF backscatter tag. At least one of the device hosting the at least one RF backscatter transmitter and the other device hosting the at least one RF backscatter receiver is configured to maintain an inventory and location of the products in the given area.

Growing community of inventors

Howell, NJ, United States of America

Karthikeyan Sundaresan