L3harris Technologies, Inc.

L3 Technologies, Inc.

Philip M Hirz

Thomas R Giallorenzi

Brent A Kenney

Radivoje Zarubica

Matthew J Reimann

Patrick L Newbold

Brian J Thorp

N Thomas Nelson

Andrew L Nelson

Jason Wilden

Brent Kenney

Jeffrey B Bench

Edwin J Hemphill

Marc Padilla

Edwin R Twitchell

James E Peterson

Lee F Carter

Christopher S Heffernan

Chad S Komer

James E Hawker

Michael S Feeney

Rhett B McCarthy

Marley D Hamblin

Brian Thorp

Radijove Zarubica

Bryan J Thorp

Indicating to a receiver node in a network that the receiver node should begin tracking signal to noise ratio (SNR) of a received signal for a new power and rate (PAR) interval for data sent from a transmitter node. A method includes determining that a new PAR interval is beginning. The method further includes adding an identifier to a data block. The identifier corresponds to the new PAR interval. The method further includes sending the data block from the transmitter node to the receiver node, where the receiver node will use the identifier to determine that a new tracking interval of SNR should be performed for the data block and subsequent data blocks having the identifier.

Deterministic power and rate control

Methods and systems for dynamically modifying a sampling operation of a sensor. The method includes obtaining a dynamically changing transmission characteristic based on an available channel bandwidth parameter. The dynamically changing transmission characteristic includes at least one of a sample rate, a time period, or a spectral bandwidth. The method further includes updating the sampling operation of the sensor based on the dynamically changing transmission characteristic. The method further includes measuring signal energy at a location of the sensor. The method further includes sampling the signal energy using the sampling operation to obtain sampled data. The method further includes providing the sampled data to a processing entity configured to analyze the data using a dynamically updated cross-ambiguity function.

Opportunistic adjustable rate cross-ambiguity function geolocation

Systems and methods for evaluating link performance over a multitude of frequencies for Signal-to-Noise Ratio (SNR) optimization and mitigating interference. The methods comprise: communicating, from a first communication device, a first signal over a given channel in a given frequency band; receiving, by the first communication device, spectral power measurements and a Signal-to-Total Power Ratio (STPR) estimate determined based on a second signal including the first signal combined with at least one of noise and one or more interference signals (the STPR estimate accounts for the receiver performance including chip rate processing gain and/or the performance of an interference cancellation circuit used to remove the interference signals from the second signal); and determining, by the first communication device, a predicted Signal-to-Noise Ratio (SNR) condition for a plurality of frequencies within the given frequency band using the STPR estimate and the spectral power measurements.

Systems and methods for decentralized link performance

Compensating for antenna gain losses due to attitude changes of a mobile local node in a network. A method includes at the local node, identifying an attitude change of the local node. As a result of identifying the attitude change of the local node, the method includes increasing a target SNR of forward data directed to one or more remote nodes by a boost value. As a result of identifying the attitude change of the local node, the method includes causing the remote node to adjust at least one of power or rate to compensate for the attitude change for subsequent reverse data sent from the remote node to the local node.

Proactive power and rate control algorithm for dynamic platforms in a mesh network

Methods and systems adapted for providing a dynamically updated geolocation system. The geolocation system measures a signal, samples the signal, and applies a cross-ambiguity function to the sampled data to calculate the location of a signal source. The sampling operation and cross-ambiguity function are updated opportunistically and adaptively based on available channel resources between a plurality of sensors and a central processing location in the system. These update methods allow control of the data rate when channel resources are impacted by the physical environment where the geolocation system is operating.

Sending network data. A method includes transmitting data on a communication link, in an environment. A network control overhead portion of the data is allocated to network control overhead data packets for controlling how data is transmitted on the communication link. A user data portion of the data is allocated to user data packets for transmitting data between users of nodes on the communication link. A change in data capacity of the communication link is identified. As a result, a change is made in the network control overhead portion of the data, changing at least one of frequency of network control overhead data packets or size of network control overhead data packets to attempt to maintain a predetermined proportion factor for the network control overhead portion as compared to the user data portion. The network control overhead portion of the data is transmitted according to the change.

Scalable network overhead for contested environments

Transmitting data in a mesh network. A method includes identifying points on a piecewise continuous surface. The piecewise continuous surface defines minimum threshold power values to maintain a predetermined signal-to-noise ratio at a predetermined bitrate for a transmitter node transmitting to one or more receiver nodes in the mesh network. Points of a constant total power surface are identified defining required ratios of transmitting power for transmitting sources of the transmitter node. One or more points on the piecewise continuous surface that intersect with the constant total power surface are identified. As a result, transmitting power levels for the transmitting sources of the transmitter node are identified. As a result, data is transmitted at or above transmitting power levels, using the transmitting sources.

Power and rate control algorithm for multi-antenna communication links in a mesh network

Transmitting a probe signal. A method includes transmitting a signal, having a predetermined total power, during a transmit cycle. The signal has a traffic channel transmitting user data and a probe channel to locate new nodes to add to the network. The transmit channel uses a first portion of the total power and the probe channel uses a second portion of the total power. The method further includes performing a probe cycle by lowering the power in the first portion of the total power and raising the power in the second portion of the total power, but maintaining the total power at the same level as the total power during the transmit cycle. The method further includes, after the probe cycle, raising the power in the first portion of the total power and lowering the power in the second portion of the total power.

Dynamic multi-channel power management for neighbor discovery

Geolocating an emitter of a low probability of detection (LPD) signal being transmitted from the emitter in an environment with a noise floor, where the LPD signal is below the noise floor. At a sensor node, a version of the LPD signal is received from the emitter. For the version of the LPD signal, cyclostationary feature detection or energy detection of the version of the LPD signal is performed. A low probability of detection descriptor word, including at least one of a frequency feature of the version of the LPD signal or an energy feature of the version of the LPD signal is created. The low probability of detection descriptor word is provided to a data processor, where the data processor is configured to use a plurality of low probability of detection descriptor words from different sensor nodes for different versions of the LPD signal to geolocate the emitter.

LPD descriptor word based geolocation

Growing community of inventors

Holladay, UT, United States of America

Philip M Hirz