Raytheon Company

Marcus Alton Teter

Scott Allen Imhoff

Brenda S Dougherty

James Joseph Richardson

Paul Christian Hershey

Mac Allen Cody

Brianne R Hoppes

John J Doubrava

Jeanette Marie Booher

Noah M Anderson

Steven T Naumann

Mark Frank Tryon

Natalie Rae Plotkin

Walter Parish Gililland, Jr

Austin Jay Jorgensen

Vikram A Prasad

Kendy Hall

Embodiments regard improved satellite position determination with age of measurement data. A method includes receiving measurement data from a satellite, in a first iteration, increasing a dimensionality of the measurement data to a specified number of dimensions resulting in N-dimensional input data, performing dynamic mode decomposition on the N-dimensional measurement data resulting in a Koopman operator and modes of the N-dimensional measurement data, adaptive filtering a time domain residue resulting in a filtered residue, and updating, based on the filtered residue and a time domain deterministic component of the N-dimensional measurement data, a state vector of an object associated with the satellite measurement data.

Preserving positioning accuracy with age of data

Apparatus, computer-readable medium, and method for optimal delivery of one or more satellite effects via reverse time heat equation isomorphism including constructing a generalized formulation of the heat equation corresponding to a commander's intent for delivery of the one or more satellite effects, performing a separation of variables to decouple a plurality of variables into a plurality of corresponding separated equations, solving the plurality of separated equations to produce candidate solutions, applying boundary conditions to each candidate solution, filtering the candidate solutions to mitigate ill-posedness of solving the inverse of the heat equation, assessing formal differences between the candidate solutions and the inverse of the heat equation, and generating an optimized schedule of the one or more satellite effects based on the assessment of the formal differences of the candidate solutions.

Device for optimal satellite effects delivery via reverse time heat isomorphism

Techniques for multi-domain systems integration and evaluation are disclosed, including: obtaining criteria associated with a strategic objective; determining that a first system, operating in a first operating domain, is only partially capable of satisfying a first criterion in the criteria; determining that a second system, operating in a second operating domain that is different from the first operating domain, is capable of augmenting the first system with respect to satisfying the first criterion; responsive to determining that the second system is capable of augmenting the first system with respect to satisfying the first criterion, modeling a multi-domain system including at least a first component from the first system and at least a second component from the second system; and generating a performance metric that objectively evaluates capabilities of the multi-domain system against the criteria associated with the strategic objective.

Multi-domain systems integration and evaluation

Systems, devices, methods, and computer-readable media for improved location determination of an orbiting device. A method can include receiving, at a transceiver of a device, measurement data from a monitor device, the measurement data representative of a physical state of a mobile object, filtering, using a first of a plurality of first filters of the device, the measurement data based on a character parameter of a state transition matrix representative of the physical state resulting in filtered measurement data, filtering, using a Kalman filter, the filtered measurement data resulting in further filtered measurement data, and providing, by the transceiver, the further filtered measurement data.

Architecture for increased multilateration position resolution

A learning automaton can be trained to merge data from input data streams, optionally with different data rates, into a single output data stream. The learning automaton can learn over time from the input data streams. The input data streams can be low-pass filtered to suppress data having frequencies greater than a time-varying cutoff frequency. Initially, the cutoff frequency can be relatively low, so that the effective data rates of the input data streams are all equal. This can ensure that initially, high data-rate data does not overwhelm low data-rate data. As the learning automaton learns, an entropy of the learning automaton changes more slowly, and the cutoff frequency is increased over time. When the entropy of the learning automaton has stabilized, the training is completed, and the cutoff frequency can be large enough to pass all the input data streams, unfiltered, to the learning automaton.

Learning automaton and low-pass filter having a pass band that widens over time

A method for preprocessing data for device operations can include preprocessing measurement data using a machine learning technique, determining, by a Kalman filter and based on (1) the preprocessed measurement data or the measurement data and (2) prediction data from a prediction model predicting a measurement associated with the measurement data, corrected measurement data, and providing the corrected measurement data based on the predicted measurement and the preprocessed measurement data.

Preprocessor for device navigation

Discussed herein are methods, devices, and systems for providing a priority-based schedule. A method or providing a priority-based schedule can include receiving, at priority processing circuitry, for each of a plurality of nodes to be scheduled, a plurality of priority type values and a corresponding weighting factor value for each priority type value of the plurality type values, determining, at the priority processing circuitry, for each of the plurality of nodes to be scheduled, a priority total based on the received plurality of priority type values and the corresponding weighting factor values, and scheduling, using scheduler circuitry communicatively coupled to the priority processing circuitry, the plurality of nodes, such that a node of the plurality of nodes with a corresponding higher priority is allocated access to the medium before another node of the plurality of nodes with a corresponding relatively lower priority.

Dynamic priority calculator for priority based scheduling

Generally discussed herein are devices, systems, and methods for determining if a master schedule will allow information to be recorded and downloaded from a node. A method can include receiving a plurality of schedules including a first schedule, a second schedule, and a list, determining, at the scheduler circuitry and based on the first schedule and the list, whether there is a threshold latency between mission data collection and downlink, determining, at the scheduler circuitry and based on the first schedule, the second schedule, and the list, whether any mission data will be overwritten in performing operations of the master schedule, and providing, by a display communicatively coupled to the scheduler circuitry, a first warning in response to determining that there is a threshold latency between mission data collection and downlink and a second warning in response to determining that mission data will be overwritten.

Tracking data latency and availability for dynamic scheduling

Statistical movement analysis method that includes defining one or more movement signature types, wherein a movement signature type includes a set of movement parameters and values for the set of movement parameters and receiving data for objects monitored by a radar system at a plurality of times, the data including values acquired for the set of movement parameters. The method also includes discriminating the data for the monitored objects by comparing movement signatures of two or more of the monitored objects for a difference of statistical significance and characterizing the monitored objects based on the movement signatures of the monitored objects. The method also includes identifying one or more of the monitored objects by comparing the received data for a monitored object with the movement signature type to determine if any of the objects monitored by the radar system are moving consistent with the movement signature type.

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Belgrade, MT, United States of America

Marcus Alton Teter