Abstract: One embodiment is directed towards a method of navigating a body. The method includes determining a respective measured direction of each of a plurality of celestial objects with respect to the body based on an output of one or more star tracking sensors mounted to the body. Calculating an expected direction of at least one of the plurality of celestial objects with respect to the body based on a current navigation solution for the body. Calculating an updated navigation solution for the body based on the expected direction of the at least one celestial object, the measured direction of the plurality of celestial objects, and an output of one or more inertial sensors mounted to the body.

Abstract: One embodiment is directed towards a method of navigating a body. The method includes determining a respective measured direction of each of a plurality of celestial objects with respect to the body based on an output of one or more star tracking sensors mounted to the body. Calculating an expected direction of at least one of the plurality of celestial objects with respect to the body based on a current navigation solution for the body. Calculating an updated navigation solution for the body based on the expected direction of the at least one celestial object, the measured direction of the plurality of celestial objects, and an output of one or more inertial sensors mounted to the body.

Abstract: A system and method for motion-based adaptive frequency estimation of a Doppler sensor is provided. The system comprises a Doppler sensor configured to output a digitized Doppler data signal, and a Doppler velocity estimation module operatively coupled to the Doppler sensor to receive the Doppler data signal. An inertial navigation system is operatively coupled to the Doppler velocity estimation module, and one or more inertial sensors is operatively coupled to the inertial navigation system. The inertial sensors are configured to transmit inertial navigation data to the inertial navigation system. The Doppler velocity estimation module calculates a speed or velocity estimate based on the Doppler data signal and the inertial navigation data. The speed or velocity estimate is then transmitted to the inertial navigation system.

Abstract: Embodiments of the present invention provide improved systems and methods for estimating N-dimensional parameters while sensing fewer than N dimensions. In one embodiment a navigational system comprises a processor and an inertial measurement unit (IMU) that provides an output to the processor, the processor providing a navigation solution based on the output of the IMU, wherein the navigation solution includes a calculation of an n-dimensional parameter. Further, the navigational system includes at most two sensors that provide an output to the processor, wherein the processor computes an estimate of an n-dimensional parameter from the output of the at most two sensors for bounding errors in the n-dimensional parameter as calculated by the processor when the trajectory measured by the IMU satisfies movement requirements, wherein “n” is greater than the number of the at most two sensors.

Abstract: A system and method for motion-based adaptive frequency estimation of a Doppler sensor is provided. The system comprises a Doppler sensor configured to output a digitized Doppler data signal, and a Doppler velocity estimation module operatively coupled to the Doppler sensor to receive the Doppler data signal. An inertial navigation system is operatively coupled to the Doppler velocity estimation module, and one or more inertial sensors is operatively coupled to the inertial navigation system. The inertial sensors are configured to transmit inertial navigation data to the inertial navigation system. The Doppler velocity estimation module calculates a speed or velocity estimate based on the Doppler data signal and the inertial navigation data. The speed or velocity estimate is then transmitted to the inertial navigation system.

Abstract: Embodiments of the present invention provide improved systems and methods for estimating N-dimensional parameters while sensing fewer than N dimensions. In one embodiment a navigational system comprises a processor and an inertial measurement unit (IMU) that provides an output to the processor, the processor providing a navigation solution based on the output of the IMU, wherein the navigation solution includes a calculation of an n-dimensional parameter. Further, the navigational system includes at most two sensors that provide an output to the processor, wherein the processor computes an estimate of an n-dimensional parameter from the output of the at most two sensors for bounding errors in the n-dimensional parameter as calculated by the processor when the trajectory measured by the IMU satisfies movement requirements, wherein “n” is greater than the number of the at most two sensors.

Abstract: A method for real-time visual odometry comprises capturing a first three-dimensional image of a location at a first time, capturing a second three-dimensional image of the location at a second time that is later than the first time, and extracting one or more features and their descriptors from each of the first and second three-dimensional images. One or more features from the first three-dimensional image are then matched with one or more features from the second three-dimensional image. The method further comprises determining changes in rotation and translation between the first and second three-dimensional images from the first time to the second time using a random sample consensus (RANSAC) process and a unique iterative refinement technique.

Abstract: Apparatus, systems, and methods for identifying a fault in an electronic system are provided. One apparatus includes memory storing a model of the electronic system, a processor, and a fault module. The processor is configured to pass system inputs through the model to generate corresponding simulated outputs, and the fault module is configured to determine the fault based on a comparison of the system outputs and the simulated outputs. A system includes an electronic system including multiple components generating system outputs based on system inputs and the apparatus for identifying a fault in the electronic system discussed above. One method includes generating a model of the electronic system, passing one or more inputs to the electronic system through the model to generate corresponding simulated outputs, and determining the fault based on a comparison of the one or more simulated outputs and one or more electronic system outputs.

Abstract: A system and method are provided for planning and controlling a plurality of machines. A mission is assigned to each machine of the plurality of machines. A plurality of system capabilities is computed in each machine and, from the plurality of computed system capabilities, a machine mission capability is computed for each machine. The mission of one or more of the machines may be selectively reassigned based on the computed machine mission capability of each machine.

Abstract: Methods and systems are provided for detecting temporal relationships that are uniquely associated with a selected root cause. The method comprises identifying error codes associated with a root cause, wherein each error code comprises a plurality of event indicators and temporal data describing when the event indicator was generated, analyzing each of the error codes to detect a combination of event indicators that is associated with error codes corresponding to the selected root cause and to a non-selected root cause, and detecting a temporal relationship involving the combination of event indicators, wherein the temporal relationship is uniquely associated with error codes corresponding to the selected root cause.

Abstract: Methods and system are provided for detecting combinations of performance indicators that are associated with a root cause. The method comprises storing a plurality of error codes, each representative of at least one performance indicator, storing descriptive data associated with each of the plurality of error codes, storing a plurality of root causes, each associated with descriptive data that corresponds to the descriptive data of the plurality of error codes, identifying the error codes from the plurality of error codes that correspond to at least one of the plurality of root causes, and analyzing the error codes that correspond to at least one root cause to determine combinations of performance indicators that are associated with the root cause.

Abstract: A system and method are provided for the determining of the potential effect(s) that a degraded system, subsystem, or component may have on the overall capabilities of a vehicle or other system, and any mitigating actions that may need to be taken. Mission-related capabilities of the system are decomposed into a plurality of lower-level capabilities that have an impact on the mission-related capabilities. One or more faults that have an impact on at least one of the lower-level capabilities are mapped to appropriate lower-level capabilities. The lower-level capabilities to which the one or more vehicle faults is mapped are computed, and values of the mission-related capabilities are computed from each of the lower-level capabilities.

Abstract: Methods and systems are provided for detecting temporal relationships that are uniquely associated with a selected root cause. The method comprises identifying error codes associated with a root cause, wherein each error code comprises a plurality of event indicators and temporal data describing when the event indicator was generated, analyzing each of the error codes to detect a combination of event indicators that is associated with error codes corresponding to the selected root cause and to a non-selected root cause, and detecting a temporal relationship involving the combination of event indicators, wherein the temporal relationship is uniquely associated with error codes corresponding to the selected root cause.

Abstract: Methods and system are provided for detecting combinations of performance indicators that are associated with a root cause. The method comprises storing a plurality of error codes, each representative of at least one performance indicator, storing descriptive data associated with each of the plurality of error codes, storing a plurality of root causes, each associated with descriptive data that corresponds to the descriptive data of the plurality of error codes, identifying the error codes from the plurality of error codes that correspond to at least one of the plurality of root causes, and analyzing the error codes that correspond to at least one root cause to determine combinations of performance indicators that are associated with the root cause.

Abstract: Apparatus, systems, and methods for identifying a fault in an electronic system are provided. One apparatus includes memory storing a model of the electronic system, a processor, and a fault module. The processor is configured to pass system inputs through the model to generate corresponding simulated outputs, and the fault module is configured to determine the fault based on a comparison of the system outputs and the simulated outputs. A system includes an electronic system including multiple components generating system outputs based on system inputs and the apparatus for identifying a fault in the electronic system discussed above. One method includes generating a model of the electronic system, passing one or more inputs to the electronic system through the model to generate corresponding simulated outputs, and determining the fault based on a comparison of the one or more simulated outputs and one or more electronic system outputs.

Abstract: A method for real-time visual odometry comprises capturing a first three-dimensional image of a location at a first time, capturing a second three-dimensional image of the location at a second time that is later than the first time, and extracting one or more features and their descriptors from each of the first and second three-dimensional images. One or more features from the first three-dimensional image are then matched with one or more features from the second three-dimensional image. The method further comprises determining changes in rotation and translation between the first and second three-dimensional images from the first time to the second time using a random sample consensus (RANSAC) process and a unique iterative refinement technique.