Abstract: Using geo-mapping data and only at least one inertial sensor, a Bayesian estimator uses at least one element of an uncorrected inertial navigation vector, of a moveable object on a surface, to estimate inertial navigation error information including corresponding statistical information. The estimated inertial navigation error information is used to error correct the uncorrected inertial navigation vector. The Bayesian filter also predicts inertial navigation error information, including corresponding statistical information, for a future time instance when a next uncorrected inertial navigation vector will be obtained.

Abstract: Using geo-mapping data and only at least one inertial sensor, a Bayesian estimator uses at least one element of an uncorrected inertial navigation vector, of a moveable object on a surface, to estimate inertial navigation error information including corresponding statistical information. The estimated inertial navigation error information is used to error correct the uncorrected inertial navigation vector. The Bayesian filter also predicts inertial navigation error information, including corresponding statistical information, for a future time instance when a next uncorrected inertial navigation vector will be obtained.

Abstract: A method is provided. The method comprises: initializing a point mass filter; initializing the one or more Bayesian filters; obtaining measurement data associated with a horizontal position on a surface; obtaining measurement data of a horizontal position and a velocity; obtaining geo-mapping data; estimating, with the point mass filter, the horizontal position on the surface based upon the geo-mapping data and the measurement data; estimating, with the one or more Bayesian filters, remaining state parameters based upon an output of the point mass filter and the measurement data; predicting, with the point mass filter, an a priori horizontal position, on a surface for a future time when the next measurement data will be obtained; and predicting, with the one or more Bayesian filters, an a priori remaining state parameters for a future time when the next measurement data will be obtained.

Abstract: An optical system comprises a pair of Risley prisms positioned along an optical axis to receive a light beam from a field of view, wherein at least one of the Risley prisms is rotatable, transverse to the optical axis, with respect to the other of the Risley prisms. At least one lens is positioned along the optical axis to receive the light beam from the pair of Risley prisms, with the at least one lens configured to focus the light beam. An optical detector array is positioned along the optical axis at an image plane, wherein the optical detector array receives the focused light beam on the image plane from the at least one lens. The optical system can be implemented as a light beam steering mechanism in a star tracker or celestial aided inertial navigation unit.

Abstract: An optical system comprises a pair of Risley prisms positioned along an optical axis to receive a light beam from a field of view, wherein at least one of the Risley prisms is rotatable, transverse to the optical axis, with respect to the other of the Risley prisms. At least one lens is positioned along the optical axis to receive the light beam from the pair of Risley prisms, with the at least one lens configured to focus the light beam. An optical detector array is positioned along the optical axis at an image plane, wherein the optical detector array receives the focused light beam on the image plane from the at least one lens. The optical system can be implemented as a light beam steering mechanism in a star tracker or celestial aided inertial navigation unit.

Abstract: A system to detect spoofing attacks is provided. The system includes a satellite-motion-and-receiver-clock-correction module, a compute-predicted-range-and-delta-range module, a subtractor, and delta-range-difference-detection logic. The satellite-motion-and-receiver-clock-correction module periodically inputs, from a global navigation satellite system (GNSS) receiver, a carrier phase range for a plurality of satellites. The satellite-motion-and-receiver-clock-correction module outputs a corrected-delta-carrier-phase range for a current epoch to a first input of a subtractor. The compute-predicted-range-and-delta-range module outputs a predicted delta range to a second input of the subtractor. The predicted delta range is based on inertial measurements observed for the current epoch. The subtractor outputs a difference between the corrected-delta-carrier-phase range and the predicted delta range for the current epoch to delta-range-difference-detection logic.

Abstract: A method is provided. The method comprises: initializing a point mass filter; initializing the one or more Bayesian filters; obtaining measurement data associated with a horizontal position on a surface; obtaining measurement data of a horizontal position and a velocity; obtaining geo-mapping data; estimating, with the point mass filter, the horizontal position on the surface based upon the geo-mapping data and the measurement data; estimating, with the one or more Bayesian filters, remaining state parameters based upon an output of the point mass filter and the measurement data; predicting, with the point mass filter, an a priori horizontal position, on a surface for a future time when the next measurement data will be obtained; and predicting, with the one or more Bayesian filters, an a priori remaining state parameters for a future time when the next measurement data will be obtained.

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 to detect spoofing attacks is provided. The system includes a satellite-motion-and-receiver-clock-correction module, a compute-predicted-range-and-delta-range module, a subtractor, and delta-range-difference-detection logic. The satellite-motion-and-receiver-clock-correction module periodically inputs, from a global navigation satellite system (GNSS) receiver, a carrier phase range for a plurality of satellites. The satellite-motion-and-receiver-clock-correction module outputs a corrected-delta-carrier-phase range for a current epoch to a first input of a subtractor. The compute-predicted-range-and-delta-range module outputs a predicted delta range to a second input of the subtractor. The predicted delta range is based on inertial measurements observed for the current epoch. The subtractor outputs a difference between the corrected-delta-carrier-phase range and the predicted delta range for the current epoch to delta-range-difference-detection logic.

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: Systems and methods for a limb strike detector are provided. In certain embodiments, a system for detecting limb strikes comprises an inertial measurement unit (IMU) that provides inertial measurements; and a processing unit that receives the inertial measurements from the IMU.

Abstract: Systems and methods for filtering GNSS-Aided navigation data for helping combine sensor data and a priori data are provided. In at least one embodiment, the method comprises identifying an un-smoothed navigation solution inclusive of a navigation system reset, wherein a value is associated with the navigation system reset. The value associated with the navigation system reset is then subtracted from the un-smoothed navigation solution to generate an initial navigation solution. Further, the value associated with the navigation system reset is incrementally added to the initial navigation solution at a configurable rate to generate a smoothed navigation solution.

Abstract: Systems and methods for a limb strike detector are provided. In certain embodiments, a system for detecting limb strikes comprises an inertial measurement unit (IMU) that provides inertial measurements; and a processing unit that receives the inertial measurements from the IMU.

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: Systems and methods for navigation using cross correlation on evidence grids are provided. In one embodiment, a system for using cross-correlated evidence grids to acquire navigation information comprises: a navigation processor coupled to an inertial measurement unit, the navigation processor configured to generate a navigation solution; a sensor configured to scan an environment; an evidence grid creator coupled to the sensor and the navigation processor, wherein the evidence grid creator is configured to generate a current evidence grid based on data received from the sensor and the navigation solution; a correlator configured to correlate the current evidence grid against a historical evidence grid stored in a memory to produce displacement information; and where the navigation processor receives correction data derived from correlation of evidence grids and adjusts the navigation solution based on the correction data.

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 navigation system includes host and remote units. Host unit includes positioning device to determine absolute position/orientation of host unit; first communication device to communicate signals; first processor; and first memory. Remote unit includes second communication device to receive signals from first communication device; second processor; and second memory. First or second processor compares first aspects of known pattern with second aspects of image of captured pattern positioned on surface at either host unit or remote unit. First or second processor determines relative position/orientation of remote unit relative to host unit based on comparison of first aspects and second aspects. First or second processor determines absolute position/orientation of remote unit based on relative position/orientation of remote unit relative to host unit and absolute position/orientation of host unit.

Abstract: A navigation device is provided herein comprising an inertial measurement unit (IMU), a camera, and a processor. The IMU provides an inertial measurement to the processor and the camera provides at least one image frame to the processor. The processor is configured to determine navigation data based on the inertial measurement and the at least one image frame, wherein at least one feature is extracted from the at least one image frame based on the navigation data.

Abstract: A navigation system includes host and remote units. Host unit includes positioning device to determine absolute position/orientation of host unit; first communication device to communicate signals; first processor; and first memory. Remote unit includes second communication device to receive signals from first communication device; second processor; and second memory. First or second processor compares first aspects of known pattern with second aspects of image of captured pattern positioned on surface at either host unit or remote unit. First or second processor determines relative position/orientation of remote unit relative to host unit based on comparison of first aspects and second aspects. First or second processor determines absolute position/orientation of remote unit based on relative position/orientation of remote unit relative to host unit and absolute position/orientation of host unit.

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.