Abstract: An inertial coasting monitoring system comprises aiding sensors onboard a vehicle, including a GNSS receiver and at least one non-GNSS aiding sensor, and an inertial measurement unit (IMU) that produces inertial measurements for the vehicle. A navigation system is coupled to the aiding sensors and the IMU. The navigation system comprises a main navigation filter and an inertial navigation system (INS). The navigation filter receives aiding data from the aiding sensors including GNSS aided data, and the INS receives inertial data from the IMU. An onboard inertial coasting monitor communicates with the navigation system, and receives inertial data from the IMU and aiding data from at least one non-GNSS aiding sensor. The inertial coasting monitor comprises inertial coast sub-filters and communicates with the navigation filter. The inertial coasting monitor performs a position detection process and/or a velocity detection process to detect if there is a fault in the aiding data.

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: An attitude estimator system is provided. The attitude estimator system includes a navigation system, a Kalman filter, and a form observations module. The navigation system receives input from a first accelerometer and gyroscope, a second accelerometer and gyroscope, and a third accelerometer and gyroscope. The form observations module receives input from at least one high performance accelerometer and/or gyroscope; forms and outputs at least one of velocity-derived observations and attitude-derived observations.

Abstract: A navigation system comprises at least one processor, a satellite navigation receiver operatively coupled to the processor and configured to receive a plurality of navigation signals from one or more navigation satellites, and an inertial measurement unit operatively coupled to the processor and configured to generate inertial measurement data. An extended Kalman filter is configured to receive the plurality of navigation signals and the inertial measurement data. A processor readable storage medium includes instructions executable by the processor to combine the plurality of satellite signals with the inertial measurement data in the extended Kalman filter to generate a navigation solution. The plurality of navigation signals includes L1 pseudorange measurements, L2 pseudorange measurements, L1 accumulated carrier phase measurements, and L2 accumulated carrier phase measurements.

Abstract: An attitude estimator system is provided. The attitude estimator system includes a navigation system, a Kalman filter, and a form observations module. The navigation system receives input from a first accelerometer and gyroscope, a second accelerometer and gyroscope, and a third accelerometer and gyroscope. The form observations module receives input from at least one high performance accelerometer and/or gyroscope; forms and outputs at least one of velocity-derived observations and attitude-derived observations.

Abstract: A navigation system comprises at least one processor, a satellite navigation receiver operatively coupled to the processor and configured to receive a plurality of navigation signals from one or more navigation satellites, and an inertial measurement unit operatively coupled to the processor and configured to generate inertial measurement data. An extended Kalman filter is configured to receive the plurality of navigation signals and the inertial measurement data. A processor readable storage medium includes instructions executable by the processor to combine the plurality of satellite signals with the inertial measurement data in the extended Kalman filter to generate a navigation solution. The plurality of navigation signals includes L1 pseudorange measurements, L2 pseudorange measurements, L1 accumulated carrier phase measurements, and L2 accumulated carrier phase measurements.