Abstract: An inertial (“INS”)/GPS receiver uses injected alignment data to determine the alignment of the INS sub-system when the receiver is in motion during start-up. The alignment data is determined from parameterized surface information, measured GPS velocity, and a known or predetermined angular relationship between the vehicle on which the receiver is mounted and an inertial measurement reference, or body, frame associated with the accelerometers and gyroscopes of the inertial measuring unit (“IMU”). The parameterized surface information, which provides a constraint, may be the orientation of the surface over which the vehicle that houses the receiver is moving. The receiver uses the initial GPS position to determine the location of the vehicle on the parameterized surface, and thus, the known surface orientation. The receiver then determines the roll, pitch and heading of the vehicle on the surface using the associated GPS velocity vector.

Abstract: An inertial (“INS”)/GPS receiver includes an INS sub-system which incorporates, into a modified Kalman filter, GPS observables and/or other observables that span previous and current times. The INS filter utilizes the observables to update position information relating to both the current and the previous times, and to propagate the current position, velocity and attitude related information. The GPS observable may be delta phase measurements, and the other observables may be, for example, wheel pick-offs (or counts of wheel revolutions) that are used to calculate along track differences, and so forth. The inclusion of the measurements in the filter together with the current and the previous position related information essentially eliminates the effect of system dynamics from the system model. A position difference can thus be formed that is directly observable by the phase difference or along track difference measured between the previous and current time epochs.

Abstract: An inertial (“INS”)/GPS receiver includes an INS sub-system which incorporates, into a modified Kalman filter, GPS observables and/or other observables that span previous and current times. The INS filter utilizes the observables to update position information relating to both the current and the previous times, and to propagate the current position, velocity and attitude related information. The GPS observable may be delta phase measurements, and the other observables may be, for example, wheel pick-offs (or counts of wheel revolutions) that are used to calculate along track differences, and so forth. The inclusion of the measurements in the filter together with the current and the previous position related information essentially eliminates the effect of system dynamics from the system model. A position difference can thus be formed that is directly observable by the phase difference or along track difference measured between the previous and current time epochs.

Abstract: A receiver that uses a single processor to control a GPS sub-system and an inertial (“INS”) sub-system and, through software integration, shares GPS and INS position and covariance information between the sub-systems. The receiver time tags the INS measurement data using a counter that is slaved to GPS time, and the receiver then uses separate INS and GPS filters to produce GPS and INS position information that is synchronized in time. The GPS/INS receiver utilizes GPS position and associated covariance information in the updating of an INS Kalman filter, which provides updated system error information that is used in propagating inertial position, velocity and attitude. Whenever the receiver is stationary after initial movement, the INS sub-system performs “zero-velocity updates,” to more accurately compensate in the Kalman filter for component measurement biases and measurement noise.

Abstract: A GPS receiver utilizes measurements which span previous and current times, such as delta phase measurements, in a modified Kalman filter. The modified Kalman filter updates position information relating to both the current and the previous times, and s propagates the current position and velocity related information. Using both the current and the previous position related information in the filter in conjunction with delta phase measurements, essentially eliminates the effect of system dynamics from the system model, and a position difference can thus be formed that is directly observable by the phase difference measured between the previous and current time epochs.

Abstract: A receiver that uses a single processor to control a GPS sub-system and an inertial (“INS”) sub-system and, through software integration, shares GPS and INS position and covariance information between the sub-systems. The receiver time tags the INS measurement data using a counter that is slaved to GPS time, and the receiver then uses separate INS and GPS filters to produce GPS and INS position information that is synchronized in time. The GPS/INS receiver utilizes GPS position and associated covariance information in the updating of an INS Kalman filter, which provides updated system error information that is used in propagating inertial position, velocity and attitude. Whenever the receiver is stationary after initial movement, the INS subsystem performs “zero-velocity updates,” to more accurately compensate in the Kalman filter for component measurement biases and measurement noise.