Speed determination system
    2.
    发明授权

    公开(公告)号:US12164043B2

    公开(公告)日:2024-12-10

    申请号:US17767657

    申请日:2020-10-05

    Abstract: A speed determination system for an aircraft including one or more interfaces arranged to receive first speed data from a first speed measurement system and second speed data from a second speed measurement system. The first speed measurement system provides the first speed data using global positioning system data. The second speed measurement system provides the second speed data based on a second speed measurement. The speed determination system includes a processor arranged to determine whether the data received from the first speed measurement system is reliable. If global positioning data is determined to be reliable, the speed determination system determines a speed from the first speed data and determines correction values for the second speed measurement system. If global positioning data is determined to be unreliable, the speed determination system determines a speed from the second speed data and the correction values.

    Azimuth Calculation Device And Azimuth Calculation Method

    公开(公告)号:US20240402362A1

    公开(公告)日:2024-12-05

    申请号:US18678430

    申请日:2024-05-30

    Abstract: An azimuth calculation device includes: a first azimuth calculation unit that calculates a first azimuth based on a satellite signal or a detection result of an external sensor; a second azimuth calculation unit that calculates a second azimuth based on an angular velocity signal; a third azimuth calculation unit that calculates a third azimuth based on the first azimuth and the second azimuth; a storage unit that stores temperature characteristic information of an angular velocity bias; a temperature characteristic estimation unit that estimates a temperature characteristic of the angular velocity bias based on the second azimuth and the third azimuth and updates the temperature characteristic information; and an angular velocity bias prediction unit that predicts the angular velocity bias based on the temperature and the temperature characteristic information. The second azimuth calculation unit calculates the second azimuth based on the angular velocity bias predicted.

    INERTIAL COASTING POSITION AND VELOCITY SOLUTION SEPARATION

    公开(公告)号:US20240337762A1

    公开(公告)日:2024-10-10

    申请号:US17575250

    申请日:2022-01-13

    CPC classification number: G01S19/49 G01S19/215

    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.

    Airborne positioning method in aviation navigation network based on multi-source information fusion

    公开(公告)号:US12061277B1

    公开(公告)日:2024-08-13

    申请号:US18383524

    申请日:2023-10-25

    Abstract: The present application discloses an airborne positioning method and system for an aviation navigation network, and relates to the technical field of satellite navigation. The airborne positioning method for an aviation navigation network is applied to an omnisource navigation system, and comprises the following steps: acquiring the original observation data of the omnisource navigation system; Filtering the original observation data based on dead reckoning to obtain filtered observation data; Unify that filtered observation data in time and space to obtain observation data to be fused; The adaptive fusion algorithm of omnisource navigation based on variance optimization is adopted to fuse the observation data to be fused to obtain the fused data; the fused data is used to characterize the position of the target aircraft at the current moment. The present application can improve the accuracy of the positioning result.

    GNSS and INS integrated navigation positioning method and system thereof

    公开(公告)号:US12019170B1

    公开(公告)日:2024-06-25

    申请号:US18496789

    申请日:2023-10-27

    CPC classification number: G01S19/393 G01S19/40 G01S19/49 G01S19/52

    Abstract: The present disclosure relates to the field of GNSS and INS integrated navigation technology, and specifically discloses a GNSS and INS integrated navigation positioning method and a system thereof. To addresses the technical problem of positioning error divergence in integrated navigation systems caused by insufficient satellite visibility or strong multipath effects in GNSS denial environments, a method combining motion constraint algorithm and neural network algorithm is proposed for robustness by the present disclosure. The motion constraint algorithm is very stable, but it cannot self-adaptively adjust the constraint threshold based on the vehicle motion state. The neural network algorithm has strong flexibility, but the obtained predicted values inevitably have outliers. The present disclosure combines motion constraints with the neural network algorithms, enabling these two algorithms to complement advantages of each other, thereby effectively improving the positioning accuracy and reliability of the integrated navigation system after GNSS losing lock.

    METHOD AND SYSTEM FOR NAVIGATION OF A VEHICLE

    公开(公告)号:US20240201399A1

    公开(公告)日:2024-06-20

    申请号:US18541232

    申请日:2023-12-15

    CPC classification number: G01S19/49 G01S19/393

    Abstract: An iterative method for navigation of a vehicle, the method comprising: at a first processing element: receiving a set of satellite navigation data for the vehicle; receiving a validity time of the set of satellite navigation data; and receiving a series of sets of inertial navigation data each indicating acceleration and angular rate of the vehicle; after the validity time, storing received sets of inertial navigation data; at a second processing element: using a navigation filter algorithm, processing the received set of satellite navigation data together with a current position, velocity and attitude value of the vehicle, and a prediction of error states made by the navigation algorithm in a previous iteration, to generate an estimated position, velocity and attitude, and prediction of error states, of the vehicle; carrying out a catch up process comprising: obtaining a stored series of one or more sets of inertial navigation data comprising one or more sets of inertial navigation data which were received between the validity time and the completion of the processing the received set of satellite navigation data; using a set of inertial navigation data of the stored series which was the first set of inertial navigation data received after the validity time, and the estimated position, velocity and attitude of the vehicle, to calculate an updated position, velocity and attitude value of the vehicle; and for any remaining sets of inertial navigation data of the stored series, in turn, in order of reception, iteratively using each set of inertial navigation data and the updated position, velocity and attitude value of the vehicle to calculate a new updated position, velocity and attitude value of the vehicle; and sending the new updated position, velocity and attitude value of the vehicle to the first processing element; and at the first processing element, after receiving the new updated position and velocity value of the vehicle from the second processing element, for subsequently received sets of inertial navigation data, in turn, in order of reception, iteratively using each received set of inertial navigation data and the new updated position, velocity and attitude value of the vehicle to calculate a new updated position, velocity and attitude value of the vehicle; wherein the new updated position, velocity and attitude value of the vehicle at the validity time is used as the current position, velocity and attitude value of the vehicle by the navigation filter algorithm.

Patent Agency Ranking