A method and apparatus for defining a model to determine a corrected trajectory of a mobile device or vehicle and a method and apparatus for determined a corrected trajectory using a defined model are provided. The model for determining a corrected trajectory includes accessing ground truth location data for a selected pathway, determining a GNSS pathway of a mobile device or vehicle, determining an IMU pathway of a mobile device or vehicle, and calculating an aggregated displacement trajectory. The apparatus for defining the model includes a communication interface configured to receive a first and second pathway, a memory configured to store a model and ground truth location data, and a processor to train the model.

Systems, methods, and computer-readable media are provided for wearable navigation systems. In some examples, a wearable navigation system may determine the distance between an object and one or more distance sensors based on signals received from an environment, where the distance sensors are part of a sensor package. In some aspects, the wearable navigation system may determine, using an inertial measurement unit, a position, speed, and acceleration of the wearable navigation system, where the inertial measurement unit is part of the sensor package. In some cases, the wearable navigation system may determine, by a Central Processing Unit (CPU) coupled to the sensor package, information associated with the object with respect to the wearable navigation system. In some instances, the wearable navigation system may generate, by an actuator system coupled to the sensor package, feedback signals in response to information associated with the object.

A localization method and system for mobile remote inspection and/or manipulation tools in confined spaces are provided. The system comprises a mobile remote inspection and/or manipulation device including a carrier movable within the confined space and an inspection and/or manipulation tool, such as an inspection camera, pose sensors arranged on the movable carrier for providing signals indicative of the position and orientation of the movable carrier, and distance sensors arranged on the movable carrier for providing signals indicative of the distance to interior surfaces of the confined space. The localization method makes use of probalistic sensor fusion of the measurement data provided by the pose sensors and the distance sensors in order to precisely determine the actual pose of the movable carrier and localize data generated by the inspection and/or manipulation tool.

FAST provides a method of “bootstrapping” a pseudo-range (PR) stage and one or more carrier-phase (CP) stages to quickly produce a highly accurate, high integrity receiver-to-receiver lever arm survey based on differential GNSS processing. The lever arm estimates of a previous stage are used to resolve the carrier phase ambiguities of the next stage. The method can be integrated with the warm-up of the integrity monitors to reduce the entire survey and warm-up startup time to 90 minutes or less, which is critical for mobile and make shift and precision approach and (automated) landing operations.

Embodiments of the present invention are an inertial measurement module, includes a mount, a circuit board, an inertial measurement assembly, a thermally conductive member and a counterweight assembly. The circuit board is mounted to a surface of the mount. The inertial measurement assembly includes a thermal resistor and an inertial measurement unit. The thermally conductive member is configured to abut against the thermal resistor and the inertial measurement unit. The counterweight assembly is mounted to the surface of the mount. A first groove is arranged on an end surface of the counterweight assembly facing the mount. A receiving space is formed by the first groove and the end surface of the mount. The thermally conductive member and the inertial measurement assembly are both received in the receiving space. The thermally conductive member is arranged at a preset distance from a bottom of the first groove.

Navigation device including an inertial navigation system coupled with a satellite navigation system, the information supplied by the satellite positioning system being used for adjusting the inertial navigation system, characterised in that the device further comprises means for measuring signals coming from base stations of a wireless cellular network, the satellite navigation system and the means for measuring signals coming from base stations of the wireless cellular network are coupled with each other by a tight coupling to form a satellite navigator and/or base-station navigator implementing an estimator with simultaneous localisation and mapping, and in that the satellite navigation system and the means for measuring signals coming from base stations of the wireless cellular network are coupled to the inertial navigation system by a loose coupling for adjusting the inertial navigation system.

In one embodiment, a method is provided. The method comprises determining a first value of a coefficient of an edge-determining algorithm in response to a spatial resolution of a first image acquired with an image capture device onboard a vehicle, a spatial resolution of a second image, and a second value of the coefficient in response to which the edge-determining algorithm generated a second edge map corresponding to the second image. The method further comprises determining, with the edge-determining algorithm in response to the coefficient having the first value, at least one edge of at least one object in the first image. The method further comprises generating, in response to the determined at least one edge, a first edge map corresponding to the first image. The method further comprises determining at least one navigation parameter of the vehicle in response to the first and second edge maps.

Disclosed is a box-regularized particle filtering process which includes an Epanechnikov kernel smoothing step. For this purpose, the process uses a special method for generating random numbers that follow an Epanechnikov probability density function. The process can be performed autonomously in a navigation system using correlation measurement, in particular on board an aircraft such as an aircraft, a flying drone or any self-propelled aerial carrier.

In one embodiment, a system includes a global navigation satellite system (GNSS) receiver unit, a first inertial measurement unit (IMU) and a second IMU. The system may further include a first micro-controller unit (MCU) coupled to the first IMU and the GNSS receiver unit to receive data from the first IMU and the GNSS receiver unit and a second MCU coupled to the second IMU and the GNSS receiver unit to receive data from the second IMU and the GNSS receiver unit.

Example navigation aids for increasing the accuracy of a navigation system are disclosed herein. An example method disclosed herein identifying, with an aircraft intent description language (AIDL) aid, an AIDL instruction as associated with a first dynamic activity level of a plurality of dynamic activity levels and determining, with the AIDL aid, an aircraft state to be affected by the AIDL instruction. The example method also includes changing, with a navigation filter, a weighting scheme for a measurement of the aircraft state obtained by an inertial navigation system (INS) of the aircraft and estimating, with the navigation filter, a trajectory of the aircraft based on the weighting scheme and the measurement.