Systems and methods for use in determining a device's speed. The system uses a plate having a front side that is perpendicular to the device's direction of travel. The airflow caused by the device's motion causes the plate to deflect from a resting position and the amount of deflection of the plate is proportional to the speed of the device. The amount of deflection is measured by a rotary encoder coupled to the plate. By properly calibrating the system, the system can determine the device's velocity simply from the airflow caused by the device's motion.

A method of determining the orientation of a device having disposed therein, in part, an inertia measurement unit, a phased array receiver, and a controller, includes, in part, detecting the difference between phases of an RF signal received by at least a pair of receive elements of the phased array receiver, determining the angle of incidence of the RF signal from the phase difference, using the angle of incidence to determine the projection of a vector on a plane of an array of transmitters transmitting the RF signal, and determining the yaw of the device from the projection of the vector. The vector is a three-dimensional vector representative of the orientation of the plane of the phased array receivers relative to the plane of the array of transmitters transmitting the RF signal.

The present application describes a machine learning method for detecting tamper. The method includes a step of training a model using one or more values obtained from one or more different sensors on an integrated module. The one or more values act as training data with respect to one or more of light, acceleration, magnetic field, rotation, temperature, pressure, humidity, and audio. The method also includes a step of predicting, via the trained model, tampering of the of the integrated module. The present application also describes a system for detecting tamper.

A method for stabilizing a magnetic field of an inertial measurement unit (IMU), is provided that includes initializing accelerometer and gyroscope (AG) heading data for the IMU and initializing accelerometer, gyroscope and magnetometer (AGM) heading data for the IMU. Determining whether a tracking state exists and completing processing of the AG heading data and the AGM heading data if the tracking state does not exist. Calculating a magnetic field error if the tracking state exists.

Systems, methods, and apparatuses for a self-locating compass for use in navigation are disclosed. The self-locating compass is operable to provide position and/or velocity without information from a global positioning system (GPS) device. The self-locating compass includes a direction finder and a Lorentz force detector. The method includes determining orientation with respect to Earth's magnetic field, measuring a Lorentz force proportional to rate of change of location with respect to the field, determining a change in location, and updating location.

An electronic device for visually representing an impact event is provided. The electronic device includes an accelerometer, a gyroscope, and a magnetometer for measuring its acceleration, angular rotation, and magnetic field intensity relative to its motion. Using any suitable filter, a normalization process is used to standardize readings from the accelerometer, gyroscope, and magnetometer. The electronic device also includes impact location and impact severity determination procedures executable by its processor from its memory module to provide an impact indicator or a visual representation of the impact which may indicate possible damage, shock or fracture incurred on the device. The impact indicator serves as a preview of impacts by displaying gradients of green, yellow and red depicted in increasing severity, i.e., from “no impact” event to “severe impact” event.

An apparatus including an interface and a processor. The interface may be configured to receive area data and sensor data from a plurality of vehicle sensors. The processor may be configured to extract road characteristics for a location from the area data, predict expected sensor readings at the location for the plurality of sensors based on the road characteristics, calculate dynamic limits for the sensor data in response to the expected sensor readings and determine a plausibility of the sensor data received from the interface when the vehicle reaches the location. The sensor data may be plausible if the sensor data is within the dynamic limits. A confidence level of the sensor data may be adjusted in response to the plausibility of the sensor data.

The described technology regards an augmented reality system and method for estimating a position of a location of interest relative to the position and orientation of a display, including receiving and selectively filtering a plurality of measurement vectors from a rate-gyroscope. Systems of the described technology include including a plurality of sensors, a processing module or other computation means, and a database. Methods of the described technology use data from the sensor package useful to accurately render graphical user interface information on a display.

A localization apparatus, the position of which in a localization space is determinable including a movement sensor system having at least one translation sensor and at least one rotation sensor for capturing movement variables that act on the localization apparatus and at least one magnetometer apparatus for capturing magnetic field data in the localization space. Rotationally invariant magnetic features are determinable by means of an internal or external data processing apparatus. A means for determining an absolute position of the localization apparatus in the localization space and the integrated data processing apparatus or a coupling to the external data processing apparatus for calculating a position while processing the measurement data of the movement sensor system using a magnetic field map that was stored in advance, having magnetic parameters of at least parts of the localization space and for processing the determined absolute position are included.

A first map comprising local features and 3D locations of the local features is generated, the local features comprising visible features in a current image and a corresponding set of covisible features. A second map comprising prior features and 3D locations of the prior features may be determined, where each prior feature: was first imaged at a time prior to the first imaging of any of the local features, and lies within a threshold distance of at least one local feature. A first subset comprising previously imaged local features in the first map and a corresponding second subset of the prior features in the second map is determined by comparing the first and second maps, where each local feature in the first subset corresponds to a distinct prior feature in the second subset. A transformation mapping a subset of local features to a subset of prior features is determined.