Abstract:
Systems, methods and instructions for creating building models of physical structures is disclosed. The building model may be a collection of floors defined by outlines containing regions that may be offset relative to a main region, and a collection of connectors. Connectors may have connection points for tracking, routing and sizing. Connectors may indicate elevation changes through georeferenced structural features. Signal elements may also be features that provide corrections when tracking. Feature descriptors are data that describes the structural configuration and signal elements enabling them to be matched to previously collected data in a database. User interface elements assist a user of a tracking device in collecting floor information, structural features and signal features and validating certain collected information based on previously known information. The height of floors may also be inferred based on sensor data from the tracking device.
Abstract:
Systems, methods and instructions for creating building models of physical structures is disclosed. The building model may be a collection of floors defined by outlines containing regions that may be offset relative to a main region, and a collection of connectors. Connectors may have connection points for tracking, routing and sizing. Connectors may indicate elevation changes through georeferenced structural features. Signal elements may also be features that provide corrections when tracking. Feature descriptors are data that describes the structural configuration and signal elements enabling them to be matched to previously collected data in a database. User interface elements assist a user of a tracking device in collecting floor information, structural features and signal features and validating certain collected information based on previously known information. The height of floors may also be inferred based on sensor data from the tracking device.
Abstract:
Disclosed herein are methods and systems for fusion of sensor and map data using constraint based optimization. In an embodiment, a computer-implemented method may include obtaining tracking data for a tracked subject, the tracking data including data from a dead reckoning sensor; obtaining constraint data for the tracked subject; and using a convex optimization method based on the tracking data and the constraint data to obtain a navigation solution. The navigation solution may be a path and the method may further include propagating the constraint data by a motion model to produce error bounds that continue to constrain the path over time. The propagation of the constraint data may be limited by other sensor data and/or map structural data.
Abstract:
Methods for calibrating a body-worn magnetic sensor by spinning the magnetic sensor 360 degrees to capture magnetic data; if the spin failed to produce a circle contained in an x-y plane fit a sphere to the captured data; determining offsets based on the center of the sphere; and removing the offsets that are in the z-direction. Computing a magnetic heading reliability of a magnetic sensor by determining an orientation of the sensor at one location; transforming the orientation between two reference frames; measuring a first vector associated with the magnetic field of Earth at the location; processing the first vector to generate a virtual vector when a second location is detected; measuring a second vector associated with the magnetic field of Earth at the second location; and calculating the magnetic heading reliability at the second location based on a comparison of the virtual vector and the second vector.
Abstract:
Disclosed herein are methods and systems for mapping irregular features. In an embodiment, a computer-implemented method may include obtaining tracking data that has dead reckoning tracking data for a tracked subject along a path and performing shape correction on the tracking data to provide a first estimate of the path.
Abstract:
A method for determining an environmental pressure change affecting a pressure sensor within a portable device to determine an elevation of the portable device is disclosed. The method involves sampling pressure data from at least one stationary pressure sensor in an area surrounding a location of the device, wherein the stationary pressure sensor in not within the portable device. The sampled pressure data is then interpolated to a time interval and a difference is computed between the interpolated pressure data over each time interval to determine a differential pressure. The location of the stationary pressure sensor is determined and the differential pressure is added to a pressure map affecting data near the location. The environmental pressure change is then computed over any interval at the location and subtracted from a pressure measurement of the pressure sensor before computing an elevation of the portable device.
Abstract:
Methods, systems, and computer readable storage media are presented for directional scaling of inertial path data to satisfy ranging constraints. The presented techniques take into account scaling confidence information. In addition to bounding potential scale corrections based on the reliability of the inertial path and the magnetic heading confidence, the techniques bound potential scale parameters based on constraints and solve for directional scale parameters.
Abstract:
System, computer program products, and methods for detecting and compensating for sensor interference. Sensor interference may result from environmental interference or from electronic signal interference. Sensor location input may be adapted or rejected when interference is detected. The system can monitor the accuracy, as well as the integrity, of all navigation sensors. The system can also automatically eliminate the faulty or compromised data from a final navigation solution.
Abstract:
Methods and systems are described for determining the elevation of tracked personnel or assets (trackees) that can take input from mounted sensors on each trackee (including barometric, inertial, magnetometer, radio frequency ranging and signal strength, light and GPS sensors), external constraints (including ranging constraints, feature constraints, and user corrections), and terrain elevation data. An example implementation of this method for determining elevation of persons on foot is described. But this method is not limited to computing elevation of personnel or to on foot movements.
Abstract:
Disclosed herein are methods and systems for fusion of sensor and map data using constraint based optimization. In an embodiment, a computer-implemented method may include obtaining tracking data for a tracked subject, the tracking data including data from a dead reckoning sensor; obtaining constraint data for the tracked subject; and using a convex optimization method based on the tracking data and the constraint data to obtain a navigation solution. The navigation solution may be a path and the method may further include propagating the constraint data by a motion model to produce error bounds that continue to constrain the path over time. The propagation of the constraint data may be limited by other sensor data and/or map structural data.