A system and method for locating, tracking, and/or monitoring the status of personnel and/or assets (collectively “trackees”), both indoors and outdoors, is provided. Tracking data obtained from any number of sources utilizing any number of tracking methods may be provided as input to a mapping application. The mapping application generates position estimates for trackees using a suite of mapping tools to make corrections to the tracking data. The mapping application further uses information from building data, when available, to enhance position estimates. Indoor tracking methods including sensor fusion methods, map matching methods, and map building methods may be implemented compute a more accurate tracking estimate for trackees. Outdoor tracking methods may be implemented to enhance outdoor tracking data by combining tracking estimates such as inertial tracks with magnetic and/or compass data if and when available, and with GPS, if and when available.

System and method for locating, tracking, and/or monitoring the status of personnel and/or assets both indoors and outdoors

Vehicle-mounted device includes an inertial measurement unit (IMU) having at least one accelerometer or gyroscope, a GPS receiver, a camera positioned to obtain unobstructed images of an area exterior of the vehicle and a control system coupled to these components. The control system re-calibrates each accelerometer or gyroscope using signals obtained by the GPS receiver, and derives information about objects in the images obtained by the camera and location of the objects based on data from the IMU and GPS receiver. A communication system communicates the information derived by the control system to a location separate and apart from the vehicle. The control system includes a processor that provides a location of the camera and a direction in which the camera is imaging based on data from the IMU corrected based on data from the GPS receiver, for use in creating the map database.

Mapping Techniques Using Probe Vehicles

Systems and methods according to the present invention describe 3D pointing devices which enhance usability by transforming sensed motion data from a first frame of reference (e.g., the body of the 3D pointing device) into a second frame of reference (e.g., a user's frame of reference). One exemplary embodiment of the present invention removes effects associated with a tilt orientation in which the 3D pointing device is held by a user.

3D pointing devices with orientation compensation and improved usability

The present invention is directed to methods and systems for locating and monitoring the status of people and moveable assets, such as first responders, including firefighters and other public service personnel, and their equipment both indoors and out. The invention can provide for locating and monitoring the status of people and assets in environments where GPS systems do not operate, or where operation is impaired or otherwise limited. The system and method uses inertial navigation to determine the location, motion and orientation of the personnel or assets and communicates with an external monitoring station to receive requests for location, motion orientation and status information and to transmit the location, motion orientation and status information to the monitoring station.

Method and system for locating and monitoring first responders

Systems and methods for controlling a movable object within an environment are provided. In one aspect, a method may comprise: determining, using at least one of a plurality of sensors carried by the movable object, an initial location of the movable object; generating a first signal to cause the movable object to navigate within the environment; receiving, using the at least one of the plurality of sensors, sensing data pertaining to the environment; generating, based on the sensing data, an environmental map representative of at least a portion of the environment; receiving an instruction to return to the initial location; and generating a second signal to cause the movable object to return to the initial location, based on the environmental map.

Multi-sensor environmental mapping

A navigation device is provided herein comprising an inertial measurement unit (IMU), a camera, and a processor. The IMU provides an inertial measurement to the processor and the camera provides at least one image frame to the processor. The processor is configured to determine navigation data based on the inertial measurement and the at least one image frame, wherein at least one feature is extracted from the at least one image frame based on the navigation data.

Camera and inertial measurement unit integration with navigation data feedback for feature tracking

A navigation system includes an inertial navigation unit. The navigation system also includes a Kalman filter that generates corrective feedback for use by the inertial navigation unit. The Kalman filter generates the corrective feedback as a function of at least one of GPS/DGPS information, sensor information, user input, terrain correlation information, signal-of-opportunity information, and/or position information output by a motion classifier.

Personal navigation using terrain-correlation and/or signal-of-opportunity information

Systems and methods for reducing vibration-induced bias errors in inertial sensors are disclosed. A system for reducing bias errors in an inertial sensor operating within an environment may include a vibration detector for sensing vibration changes within the environment proximate to the inertial sensor, and a Kalman filter for computing an estimate of the navigational error produced by the inertial sensor due to a vibration-induced bias shift detected by the vibration detector. The vibration detector can be configured to measure an accelerometer output of the inertial sensor over a Kalman filter cycle, and then use the standard deviation of such output to obtain a statistical measure of the vibration within the environment. In some embodiments, the inertial sensor may include an inertial measurement unit (IMU) connected to an error compensation unit and strapdown navigator, each of which can be fed navigation corrections determined by the Kalman filter.

Systems and methods for reducing vibration-induced errors in inertial sensors

This paper is devoted to the terrain aided navigation (TAN) systems based on the state estimation algorithms. In particular, the emphasis is laid on the design of the Bayesian Rao–Blackwellized point-mass filter for nonlinear state-space models of a specific structure typically used in the terrain aided navigation. The proposed filter preserves advantages of the point-mass filter, including the high estimation accuracy, robust initialization, deterministic nature of the algorithm, and predictable computational complexity, while the computational complexity is significantly reduced. The performance of the Rao–Blackwellized point-mass filter is illustrated using a simulated numerical example and a TAN system based on the real data.

Design of Rao–Blackwellized Point-Mass Filter With Application in Terrain Aided Navigation

The problem of underwater navigation for an individual diver is particularly challenging. GPS navigation is unsuitable for most underwater operations and particularly covert operations use because the GPS RF signal is attenuated below usable levels as it penetrates the water column. Dead reckoning methods, which rely on magnetic compass and approximate distance measurements, are susceptible to magnetic interference, inaccurate distance estimates and current induced drift. Pure inertial navigation methods require expensive systems to meet mission accuracy objectives, due to mission lengths of several hours. Advances in the performance of MEMS inertial sensors, solid state compasses and the development of water based Doppler velocity sensors have enabled a positioning solution that meet USMC diver cost and performance goals. A technology development team organized by Honeywell has developed a self-contained prototype system that integrates a GPS receiver, an inertial measurement unit, a solid state magnetometer, a pressure sensor and a multi-axis Doppler velocity sensor that functions as a surface or underwater navigator and also enables the user to perform underwater surveying and mapping. The sensor integration approach was based on a Kalman filter aided strapdown navigator. Gyro and accelerometer information is processed by the strapdown navigation algorithms to produce navigation solution. An extended Kalman filter processes the GPS, magnetometer, Doppler Velocity Log (DVL), and depth sensor measurement to aid the navigation solution and update sensor error estimates. This paper presents an overview of the system hardware and software implementation as well as test results from ocean trials off the coast of Hawaii.

Wesley J. Hawkinson

Papers

Camera and inertial measurement unit integration with navigation data feedback for feature tracking

Personal navigation using terrain-correlation and/or signal-of-opportunity information

Systems and methods for reducing vibration-induced errors in inertial sensors

Design of Rao–Blackwellized Point-Mass Filter With Application in Terrain Aided Navigation

Tactical underwater navigation system (TUNS)