Abstract: Systems and methods are provided for an advanced pedometer, which may include: a first accelerometer for providing first acceleration information for a first direction; a second accelerometer for providing second acceleration information for a second direction; a third accelerometer for providing third acceleration for a third direction; a clock for providing time information associated with the first acceleration information, the second acceleration information, and the third acceleration information; and a processing module comprising one or more processors.

Abstract: Systems and methods are provided for an advanced pedometer, which may include: a first accelerometer for providing first acceleration information for a first direction; a second accelerometer for providing second acceleration information for a second direction; a third accelerometer for providing third acceleration for a third direction; a clock for providing time information associated with the first acceleration information, the second acceleration information, and the third acceleration information; and a processing module comprising one or more processors.

Abstract: The need for geo-registered features is avoided by a system for estimating a motion of a first sensor during a time interval. The system has a second sensor where the first sensor and the second sensor sense the same geo-location during the time interval. The first sensor computes a first target location error from sensing the geo-location. The second sensor also computes a second target location error from sensing the geo-location. A data link interconnects the first sensor and the second sensor, the data link transmitting the second target location error computed by the second sensor to the first sensor during the time interval. A processor at the first sensor combines the first target location error and the second target location error in a first sensor observation model, where the sensor observation model is descriptive of the motion of the first sensor. The observation model is used with a Kalman filter to update the position of the first sensor.

Abstract: A position estimation system including a first arrangement for providing an image with a known target in a known reference frame. A second arrangement correlates the image with a stored image. The correlation is used to compute an error with respect to a position estimate. In a specific embodiment, the error is referenced with respect to first (x), second (y) and third (z) directions. A target location error is computed with respect to a stored image provided by a target image catalog. The target image catalog includes target geo-locations and digital terrain elevation data. In an illustrative application, the image data is provided by synthetic aperture radar and forward-looking infrared systems. An observation model and a measure noise matrix are Kalman filtered to ascertain a position error in navigation data generated by an integrated inertial navigation and Global Positioning system.

Abstract: A position estimation system including a first arrangement for providing an image with a known target in a known reference frame. A second arrangement correlates the image with a stored image. The correlation is used to compute an error with respect to a position estimate. In a specific embodiment, the error is referenced with respect to first (x), second (y) and third (z) directions. A target location error is computed with respect to a stored image provided by a target image catalog. The target image catalog includes target geo-locations and digital terrain elevation data. In an illustrative application, the image data is provided by synthetic aperture radar and forward-looking infrared systems. An observation model and a measure noise matrix are Kalman filtered to ascertain a position error in navigation data generated by an integrated inertial navigation and Global Positioning system.

Abstract: The need for geo-registered features is avoided by a system for estimating a motion of a first sensor during a time interval. The system has a second sensor where the first sensor and the second sensor sense the same geo-location during the time interval. The first sensor computes a first target location error from sensing the geo-location. The second sensor also computes a second target location error from sensing the geo-location. A data link interconnects the first sensor and the second sensor, the data link transmitting the second target location error computed by the second sensor to the first sensor during the time interval. A processor at the first sensor combines the first target location error and the second target location error in a first sensor observation model, where the sensor observation model is descriptive of the motion of the first sensor. The observation model is used with a Kalman filter to update the position of the first sensor.