Abstract: A method is provided for estimating parameters useful to determine the position of a global navigation satellite system (GNSS) receiver or a change in the position thereof. The method includes the steps of: obtaining at least one GNSS signal received at the GNSS receiver from each of a plurality of GNSS satellites; obtaining, from at least one network node, precise satellite information on: (i) the orbit or position of at least one of the plurality of GNSS satellites, and (ii) a clock offset of at least one of the plurality of GNSS satellites; identifying, among the obtained GNSS signals, a subset of at least one GNSS signal possibly affected by a cycle slip, the identified subset being hereinafter referred to as cycle-slip affected subset; and estimating parameters useful to determine the position of the GNSS receiver or a change in the position of the GNSS receiver using at least some of the obtained GNSS signals which are not in the cycle-slip affected subset, and the precise satellite information.

Abstract: Methods and apparatus are described for processing a set of GNSS signal data derived from signals of GNSS satellites observed at reference station receivers, the data representing code observations and carrier observations on each of at least two carriers over multiple epochs, comprising: obtaining an orbit start vector comprising: a time sequence of predicted positions and predicted velocities for each satellite over a first interval, and the partial derivatives of the predicted positions and predicted velocities with respect to initial positions, initial velocities, force model parameters and Earth orientation parameters, obtaining ionospheric-free linear combinations of the code observations and the carrier observations for each satellite at multiple reference stations, and iteratively correcting the orbit start vector using at each epoch the ionospheric-free linear combinations and predicted Earth orientation parameters, as soon as the ionospheric-free linear combinations of the epoch are available, to ob

Abstract: The technology described herein includes a system and/or a method of risk management for object identification. The method includes selecting at least two fusion functions from a plurality of fusion functions. Each of the fusion functions is associated with a different risk bias. The method further includes fusing a received set of data based on each fusion function to form at least two sets of fused data. The method further includes generating a probability of identification of the classification of the object based on each set of the fused data. The method further includes determining a risk bias difference between the probability of identification of each set of the fused data.

Abstract: A method is provided for estimating parameters useful to determine the position of a global navigation satellite system (GNSS) receiver or a change in the position thereof. The method includes the steps of: obtaining at least one GNSS signal received at the GNSS receiver from each of a plurality of GNSS satellites; obtaining, from at least one network node, precise satellite information on: (i) the orbit or position of at least one of the plurality of GNSS satellites, and (ii) a clock offset of at least one of the plurality of GNSS satellites; identifying, among the obtained GNSS signals, a subset of at least one GNSS signal possibly affected by a cycle slip, the identified subset being hereinafter referred to as cycle-slip affected subset; and estimating parameters useful to determine the position of the GNSS receiver or a change in the position of the GNSS receiver using at least some of the obtained GNSS signals which are not in the cycle-slip affected subset, and the precise satellite information.

Abstract: Methods and apparatus are described for processing a set of GNSS signal data derived from signals of GNSS satellites observed at reference station receivers, the data representing code observations and carrier observations on each of at least two carriers over multiple epochs, comprising: obtaining an orbit start vector comprising: a time sequence of predicted positions and predicted velocities for each satellite over a first interval, and the partial derivatives of the predicted positions and predicted velocities with respect to initial positions, initial velocities, force model parameters and Earth orientation parameters, obtaining ionospheric-free linear combinations of the code observations and the carrier observations for each satellite at multiple reference stations, and iteratively correcting the orbit start vector using at each epoch the ionospheric-free linear combinations and predicted Earth orientation parameters, as soon as the ionspheric-free linear combinations of the epoch are available, to obt

Abstract: In a method of autonomous orbit projection performed within a Global Navigation Satellite System (GNSS) receiver, distinct broadcast orbits are received over time from a GNSS satellite during operation of the GNSS receiver. A plurality of the distinct broadcast orbits are stored within the GNSS receiver. Within the GNSS receiver, a plurality of the stored broadcast orbits are converted into a time series of range data for the GNSS satellite. A projected orbit for the GNSS satellite is determined by utilizing the time series of range data as an input to an orbit projector of the GNSS receiver.

Abstract: A method and system for of fusing the outputs of multiple sensors. The output of each sensor including a sensor class probability vector based on each sensor's classification database is input to a fusion engine which estimates a base class probability vector based on the sensor class probabilities output by the sensors and a preconfigured base database including base classes.

Abstract: In one aspect, a method to assign observations includes receiving first observations of a first sensor system, receiving second observations of a second sensor system and assigning a set of pairs of the first and second observations predicted to correspond to the same physical position. The assigning includes using a likelihood function that specifies a likelihood for each assigned pair. The likelihood is dependent on the assignment of any other assigned pairs in the set of assigned pairs. The assigning also includes determining the set of assigned pairs for the first and second observations based on the likelihood function. The likelihood function uses a gate value determined from estimating a true volume using nearest neighbor distances determined from the first and second observations.

Abstract: In a method of autonomous orbit projection performed within a Global Navigation Satellite System (GNSS) receiver, distinct broadcast orbits are received over time from a GNSS satellite during operation of the GNSS receiver. A plurality of the distinct broadcast orbits are stored within the GNSS receiver. Within the GNSS receiver, a plurality of the stored broadcast orbits are converted into a time series of range data for the GNSS satellite. A projected orbit for the GNSS satellite is determined by utilizing the time series of range data as an input to an orbit projector of the GNSS receiver.

Abstract: A method and system for of fusing the outputs of multiple sensors. The output of each sensor including a sensor class probability vector based on each sensor's classification database is input to a fusion engine which estimates a base class probability vector based on the sensor class probabilities output by the sensors and a preconfigured base database including base classes.

Abstract: In one aspect, a method to assign observations includes receiving first observations of a first sensor system, receiving second observations of a second sensor system and assigning a set of pairs of the first and second observations predicted to correspond to the same physical position. The assigning includes using a likelihood function that specifies a likelihood for each assigned pair. The likelihood is dependent on the assignment of any other assigned pairs in the set of assigned pairs. The assigning also includes determining the set of assigned pairs for the first and second observations based on the likelihood function. The likelihood function uses a gate value determined from estimating a true volume using nearest neighbor distances determined from the first and second observations.

Abstract: A method for tracking a target having substantially constrained movement utilizes the steps of determining constrains for movement of the target, obtaining information on movement of the target, and predicting that the target will continue to move upon a route segment after the target has begun to move thereupon. The constraints are made up of a plurality of separate alternate route segments. Predicting that the target will continue to move upon the route segment upon which it is previously moving facilitates targeting, intercept and intelligence with a substantial degree of reliability, particularly when continuing information, such as radar returns, is not available.