Abstract: Provided are systems, methods, and devices for identifying correct satellite signals to improve the accuracy of a satellite navigation system. In some embodiments, identifying correct satellite signals may include receiving a plurality of satellite signals; demodulating the satellite signals to extract a first plurality of parameters; determining a first subset of parameters from the first plurality of parameters, wherein the first subset of parameters is based on a first geographic location; determining a second subset of parameters from a second plurality of parameters outside the first subset, the second plurality of parameters comprising one or more parameters of the first plurality of parameters outside the first subset, wherein the second subset of parameters is based on a second geographic location; and identifying an exemplary subset from the first subset and the second subset, wherein the exemplary subset comprises parameters corresponding to correct satellite signals.

Abstract: Computer-implemented systems and methods are disclosed for distance and congestion-aware resource deployment. In some embodiments, a method is provided to estimate a vehicle deployment region. The method includes constructing a graph data structure using at least in part a single invocation of a form of Dijkstra's algorithm. The method additionally includes partitioning an angular space centered on a vehicle location into a plurality of angular space regions, the vehicle location corresponding to a current or potential location of the vehicle.

Abstract: A signal processing module (50) comprises a difference signal generating module (60) for generating at least one difference signal (?) from a first and a second acceleration measurement vector signal (S1, S2), the first and the second acceleration measurement vector signal (S1, S2) respectively comprising a first and a second sequence of vector signal samples, the vector signal samples comprising at least a first and a second linearly independent acceleration measurement signal component, wherein the vector signal samples represent a measurement result of an acceleration sensor having a variable orientation as a function of time, wherein samples in the first sequence have a corresponding sample in the second sequence.

Abstract: A long-term navigation method using an inertial unit associated with a system of axes X, Y, Z and mounted on a vehicle traveling relative to the Earth in order to measure its movements relative to an inertial frame of reference having axes Xi, Yi, and Zi. The method includes the steps of acting in permanent manner to measure an orientation of the system of axes X, Y, Z in the inertial frame of reference and applying a predetermined sequence of turnovers to the inertial unit in the inertial frame of reference about first and second axes that are substantially perpendicular to each other and in such a manner that at the end of the sequence the inertial unit is in a final orientation identical to its initial orientation relative to the inertial frame of reference, with the turnovers canceling within the sequence.

Abstract: A system and method for more accurately and robustly determining the heading of a vehicle by taking measurements of angle rates using rate sensors mounted on a movable mechanical assembly. In a quasi-static state of the vehicle, the mechanical assembly is rotated around axes perpendicular to the tangent plane of the Earth, and angle rates are measured by the rate sensors at different rotational angles of the mechanical assembly. The measurements of the angle rates are then computed to determine the initial heading of the vehicle relative to the true north of the Earth in the quasi-static state of the vehicle. After determining the initial heading, navigation state propagation is performed to determine the heading of the vehicle in non-quasi-static state of the vehicle. By taking measurements of the rate sensors at different rotation angles and performing computation, the heading of the vehicle relative to the Earth's true north can be determined using less accurate angle sensors.

Abstract: Embodiments of the invention provide a blending filter based on extended Kalman filter (EKF), which optimally integrates the IMU navigation data with all other satellite measurements tightly-coupled integration filter. This blending filter can be easily implemented with minor modification to the position engine of stand-alone GNSS receiver. Provided is a low-complexity tightly-coupled integration filter for sensor-assisted global navigation satellite system (GNSS) receiver. The inertial measurement unit (IMU) contains inertial sensors such as accelerometer, magnetometer, and/or gyroscopes Embodiments also include method for pedestrian dead reckoning (PDR) data conversion for ease of GNSS/PDR integration. The PDR position data is converted to user velocity measured at the time instances where GNSS position/velocity estimates are available.

Abstract: Systems and methods for determining a position of a vehicle are described. The system includes at least one GNSS sensor mounted to the vehicle for receiving GNSS signals of a global positioning system and at least one physical sensor mounted to the vehicle for generating physical data indicative of a physical parameter of at least a part of the vehicle. The system also includes a recursive statistical estimator, such as a Kalman Filter, in communication with the GNSS sensor(s) for seeding the recursive statistical estimator with an output of the GNSS sensor(s) to determine an estimated position of the vehicle. A data fusion module combines the estimated position and velocity of the vehicle with the physical data thus generating combined data, which is used to seed the recursive statistical estimator to determine an updated estimated position of the vehicle.

Abstract: A long-term navigation method using an inertial unit associated with a system of axes X, Y, Z and mounted on a vehicle traveling relative to the Earth in order to measure its movements relative to an inertial frame of reference having axes Xi, Yi, and Zi. The method includes the steps of acting in permanent manner to measure an orientation of the system of axes X, Y, Z in the inertial frame of reference and applying a predetermined sequence of turnovers to the inertial unit in the inertial frame of reference about first and second axes that are substantially perpendicular to each other and in such a manner that at the end of the sequence the inertial unit is in a final orientation identical to its initial orientation relative to the inertial frame of reference, with the turnovers canceling within the sequence.

Abstract: A vehicle awareness system for monitoring remote vehicles relative to a host vehicle. The vehicle awareness system includes at least one object sensing device and a vehicle-to-vehicle communication device. A data collection module is provided for obtaining a sensor object data map and vehicle-to-vehicle object data map. A fusion module merges the sensor object data map and vehicle-to-vehicle object data map for generating a cumulative object data map. A tracking module estimates the relative position of the remote vehicles to the host vehicle.

Abstract: A computer controlled object oriented programming system for distributive program development over networks such as the internet with means for interfacing a plurality of programming objects with each other to provide combination objects combining programming functions of said objects, each object including predetermined interface data defining a required common interface with the other programming objects as well as a framework of events and attributes and methods for manipulating the attributes. These objects may be combined with each other via their common interfaces to form combination objects, and such combination objects may in turn be further combined with other objects and combination objects to form objects of increasing complexity which function as program routine versions.