Time filter

Source Type

San Mateo, CA, United States

Miller I.,Coherent Navigation, Inc. | Campbell M.,Cornell University | Huttenlocher D.,Cornell University
IEEE Transactions on Robotics

A novel-tracking algorithm is presented as a computationally feasible, real-time solution to the joint estimation problem of data assignment and dynamic obstacle tracking from a potentially moving robotic platform. The algorithm implements a RaoBlackwellized particle filter (RBPF) to factorize the joint estimation problem into 1) a data assignment problem solved via particle filter and 2) a multiple dynamic obstacle-tracking problem solved with efficient parametric filters. The parametric filters make use of a new target representation and stable features developed specifically for tracking full-size vehicles in a dense traffic environment. The algorithm is validated in real time, both in controlled experiments with full-size robotic vehicles and on data collected at the 2007 Defense Advanced Research Projects Agency (DARPA) Urban Challenge. © 2010 IEEE. Source

Coherent Navigation, Inc. | Date: 2014-02-24

A navigation system includes a navigation radio and a sensor onboard a vehicle. The navigation radio receives and processes low earth orbit RF signals to derive range observables for a corresponding LEO satellite. A sensor is operable to generate at least one of vehicle speed data, acceleration data, angular rate data and rotational angle data under high vehicle dynamics. The navigation radio includes a navigation code operable to obtain a position, velocity and time solution (a navigation solution) based on the one or more range observables, ephemerides for the corresponding LEO satellite, a heading pseudomeasurement, a navigation radio altitude pseudomeasurement; one or more vehicle velocity pseudomeasurements orthogonal to the altitude pseudomeasurements; and the generated at least one of vehicle speed data, acceleration data, angular rate data and rotational angle data. The navigation radio uses the navigation solution to acquire a GPS signal during interference with a coarse acquisition GPS signal.

Coherent Navigation, Inc. | Date: 2014-04-03

A system and method of continuous carrier wave reconstruction includes a radio navigation receiver that includes one or more processors, memory coupled to the one or more processors, and an input for receiving a signal from a transmitter. The signal has a phase. The one or more processors are configured to obtain phase lock on the received signal, extract first phase information from the received signal, detect a loss in phase lock on the received signal, and extrapolate second phase information while phase lock is lost using a model of the phase. In some embodiments, the one or more processors are further configured to reconstruct the carrier signal based on the first and second phase information. In some embodiments, the one or more processors are further configured to scale the first and second phase information from a first nominal frequency of the received signal to a different second nominal frequency.

Coherent Navigation, Inc. | Date: 2010-09-23

A method and apparatus for simulating radio-frequency Global Navigation Satellite System (GNSS) signals that are carrier-phase and code-phase aligned with ambient GNSS signals at a user-specified location in the vicinity of the simulator. Such phase alignment allows the synthesized signals to be made to appear substantially the same as the authentic signals to a target receiver, allowing the target receiver to transition seamlessly between authentic and simulated signals. The method is embodied in a device, a phase-coherent GNSS signal simulator, which can be implemented on a digital signal processor for embedded applications.

Agency: Department of Defense | Branch: Navy | Program: STTR | Phase: Phase I | Award Amount: 80.00K | Year: 2011

An emitter detection and localization (EML) technique has been researched and developed that utilizes long-coherent integration. This technique enables EML over a broad range of emitter frequencies and signal types. The EML system is composed of sensor nodes and a processing center that carries out the bulk of the signal processing. Adaptive network bandwidth utilization is applied to make the system practical.

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