The Johns Hopkins University

James H Higbie

Robert Osiander

Daniel G Jablonski

Dennis K Wickenden

Robert B Givens

Cash J Costello

Nicholas D Beser

George R Barrett

Thomas J Kistenmacher

Donna C Paulhamus

Margaret Ann Darrin

John L Champion

Scott T Radcliffe

Douglas A Oursler

Michael A Karls

Thomas E Duerr

The Digital Video Authenticator (DVA) addresses law enforcement concerns for a means to authenticate digital video (DV) so that it will be admissible and trusted as evidence in court. The DVA is a peripheral device attached to a commercial digital video recording device whose purpose is to generate and record authentication data simultaneously as DV is recorded by the video recording device. Verification of the authenticity of a DV sample will be accomplished using non-real-time software tools. The DVA system and method reads digital video (DV) data from a digital video recording device; parses the DV data into elements representing video, audio, control and timing data; and creates digital signatures that can be used to validate the original DV tape. The combination of secure digital signatures and repeatability of the DV data stored on tape provides the basis for proving the original video has not been modified.

Digital video authenticator

A Lorentz force-driven mechanical resonator apparatus that utilizes a high-Q resonant structure as both a mixing device and a high-Q bandpass filter. Specifically, an external time varying, but quasistatic, magnetic field is applied to the resonating device while simultaneously running a time varying electrical current through the device. The resulting Lorentz force (I&times;B) is proportional to the vector product of the electrical current in the bar (I) and the external magnetic field (B). Integrating such a resonant device with a magnetic field coil produces the functionality of an ideal radio frequency (RF) mixer coupled with a high-Q intermediate frequency (IF) filter. Wide tunability provides the capability to scan, or even step, an array of filters having very narrow bandwidths via a common local oscillator to a desired frequency range.

Lorentz force driven mechanical filter/mixer designs for RF applications

A system is provided which combines the advantages of Adaptive Antenna Arraying and Adaptive Locally-Optimum Detection, as well as Adaptive Filtering, signal processing techniques and achieves the capabilities of all these techniques. The present invention represents the first successful integrated system for performing signal processing techniques associated with an Adaptive Antenna Array (AAA) system and an Adaptive Locally-Optimum Detection (ALOD) system. The system automatically distributes interference signals among Adaptive Antenna Arraying and Adaptive Locally-Optimum Detection sub-systems according to which sub-system's algorithms can provide a more optimum suppression of the interference signals. The system permits an adaptive antenna array with a given number of antenna elements to effectively suppress a larger number of interferers than it otherwise could, and to adapt more quickly to a rapidly changing interference scenario. For an adaptive antenna array with a small number of antenna elements, e.g., two to four, the system provides added interference suppression capability than could be done by adding antenna elements to the adaptive antenna array. The system is primarily designed for incorporation within systems using Direct Sequence Spread Spectrum signals, such as Global Positioning System (GPS) signals. In a preferred embodiment the inventive system is incorporated within a conventional GPS receiver which tends to be vulnerable to jamming by interference signals.

Integrated adaptive antenna array and adaptive locally-optimum detection system

A signal processing technique is described which suppresses interference in spread-spectrum communications receive systems by optimizing the detection process dynamically against the current interference. This is accomplished by estimating the statistics of the interference and then using this information to derive the locally-optimum mapping to apply to the signal of interest plus interference. As the statistics of the interference change, the measured distributions and the resulting transformations also change. The adaptation is open loop so convergence problems do not arise.

Adaptive locally-optimum detection signal processor and processing

Growing community of inventors

Catonsville, MD, United States of America

James H Higbie