Vector neural network for low signal-to-noise ratio detection of a target
US5210798A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Mar 11, 1991 |
| Grant date | May 11, 1993 |
| Priority date | — |
| Expiry date | Mar 11, 2011 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S348/909
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A vector neural network (VNN) of interconnected neurons is provided in transition mappings of potential targets wherein the threshold (energy) of a single frame does not provide adequate information (energy) to declare a target position. The VNN enhances the signal-to-noise ratio (SNR) by integrating target energy over multiple frames including the steps of postulating massive numbers of target tracks (the hypotheses), propagating these target tracks over multiple frames, and accommodating different velocity target by pixel quantization. The VNN then defers thresholding to subsequent target stages when higher SNR's are prevalent so that the loss of target information is minimized, and the VNN can declare both target location and velocity. The VNN can further include target maneuver detection by a process of energy balancing hypotheses.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.