Vector neural network for low signal-to-noise ratio detection of a target

• US 5,210,798 A
• Filed: 03/11/1991
• Issued: 05/11/1993
• Est. Priority Date: 07/19/1990
• Status: Expired due to Term

• Current Assignee: Litton Systems Incorporated
• Original Assignee: Litton Systems Incorporated
• Inventors: Smith, William F., Johnson, David D., Ekchian, Leon K.
• Primary Examiner(s): Boudreau, Leo H.
• Assistant Examiner(s): STELLRECHT, BARRY
• Application Number:
  US07/667,633
• Time in Patent Office: 792 Days
• Field of Search: 342/96, 382/14, 358/125, 395/22
• US Class Current: 382/103
• CPC Class Codes: G01S 13/726 Multiple target tracking
• CPC Class Codes: G01S 7/417 involving the use of neural networks
• CPC Class Codes: G06N 3/04 Architecture, e.g. interconnection topology
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: Y10S 348/909 Noise responsive signal processing

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.

Claims

1. A vector neural network (VNN) for the detection of a potential target where the energy of the target is insufficient in reference to a determinable signal-to-noise ratio (SNR) operating condition CHARACTERIZED IN THAT THE VNN comprises:

a) first means to establish operating control parameters for the VNN in response to the SNR where said control parameters include

(1) postulating a plurality of target tracks,

(2) propagating said tracks in a network of interconnected neurons,

(3) encoding said tracks to directional target energies,

b) second means to integrate target energies along at least one target track to develop a continuous target track over a function of both time and space,

c) third means to declare a target location by deferred thresholding of said integrated target energies relative to the SNR, and

d) fourth means to determine target direction by a backflow process with associated switching of said integrated target energies along said continuous target track.

2. The VNN of claim 1 in which target declaration includes target velocity.

3. The VNN of claim 2 in which said target declaration includes target acceleration.