Sensor registration by global optimization procedures

• US 7,974,816 B2
• Filed: 12/02/2009
• Issued: 07/05/2011
• Est. Priority Date: 06/20/2007
• Status: Active Grant

• Current Assignee: AT&T Intellectual Property II LP (AT&T, Inc.), Raytheon Company (Rtx Corporation), University of Florida Research Foundation, Incorporated (State University System of Florida)
• Original Assignee: AT&T Intellectual Property II LP (AT&T, Inc.), Raytheon Company (Rtx Corporation), University of Florida Research Foundation, Incorporated (State University System of Florida)
• Inventors: Hirsch, Michael Jacob, Pardalos, Panagote Miltiades, Resende, Mauricio Guilherme de Carvalho
• Primary Examiner(s): Wachsman; Hal D
• Application Number:
  US12/629,377
• Publication Number:
  US 20100076726A1
• Time in Patent Office: 580 Days
• Field of Search: 702/189, 702/104, 702/127, 702/181
• US Class Current: 702/189
• CPC Class Codes: G06F 7/544 for evaluating functions by calculation G06F7/4824 takes precedence

Abstract

Disclosed are method and apparatus for registering multiple sensors collecting data from multiple objects. Sensor registration is decomposed into a two-step procedure. The first step corrects systematic errors. The second step assigns objects measured by one sensor to objects measured by a second sensor. Systematic errors are corrected by generating the global minimum of a systematic error function. One embodiment for generating the global minimum uses a Continuous Greedy Randomized Adaptive Search Procedure.

Claims

1. A measurement system comprising:

a first sensor configured to sense a first set of measurements from a first plurality of objects;

a second sensor configured to sense a second set of measurements from a second plurality of objects; and

a computer comprising;

a sensor network interface configured to receive the first set of measurements and the second set of measurements;

a central processing unit configured to execute computer program instructions; and

a data storage storing computer program instructions defining;

generating a likelihood function associating a data element from the first set of measurements with a data element from the second set of measurements;

generating a systematic error function based at least in part on the likelihood function;

minimizing the systematic error function; and

,

assigning an object from the first plurality of objects to an object from the second plurality of objects, based at least in part on the minimized systematic error function.

2. The measurement system of claim 1, wherein the computer program instructions defining assigning comprise computer program instructions defining:

assigning using a linear assignment method.

3. The measurement system of claim 1, wherein the computer program instructions defining minimizing the systematic error function comprise computer instructions defining:

generating a global minimum of the systematic error function.

4. The measurement system of claim 1, wherein the computer program instructions defining minimizing the systematic error function comprise computer instructions defining:

using a Continuous Greedy Randomized Adaptive Search Procedure.