SYSTEM AND METHOD FOR MULTIPLE TARGET TRACKING

• US 20130035915A1
• Filed: 10/12/2012
• Published: 02/07/2013
• Est. Priority Date: 04/15/2010
• Status: Abandoned Application

• Current Assignee: AGT International GMBH
• Original Assignee: Ats Group (Ip Holdings) Limited
• Inventors: Painsky, Amichai
• Application Number:
  US13/651,090
• Publication Number:
  US 20130035915A1
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: G01S 13/726 Multiple target tracking
• CPC Class Codes: G01S 13/86 Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06F 18/20 Analysing
• CPC Class Codes: G06V 2201/07 Target detection

Abstract

Embodiments of the present invention generally relate to systems and methods comprising First Order Multiple Hypothesis Testing for a Global Nearest Neighbor Data Correlation solution. Generating and storing multiple target hypotheses to allow immediate recovery in case of a false decision in uncertain association environment, improves the system'"'"'s ability to handle multiple target tracking, in terms of tracker error, and creates a more accurate situational picture for a system'"'"'s operator. Introducing the quality factor, and a configurable number of maximum hypotheses testing, assures the system is easily adjustable to different environments, to balance tradeoffs between its estimation accuracy and computational load.

Claims

1. A method for tracking multiple targets, the method comprising:

estimating at least one predicted set of states of the multiple targets for a given time;

obtaining, for the given time, a set of observations acquired from at least one sensor;

calculating a plurality of associations as a function of the at least one predicted set of states and the set of observations;

generating, as a function of the plurality of associations, a respective plurality of updated sets of states of the multiple targets for the given time;

selecting, from the plurality of updated sets of states, a set of states defining a best correlation with the set of observations; and

setting, for the given time, respective states of the multiple targets in accordance with the selected set of states.

2. The method of claim 1, further comprising:

displaying the selected set of states.

3. The method of claim 1, wherein the plurality of associations is a first plurality of associations, wherein the set of observations is a first set of observations, wherein estimating at least one first set of states comprises:

estimating the at least one predicted set of states as a function of at least one set of a second plurality of updated sets of states of the multiple targets, wherein the at least one set of a second plurality of updated sets of states is generated as a function of a second plurality of associations, wherein the second plurality of associations are calculated as a function of estimates of states of the multiple targets and a second set of observations for a time prior to the given time.

4. A tangible computer-readable storage medium comprising program instructions, wherein the program instructions are computer executable to:

estimate at least one predicted set of states of the multiple targets for a given time;

obtain, for the given time, a set of observations acquired from at least one sensor;

calculate a plurality of associations as a function of the at least one predicted set of states and the set of observations;

generate, as a function of the plurality of associations, a respective plurality of updated sets of states of the multiple targets for the given time;

select, from the plurality of updated sets of states, a set of states defining a best correlation with the set of observations; and

set, for the given time, respective states of the multiple targets in accordance with the best set of states.

5. The tangible computer-readable storage medium of claim 4, wherein the program instructions are computer executable to:

display the selected set of states.

6. The tangible computer-readable storage medium of claim 4, wherein the plurality of associations is a first plurality of associations, wherein the set of observations is a first set of observations;

wherein the program instructions are computer executable to;

estimate the at least one predicted set of states as a function of at least one set of a second plurality of updated sets of states of the multiple targets, wherein the at least one set of a second plurality of updated sets of states is generated as a function of a second plurality of associations, and wherein the second plurality of associations are calculated as a function of estimates of states of the multiple targets and a second set of observations for a time prior to the given time.

7. A system comprising:

a processor, memory and a data correlation engine, wherein the data correlation engine is adapted to;

estimate at least one predicted set of states of the multiple targets for a given time;

obtain, for the given time, a set of observations acquired from at least one sensor;

calculate a plurality of associations as a function of the at least one predicted set of states and the set of observations;

generate, as a function of the plurality of associations, a respective plurality of updated sets of states of the multiple targets for the given time;

select, from the plurality of updated sets of states, a set of states defining a best correlation with the set of observations; and

set, for the given time, respective states of the multiple targets in accordance with the best set of states.

8. The system of claim 7, further comprising a display adapted to display the selected set of states.

9. The system of claim 7, wherein the plurality of associations is a first plurality of associations, wherein the set of observations is a first set of observations;

wherein the data correlation engine is further adapted to estimate the at least one predicted set of states as a function of at least one set of a second plurality of updated sets of states of the multiple targets, wherein the at least one set of a second plurality of updated sets of states is generated as a function of a second plurality of associations, and wherein the second plurality of associations are calculated as a function of estimates of states of the multiple targets and a second set of observations for a time prior to the given time.