Process for determining the position of a moving object using magnetic gradientmetric measurements

• US 6,539,327 B1
• Filed: 06/26/2000
• Issued: 03/25/2003
• Est. Priority Date: 09/11/1997
• Status: Expired due to Fees

• Current Assignee: Commissariat a L'Energie Atomique (AES Corporation)
• Original Assignee: Commissariat a L'Energie Atomique (AES Corporation)
• Inventors: Blanpain, Roland, Flament, Bruno, Jauffret, Claude, Dassot, Gilles
• Primary Examiner(s): Hilten, John S.
• Assistant Examiner(s): Washburn, Douglas N
• Application Number:
  US09/508,482
• Time in Patent Office: 1,002 Days
• Field of Search: 324/207.11, 700/89, 701/207, 702/150, 702/152
• US Class Current: 702/150
• CPC Class Codes: G01V 3/081 the magnetic field is produced by the objects or geological structures characterised by the method of magnetic field measurement G01R33/00

Abstract

A process for determining the position of a moving object, by the following steps: scalar measurements are acquired by a set of sensors all installed on the same site, at a position known at each instant; the trajectory of the object is determined approximately by a model; the measurements output from each sensor are combined to obtain spatial gradient measurements representative of the vector electromagnetic disturbance of the moving object; a vector of parameters characteristic of the model is estimated as a function of gradient measurements and as a function of the position of the sensors; and the position of the object is determined as a function of the position of the sensors and the parameters vector.

Claims

1. A process for determining the position of a moving object comprising:

acquiring scalar measurements by a set of sensors capable of movement during said process and adapted to transmit their positions at each of a plurality of instants;

estimating a trajectory of the object by a model;

combining the measurements output from each sensor to obtain spatial gradient measurements representative of the vector magnetic disturbance of the moving object;

estimating a vector of parameters characteristic of the model as a function of gradient measurements and as a function of the position of the sensors; and

determining the position of the object as a function of the position of the sensors and the parameters vector;

wherein the sensors are all installed at substantially the same physical location.

2. A process according to claim 1, further comprising modeling the movement of the object based on a uniform movement along a straight line, the parameters vector being (θ

, r/v, v′

/v), where θ

is the azimuth of the object at a reference instant taken with respect to the North direction, r is the source/sensor distance at the same reference instant, v′

is the speed of the object, and v is the modulus of the speed.

3. A process according to claim 1, further comprising using magnetic measurements in combination with acoustic measurements.

4. A process according to claim 1, further comprising using electromagnetic measurements output from scalar magnetometers used in gradientmeters.

5. A process according to claim 1, further comprising estimating the parameters vector using an algorithm that maximizes the probability of the tracking parameters vector or state vector with respect to the probability distribution of measurement noise.

6. A process according to claim 5, further comprising using minimization algorithms to minimize the error between the measured signals and the signals reconstructed with the model used to approximate the trajectory of the object when the measurement noise is approximately gaussian.

8. A process according to claim 5, wherein at least one sensor is moved during said process.

9. A process according to claim 1, wherein the speed of vehicles is counted, classified and estimated.

10. A process according to claim 1, wherein said process is used for submarine surveillance.

7. A process for determining the position of a moving object comprising:

acquiring scalar measurements by a set of sensors capable of movement during said process and adapted to transmit their positions at each of a plurality of instants;

estimating a trajectory of the object by a model;

combining the measurements output from each sensor to obtain spatial gradient measurements representative of the vector magnetic disturbance of the moving object;

estimating a vector of parameters characteristic of the model as a function of gradient measurements and as a function of the position of the sensors; and

determining the position of the object as a function of the position of the sensors and the parameters vector;

wherein the sensors are all installed at substantially the same physical location; and

further comprising using together an azimuth method and a Doppler phenomenon observed in the case of sources radiating a narrow band signal around a stable central frequency.

11. A process according to claim 7, further comprising modeling the movement of the object based on a uniform movement along a straight line, the parameters vector being (θ

, r/v, v′

/v), where θ

is the azimuth of the object at a reference instant taken with respect to the North direction, r is the source/sensor distance at the same reference instant, v′

is the speed of the object, and v is the modulus of the speed.

12. A process according to claim 7, further comprising using magnetic measurements in combination with acoustic measurements.

13. A process according to claim 7, further comprising using electromagnetic measurements output from scalar magnetometers used in gradientmeters.

14. A process according to claim 7, further comprising estimating the parameters vector using an algorithm that maximizes the probability of the tracking parameters vector or state vector with respect to the probability distribution of measurement noise.

15. A process according to claim 14, further comprising using minimization algorithms to minimize the error between the measured signals and the signals reconstructed with the model used to approximate the trajectory of the object when the measurement noise is approximately gaussian.

16. A process according to claim 14, wherein at least one sensor is moved during said process.

17. A process according to claim 7, wherein the speed of vehicles is counted, classified and estimated.

18. A process according to claim 7, wherein said process is used for submarine surveillance.