System, method and product for locating vehicle key using neural networks

• US 9,182,473 B2
• Filed: 05/07/2013
• Issued: 11/10/2015
• Est. Priority Date: 05/10/2012
• Status: Active Grant

• Current Assignee: Lear Corporation
• Original Assignee: Lear Corporation
• Inventors: Margalef, Jordi Virgili, Cuesta, Daniel Cirujano, Martinez, Gema Barreda, Deshpande, Sameer, Macovei, Petru
• Primary Examiner(s): Liu, Harry
• Application Number:
  US13/888,466
• Publication Number:
  US 20130300608A1
• Time in Patent Office: 917 Days
• Field of Search: 342/451, 342/450, 342/463
• US Class Current: 1/1
• CPC Class Codes: G01S 5/0252 Radio frequency fingerprinting

Abstract

A system, method and product for determining a vehicle key fob location. The system may include a control unit for mounting in a vehicle and configured to receive multiple signals, each representing a strength of a wireless signal transmitted between the fob and one of multiple antennas located on a vehicle, and multiple neural networks having a cascade topology. The neural networks may include a first neural network for determining one of a vehicle internal position and a vehicle external position of the fob based on the wireless signal strengths, a second neural network in communication with the first neural network for determining one of multiple vehicle interior positions of the fob based on the wireless signal strengths, and a third neural network in communication with the first neural network for determining one of multiple vehicle exterior positions of the fob based on the wireless signal strengths.

Claims

1. A system for determining a location of a key fob for use in a vehicle access system, the location system comprising:

a control unit for mounting in a vehicle, the control unit configured to receive a plurality of signals, each signal representing a strength of a wireless signal transmitted between the key fob and one of a plurality of antennas located on a vehicle; and

a plurality of neural networks having a cascade topology, the plurality of neural networks comprising

a first neural network for determining one of a vehicle internal position and a vehicle external position of the key fob based on the wireless signal strengths, wherein determining one of a vehicle internal position and a vehicle external position comprises calculating a plurality of intermediate internal/external position neurons having learned weights and activation functions associated therewith, and calculating an internal/external output neuron for use in indicating one of the vehicle internal position and the vehicle external position of the key fob,

a second neural network in communication with the first neural network, the second neural network for determining one of a plurality of vehicle interior positions of the key fob based on the wireless signal strengths, wherein determining one of a plurality of vehicle interior positions comprises calculating a plurality of intermediate interior position neurons having learned weights and activation functions associated therewith, and calculating a plurality of interior position output neurons for use in indicating one of a plurality of vehicle interior positions of the key fob, and

a third neural network in communication with the first neural network, the third neural network for determining one of a plurality of vehicle exterior positions of the key fob based on the wireless signal strengths, wherein determining one of a plurality of vehicle exterior positions of the key fob comprises calculating a plurality of intermediate exterior position neurons having learned weights and activation functions associated therewith, and calculating a plurality of exterior position output neurons for use in indicating one of a plurality of vehicle exterior positions of the key fob.

2. The system of claim 1 wherein the control unit is further configured to receive a key detection trigger for use in initiating a determination of a key fob location.

3. The system of claim 1 further comprising a plurality of antennas, each antenna configured for mounting at a location on the vehicle.

4. The system of claim 1 further comprising a key fob, the key fob comprising an antenna for enabling communication between the key fob and the plurality of antennas located on the vehicle.

5. The system of claim 1 wherein the learned weights and activation functions associated with the neurons of the plurality of neural networks represent neural network codings for storage in a memory on-board the vehicle.

6. The system of claim 1 wherein the each of the plurality of neural networks is adapted for training to learn the weights and activation functions associated with the neurons of the neural network.

7. The system of claim 1 wherein the plurality of neural networks comprise software for storage in a memory on-board the vehicle.

8. The system of claim 1 wherein

the first neural network comprises eight input neurons, five intermediate internal/external location neurons, and one internal/external output neuron;

the second neural network comprises eight input neurons, three intermediate interior position neurons, and four interior output neurons; and

the third neural network comprises eight input neurons, three intermediate exterior position neurons, and four exterior output neurons.

9. A computer readable medium having non-transitory computer executable instructions stored thereon for determining a location of a key fob for use in a vehicle access system, the computer executable instructions comprising instructions for:

determining one of a vehicle internal position and a vehicle external position of the key fob based on signal strengths of a plurality of wireless signal transmitted between the key fob and a plurality of antennas located on a vehicle, wherein determining one of a vehicle internal position and a vehicle external position comprises a first neural network calculating a plurality of intermediate internal/external position neurons having learned weights and activation functions associated therewith, and calculating an internal/external output neuron for use in indicating one of the vehicle internal position and the vehicle external position of the key fob;

determining one of a plurality of vehicle interior positions of the key fob based on the wireless signal strengths, wherein determining one of a plurality of vehicle interior positions comprises a second neural network calculating a plurality of intermediate interior position neurons having learned weights and activation functions associated therewith, and calculating a plurality of interior position output neurons for use in indicating one of a plurality of vehicle interior positions of the key fob; and

determining one of a plurality of vehicle exterior positions of the key fob based on the wireless signal strengths, wherein determining one of a plurality of vehicle exterior positions of the key fob comprises a third neural network calculating a plurality of intermediate exterior position neurons having learned weights and activation functions associated therewith, and calculating a plurality of exterior position output neurons for use in indicating one of a plurality of vehicle exterior positions of the key fob;

wherein the first, second and third neural networks have a cascade topology.

10. The computer readable medium of claim 9 wherein the computer executable instructions further comprise instructions for initiating a determination of a key fob location based on a key detection trigger.

11. The computer readable medium of claim 9 wherein the computer executable instructions further comprise instructions for storing neural network codings representing the learned weights and activation functions associated with the neurons of the neural networks.

12. The computer readable medium of claim 9 wherein the computer executable instructions further comprise instructions for learning the weights and activation functions associated with the neurons of the neural networks.

13. The computer readable medium of claim 9 wherein

the first neural network comprises eight input neurons, five intermediate internal/external location neurons, and one internal/external output neuron;

the second neural network comprises eight input neurons, three intermediate interior position neurons, and four interior output neurons; and

the third neural network comprises eight input neurons, three intermediate exterior position neurons, and four exterior output neurons.

14. A method for determining a location of a key fob for use in a vehicle access system, the method comprising:

receiving a plurality of signals, each signal representing a strength of a wireless signal transmitted between the key fob and one of a plurality of antennas located on a vehicle;

determining one of a vehicle internal position and a vehicle external position of the key fob based on the wireless signal strengths, wherein determining one of a vehicle internal position and a vehicle external position comprises a first neural network calculating a plurality of intermediate internal/external position neurons having learned weights and activation functions associated therewith, and calculating an internal/external output neuron for use in indicating one of the vehicle internal position and the vehicle external position of the key fob;

determining one of a plurality of vehicle interior positions of the key fob based on the wireless signal strengths, wherein determining one of a plurality of vehicle interior positions comprises a second neural network calculating a plurality of intermediate interior position neurons having learned weights and activation functions associated therewith, and calculating a plurality of interior position output neurons for use in indicating one of a plurality of vehicle interior positions of the key fob; and

determining one of a plurality of vehicle exterior positions of the key fob based on the wireless signal strengths, wherein determining one of a plurality of vehicle exterior positions of the key fob comprises a third neural network calculating a plurality of intermediate exterior position neurons having learned weights and activation functions associated therewith, and calculating a plurality of exterior position output neurons for use in indicating one of a plurality of vehicle exterior positions of the key fob;

wherein the first, second and third neural networks have a cascade topology.

15. The method of claim 14 further comprising receiving a key detection trigger for use in initiating a determination of a key fob location.

16. The method of claim 14 further comprising mounting a plurality of antennas at a plurality of locations on the vehicle.

17. The method of claim 14 further comprising providing a key fob, the key fob comprising an antenna for enabling communication between the key fob and the plurality of antennas located on the vehicle.

18. The method of claim 14 further comprising storing, in a memory on-board the vehicle, neural network codings representing the learned weights and activation functions associated with the neurons of the neural networks.

19. The method of claim 14 further comprising learning, by each of the neural networks, the weights and activation functions associated with the neurons of the neural network.

20. The method of claim 14 wherein

the first neural network comprises eight input neurons, five intermediate internal/external location neurons, and one internal/external output neuron;

the second neural network comprises eight input neurons, three intermediate interior position neurons, and four interior output neurons; and

the third neural network comprises eight input neurons, three intermediate exterior position neurons, and four exterior output neurons.