Determining a location of motion detected from wireless signals based on prior probability

• US 10,506,384 B1
• Filed: 12/03/2018
• Issued: 12/10/2019
• Est. Priority Date: 12/03/2018
• Status: Active Grant

• Current Assignee: Cognitive Systems Corp.
• Original Assignee: Cognitive Systems Corp.
• Inventors: Omer, Mohammad, Devison, Stephen Arnold
• Primary Examiner(s): Ajayi, Joel
• Application Number:
  US16/207,649
• Time in Patent Office: 372 Days
• Field of Search: 4554561
• CPC Class Codes: G01S 13/003 Bistatic radar systems; Multistatic radar systems
• CPC Class Codes: G01S 7/006 using shared front-end circuitry, e.g. antennas G01S13/765, G01S13/825 take precedence
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/33 for indoor environments, e.g. buildings
• CPC Class Codes: H04W 4/80 Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication

Abstract

In a general aspect, a method for determining a location of motion detected by wireless communication devices in a wireless communication network includes obtaining motion data associated with a first time frame. The method also includes identifying a first wireless link, of a plurality of wireless links, based on a magnitude of a motion indicator value associated with the first wireless link relative to the other motion indicator values in a set of motion indicator values. The method additionally includes generating a first probability vector based on a predetermined map and the first wireless link and obtaining a second probability vector generated from motion data associated with a prior time frame. The method further includes determining, by operation of a data processing apparatus, a location of motion detected from wireless signals exchanged during the first time frame.

Claims

1. A method comprising:

obtaining motion data associated with a first time frame, the motion data comprising a set of motion indicator values indicating motion detected from wireless signals exchanged during the first time frame on a plurality of wireless links in a wireless communication network, each of the wireless links defined between a respective pair of wireless communication devices in the wireless communication network, each of the motion indicator values associated with a respective wireless link;

identifying a first wireless link, of the plurality of wireless links, based on a magnitude of a motion indicator value associated with the first wireless link relative to the other motion indicator values in the set of motion indicator values;

generating a first probability vector based on a predetermined map and the first wireless link,

wherein the first probability vector comprises first values assigned to the respective wireless communication devices, the first values representing first probabilities of motion at the respective wireless communication devices during the first time frame, and

wherein the predetermined map comprises a first map value and a second map value, the first map value assigned to a transmitting wireless communication device of the first wireless link, the second map value assigned to a receiving wireless communication device of the first wireless link;

obtaining a second probability vector generated from motion data associated with a prior time frame, the second probability vector comprising second values assigned to the respective wireless communication devices, the second values representing prior probabilities of motion at the respective wireless communication devices during the prior time frame;

generating a third probability vector by multiplying the second values from the second probability vector with the first values from the first probability vector, the third probability vector comprising third values assigned to the respective wireless communication devices, the third values representing current probabilities of motion at the respective wireless communication devices during the first time frame;

identifying a first wireless communication device associated with the highest of the third values; and

identifying, by operation of a data processing apparatus, a location associated with the first wireless communication device as a location of the motion detected from the wireless signals exchanged during the first time frame.

2. The method of claim 1, comprising:

repeating the operations, over multiple iterations for respective time frames, of obtaining motion data, identifying the first wireless link, generating the first probability vector, obtaining the second probability vector, generating the third probability vector, identifying the wireless communication device, and identifying the location; and

wherein the third probability vector of a previous iteration serves as the second probability vector of a present iteration, thereby allowing the third probability vector to be recursively updated.

3. The method of claim 1, wherein the plurality of wireless links comprises sets of wireless links that allow bi-directional communication between a respective pair of wireless communication devices, each set of wireless links having at least one wireless link per direction in the bi-directional communication.

4. The method of claim 1, wherein the magnitude of the motion indicator value associated with the first wireless link is a highest motion indicator value in the set of motion indicator values.

5. The method of claim 1, wherein the first map value corresponds to a highest first value of the first probability vector and the second map value correspond to a second-highest first value of the first probability vector.

6. The method of claim 1, wherein the predetermined map comprises a third map value assigned to one or more wireless communication devices not associated with the first wireless link.

7. The method of claim 1,

wherein identifying a first wireless link comprises identifying a first subset of the plurality of wireless links based on magnitudes of motion indicator values associated with the respective wireless links;

and

wherein generating a first probability vector comprises generating a first probability vector for each of the first subset of wireless links based on the predetermined map and each respective wireless link in the first subset.

8. The method of claim 7,

wherein the first subset of wireless links comprises the first wireless link and a second wireless link;

wherein the magnitude of the motion indicator associated with the first wireless link is a highest motion indicator value; and

wherein the magnitude of the motion indicator associated with the second wireless link is a second-highest motion indicator value.

9. The method of claim 7, comprising:

wherein generating a third probability vector comprises multiplying the second values from the second probability vector with the first values from each respective first probability vector, the third probability vector comprising third values assigned to the respective wireless communication devices, the third values representing current probabilities of motion at the respective wireless communication devices during the first time frame.

10. A motion detection system comprising:

a plurality of wireless communication devices configured to exchange wireless signals on a plurality of wireless links, each of the wireless links defined between a respective pair of the wireless communication devices; and

a data processing apparatus configured to perform operations comprising;

obtaining motion data associated with a first time frame, the motion data comprising a set of motion indicator values indicating motion detected from wireless signals exchanged during the first time frame on the plurality of wireless links, each of the motion indicator values associated with a respective wireless link;

identifying a first wireless link, of the plurality of wireless links, based on a magnitude of a motion indicator value associated with the first wireless link relative to the other motion indicator values in the set of motion indicator values;

generating a first probability vector based on a predetermined map and the first wireless link,

wherein the first probability vector comprises first values assigned to the respective wireless communication devices, the first values representing first probabilities of motion at the respective wireless communication devices during the first time frame, and

wherein the predetermined map comprises a first map value and a second map value, the first map value assigned to a transmitting wireless communication device of the first wireless link, the second map value assigned to a receiving wireless communication device of the first wireless link;

obtaining a second probability vector generated from motion data associated with a prior time frame, the second probability vector comprising second values assigned to the respective wireless communication devices, the second values representing prior probabilities of motion at the respective wireless communication devices during the prior time frame;

generating a third probability vector by multiplying the second values from the second probability vector with the first values from the first probability vector, the third probability vector comprising third values assigned to the respective wireless communication devices, the third values representing current probabilities of motion at the respective wireless communication devices during the first time frame;

identifying a first wireless communication device associated with the highest of the third values; and

identifying, by operation of a data processing apparatus, a location associated with the first wireless communication device as a location of the motion detected from the wireless signals exchanged during the first time frame.

11. The motion detection system of claim 10, wherein the operations comprise:

repeating the operations, over multiple iterations for respective time frames, of obtaining motion data, identifying the first wireless link, generating the first probability vector, obtaining the second probability vector, generating the third probability vector, identifying the first wireless communication device, and identifying the location; and

wherein the third probability vector of a previous iteration serves as the second probability vector of a present iteration, thereby allowing the third probability vector to be recursively updated.

12. The motion detection system of claim 10, wherein the plurality of wireless links comprises sets of wireless links that allow bi-directional communication between a respective pair of wireless communication devices, each set of wireless links having at least one wireless link per direction in the bi-directional communication.

13. The motion detection system of claim 10, wherein the magnitude of the motion indicator value associated with the first wireless link is a highest motion indicator value in the set of motion indicator values.

14. The motion detection system of claim 10, wherein a wireless communication device comprises the data processing apparatus.

15. The motion detection system of claim 10,

wherein identifying a first wireless link comprises identifying a first subset of the plurality of wireless links based on magnitudes of motion indicator values associated with the respective wireless links;

and

wherein generating a first probability vector comprises generating a first probability vector for each of the first subset of wireless links based on the predetermined map and each respective wireless link in the first subset.

16. The motion detection system of claim 15, wherein the operations comprise:

wherein generating a third probability vector comprises multiplying the second values from the second probability vector with the first values from each first probability vector, the third probability vector comprising third values assigned to the respective wireless communication devices, the third values representing current probabilities of motion at the respective wireless communication devices during the first time frame.

17. A non-transitory computer-readable medium containing program instructions for causing a data processing apparatus to perform operations comprising:

obtaining motion data associated with a first time frame, the motion data comprising a set of motion indicator values indicating motion detected from wireless signals exchanged during the first time frame on a plurality of wireless links in a wireless communication network, each of the wireless links defined between a respective pair of wireless communication devices in the wireless communication network, each of the motion indicator values associated with a respective wireless link;

identifying a first wireless link, of the plurality of wireless links, based on a magnitude of a motion indicator value associated with the first wireless link relative to the other motion indicator values in the set of motion indicator values;

generating a first probability vector based on a predetermined map and the first wireless link,

wherein the first probability vector comprises first values assigned to the respective wireless communication devices, the first values representing first probabilities of motion at the respective wireless communication devices during the first time frame, and

wherein the predetermined map comprises a first map value and a second map value, the first map value assigned to a transmitting wireless communication device of the first wireless link, the second map value assigned to a receiving wireless communication device of the first wireless link;

obtaining a second probability vector generated from motion data associated with a prior time frame, the second probability vector comprising second values assigned to the respective wireless communication devices, the second values representing prior probabilities of motion at the respective wireless communication devices during the prior time frame;

generating a third probability vector by multiplying the second values from the second probability vector with the first values from the first probability vector, the third probability vector comprising third values assigned to the respective wireless communication devices, the third values representing current probabilities of motion at the respective wireless communication devices during the first time frame;

identifying a first wireless communication device associated with the highest of the third values; and

identifying, by operation of a data processing apparatus, a location associated with the first wireless communication device as a location of the motion detected from the wireless signals exchanged during the first time frame.

18. The non-transitory computer-readable medium of claim 17, wherein the operations comprise:

repeating the operations, over multiple iterations for respective time frames, of obtaining motion data, identifying the first wireless link, generating the first probability vector, obtaining the second probability vector, generating the third probability vector, identifying the first wireless communication device, and identifying the location; and

wherein the third probability vector of a previous iteration serves as the second probability vector of a present iteration, thereby allowing the third probability vector to be recursively updated.

19. The non-transitory computer-readable medium of claim 17, wherein the plurality of wireless links comprises sets of wireless links that allow bi-directional communication between a respective pair of wireless communication devices, each set of wireless links having at least one wireless link per direction in the bi-directional communication.

20. The non-transitory computer-readable medium of claim 17, wherein the magnitude of the motion indicator value associated with the first wireless link is a highest motion indicator value in the set of motion indicator values.

21. The non-transitory computer-readable medium of claim 17, wherein a wireless communication device comprises the data processing apparatus.

22. The non-transitory computer-readable medium of claim 17, wherein the first map value corresponds to a highest first value of the first probability vector and the second map value correspond to a second-highest first value of the first probability vector.

23. The non-transitory computer-readable medium of claim 17,

wherein identifying a first wireless link comprises identifying a first subset of wireless links based on magnitudes of motion indicator values associated with the respective wireless links;

and

wherein generating a first probability vector comprises generating a first probability vector for each of the first subset of wireless links based on the predetermined map and each respective wireless link in the first subset.

24. The non-transitory computer-readable medium of claim 23, wherein the operations comprise:

wherein generating a third probability vector comprises multiplying the second values from the second probability vector with the first values from each respective first probability vector, the third probability vector comprising third values assigned to the respective wireless communication devices, the third values representing current probabilities of motion at the respective wireless communication devices during the first time frame.