Gesture recognition using multiple antenna

1. A device configured to identify a micro-gesture associated with a target object, the device comprising:

at least two antennas to transmit a plurality of outgoing radio frequency (RF) signals, each antenna configured to:

transmit a respective outgoing radio frequency (RF) signal of the plurality of outgoing RF signals; and

receive an incoming RF signal generated by at least one transmitted outgoing RF signal of the plurality of outgoing RF signals reflecting off the target object;

a digital signal processing component configured to:

process a first set of data originating from incoming RF signals to extract information about the target object, the information comprising a shape of the object corresponding to at least two points in time; and

a machine-learning component configured to:

receive the information extracted by the digital signal processing component; and

process the information to identify the micro-gesture.

2. The device as recited in claim 1 , wherein the digital signal processing component is further configured to transform digital samples of incoming RF signals into a 3-dimensional (3D) spatial profile of the target object.

3. The device as recited in claim 2 , wherein the machine-learning component is further configured to process the information using a Random Forrest algorithm.

4. The device as recited in claim 1 , wherein the digital signal processing component is further configured to determine transmission parameters for each respective outgoing RF signal effective to transmit a specific diversity scheme.

5. The device as recited in claim 4 , wherein the specific diversity scheme comprises a beamforming scheme.

6. The device as recited in claim 1 , wherein the target object comprises a hand.

7. The device as recited in claim 1 further comprising an output logic component configured to:

receive multiple input notifications, each input notification indicating a respective instance of the micro-gesture that has been identified; and

filter the multiple input notifications into one output notification.

8. The device as recited in claim 1 further configured to:

receive at least one input configuration parameter; and

modify, based upon the at least one input configuration parameter, a transmission parameter of at least one respective outgoing radio frequency (RF) signal.

9. The device as recited m claim 1 , wherein the device comprises a System-on-Chip (SoC).

10. A method for identifying a micro-gesture performed by a hand, the method comprising:

transmitting a plurality of outgoing RF signals, each outgoing RF signal transmitted on a respective antenna of a plurality of antennas;

capturing, at least two incoming RF signals generated by at least two outgoing RF signals of the plurality of outgoing RF signals reflecting off the hand; and

processing the at least two captured incoming RF signals to identify the micro-gesture performed by the hand, the micro-gesture comprising a movement on a millimeter scale.

11. The method as recited in claim 10 , wherein the processing comprises:

extracting information from each respective RF signal of the at least two captured incoming RF signals; and

processing the information extracted from each respective RF signal to generate a 3-dimensional (3D) spatial profile of the hand.

12. The method as recited in claim 10 further comprising:

configuring the plurality of outgoing radio frequency (RF) signals based, at least in part, on an expected receive-side algorithm used to process the at least two incoming RF signals.

13. The method as recited in claim 10 , wherein the processing comprises: extracting information from each respective RF signal of the at least two captured incoming RF signals, the information comprising at least one of:

velocity information associated with the target object;

orientation information associated with the target object;

directional movement information associated with the target object;

shape information associated with the target object; or

size information associated with the target object.

14. The method as recited in claim 10 , the processing the at least two captured incoming RF signals to identify the micro-gesture further comprising:

identifying a portion of the hand as being stationary; and

identifying a portion of the hand as having movement.

15. The method as recited in claim 10 , the processing the at least two captured incoming RF signals further comprising:

extracting data from the at least two captured incoming RF signals to generate a first level of information that classifies a target object as the hand;

extracting, from the first level of information, a second level of information that identifies the micro-gesture from a plurality of hand-related micro-gestures.

16. A device for detecting a micro-gesture performed by a hand, the device comprising:

a gesture sensor component comprising:

at least two antenna, each respective antenna associated with a respective transceiver path;

at least one processor;

one or more computer-readable storage devices; and

one or more Application Programming Interfaces (APis) stored on the one or more computer-readable storage devices which, responsive to execution by the at least one processor, configure the gesture sensor component to detect the micro-gesture by causing the gesture sensor component to perform operations comprising:

transmitting a plurality of outgoing radio frequency (RF) signals, each outgoing radio frequency (RF) signal being transmitted on a respective antenna of the at least two antenna;

receiving at least two incoming RF signals originating from at least two outgoing RF signals of the plurality of outgoing RF signals reflecting off the hand; and

processing the at least two RF signals to detect the micro-gesture by processing data from at least two respective transceiver paths, the micro-gesture comprising a relative movement between a portion of the hand and another portion of the hand.

17. The device as recited in claim 16 , wherein at least one API of the one or more APIs comprises one of:

an API to configure transmission parameters associated with the plurality of outgoing RF signals;

an API to configure a digital signal processing component that performs, at least in part, the processing the at least two RF signals; or

an API to configure a machine-learning component that performs, at least in part, the processing the at least two RF signals.

18. The device as recited in claim 16 , wherein at least one API of the one or more APIs is configured to enable registration for an event notification when the micro-gesture is detected.

19. The device as recited in claim 16 , wherein processing the at least two RF signals to detect the micro-gesture further comprises utilizing a pipeline to extract information from the at least two RF signals at different stages of the pipeline, and detect the micro-gesture using the information extracted from the at least two RF signals.

20. The device as recited in claim 16 , wherein the processing the at least two RF signals further comprises processing the at least two RF signals using a short-range object detection mode.