Cross-correlation system and method for spatial detection using a network of rf repeaters

A cross-correlation method, comprising:

• inputting, by control circuitry, training sensor data from a plurality of sensors into a deep neural network;
• training, by the control circuitry, the deep neural network for:
• cross-correlating the training sensor data from the plurality of sensors at an input sampling stage,
• determining a relationship between the cross-correlated sensor data and an identity of each of one or more users represented in the cross-correlated sensor data, and
• tracking subsequent movements of the one or more users based on the cross-correlated sensor data;
• obtaining, by the control circuitry, first sensor data of a first user from a communication system and second sensor data from a first portable device carried by the first user;
• obtaining, by the control circuitry, cross-correlated information of the first user by utilizing the trained deep neural network;
• and
• recognizing, by the control circuitry, a first gesture specific to the first user based on the cross-correlated information of the first user, wherein the first gesture corresponds to a single hand gesture.

A non-transitory computer-readable medium having stored thereon, computer implemented instructions, which when executed by a computer in a communication apparatus, causes the communication apparatus to execute operations, the operations comprising:

• inputting training sensor data from a plurality of sensors into a deep neural network;
• training the deep neural network for:
• cross-correlating the training sensor data from the plurality of sensors at an input sampling stage,
• determining a relationship between the cross-correlated sensor data and an identity of each of one or more users represented in the cross-correlated sensor data, and
• tracking subsequent movements of the one or more users based on the cross-correlated sensor data;
• obtaining first sensor data of a first user from a communication system and second sensor data from a first portable device carried by the first user;
• obtaining cross-correlated information of the first user by utilizing the trained deep neural network;
• and
• recognizing a first gesture specific to the first user based on the cross-correlated information of the first user, wherein the first gesture corresponds to a single hand gesture.