Abstract: A method including accessing a network graph including: a set of transceiver nodes representing a set of transceivers operating in a mesh network of transceivers; a set of transmitter nodes representing a set of transmitters communicating with the mesh network of transceivers; and a set of edges, each connecting a pair of nodes in the set of nodes. The method also includes: identifying a subgraph of the network graph associated with a node in the set of nodes, the node representing a transceiver; accessing a network state of the subgraph comprising a set of edge values for each edge in the subgraph; calculating a probability of failure of the transceiver based on the network state of the subgraph; and in response to detecting the probability of failure of the transceiver exceeding a threshold likelihood, triggering a corrective action at the transceiver.

Abstract: A method includes: receiving a ranging signal from the transmitter including a set of multiplexed sub-signals, each multiplexed sub-signal characterized by a frequency in a set of frequencies; calculating a sample-based time-of-arrival estimate based on the series of time-domain samples of the ranging signal; calculating a sample-based uncertainty of the sample-based time-of-arrival; for each sub-signal pair in a subset of multiplexed sub-signals of the set of multiplexed sub-signals, extracting a phase difference of the sub-signal pair; calculating a phase-based time-of-arrival estimate based on the phase difference of each sub-signal pair in the subset of multiplexed sub-signals; calculating a phase-based uncertainty of the phase-based time-of-arrival estimate; and calculating a hybrid time-of-arrival estimate as a weighted combination of the sample-based time-of-arrival estimate, the phase-based time-of-arrival estimate, based on the sample-based uncertainty and the phase-based uncertainty.

Abstract: A method includes: receiving a ranging signal from the transmitter comprising a set of multiplexed sub-signals, each multiplexed sub-signal characterized by a frequency in a set of frequencies; calculating a time-based time-of-arrival estimate based on the series of time-domain samples of the ranging signal; calculating a time-based uncertainty of the time-based time-of-arrival; for each sub-signal pair in a subset of multiplexed sub-signals of the set of multiplexed sub-signals, extracting a phase difference of the sub-signal pair; calculating a phase-based time-of-arrival estimate based on the phase difference of each sub-signal pair in the subset of multiplexed sub-signals; calculating a phase-based uncertainty of the phase-based time-of-arrival estimate; and calculating a hybrid time-of-arrival estimate as a weighted combination of the time-based time-of-arrival estimate, the phase-based time-of-arrival estimate, based on the time-based uncertainty and the phase-based uncertainty.

Abstract: In an example, the present invention provides a method for processing rf backscattered signals. The method includes generating a plurality of rf signals numbered from 1 to N, where N is an integer greater than 1, from, respectively, a plurality of rf sources numbered from 1 to N. In an example, each of the rf sources is an antenna. In an example, the method includes transferring the plurality of rf signals to a predetermined region of space. The method includes receiving a stream of back scattered signals derived from each of the rf signals numbered from 1 to N from the predetermined space, each stream of back scattered signals being one of a plurality of backscattered signals numbered 1 to N corresponding, respectively, to the plurality of rf sources numbered from 1 to N.

Abstract: A method including accessing a network graph including: a set of transceiver nodes representing a set of transceivers operating in a mesh network of transceivers; a set of transmitter nodes representing a set of transmitters communicating with the mesh network of transceivers; and a set of edges, each connecting a pair of nodes in the set of nodes. The method also includes: identifying a subgraph of the network graph associated with a node in the set of nodes, the node representing a transceiver; accessing a network state of the subgraph comprising a set of edge values for each edge in the subgraph; calculating a probability of failure of the transceiver based on the network state of the subgraph; and in response to detecting the probability of failure of the transceiver exceeding a threshold likelihood, triggering a corrective action at the transceiver.

Abstract: A method includes: receiving a ranging signal from the transmitter comprising a set of multiplexed sub-signals, each multiplexed sub-signal characterized by a frequency in a set of frequencies; calculating a time-based time-of-arrival estimate based on the series of time-domain samples of the ranging signal; calculating a time-based uncertainty of the time-based time-of-arrival; for each sub-signal pair in a subset of multiplexed sub-signals of the set of multiplexed sub-signals, extracting a phase difference of the sub-signal pair; calculating a phase-based time-of-arrival estimate based on the phase difference of each sub-signal pair in the subset of multiplexed sub-signals; calculating a phase-based uncertainty of the phase-based time-of-arrival estimate; and calculating a hybrid time-of-arrival estimate as a weighted combination of the time-based time-of-arrival estimate, the phase-based time-of-arrival estimate, based on the time-based uncertainty and the phase-based uncertainty.

Abstract: A method includes: scheduling transmission of a first synchronization signal by a first node; and scheduling transmission of a second synchronization signal by a second node. The method also includes, after transmission of the first synchronization signal: receiving, from the first node, a first phase reference associated with the first synchronization signal; and receiving, from the second node, a first phase-of-arrival of the first synchronization signal at the second node. The method additionally includes, after transmission of the second synchronization signal: receiving, from the second node, a second phase reference associated with the second synchronization signal; and receiving, from the first node, a second phase-of-arrival of the second synchronization signal at the first node.

Abstract: In an example, the present invention provides a method for processing rf backscattered signals. The method includes generating a plurality of rf signals numbered from 1 to N, where N is an integer greater than 1, from, respectively, a plurality of rf sources numbered from 1 to N. In an example, each of the rf sources is an antenna. In an example, the method includes transferring the plurality of rf signals to a predetermined region of space. The method includes receiving a stream of back scattered signals derived from each of the the rf signals numbered from 1 to N from the predetermined space, each stream of back scattered signals being one of a plurality of backscattered signals numbered 1 to N corresponding, respectively, to the plurality of rf sources numbered from 1 to N.

Abstract: A method includes: scheduling transmission of a first synchronization signal by a first node; and scheduling transmission of a second synchronization signal by a second node. The method also includes, after transmission of the first synchronization signal: receiving, from the first node, a first phase reference associated with the first synchronization signal; and receiving, from the second node, a first phase-of-arrival of the first synchronization signal at the second node. The method additionally includes, after transmission of the second synchronization signal: receiving, from the second node, a second phase reference associated with the second synchronization signal; and receiving, from the first node, a second phase-of-arrival of the second synchronization signal at the first node.

Abstract: A method includes: receiving a ranging signal from the transmitter comprising a set of multiplexed sub-signals, each multiplexed sub-signal characterized by a frequency in a set of frequencies; calculating a time-based time-of-arrival estimate based on the series of time-domain samples of the ranging signal; calculating a time-based uncertainty of the time-based time-of-arrival; for each sub-signal pair in a subset of multiplexed sub-signals of the set of multiplexed sub-signals, extracting a phase difference of the sub-signal pair; calculating a phase-based time-of-arrival estimate based on the phase difference of each sub-signal pair in the subset of multiplexed sub-signals; calculating a phase-based uncertainty of the phase-based time-of-arrival estimate; and calculating a hybrid time-of-arrival estimate as a weighted combination of the time-based time-of-arrival estimate, the phase-based time-of-arrival estimate, based on the time-based uncertainty and the phase-based uncertainty.

Abstract: A method includes: receiving a ranging signal from the transmitter comprising a set of multiplexed sub-signals, each multiplexed sub-signal characterized by a frequency in a set of frequencies; calculating a time-based time-of-arrival estimate based on the series of time-domain samples of the ranging signal; calculating a time-based uncertainty of the time-based time-of-arrival; for each sub-signal pair in a subset of multiplexed sub-signals of the set of multiplexed sub-signals, extracting a phase difference of the sub-signal pair; calculating a phase-based time-of-arrival estimate based on the phase difference of each sub-signal pair in the subset of multiplexed sub-signals; calculating a phase-based uncertainty of the phase-based time-of-arrival estimate; and calculating a hybrid time-of-arrival estimate as a weighted combination of the time-based time-of-arrival estimate, the phase-based time-of-arrival estimate, based on the time-based uncertainty and the phase-based uncertainty.

Abstract: A method includes: receiving a ranging signal from the transmitter comprising a set of multiplexed sub-signals, each multiplexed sub-signal characterized by a frequency in a set of frequencies; calculating a time-based time-of-arrival estimate based on the series of time-domain samples of the ranging signal; calculating a time-based uncertainty of the time-based time-of-arrival; for each sub-signal pair in a subset of multiplexed sub-signals of the set of multiplexed sub-signals, extracting a phase difference of the sub-signal pair; calculating a phase-based time-of-arrival estimate based on the phase difference of each sub-signal pair in the subset of multiplexed sub-signals; calculating a phase-based uncertainty of the phase-based time-of-arrival estimate; and calculating a hybrid time-of-arrival estimate as a weighted combination of the time-based time-of-arrival estimate, the phase-based time-of-arrival estimate, based on the time-based uncertainty and the phase-based uncertainty.

Abstract: In an example, the present invention provides a method for processing rf backscattered signals. The method includes generating a plurality of rf signals numbered from 1 to N, where N is an integer greater than 1, from, respectively, a plurality of rf sources numbered from 1 to N. In an example, each of the rf sources is an antenna. In an example, the method includes transferring the plurality of rf signals to a predetermined region of space. The method includes receiving a stream of back scattered signals derived from each of the the rf signals numbered from 1 to N from the predetermined space, each stream of back scattered signals being one of a plurality of backscattered signals numbered 1 to N corresponding, respectively, to the plurality of rf sources numbered from 1 to N.

Abstract: A method for assisting corneal severity identification, the method comprising obtaining a corneal configuration data set of a cornea to be examined by a tomography such as an optical coherence tomography; visualizing the corneal configuration data set of the cornea to be examined along with a number of pre-existing corneal configuration data sets of disorder corneas, disorder-suspect corneas and normal corneas obtained by the tomography using t-distributed Stochastic Neighbor Embedding in a two or three dimensional map, and judging corneal severity from the map.

Abstract: A method for assisting corneal severity identification, the method comprising obtaining a corneal configuration data set of a cornea to be examined by a tomography such as an optical coherence tomography; visualizing the corneal configuration data set of the cornea to be examined along with a number of pre-existing corneal configuration data sets of disorder corneas, disorder-suspect corneas and normal corneas obtained by the tomography using t-distributed Stochastic Neighbor Embedding in a two or three dimensional map, and judging corneal severity from the map.