CN113474671A - System and method for precise radio frequency location using time difference of arrival for time scanning - Google Patents

Abstract

Systems and devices for determining a location of a wireless node in a network architecture are disclosed. In one example, an asynchronous system includes first and second wireless nodes, each having a wireless device with one or more processing units and RF circuitry to transmit and receive communications in a wireless network architecture. The system also includes a third wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first and second wireless nodes in the wireless network architecture. The one or more processing units of the first wireless node are configured to transmit or execute instructions to determine a location coordinate hypothesis and a transmit time hypothesis for the third wireless node to transmit communications to, determine an error function associated with the transmit time hypothesis for each receive path j of the first and second wireless nodes at the location coordinate hypothesis, and determine a probability function for the error function for each receive path j of the first and second wireless nodes using statistical characteristics of path measurement accuracy.

Description

System and method for precise radio frequency location using time difference of arrival for time scanning

RELATED APPLICATIONS

This application claims benefit of U.S. application No. 16/283,780, filed 24.2.2019, the entire disclosure of which is incorporated herein by reference.

Technical Field

Embodiments of the present invention relate to a system and method for precise radio frequency location using time differences of arrival information.

Background

Wireless sensor networks have been studied for many years in the consumer electronics and computer industries. In a typical wireless sensor network, one or more sensors are implemented in conjunction with a radio to enable wireless collection of data for one or more sensor nodes deployed within the network. Each sensor node may include one or more sensors and will include a radio and a power supply for powering the operation of the sensor node. Location detection of nodes in indoor wireless networks is useful and important in many applications.

To determine the position of a wireless equipped object in three-dimensional space, positioning based on time difference of arrival (TDoA) techniques for multipoint positioning is performed using radio frequency measurements. RF-based positioning may be performed in a variety of ways. An exemplary embodiment includes a hub and a plurality of sensor nodes. Note that a hub may be replaced with a node, or indeed, one or more nodes may be replaced with a hub. The distances between all individual pairs are estimated via RF communication using radio frequency techniques. In TDoA, a node transmits a signal. A plurality of other nodes receive the signals and calculate the time difference between the reception of each receiving node. TDoA requires synchronization of the receiver to accurately measure the difference in reception time. This may be done by operating all receivers on a shared clock and comparing the absolute timestamps. In systems where a shared clock is not available, the receivers must otherwise be synchronized.

Disclosure of Invention

For embodiments of the present invention, systems and apparatus for determining the location of wireless sensor nodes in a network architecture are disclosed herein. In one example, an asynchronous system includes a first wireless node and a second wireless node, each having a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in a wireless network architecture. The system also includes a third wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first wireless node and the second wireless node in the wireless network architecture. The one or more processing units of the first wireless node are configured to transmit or execute instructions to determine a location coordinate hypothesis and a transmit time hypothesis for the third wireless node to transmit communications to, determine an error function associated with the transmit time hypothesis for each receive path j of the first and second wireless nodes at the location coordinate hypothesis, and determine a probability function for the error function for each receive path j of the first and second wireless nodes using statistical characteristics of path measurement accuracy.

In one example, a computer-implemented method for locating a wireless arbitrary device in a wireless network architecture, comprising: initializing a wireless network having a plurality of wireless anchor nodes i; determining a three-dimensional position coordinate hypothesis for a wireless arbitrary device having an unknown position; meterCalculating a distance d from each wireless anchor node i to a position coordinate hypothesis_i(ii) a And obtaining channel state information from each wireless anchor node i and a signal arrival timestamp T from each wireless anchor node i_i。

In another example, a computer-implemented method for locating a wireless node in a wireless network architecture, comprising: initializing a wireless network architecture having a plurality of wireless anchor nodes; determining a location coordinate hypothesis for a wireless node having an unknown location using at least one of the anchor node and the cloud-based entity; calculating a distance from each anchor node i to a position coordinate hypothesis; and obtaining channel state information and a signal arrival time stamp T from each anchor node i_i。

Other features and advantages of embodiments of the present invention will become apparent from the accompanying drawings and the following detailed description.

Drawings

Embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:

fig. 1A illustrates an example system of a wireless node according to one embodiment.

Fig. 1B illustrates an example system of a wireless node having multiple hubs for communication, according to one embodiment.

Fig. 2A illustrates a system for locating a node using time difference of arrival, according to one embodiment.

FIG. 2B illustrates an asynchronous system for time-of-flight estimation according to another embodiment.

Fig. 2C shows, in one embodiment, a two-way ToF measurement system 1000.

Fig. 3 shows a timing diagram of the communication of the system 200 according to one embodiment.

Fig. 4 illustrates a system for locating a node using time difference of arrival in accordance with an alternative embodiment.

Fig. 5 illustrates a timing diagram of communications of system 400 according to one embodiment.

FIG. 6 illustrates a method for determining a location estimate for a node using a time difference of arrival technique, according to one embodiment.

Fig. 7A illustrates an exemplary embodiment of a hub implemented as a cover 1500 for an electrical outlet, according to one embodiment.

Fig. 7B illustrates an exemplary embodiment of an exploded view of a block diagram of a hub implemented as a cover for an electrical outlet, according to one embodiment.

Fig. 8A illustrates an exemplary embodiment of a hub implemented as a card deployed in a computer system, appliance, or communications hub, according to one embodiment.

Fig. 8B illustrates an exemplary embodiment of a block diagram of a hub 964 implemented as a card deployed in a computer system, appliance, or communications hub, according to one embodiment.

Fig. 8C illustrates an exemplary embodiment of a hub implemented within an appliance (e.g., an intelligent washing machine, an intelligent refrigerator, an intelligent thermostat, other intelligent appliances, etc.) according to one embodiment.

Fig. 8D illustrates an exemplary embodiment of an exploded view of a block diagram of a hub 1684 implemented within an appliance (e.g., an intelligent washing machine, an intelligent refrigerator, an intelligent thermostat, other intelligent appliances, etc.), according to one embodiment.

FIG. 9 shows a block diagram of a sensor node according to an embodiment.

Fig. 10 shows a block diagram of a system or appliance 1800 having a hub according to one embodiment.

FIG. 11 illustrates a time scanning method for determining a location estimate for a node using a time difference of arrival technique, according to one embodiment.

Fig. 12 illustrates a wireless architecture that uses a time difference of arrival technique to implement a time scanning method for determining a location estimate for a node, according to one embodiment.

Fig. 13 illustrates a beamforming method in the frequency domain for determining a location estimate of a node according to one embodiment.

Fig. 14 illustrates a wireless architecture for implementing a beamforming method for determining a location estimate of a node, according to one embodiment.

Fig. 15 illustrates a beamforming method in the time domain for determining a location estimate of a node according to one embodiment.

Detailed Description

Systems and methods for accurate radio frequency location using time differences of arrival information are disclosed. In one example, an asynchronous system for locating a node in a wireless network architecture includes first, second, and third wireless nodes, each having a wireless device with one or more processing units and RF circuitry for sending and receiving communications in the wireless network architecture. The system also includes a fourth wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first, second, and third wireless nodes in the wireless network architecture. The first wireless node sends communications to the second, third and fourth wireless nodes, receives communications with acknowledgement packets from the fourth wireless node, and determines time differences in arrival information between the first wireless node and the second wireless node and between the first wireless node and the third wireless node.

In one example, the one or more processing units of the first wireless node are configured to execute instructions for a multipoint positioning algorithm to determine the location of the fourth wireless node using time differences of arrival information.

In various applications of wireless sensor networks, it may be desirable to determine the location of sensor nodes within the network. For example, such information may be used to estimate the relative positions of sensors such as security cameras, motion sensors, temperature sensors, and other such sensors as would be apparent to one skilled in the art. This information can then be used to generate enhanced information such as temperature maps, motion paths, and multi-view image capture. Accordingly, positioning systems and methods are desired that enable accurate, low power, and context aware positioning of nodes in wireless networks, particularly indoor environments. For this purpose, it is also assumed that the indoor environment includes a near-indoor environment such as in an area around buildings and other structures, where similar problems may exist (e.g., the presence of nearby walls, etc.).

Wireless sensor networks are described for use in indoor environments including homes, apartments, offices, and commercial buildings, as well as nearby outside venues such as parking lots, sidewalks, and gardens. Wireless sensor networks may also be used in any type of building, structure, enclosure, vehicle, boat, etc. where there is a power source. The sensor system provides good battery life for the sensor nodes while maintaining a long communication distance.

Embodiments of the present invention provide systems, devices and methods for position detection in an indoor environment. U.S. patent application No. 14/830,668 filed on 8/19/2015, which is incorporated by reference, discloses RF-based positioning technology. In particular, the system, apparatus and method implement positioning in a wireless sensor network, using mainly a tree-like network structure to communicate with periodic grid-based features for path length estimation when positioning is needed. The wireless sensor network has improved positioning accuracy while providing good indoor communication quality by using high frequency positioning and low frequency communication.

Tree-like wireless sensor networks are attractive for many household appliances due to their reduced power consumption requirements associated with radio signal reception functionality. Exemplary tree network architectures have been described in U.S. patent application No. 14/607,045 filed on day 1/29 of 2015, U.S. patent application No. 14/607,047 filed on day 1/29 of 2015, U.S. patent application No. 14/607,048 filed on day 1/29 of 2015, and U.S. patent application No. 14/607,050 filed on day 1/29 of 2015, which are incorporated by reference herein in their entirety.

Another common type of wireless network is a mesh network. In this network, communication occurs between one or more neighbors, and information may then be passed along the network using a multi-hop (multi-hop) architecture. This can be used to reduce transmission power requirements as information is sent over shorter distances. On the other hand, since the receiving radio must be frequently turned on to enable the multi-hop communication scheme, the receiving radio power demand may increase.

Fig. 1A illustrates an example system of a wireless node according to one embodiment. The example system 100 includes a wireless node 110 and 116. The nodes communicate bi-directionally using communications 120 (e.g., node identification information, sensor data, node status information, synchronization information, positioning information, other such information for wireless sensor networks, time of flight (TOF) communications, etc.). Based on using time-of-flight measurements, the path length between individual node pairs can be estimated. For example, a single time-of-flight measurement between node 110 and node 111 may be achieved by sending a signal from node 110 to node 111 at a known time. Node 111 receives the signal, records the timestamp of the signal of received communication 120, and may then, for example, send a return signal back to a with the timestamp of the sent return signal. The node 110 receives the signal and records the timestamp of the reception. Based on these two transmitted and received timestamps, an average time of flight between node 110 and node 111 may be estimated. This process may be repeated multiple times at multiple frequencies to improve accuracy and eliminate or reduce degradation due to low channel quality at a particular frequency. A set of path lengths may be estimated by repeating the process for each node pair. For example, in FIG. 1, the path length is TOF 150-160. Then, by using the geometric model, the relative position of the individual nodes can be estimated based on a triangulation-like procedure.

The triangulation process is not feasible in tree networks because only the path length between any node and the hub can be measured. This limits the positioning capabilities of the tree network. In order to preserve the energy benefits of a tree network while allowing positioning, in one embodiment of the invention, the tree network for communication is combined with a mesh network function for positioning. After the positioning is done using the mesh network function, the network switches back to tree communication and only the time of flight between the node and the hub is measured periodically. Assuming these times of flight remain relatively constant, then assuming the nodes have not moved and no energy is wasted, the network attempts to re-run the grid-based positioning. On the other hand, when a change in path length in the tree network is detected, the network switches to a mesh-based system and re-triangulates to determine the location of each node in the network.

In another example, a multipoint positioning algorithm is performed using time differences of arrival information of a plurality of nodes to determine a location of a wireless node having an unknown location.

Fig. 1B illustrates an example system of a wireless node having multiple hubs for communication, according to one embodiment. System 700 includes a central hub 710 with wireless control device 711, a hub 720 with wireless control device 721, a hub 782 with wireless control device 783, and additional hubs including hub n with wireless control device n. Additional hubs, not shown, may communicate with central hub 710, other hubs, or may be additional central hubs. Each hub communicates bi-directionally with other hubs and with one or more sensor nodes. The hub is also designed to bi-directionally communicate with other devices (e.g., client devices, mobile devices, tablet devices, computing devices, smart appliances, smart TVs, etc.) including the device 780.

Sensor nodes 730, 740, 750, 760, 770, 788, 792, n, and n +1 (or terminal nodes) each include a wireless device 731, 741, 751, 761, 771, 789, 793, 758, and 753, respectively. A sensor node is an end node if it communicates only upstream with a higher level hub or node, but not downstream with another hub or node. Each wireless device includes RF circuitry with a transmitter and receiver (or transceiver) to enable bi-directional communication with a hub or other sensor node.

In one embodiment, central hub 710 communicates with hubs 720, 782, hub n, device 780, and nodes 760 and 770. These communications include communications 722, 724, 774, 772, 764, 762, 781, 784, 786, 714, and 712 in a wireless asymmetric network architecture. The central hub with wireless control device 711 is configured to send and receive communications to and from other hubs to control and monitor the wireless asymmetric network architecture, including assigning node groups and guaranteed time signals for each group.

Hub 720 communicates with central hub 710 and also communicates with sensor nodes 730, 740, and 750. Communication with the sensor nodes includes communications 732, 734, 742, 744, 752, and 754. For example, from the perspective of hub 720, communication 732 is received by the hub and communication 734 is sent to the sensor node. From the perspective of sensor node 730, communication 732 is sent to hub 720 and communication 734 is received from the hub.

In one embodiment, a central hub (or other hub) assigns nodes 760 and 770 to group 716, nodes 730, 740, and 750 to group 715, nodes 788 and 792 to group 717, and nodes n and n +1 to group n. In another example, groups 716 and 715 are combined into a single group.

By using the architecture shown in fig. 1, nodes that require long battery life minimize the energy consumed on communication, higher level nodes in the tree hierarchy may be implemented using available energy, or may alternatively use batteries that provide higher capacity or provide shorter battery life. To facilitate long battery life on battery-powered end nodes, communication may be established between these nodes and their superior peer nodes (hereinafter referred to as lowest level hubs) to generate minimal transmit and receive traffic between the lowest level hubs and the end nodes.

In one embodiment, a node spends most of its time (e.g., more than 90% of its time, more than 95% of its time, about 98% or more than 99% of its time) in a low-energy, non-communicating state. When a node wakes up and enters a communication state, the node is operable to transmit data to the lowest level hub. The data may include node identification information, sensor data, node status information, synchronization information, positioning information, and other such information for the wireless sensor network.

To determine the distance between two objects based on RF, ranging measurements are made (i.e., the distance between a pair of objects is estimated using RF communication). To this end, RF signals are transmitted from one device to another. Fig. 3-8C of U.S. patent application No. 15/173,531 show an embodiment of a time-of-flight measurement system.

Time-of-flight measurements are inherently sensitive to the timing of operations within the network, and therefore the clock of the device performing the measurement is important. In one embodiment, nodes at unknown locations may be located via TDoA without a shared clock. Additional transactions between known nodes are used to synchronize the receiving nodes. It should be noted that the location of a known node may be determined using positioning as described in U.S. patent application No. 15/173,531.

Fig. 2A illustrates a system for locating a node using time difference of arrival, according to one embodiment. System 200 is configured with a master node 210(M210), a node 240 at an unknown location (N240), and listening (sniff) nodes (e.g., S220, 230, etc.). Master node 210 first performs a two-way time of flight with RTT and fractional distance (as described in U.S. patent application No. 15/173, 531) for each of the listening nodes. For example, FIG. 2B illustrates an asynchronous system for time-of-flight estimation, according to one embodiment. Device 810 first sends RF signal 812 with data packets to device 820 at time T1. The packet arrives at device 820 at time T2, triggering the packet detection algorithm in device 820 to register the time. The device 820 then sends a signal 822 with the data packet back at time T3, the signal 822 arrives at the device 810 at time T4, and triggers the device 810 to register the time and process the waveform. It should be noted that unlike the case of a fully synchronized system, T1 and T4 are times recorded on device 810 and are therefore reference clocks thereto. T2 and T3 were recorded based on the time reference of device 820. A rough time estimate is

2xToF＝(T4-T1)–(T3-T2)

Since T4 and T1 are sampled at the same clock, there is no arbitrary phase between T4 and T1. Therefore, the T4-T1 times are accurate; the same principle applies to T3-T2. Thus, the measurement is not affected by any phase drift between the two devices due to the asynchronous nature of the system. Similar to the previous embodiment, the measurementLimited by the resolution of the sampling clock period of T1/T2/T3/T4. To improve this accuracy, frequency response measurements may be performed on both devices. Device 820 measures channel response using data packets from device 810, and device 810 measures channel response using data packets from device 820. Since the two devices are not synchronized, there is an uncertainty in the phase between the two clocks, here denoted as T_offset. This phase shift of the clock manifests itself as an extra phase of the channel response measurement on each side, but it can be eliminated by multiplying the channel responses from both sides. Assuming the channel response is the same as before, the measurement from device 820 will be:

H₈₂₀(f)＝H(f)e^{-j2πfToffset}

the measurements from device 810 will be:

H₈₁₀(f)＝H(f)e^{+j2πfToffset}

thus, the combined channel response is:

H₈₁₀(f)H₈₂₀(f)＝H(f)²＝(∑Ake^-j2πfΔTk)²

this cancels out the phase difference between the two clocks. Similar to the previous embodiments, algorithms such as matrix pen, MUSIC, etc. can be used to estimate the signal from H₈₁₀(f)H₈₂₀(f) Which yields 2min Δ Tk, and the distance measurement is given by:

distance [ (T4-T1)/2- (T3-T2)/2-S { H { (H) }₈₁₀(f)H₈₂₀(f)}/2]xC

Alternatively, T_offsetCan be estimated by:

H₈₁₀(f)/H₈₂₀(f)＝e^{+2j2πfToffset}

T_offsetis half the phase slope of the divided channel response. The channel response in either direction can be corrected by the calculated offset. The distance estimate may then be calculated as:

distance [ (T4-T1)/2- (T3-T2)/2-S { H { (H) }₈₁₀(f)}-T_offset]xC

Or

Distance [ (T4-T1)/- (T3-T2)/2-S { H { (T4-T1)/]₈₂₀(f)}+T_offset]xC

This method is superior to the multiplication method. H (f)²The channel response includes terms that double the amplitude and distance of each path and cross terms that line every 2 paths. That is for the case of 2 paths, A₈₁₀ ²e^j2πf2ΔT1、A₈₂₀ ²e^j2πf2ΔT2And A₈₁₀A₈₂₀e^{j2πf(ΔT1+ΔT2)}. When applied to the one-way channel response h (f), the fine estimation method is more efficient and more robust to noise, since there are fewer paths to distinguish and a lower dynamic range.

The aforementioned short path elimination algorithm may also be used in asynchronous systems such as those disclosed above.

As shown above, in an asynchronous system, information from two devices needs to be combined for calculation. To this end, in one embodiment, one device may transmit information to another device using the same RF signals previously mentioned (e.g., 812, 822, 1022, 1023) or using a separate RF signal path 1024, as shown in fig. 2C in one embodiment of the two-way ToF measurement system 1000.

Fig. 3 shows a timing diagram of the communication of the system 200 according to one embodiment. N240 is configured to transmit a communication (e.g., a transmitted data packet) received as data packets 241 and 243 (e.g., an acknowledgement data packet) in response to communication 212 (e.g., a unicast data packet) from primary node 210. The system utilizes a master node as an Access Point (AP) and has an unknown node (e.g., sensor node, mobile device, smart watch, etc.) associated with it or is established by other means. Listening nodes 220 and 230 are configured to receive any data packets transmitted by the master node or N240. Master node at time T₁Communication 212 is sent to N240 (e.g., forwarding packets). N240 at time T₂The communication is received 212. Each listening node records a detection timestamp and Channel State Information (CSI) of the received communication (e.g., node 220 at time T)₃Upon receipt of the forwarded data packet 202, node 230 is at time T₄ReceivingTo forwarding packet 204). Packets 202, 204, and 212 originate from the same communication from M210. The unknown node N240 sends a communication received as data packets 241 and 243 (e.g., at time T) in response to receiving the communication 212₅Acknowledgement packet). Both the listening node and the master node record the received communication 241-₆、T₇And T₈Received acknowledgement packet) and CSI.

The master node that is to listen to the ToF and the timestamps and CSI information on the master node and listening nodes may then be combined to determine the location of node 240. T between the master node and each listening node is calculated according to equation 1 below_DoA. These TDoA values can then be used in a standard TDoA multipoint positioning algorithm to determine the location of N240.

The TDoA between each listening node and the master node is determined as follows. Ideally, TDoA is simply the first time T when the master slave node 240 receives an acknowledgement packet₆And a second time T when the snooping node receives the acknowledgement packet from node 240₇The difference (delta) therebetween.

However, the master node and the listening nodes have independent clock references with counter offsets and phase and frequency offsets from each other. To address this issue, in one example, the data packets of the communication 212 at the primary node are sent at a time (e.g., at time T)₁Forwarding packet 212) serves as a time reference for both the master node and the listening node.

Equation 1:

T_DoAM210-S220＝T₆-T₇

＝(T₆–T₁)-(T₇–T₁)

＝(T₆–T₁)-(T₇–(T₃–T_{oF M210-S220})

＝(RTT_{M210–N240 sampling}+T_{frac M210-N240})-(T_{S220 Ack Rx sampling}+T_{S220 Ack Rx frac}–(T_{S220 forw Rx sampling}+T_{S220 forw Rx frac}-T_{oF M210-S220}))

the time at which the listening node receives the communications 242 and 243 (e.g., listening acknowledgement receipt) may be aligned with the master node forwarding packet transmission by subtracting the timestamp for the acknowledgment forwarding receipt of the received communications 242 and 243 and the previously measured ToF calculated between the master and listening nodes.

By using Channel State Information (CSI) for the fractional sample estimate received for each data packet, the time resolution of TDoA can be better than the rate of the sampling clock. The CSI may be used to compute fractional sample estimates using the slope of the phase (in a single line-of-sight path) or using techniques such as matrix-writing, MUSIC, or IFFT. Fig. 2 and 3 and equation 1 show examples of systems and how TDoA is calculated. Equation 2 shows how the delay caused by the difference in the reference clocks is eliminated.

Equation 2:

T₆’＝T₆+t_dM210-N240+t_dN240-M210

T₇’＝T₇+t_dS220-N240+t_dN240-M210

T₃’＝T₃+t_dS220-M210

T_DoA’＝T₆’–T₇’

＝T_DoA+t_dM210-N240+t_dN240-M210-t_dS220-N240-t_dN240-M210+t_dS220-M210

note that: t is t_dS220-M210＝t_dS220-N240+t_dN240-M210

＝t_dS220-N240-t_dM210-N240

t_dS220-M210-t_dS220-N240+t_dM210-N240＝0

T_DoA’＝T_DoA

This process may be repeated for multiple data packets in order to improve the signal-to-noise ratio (SNR). The TDoA for each packet may be calculated and then averaged. Alternatively, the timestamp and CSI may be averaged prior to combining. To average the CSI, the amplitude and phase must be averaged independently and then combined. By reconfiguring the system with different unknown nodes, the location of multiple nodes can be found.

Fig. 4 illustrates a system for locating a node using time difference of arrival in accordance with an alternative embodiment. System 400 is configured with one master node 410(M410), one node 440(N440) at an unknown location, and listening nodes (e.g., S420, S430, etc.). Fig. 5 illustrates a timing diagram of communications of system 400 according to one embodiment. Unknown node N440 may initiate a packet transaction. N440 at time T₁A communication 441 (e.g., a forwarding packet 441) is sent to the master (M) node 410. The master node 410 is at time T₂A communication is received 441. The master node 410 is at time T₅The response is made via communication 412 (e.g., an acknowledgement packet 412). Listening nodes 420 and 430 listen at time T₄And T₃Communications 442-443 from N440 (e.g., forwarding packets 442-443) and communications 402 and 404 from primary node 410 (e.g., acknowledgement packets 402 and 404). Listening node 420 at time T₃Communication 443 is received and at time T₆A communication is received 402. Listening node 430 at time T₄Communication 442 is received and at time T₇A communication 404 is received. The received data packets 441- > 443 originate from the same communication from N440.

The TDoA is now calculated based on the forwarded packet arriving from N440 to the master and listening nodes. Now, according to equation 3 and the delta offset equals T₆-T₅-T_{oF M410-S420}Aligning the timing between the nodes using the packet transmission time of the acknowledgement packet from the master node:

T_{DoA M410-S420}＝T₂–T₃ ^M410

＝T₂–T₃delta offset between clocks of M410 and S420

＝(T₂–T₃)+T₆–T₅-T_{oF M410-S420}

＝(T_{2 sampling}+_T2frac–T_3sampling-T_{3 frac})+T_{6 sampling}+T_{6 frac}-T_{5 sampling}–T_{5 frac}-T_{oF M410-S420}

FIG. 6 illustrates a method for determining a location estimate for a node using a time difference of arrival technique, according to one embodiment. The operations of method 600 may be performed by a wireless device, a wireless control device (e.g., an apparatus) of a hub, or a system including processing circuitry or processing logic. Processing logic may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine or device), or a combination of both. In one embodiment, the hub performs the operations of method 600.

Upon initialization of the wireless network architecture, at operation 601, the processing logic of the system is configured with a first node (e.g., a master node), second and third wireless nodes (e.g., listening nodes), and a fourth node (e.g., a sensor node, a mobile device, a smart watch, etc.) at an unknown location. At operation 602, a first node (e.g., a master node) performs a two-way time of flight having an RTT and a fractional distance (as described in U.S. patent application No. 15/173,531) from second and third nodes (e.g., listening nodes).

At operation 604, the first node sends a communication with forwarded data packets to the second, third and fourth nodes at a first time. At operation 606, the fourth node receives the communication at a second time. At operation 608, the second and third nodes receive the communications at the third time and the fourth time, respectively. At operation 610, the fourth node is configured to send a communication with acknowledgement packets to the first, second and third nodes at a fifth time in response to the communication (e.g., forwarding the packets) from the first node. In one example, the system utilizes a master node as an Access Point (AP) and has an unknown fourth node associated therewith or is otherwise established. The listening node is configured to receive any data packets transmitted by the master node or an unknown fourth node. Each of the listening nodes records a detection timestamp and Channel State Information (CSI) of the received communication. At operation 612, the listening node and the master node both record the timestamp and CSI of the received communication (e.g., acknowledgment packets received at the sixth, seventh, and eighth times).

Then, at operation 614, the master node that is to listen to the ToF and the timestamp and CSI information at the master node and the listening nodes may be combined to determine the location of the unknown fourth node. Calculating T between the master node and each listening node according to equation 1_DoA. These TDoA values can then be used in a standard TDoA multipoint positioning algorithm to determine the location of N240.

In one example, the TDoA algorithm discussed herein is used to locate a fourth node (e.g., a sensor node, a mobile device, a smart watch, a robot, etc.) at an unknown location. Thus, the user of the fourth node may locate the node without having to search for the node.

The communication between the hub and the nodes discussed herein may be implemented using a variety of ways, including but not limited to: direct wireless communication using radio frequencies; power line communication achieved by modulating a signal onto an electric wire inside a house, apartment, commercial building, or the like; WiFi communication using such standard WiFi communication protocols as 802.11a, 802.11b, 802.11n, 802.11ac, and other such WiFi communication protocols as will be apparent to one of ordinary skill in the art; cellular communications such as GPRS, EDGE, 3G, HSPDA, LTE, 5G, and other cellular communication protocols that will be apparent to one of ordinary skill in the art; bluetooth communication; communication using well known wireless sensor network protocols such as Zigbee and other wired or wireless based communication schemes will be apparent to those of ordinary skill in the art.

In one embodiment, by using frequency domain techniques, a model may be established for the signal received from the wireless device and used to extract the delay at a finer resolution than is achievable via the sampling clock. This may be possible if appropriate Channel State Information (CSI) is available, for example, in Wi-Fi, LTE or 5G, since CSI is typically collected as part of an overall OFDM or SC-FDMA implementation.

Embodiments of radio frequency communication between end nodes and hubs may be implemented in a variety of ways including narrowband, channel-overlapped, channel-stepped, multi-channel wideband, and ultra-wideband communication.

A hub may be physically implemented in a variety of ways according to embodiments of the present invention. Fig. 7A illustrates an exemplary embodiment of a hub implemented as a cover 1500 for an electrical outlet, according to one embodiment. The cover 1500 (e.g., faceplate) includes a hub 1510 and connections 1512 (e.g., communication links, signal lines, electrical connections, etc.) that couple the hub to the power receptacle 1502. Alternatively (or additionally), the hub is coupled to the receptacle 1504. The cover 1500 covers or surrounds the power outlets 1502 and 1504 for safety and aesthetic purposes.

Fig. 7B illustrates an exemplary embodiment of an exploded view of a block diagram of a hub 1520 implemented as a cover for an electrical outlet, according to one embodiment. The hub 1520 includes a power rectifier 1530 that converts Alternating Current (AC) that periodically reverses direction to Direct Current (DC) that flows in only one direction. The power rectifier 1530 receives AC from the receptacle 1502 via connection 1512 (e.g., a communication link, signal line, electrical connection, etc.) and converts the AC to DC for power to the controller circuitry 1540 via connection 1532 (e.g., a communication link, signal line, electrical connection, etc.) and to the RF circuitry 1550 via connection 1534 (e.g., a communication link, signal line, electrical connection, etc.). The controller circuitry 1540 includes or is coupled to a memory 1542 that stores instructions executed by processing logic 1544 (e.g., one or more processing units) of the controller circuitry 1540 to control the operation of the hub to form, monitor, and perform positioning of the wireless asymmetric network as discussed herein. RF circuitry 1550 may include a transceiver or separate transmitter 1554 and receiver 1556 that function to transmit and receive bi-directional communications with the wireless sensor node via antenna 1552. The RF circuitry 1550 is in bidirectional communication with the controller circuitry 1540 via a connection 1534 (e.g., a communication link, signal line, electrical connection, etc.). RF circuitry 1550 includes at least one of LAN RF circuitry, WAN RF circuitry, and cellular RF circuitry. Hub 1520 may be a wireless control device 1520, or the combination of controller circuitry 1540, RF circuitry 1550, and antenna 1552 may form a wireless control device as discussed herein.

Fig. 8A illustrates an exemplary embodiment of a hub implemented as a card deployed in a computer system, appliance, or communications hub, according to one embodiment. As indicated by arrow 1663, the card 1662 may be inserted into a system 1660 (e.g., a computer system, appliance, or communications hub).

Fig. 8B illustrates an exemplary embodiment of a block diagram of a hub 1664 implemented as a card deployed in a computer system, appliance, or communications hub, according to one embodiment. The hub 1664 includes a power supply 1666, the power supply 1666 providing power (e.g., a DC power supply) to the controller circuitry 1668 via a connection 1674 (e.g., a communication link, a signal line, an electrical connection, etc.), and providing power to the RF circuitry 1670 via a connection 1676 (e.g., a communication link, a signal line, an electrical connection, etc.). The controller circuit 1668 includes, or is coupled to, a memory 1661 that stores instructions executed by processing logic 1663 (e.g., one or more processing units) of the controller circuit 1668 to control operation of the hub to form, monitor, and perform positioning of the wireless asymmetric network as discussed herein. The RF circuitry 1670 may include a transceiver or separate transmitter 1675 and receiver 1677 that function to transmit and receive bi-directional communications with the wireless sensor node via antenna 1678. The RF circuitry 1670 communicates bi-directionally with the controller circuitry 1668 via connection 1672 (e.g., a communication link, signal line, electrical connection, etc.). The RF circuitry 1670 includes at least one of LAN RF circuitry, WAN RF circuitry, and cellular RF circuitry. The hub 1664 may be a wireless control device 1664 or a controller circuit 1668, and the combination of the RF circuit 1670 and the antenna 1678 may form a wireless control device as discussed herein.

Fig. 8C illustrates an exemplary embodiment of a hub implemented within an appliance (e.g., an intelligent washing machine, an intelligent refrigerator, an intelligent thermostat, other intelligent appliances, etc.) according to one embodiment. The device 1680 (e.g., an intelligent laundry machine) includes a hub 1682.

Fig. 8D illustrates an exemplary embodiment of an exploded view of a block diagram of a hub 1684 implemented within an appliance (e.g., an intelligent washing machine, an intelligent refrigerator, an intelligent thermostat, other intelligent appliances, etc.), according to one embodiment. The hub includes a power supply 1686, the power supply 1686 provides power (e.g., a DC power supply) to the controller circuit 1690 via a connection 1696 (e.g., a communication link, a signal line, an electrical connection, etc.) and provides power to the RF circuit 1692 via a connection 1698 (e.g., a communication link, a signal line, an electrical connection, etc.). The controller circuit 1690 includes, or is coupled to, a memory 1691 that stores instructions for execution by the processing logic 1688 (e.g., one or more processing units) of the controller circuit 1690 to control operation of the hub to form, monitor and execute the positioning of the wireless asymmetric network as discussed herein. RF circuit 1692 may include a transceiver or separate transmitter 1694 and receiver 1695 that function to transmit and receive bi-directional communications with the wireless sensor node via antenna 1699. The RF circuit 1692 bi-directionally communicates with the controller circuit 1690 via a connection 1689 (e.g., a communication link, signal line, electrical connection, etc.). The RF circuit 1692 includes at least one of a LAN RF circuit, a WAN RF circuit, and a cellular RF circuit. The hub 1684 may be a wireless control device 1684 or a controller circuit 1690, and the combination of the RF circuit 1692 and the antenna 1699 may form a wireless control device as discussed herein.

In one example, any of the RF circuits described herein may include at least one of a LAN RF circuit, a WAN RF circuit, and a cellular RF circuit.

In one embodiment, an apparatus (e.g., a hub) for providing a wireless asymmetric network architecture includes memory to store instructions, processing logic (e.g., one or more processing units, processing logic 1544, processing logic 1663, processing logic 1688, processing logic 1763, processing logic 1888) to execute the instructions to establish and control the hub for communications in the wireless asymmetric network architecture, and Radio Frequency (RF) circuitry (e.g., RF circuitry 1550, RF circuitry 1670, RF circuitry 1692, RF circuitry 1890) including multiple antennas (e.g., antenna 1552, antenna 1678, antenna 1699, antennas 1311, 1312, 1313, etc.) to transmit and receive communications in the wireless asymmetric network architecture. The RF circuitry and the plurality of antennas transmit communications to a plurality of sensor nodes (e.g., node 1, node 2), each having a wireless device with a transmitter and a receiver (or a transceiver and transmitter of a receiver function) to enable bidirectional communications with the RF circuitry of the device in a wireless asymmetric network architecture.

In one example, a memory for storing instructions includes one or more processing units to execute the instructions to control a plurality of sensor nodes in a wireless network architecture and to determine locations of the plurality of sensor nodes and Radio Frequency (RF) circuitry to transmit communications to and receive communications from the plurality of sensor nodes, each node having a wireless device with a transmitter and a receiver to enable bidirectional communication with RF circuitry of a device in the wireless network architecture. The one or more processing units of the device are configured to execute instructions to send communications to the first, second and third wireless nodes, receive communications with acknowledgement packets from the third node having an unknown location, and determine time differences of arrival information between the device and the first wireless node and between the device and the second wireless node.

In one example, the device is powered by a mains power source and the plurality of sensor nodes are each powered by a battery source to form a wireless network architecture.

Various batteries may be used in the wireless sensor node, including lithium-based chemistries such as lithium-ion, lithium polymer, lithium phosphate, and other such chemistries as will be apparent to those of ordinary skill in the art. Other chemistries that may be used include nickel metal hydride, standard alkaline battery chemistries, silver zinc and zinc air battery chemistries, standard carbon zinc battery chemistries, lead acid battery chemistries, or any other chemistry that will be apparent to one of ordinary skill in the art.

The present invention also relates to apparatus for performing the operations described herein. This apparatus may be specially constructed for the required purposes, or it may comprise a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer readable storage medium, such as but not limited to: any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic-optical disks, read-only memories (ROMs), Random Access Memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any type of media suitable for storing electronic instructions.

The algorithms and displays presented herein are not inherently related to any particular computer or other apparatus. Various general-purpose systems may be used with programs in accordance with the teachings herein, or it may prove convenient to construct a more specialized apparatus to perform the required method operations.

FIG. 9 shows a block diagram of a sensor node according to an embodiment. The sensor node 1700 includes a power source 1710 (e.g., an energy source, a battery source, a primary battery, a rechargeable battery, etc.) that provides power (e.g., a DC power source) to the controller circuit 1720 via a connection 1774 (e.g., a communication link, a signal line, an electrical connection, etc.), to the RF circuitry 1770 via a connection 1776 (e.g., a communication link, a signal line, an electrical connection, etc.), and to the sensing circuitry 1740 via a connection 1746 (e.g., a communication link, a signal line, an electrical connection, etc.). The controller circuit 1720 includes, or is coupled to, a memory 1761 that stores instructions executed by processing logic 1763 (e.g., one or more processing units) of the controller circuit 1720 to control operation of the sensor nodes to form and monitor a wireless asymmetric network as discussed herein. The RF circuitry 1770 (e.g., communication circuitry) can include a transceiver or separate transmitter 1775 and receiver 1777 that function to transmit and receive bi-directional communications with the hub and optional wireless sensor nodes via antenna 1778. The RF circuitry 1770 is in bidirectional communication with the controller circuitry 1720 via a connection 1772 (e.g., an electrical connection). The RF circuitry 1770 includes at least one of LAN RF circuitry, WAN RF circuitry, and cellular RF circuitry. Sensing circuitry 1740 includes various types of sensing circuitry and sensors, including image sensor and circuitry 1742, humidity sensor and circuitry 1743, temperature sensor and circuitry, humidity sensor and circuitry, air quality sensor and circuitry, light sensor and circuitry, motion sensor and circuitry 1744, audio sensor and circuitry 1745, magnetic sensor and circuitry 1746, and sensor and circuitry n, among others.

The wireless location techniques disclosed herein may be combined with other state information to improve location accuracy throughout the network. For example, in a wireless sensor where one or more nodes contain a camera, the captured images may be used with image processing and machine learning techniques to determine whether the sensor nodes being monitored are in the same scene, and therefore likely in the same room. Similar benefits may be achieved by using periodic illumination and photodetectors. By strobing the illumination and detecting with a photodetector, the presence of a light path can be detected, possibly indicating the absence of an opaque wall between the strobe and the detector. In other embodiments, the magnetic sensor may be integrated into the sensor node and may act as a compass to detect the direction of the sensor node being monitored. This information can then be used with the positioning information to determine whether the sensor is located on a wall, floor, ceiling, or other location.

In one example, each sensor node may comprise an image sensor, and each surrounding wall of the house comprises one or more sensor nodes. The hub analyzes the sensor data, including the image data and optionally the orientation data and the positioning information, to determine the absolute position of each sensor node. The hub may then construct a three-dimensional image of each room of the building for the user. A plan view may be generated with the locations of walls, windows, doors, etc. The image sensor may capture an image indicative of a change in reflection, which may be indicative of a building integrity problem (e.g., water, roof leaks, etc.).

Fig. 10 shows a block diagram of a system 1800 with a hub according to one embodiment. System 1800 includes or is integrated with hub 1882 or a central hub of a wireless asymmetric network architecture. The system 1800 (e.g., computing device, smart TV, smart appliance, communication system, etc.) may communicate with any type of wireless device (e.g., cellular phone, wireless phone, tablet, computing device, smart TV, smart appliance, etc.) for sending and receiving wireless communications. System 1800 includes a processing system 1810, which includes a controller 1820 and a processing unit 1814. The processing system 1810 communicates with the following via one or more bidirectional communication links or signal lines 1898, 1818, 1815, 1816, 1817, 1813, 1819, 1811, respectively: a hub 1882, an input/output (I/O) unit 1830, a Radio Frequency (RF) circuit 1870, an audio circuit 1860, optics 1880 for capturing one or more images or video, an optional motion unit 1844 (e.g., an accelerometer, gyroscope, etc.) for determining motion data (e.g., in three-dimensional space) for the system 1800, a power management system 1840, and a machine-accessible non-transitory medium 1850.

The hub 1882 includes a power supply 1891 that provides power (e.g., a DC power supply) to the controller circuitry 1884 via a connection 1885 (e.g., a communication link, signal line, electrical connection, etc.) and to RF circuitry 1890 via a connection 1887 (e.g., a communication link, signal line, electrical connection, etc.). The controller circuit 1884 includes, or is coupled to, memory 1886 that stores instructions executed by processing logic 1888 (e.g., one or more processing units) of the controller circuit 1884 to control operation of the hub to form and monitor the wireless asymmetric network as discussed herein. RF circuitry 1890 may include a transceiver or separate Transmitter (TX)1892 and Receiver (RX)1894 that function to transmit and receive bi-directional communications via antenna 1896 and a wireless sensor node or other hub. The RF circuitry 1890 communicates bi-directionally with the controller circuitry 1884 via connections 1889 (e.g., communication links, signal lines, electrical connections, etc.). The RF circuitry 1890 includes at least one of LAN RF circuitry, WAN RF circuitry, and cellular RF circuitry. The hub 1882 may be a wireless control 1884 or a controller circuit 1884, and the combination of the RF circuit 1890 and the antenna 1896 may form a wireless control as discussed herein.

The RF circuitry 1870 and antenna 1871 of the system, or the RF circuitry 1890 and antenna 1896 of the hub 1882, are used to transmit and receive information over a wireless link or network to one or more other wireless devices or sensor nodes of the hub discussed herein. Audio circuitry 1860 is coupled to audio speaker 1862 and microphone 1064, and includes known circuitry for processing voice signals. The one or more processing units 1814 communicate with one or more machine-accessible non-transitory media 1850 (e.g., computer-readable media) via a controller 1820. Medium 1850 may be any device or medium (e.g., storage device, storage medium) that can store code and/or data for use by one or more processing units 1814. Medium 1850 may include memory hierarchies including, but not limited to, cache, main memory, and secondary memory.

Medium 1850 or memory 1886 store one or more sets of instructions (or software) embodying any one or more of the methodologies or functions described herein. The software may include an operating system 1852, web services software 1856 for creating, monitoring and controlling wireless asymmetric network architectures, a communications module 1854, and application programs 1858 (e.g., home or building security applications, home or building integrity applications, developer applications, etc.). The software may also reside, completely or at least partially, within the medium 1850, the memory 1886, the processing logic 1888, or within the processing unit 1814 during execution thereof by the apparatus 1800. The components shown in fig. 18 may be implemented in hardware, software, firmware, or any combination thereof, including one or more signal processing and/or application specific integrated circuits.

The communication module 1854 enables communication with other devices. The I/O unit 1830 communicates with different types of input/output (I/O) devices 1834 (e.g., a display, a Liquid Crystal Display (LCD), a plasma display, a Cathode Ray Tube (CRT), a touch display device or a touch screen for receiving user input and displaying output, an optional alphanumeric input device).

Any of the following examples may be combined into a single embodiment, or the examples may be separate embodiments. In one example, an asynchronous system for locating a node in a wireless network architecture comprises: a first wireless node and a second wireless node, each wireless node having a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in a wireless network architecture; and a wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first wireless node and the second wireless node in a wireless network architecture. The one or more processing units of the first wireless node are configured to execute instructions to send a communication to the second wireless node and a wireless node with an unknown location to receive the communication with the acknowledgement packet from the wireless node and determine a time difference in arrival information between the first wireless node and the second wireless node.

In another example, a system includes a third wireless node having a wireless device with one or more processing units and RF circuitry for sending and receiving communications in a wireless network architecture. The one or more processing units of the first wireless node are configured to execute instructions for a multilateration algorithm to determine a location of a wireless node having an unknown location using time differences in arrival information between the first wireless node and the second wireless node and between the first wireless node and the third wireless node.

In another example, a first wireless node has a first reference clock signal and a second wireless node has a second reference clock signal.

In another example, the one or more processing units of the wireless node having the unknown location are configured to execute instructions to transmit a communication including an acknowledgement packet to the first, second, and third wireless nodes in response to receiving the communication with the forwarded packet from the first node.

In another example, the one or more processing units of the second and third wireless nodes are configured to execute instructions to receive a communication including a forwarded data packet from the first wireless node and an acknowledgement data packet from the fourth wireless node to record a timestamp and channel state information for each received forwarded data packet and acknowledgement data packet.

In another example, the transmission time of the forwarded data packet from the first wireless node is used as a time reference for the first, second and third wireless nodes.

In another example, the time difference in arrival information between the first wireless node and the second wireless node is determined based on a first time when the first wireless node receives the acknowledgement data packet from the fourth wireless node, a second time when the second wireless node receives the acknowledgement data packet from the fourth wireless node, and a time reference.

In another example, the one or more processing units of the first wireless node are configured to execute the instructions to determine a difference between the first time and the time reference, and also to determine a difference between the second time and the time reference.

In another example, the one or more processing units of the first wireless node are configured to execute the instructions to determine a time difference of arrival information based on determining a time-of-flight estimate for the positioning, the time-of-flight estimate based on time estimates of round trip times for communications between the first wireless node and the second wireless node and communications between the first wireless node and the third wireless node.

In one example, an apparatus includes: the wireless device includes a memory to store instructions, one or more processing units to execute the instructions to control and determine locations of a plurality of sensor nodes in a wireless network architecture, and Radio Frequency (RF) circuitry to transmit communications to and receive communications from the plurality of sensor nodes, each sensor node having a wireless apparatus with a transmitter and a receiver to enable bidirectional communication with the RF circuitry of the device in the wireless network architecture. The one or more processing units of the device are configured to execute instructions to send communications to the first, second and third wireless nodes, receive communications with acknowledgement packets from the third node having an unknown location, and determine time differences of arrival information between the device and the first wireless node and between the device and the second wireless node.

In another example, the one or more processing units of the apparatus are configured to execute instructions for a multipoint positioning algorithm to determine the location of the third wireless node using a time difference of arrival information.

In another example, the device has a first reference clock signal and the first wireless node has a second reference clock signal.

In another example, the transmitted communication includes a transmission time of forwarded packets transmitted to the first, second and third wireless nodes, the transmission time serving as a time reference for the device, the first wireless node and the second wireless node.

In another example, the time difference in arrival information between the device and the first wireless node is determined based on a first time when the device receives the acknowledgement packet from the third wireless node, a second time when the first wireless node receives the acknowledgement packet from the third wireless node, and a time reference.

In another example, one or more processing units of the device are configured to execute instructions to determine a difference between the first time and the time reference, and also to determine a difference between the second time and the time reference.

In one example, a system for locating a node in a wireless network architecture comprises: first, second and third wireless nodes, each wireless node having a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in a wireless network architecture; and a fourth wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first, second and third wireless nodes in a wireless network architecture. The one or more processing units of the first wireless node are configured to execute instructions to receive a communication from the fourth node having a forwarded data packet, send the communication to the second, third and fourth wireless nodes in response to the forwarded data packet, and determine a time difference in arrival information between the first and second wireless nodes and between the first and third wireless nodes.

In another example, the one or more processing units of the first wireless node are configured to execute instructions for a multipoint positioning algorithm to determine the location of the fourth wireless node using time differences of arrival information.

In another example, a first wireless node has a first reference clock signal and a second wireless node has a second reference clock signal.

In another example, the one or more processing units of the fourth wireless node are configured to execute instructions to transmit a communication comprising a forwarded data packet to the first, second, and third wireless nodes.

In another example, the one or more processing units of the second and third wireless nodes are configured to execute instructions to receive a communication from the fourth wireless node that includes a forwarding data packet and an acknowledgement data packet from the first wireless node, and to record a timestamp and channel state information for each received forwarding data packet and acknowledgement data packet.

In another example, the time difference in arrival information between the first wireless node and the second wireless node is determined based on a first time when the first wireless node receives the forwarded data packet from the fourth wireless node, a second time when the second wireless node receives the forwarded data packet from the fourth wireless node, and a time offset between the first reference clock signal and the second reference clock signal.

In another example, the one or more processing units of the first wireless node are configured to execute instructions to determine a time offset between the first reference clock signal and the second reference clock signal based on a third time when the second wireless node receives an acknowledgement packet from the first wireless node, a fourth time when the first wireless node transmits the acknowledgement packet to the second wireless node, and a time of flight estimate for communication between the first wireless node and the second wireless node.

FIG. 11 illustrates a time scanning method for determining a location estimate for a node using a time difference of arrival technique, according to one embodiment. The operations of method 1100 may be performed by a wireless device, a wireless control device (e.g., an apparatus) of a hub, or a system including processing circuitry or processing logic. Processing logic may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine or device), or a combination of both. In one embodiment, at least one of the hub and the remote cloud-based device or entity performs the operations of method 1100.

At initialization of a wireless network architecture (e.g., wireless Local Area Network (LAN), wireless Wide Area Network (WAN), wireless cellular network), at operation 1101, the processing logic of the system is configured to have a first node (e.g., master node 1210), second and third wireless nodes (e.g., listening nodes 1220, 1230), and a fourth node 1240 (e.g., sensor node, mobile device, smart watch, etc.) at an unknown location as shown in fig. 12. At operation 1102, a first node (e.g., a master node) performs a two-way time of flight having an RTT and a fractional distance (as described in U.S. patent application No. 15/173,531) from second and third nodes (e.g., listening nodes). The method may determine or obtain location coordinates of the anchor node (e.g., first, second, and third nodes 1210, 1220, 1230) based on the time-of-flight measurements.

At operation 1104, the method determines a position coordinate hypothesis and a transmit time hypothesis (x, y, z, t) for a transmitted communication of an arbitrary device (e.g., the fourth node 1240). Each of the anchor nodes records a detection timestamp and Channel State Information (CSI) of the received communication. At operation 1106, the method determines and locates (x)_i，y_i，z_i) At a time tr, each receiving path j of a receiving device i (e.g., anchor node) of_jiThe transmission time at (a) assumes an associated error function, (e.g., epsilon ═ sqrt ((x)_i-x)^2+(y_i-y)^2)-(tr_ji-t); epsilon 1215). In operation 1108, the method forms a probability function, P, using statistical properties of the path measurement accuracy_ij(epsilon)。P_ij(eps) can be of any form, and examples include normal distributions a (i) e ^ epsilon (-epsilon ^2/b (i)), where a (i) and b (i) can be functions of path attributes.

In operation 1110, the method adds together the probability functions of all paths j to form P for each device i_i(epsilon). In operation 1112, the method combines all P from all devices i_iThe (epsilon) functions are multiplied to form P (x, y, z, t). The numerical implementation of the multiplication can also be by summation log (P)_i) Instead. At operation 1114, the method evaluates P (x, y, z, t) for any feasible coordinates and transmission time hypotheses. At operation 1116, the method targets any feasible coordinate sumThe transmission time hypothesis chooses the highest probability P (x, y, z, t).

In one example, the system utilizes a master node as an Access Point (AP) and has an unknown fourth node associated therewith or is otherwise established. The listening node is configured to receive any data packets transmitted by the master node or an unknown fourth node. Each of the listening nodes records a detection timestamp and Channel State Information (CSI) of the received communication. Both the listening node and the master node record the time stamp and CSI of the received communication.

Figure 12 shows a wireless architecture for time scanning TDoA according to one embodiment. The anchor nodes 1210, 1220, 1230 each send and receive communications from a node 1240 having an unknown location. The anchor node receives communications from node 1240 along paths 1212, 1222, and 1232, where multiple paths j are indicated by radii 1211, 1221, and 1231 for each node. Multiple paths may be caused by communication reflections within an environment (e.g., an indoor environment, a building, a room). Each node has an error function (e.g., epsilon 1215) that represents the difference between the predicted coordinates and the actual location of node 1240. Each anchor node also has a time offset (e.g., time offset 1216) based on the difference between the actual transmission time transmitted from node 1240 and the transmission time assumption for node 1240.

With respect to existing methods, beamforming methods locate a device based on the transmitter response of the measuring device. The calculation is performed in the time domain. However, it is difficult to estimate the distance to any device because its transmitter response is unknown and converting the Channel State Information (CSI) to the time domain creates artifacts.

The present design utilizes existing powerful beamforming algorithms (for steering vector finding) to overcome the existing TDoA problem. With any position assumption, estimates of the transmitter response of any device can be coherently added together in the frequency domain.

Fig. 13 illustrates a beamforming method in the frequency domain for determining a location estimate of a node according to one embodiment. The operations of method 1300 may be performed by a wireless device, a wireless control device (e.g., an apparatus) of a hub, or a system including processing circuitry or processing logic. Processing logic may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine or device), or a combination of both. In one embodiment, at least one of the hub, the anchor node, and the remote cloud-based device or entity performs the operations of method 1300.

Upon initialization of a wireless network architecture (e.g., wireless Local Area Network (LAN), wireless Wide Area Network (WAN), wireless cellular network), at operation 1301, the processing logic of the system is configured with an anchor node (e.g., master node 1410), at least one additional anchor wireless node (e.g., listening node 1420), and a node 1440 (e.g., sensor node, mobile device, smart watch, etc.) at an unknown location as shown in fig. 14. At operation 1302, a node (e.g., a master node) performs a bidirectional time of flight having an RTT and a fractional distance of at least one anchor node (e.g., at least one listening node), as described in U.S. patent application No. 15/173,531. Each of the anchor nodes records a detection timestamp and Channel State Information (CSI) according to the channels 1412 and 1422 of the received communication.

At operation 1304, the method determines a position coordinate hypothesis (x, y, z) for the node with unknown position and calculates a distance d from each listening anchor node i (e.g., nodes 1410, 1420) with an operational receiver to the position coordinate (e.g., 1450)_i(e.g., 1452, 1454).

In operation 1306, the method obtains CSI from each anchor node i_i(f) And signal arrival time stamp T_iAnd by shifting the time by d_i-T_iAdd to the original CSI to calculate the modified CSI: CSI_m，i＝CSI_i·e^(jω(d_i-T_i)). By making such a time offset, the combined CSI will have high energy in the correct position hypothesis. If the anchor points are not synchronized, the anchor point clock phase difference must be measured and included in the timestamp. Only the relative timestamp values are needed and therefore a constant can be subtracted from all timestamps to keep them as small as possible. Smaller time stamp valueThe accuracy of the following operations can be improved.

In operation 1308, the method determines to make e (x, y, z) ═ Σ f Σ i | vi · CSI_m,i(f) | ^2 maximized composite steering vector v.

At operation 1310, the method evaluates e (x, y, z) for any feasible coordinate hypothesis and selects the coordinate location with the highest value.

Assuming each listening anchor node computes an estimate of the transmitter response of any device, all estimates may be added together coherently in the frequency domain with any position assumption. The sum will have the highest value when assumed to correspond to the actual position of any device.

Fig. 15 illustrates a beamforming method in the time domain for determining a location estimate of a node according to one embodiment. The operations of method 1500 may be performed by a wireless device, a wireless control device (e.g., an apparatus) of a hub, or a system including processing circuitry or processing logic. Processing logic may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine or device), or a combination of both. In one embodiment, at least one of the hub, the anchor node, and the remote cloud-based device or entity performs the operations of method 1500.

Upon initialization of a wireless network architecture (e.g., wireless Local Area Network (LAN), wireless Wide Area Network (WAN), wireless cellular network), at operation 1502, the processing logic of the system is configured with an anchor node (e.g., master node 1410), at least one additional anchor wireless node (e.g., listening node 1420), and a node 1440 (e.g., sensor node, mobile device, smart watch, etc.) at an unknown location as shown in fig. 14. At operation 1502, an anchor node (e.g., master node) performs a bidirectional time of flight having an RTT and a fractional distance of at least one anchor node (e.g., at least one listening node), as described in U.S. patent application No. 15/173,531. Each of the anchor nodes records a detection timestamp and Channel State Information (CSI) according to the channels 1412 and 1422 of the received communication.

At operation 1504, the method determines a toolThe location coordinates of nodes with unknown locations are assumed to be (x, y, z) and the distance d from each listening anchor node i (e.g., nodes 1410, 1420) to the location coordinates is calculated_i(e.g., 1452, 1454).

In operation 1506, the method obtains channel state information (e.g., CSI) from each anchor node i_i(f) ) and a signal arrival timestamp T_iAnd calculating the modified CSI by adding a time offset to the original CSI:

CSI_m，i＝CSI_i·e^(jω(d_i-T_i)). Optionally, in operation 1506, the CSI may be multiplied by a fourier transform of the window function. The windowing function described below may be used to reduce noise and spurious components resulting from the conversion from the frequency domain to the time domain.

In operation 1508, the method maps each CSI using spark approximation, matrix pencil, etc_m,iConversion to time domain response h_i(t) of (d). At operation 1510, the method adds the amplitudes of all responses together s (t) ═ Σ \_i|h_i|。

At operation 1512, the method filters out spurious components, for example, by convolving s (t) with an appropriate window function corresponding to the desired position accuracy and estimated distance measurement accuracy. Some of the conversion methods in operation 1508 may generate spurious components in the time-domain channel response. Sometimes the magnitudes of these spurious components may be close to the actual delay path components. If the resolution of the conversion is higher than required for positioning accuracy, the spurious component can be attenuated by a window function. The window function may be a simple average of several time samples, and more complex shapes better suited to a particular conversion method or convolution step may be omitted altogether. At operation 1514, the method selects the highest value s of the output_max。

At operation 1516, the method evaluates s against any feasible coordinate hypotheses_maxAnd the coordinate position with the highest value is selected.

Existing beamforming methods include locating a device based on the transmitter response of the measurement device. However, since its transmitter response is unknown, it is difficult to estimate the distance to any device. Coherently adding the frequency domain responses together requires estimating the phase of each anchor node that may cause errors.

The method 1500 of fig. 15 performs a conversion from the frequency domain to the time domain to remove the unknown phase of the anchor node. If each listening anchor node computes an estimate of the transmitter time response magnitude for any device, then all estimates can be added together for any location hypothesis. The sum will have the highest amplitude peak when assumed to correspond to the actual position of any device.

Any of the following examples may be combined into a single embodiment, or the examples may be separate embodiments. In one example of the first embodiment, a computer-implemented method for locating a wireless arbitrary device in a wireless network architecture, comprises: initializing a wireless network architecture having a plurality of wireless anchor nodes; determining a location coordinate hypothesis and a transmit time hypothesis for a transmitted communication of the wireless arbitrary device using at least one of the anchor node and the cloud-based entity; determining an error function associated with a transmit time hypothesis at the location coordinate hypothesis receiving each receive path j of the plurality of anchor nodes; and determining a probability function of the error function for each received path j for each anchor node using statistical characteristics of the path measurement accuracy.

In another example of the first embodiment, the computer-implemented method further comprises adding the probability functions of all paths j to form a probability function of the error function for each of the plurality of anchor nodes.

In another example of the first embodiment, the computer-implemented method further comprises multiplying the probability functions of the error functions for each of the plurality of anchor nodes to form a probability function P (x, y, z, t) for a wireless arbitrary device's three-dimensional coordinate position and transmit time hypothesis.

In another example of the first embodiment, the computer-implemented method further comprises evaluating a probability function of the three-dimensional coordinate position and the transmission time hypothesis for any feasible coordinate and transmission time hypothesis; and selecting at least one hypothesis from the highest probabilities P (x, y, z, t) for any feasible coordinate and transmit time hypothesis.

In another example of the first embodiment, the computer-implemented method further comprises evaluating a probability function of the three-dimensional coordinate position and the transmission time hypothesis for any feasible transmission time hypothesis; and adding together the values of P (x, y, z, t) within at least one predetermined range x, y and z; and determining the range in which any device is most likely to be located by selecting the range with the highest sum.

In another example of the first embodiment, the computer-implemented method further comprises adding together the values of P (x, y, z, t) in a range of x, y, and z around the selected highest probability such that the sum equals a predetermined value; and using the size of the range as an indication of positioning accuracy.

In another example of the first embodiment, the error function includes sqrt ((x)_i-x)^2+(y_i-y)^2)-(tr_ji-t) with position (x)_i，y_i，z_i) Each receive path j of the receive anchor node of (1) at time tr_jiAre associated.

In one example of the second embodiment, an asynchronous system for node location in a wireless network architecture, comprising: a first wireless node and a second wireless node, each wireless node having a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in a wireless network architecture; and a third wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first and second wireless nodes in the wireless network architecture, wherein the one or more processing units of the first wireless node are configured to transmit instructions or execute instructions to the cloud-based entity to determine a location coordinate hypothesis and a transmission time hypothesis for a transmission communication of the third wireless node, determine an error function associated with the transmission time hypothesis for each reception path j of the first and second wireless nodes at the location coordinate hypothesis, and determine a probability function for the error function for each reception path j of the first and second wireless nodes using statistical characteristics of path measurement accuracy.

In another example of the second embodiment, the one or more processing units of the first wireless node or the cloud-based entity executes instructions to add the probability functions of all paths j to form a probability function of the error functions of the first and second wireless nodes.

In another example of the second embodiment, the one or more processing units of the first wireless node or the cloud-based entity is configured to execute instructions to multiply the probability functions of the error functions of the first and second wireless nodes to form a probability function P (x, y, z, t) of the three-dimensional coordinate position and transmission time hypothesis of the third wireless node.

In another example of the second embodiment, the one or more processing units or cloud-based entities of the first wireless node are configured to execute instructions to evaluate a probability function of the three-dimensional coordinate position and the transmission time hypothesis for any feasible coordinate and transmission time hypothesis, and to select the highest probability P (x, y, z, t) for any feasible coordinate and transmission time hypothesis.

In another example of the second embodiment, the first wireless node has a first reference clock signal, the second wireless node has a second reference clock signal, and the third wireless node has a third reference clock signal.

In another example of the second embodiment, the wireless network architecture comprises a wireless WAN architecture.

In another example of the second embodiment, the wireless network architecture comprises at least one of a wireless Local Area Network (LAN) network architecture and a wireless WAN architecture.

In another example of the second embodiment, the first wireless node includes wireless Wide Area Network (WAN) RF circuitry for transmitting and receiving wireless RF communications.

In one example of the third embodiment, a computer-implemented method for locating a wireless arbitrary device in a wireless network architecture, comprises: initializing a wireless network having a plurality of wireless anchor nodes i; determining a three-dimensional position coordinate hypothesis for a wireless arbitrary device having an unknown position; calculating the distance d from each listening wireless anchor node i to the position coordinate hypothesis_i(ii) a And obtaining channel state information from each wireless anchor node i and a signal arrival timestamp T from each wireless anchor node i_i。

In another example of the third embodiment, the computer-implemented method further comprises distance d based on the original channel state information from each anchor node i_iAnd signal arrival time stamp T_iTo calculate the modified channel state information.

In another example of the third embodiment, the computer-implemented method further comprises determining a composite steering vector v that maximizes a function of the variables with the position coordinate hypothesis, wherein the function is based on the steering vector and the modified channel state information.

In another example of the third embodiment, the computer-implemented method further comprises evaluating the function for any feasible coordinate hypothesis and selecting the coordinate location with the highest value.

In one example of a fourth embodiment, an asynchronous system for locating a node in a wireless network architecture, comprising: a first wireless node and a second wireless node, each wireless node having a wireless device with one or more processing units and RF circuitry to send and receive communications in a wireless network architecture; and a third wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first and second wireless nodes in the wireless network architecture, wherein the one or more processing units of the first wireless node are configured to send or execute instructions to a cloud-based entity to determine a three-dimensional location coordinate hypothesis for the third wireless node device having the unknown location, calculate distances to the location coordinate hypothesis from the first and second wireless nodes, and obtain channel state information from the first and second wireless nodes and signal arrival timestamps T from the first and second wireless nodes.

In another example of the fourth embodiment, the one or more processing units or cloud-based entities of the first wireless node execute instructions to determine the channel state information based on the channel state information from the first and second wireless nodes,Calculated distance, signal arrival time stamp T_iAnd the known received responses of the first and second wireless nodes to calculate a transmitter response of the third wireless device.

In another example of the fourth embodiment, the one or more processing units of the first wireless node or the cloud-based entity is configured to execute instructions to determine a composite steering vector v that maximizes a function of the variables with the position coordinate hypothesis, wherein the function is based on the steering vector and the calculated transmitter response of the third wireless node.

In another example of the fourth embodiment, the one or more processing units or cloud-based entities of the first wireless node are configured to execute instructions to evaluate the function and select the coordinate location with the highest value for any feasible coordinate hypothesis.

In another example of the fourth embodiment, the first wireless node has a first reference clock signal, the second wireless node has a second reference clock signal, and the third wireless node has a third reference clock signal; and wherein the first and second reference clock phase differences are cancelled before the usage signal reaches the timestamp.

In one example of a fifth embodiment, a computer-implemented method for locating a wireless node in a wireless network architecture includes initializing a wireless network architecture having a plurality of wireless anchor nodes i; determining a location coordinate hypothesis for a wireless node having an unknown location using at least one of the anchor node and the cloud-based entity; calculating a distance from each anchor node i to a position coordinate hypothesis; and obtaining channel state information and a signal arrival time stamp T from each anchor node i_i。

In another example of the fifth embodiment, the computer-implemented method further comprises distance d based on the original channel state information from each anchor node i_iAnd signal arrival time stamp T_iTo calculate the modified channel state information.

In another example of the fifth embodiment, the computer-implemented method further comprises distance d based on the original channel state information from each anchor node i_iTime stamp of arrival of signal T_iTo calculate the modified channel state information.

In another example of the fifth embodiment, the computer-implemented method further comprises converting each modified channel state information of the wireless of each anchor node into a time-domain channel response h_i(t); and all time domain response amplitudes abs (h) in the time domain_i) Are added together to produce the sum s (t) of the transmitter responses.

In another example of the fifth embodiment, the computer-implemented method further comprises convolving s (t) with a suitable window function to produce the output, the window function corresponding to the desired position accuracy and the estimated distance measurement accuracy.

In another example of the fifth embodiment, the computer-implemented method further comprises selecting a highest value of the output, s_max。

In another example of the fifth embodiment, the computer-implemented method further comprises evaluating s for any feasible coordinate hypothesis_maxAnd the coordinate position with the highest value is selected.

In another example of the fifth embodiment, the wireless network architecture comprises a wireless WAN architecture.

In another example of the fifth embodiment, the wireless network architecture comprises at least one of a wireless Local Area Network (LAN) network architecture and a wireless WAN architecture.

The phrase "at least one of a and B" is to be understood as "a only, B only, or both a and B". The phrase "at least one selected from the groups a and B" is to be understood as "a only, B only or both a and B". The phrase "A, B or at least one of C" should be understood as "a only, B only, C only, or any combination of A, B or C".

In the foregoing specification, the invention has been described with reference to specific exemplary embodiments thereof. It will, however, be evident that various modifications and changes may be made thereto without departing from the broader spirit and scope of the invention. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.

Claims (32)

1. A computer-implemented method for locating a wireless arbitrary device in a wireless network architecture, comprising:

initializing a wireless network architecture having a plurality of wireless anchor nodes;

determining a location coordinate hypothesis and a transmit time hypothesis for the wireless arbitrary device's transmit communication using at least one of an anchor node and a cloud-based entity;

determining an error function associated with the transmit time hypothesis for each receive path j receiving a plurality of anchor nodes at the location coordinate hypothesis; and

statistical properties of the path measurement accuracy are used to determine a probability function for the error function for each receive path j for each anchor node.

2. The computer-implemented method of claim 1, further comprising:

the probability functions for all paths j are added to form a probability function for the error function for each of the plurality of anchor nodes.

3. The computer-implemented method of claim 2, further comprising:

multiplying the probability functions of the error functions of each of the plurality of anchor nodes to form a probability function P (x, y, z, t) for a three-dimensional coordinate position and transmit time hypothesis for the wireless arbitrary device.

4. The computer-implemented method of claim 3, further comprising:

evaluating a probability function of the three-dimensional coordinate position and the transmission time hypothesis aiming at any feasible coordinate and transmission time hypothesis; and

at least one hypothesis is selected from the highest probabilities P (x, y, z, t) for any feasible coordinate and transmit time hypothesis.

5. The computer-implemented method of claim 3, further comprising:

evaluating a probability function of the three-dimensional coordinate position and the transmission time hypothesis for any feasible transmission time hypothesis; and

adding together the values of P (x, y, z, t) within at least one predetermined range x, y and z; and

the range in which any device is most likely to be located is determined by selecting the range with the highest sum.

6. The computer-implemented method of claim 4, further comprising:

adding together the values of P (x, y, z, t) in the range of x, y and z around the selected highest probability such that the sum equals a predetermined value; and

the size of the range is used as an indication of the positioning accuracy.

7. The computer-implemented method of claim 1, wherein the error function comprises sqrt ((x)_i-x)^2+(y_i-y)^2)-(tr_ji-t) with position (x)_i，y_i，z_i) Each receive path j of the receive anchor node of (1) at time tr_jiAre associated.

8. An asynchronous system for locating a node in a wireless network architecture, comprising:

a first wireless node and a second wireless node, each of the first wireless node and the second wireless node having a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in the wireless network architecture; and

a third wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first and second wireless nodes in the wireless network architecture, wherein the one or more processing units of the first wireless node are configured to send or execute instructions to a cloud-based entity to determine a location coordinate hypothesis and a transmit time hypothesis for a transmitted communication of the third wireless node, determine an error function associated with the transmit time hypothesis for each receive path j receiving the first and second wireless nodes at the location coordinate hypothesis, and determine a probability function for the error function for each receive path j of the first and second wireless nodes using statistical characteristics of path measurement accuracy.

9. The asynchronous system of claim 8, wherein the one or more processing units of the first wireless node or the cloud-based entity execute instructions to add the probability functions of all paths j to form a probability function of the error functions of the first wireless node and the second wireless node.

10. The asynchronous system of claim 9, wherein the one or more processing units of the first wireless node or the cloud-based entity is configured to execute instructions to multiply probability functions of error functions of the first wireless node and the second wireless node to form a probability function P (x, y, z, t) of a three-dimensional coordinate position and transmit time hypothesis for the third wireless node.

11. The asynchronous system of claim 10, wherein the one or more processing units or cloud-based entities of the first wireless node are configured to execute instructions to evaluate a probability function of three-dimensional coordinate position and transmission time hypotheses for any feasible coordinate and transmission time hypotheses, and

the highest probability P (x, y, z, t) is chosen for any feasible coordinate and transmission time hypothesis.

12. The asynchronous system of claim 8 wherein the first wireless node has a first reference clock signal, the second wireless node has a second reference clock signal, and the third wireless node has a third reference clock signal.

13. The asynchronous system of claim 8, wherein the wireless network architecture comprises a wireless WAN architecture.

14. The asynchronous system of claim 8, wherein the wireless network architecture comprises at least one of a wireless Local Area Network (LAN) network architecture and a wireless WAN architecture.

15. The asynchronous system of claim 8 wherein the first wireless node comprises wireless Wide Area Network (WAN) RF circuitry for sending and receiving wireless RF communications.

16. A computer-implemented method for locating a wireless arbitrary device in a wireless network architecture, comprising:

initializing a wireless network architecture with a plurality of wireless anchor nodes i;

determining a three-dimensional position coordinate hypothesis for a wireless arbitrary device having an unknown position;

calculating a distance d from each listening wireless anchor node i to the location coordinate hypothesis_i(ii) a And

obtaining channel state information from each wireless anchor node i and a signal arrival timestamp T from each wireless anchor node i_i。

17. The computer-implemented method of claim 16, further comprising:

original channel state information and distance d based on each anchor node i_iAnd signal arrival time stamp T_iTo calculate the modified channel state information.

18. The computer-implemented method of claim 16, further comprising:

determining a composite steering vector v that maximizes a function of the variables with the position coordinate hypothesis, wherein the function is based on the steering vector and the modified channel state information.

19. The computer-implemented method of claim 16, further comprising:

the function is evaluated for any feasible coordinate hypothesis and the coordinate position with the highest value is selected.

20. An asynchronous system for locating a node in a wireless network architecture, comprising:

a first wireless node and a second wireless node, each of the first wireless node and the second wireless node having a wireless device with one or more processing units and RF circuitry for sending and receiving communications in the wireless network architecture; and

a third wireless node having an unknown location and a wireless device having a transmitter and a receiver to enable communication with the first and second wireless nodes in the wireless network architecture, wherein the one or more processing units of the first wireless node are configured to send or execute instructions to a cloud-based entity to determine a three-dimensional location coordinate hypothesis of the third wireless node device having an unknown location, calculate distances to the location coordinate hypothesis from the first and second wireless nodes, and obtain channel state information from the first and second wireless nodes and signal arrival timestamps, T, from the first and second wireless nodes.

21. The asynchronous system of claim 20, wherein one or more processing units of the first wireless node or a cloud-based entity execute instructions to perform operations based on channel state information, calculated distance, signal arrival timestamp T from the first wireless node and the second wireless node_iAnd calculating a transmitter response of a third wireless device from the known received responses of the first wireless node and the second wireless node.

22. The asynchronous system of claim 20, wherein the one or more processing units of the first wireless node or the cloud-based entity is configured to execute instructions to determine a composite steering vector v that maximizes a function of variables with the position coordinate hypothesis, wherein the function is based on a steering vector and a calculated transmitter response of the third wireless node.

23. The asynchronous system of claim 20, wherein the one or more processing units or cloud-based entities of the first wireless node are configured to execute instructions to evaluate a function and select a coordinate location with a highest value for any feasible coordinate hypothesis.

24. The asynchronous system of claim 20, wherein the first wireless node has a first reference clock signal, the second wireless node has a second reference clock signal, and the third wireless node has a third reference clock signal; and wherein a phase difference of the first reference clock and the second reference clock is cancelled before a usage signal arrives at a timestamp.

25. A computer-implemented method for locating a wireless arbitrary device in a wireless network architecture, comprising:

initializing a wireless network architecture with a plurality of wireless anchor nodes i;

determining a location coordinate hypothesis for a wireless node having an unknown location using at least one of the anchor node and the cloud-based entity;

calculating a distance from each anchor node i to the location coordinate hypothesis; and

obtaining channel state information and signal arrival time stamp T from each anchor node i_i。

26. The computer-implemented method of claim 25, further comprising: distance d based on raw channel state information from each anchor node i_iAnd signal arrival time stamp T_iTo calculate the modified channel state information.

27. The computer-implemented method of claim 25, further comprising:

converting the modified channel state information for each radio of each anchor node into a time-domain channel response h_i(t); and

all time domain response amplitudes sigma in time domain_i|h_iL are added together to produce the sum s (t) of the transmitter responses.

28. The computer-implemented method of claim 27, further comprising:

convolving s (t) with an appropriate window function to produce an output, the window function corresponding to the desired position accuracy and the estimated distance measurement accuracy.

29. The computer-implemented method of claim 28, further comprising:

selecting the highest value s of the output_max。

30. The computer-implemented method of claim 29, further comprising:

evaluating s for any feasible coordinate hypothesis_maxAnd the coordinate position with the highest value is selected.

31. The computer-implemented method of claim 25, wherein the wireless network architecture comprises a wireless WAN architecture.

32. The computer-implemented method of claim 25, wherein the wireless network architecture comprises at least one of a wireless Local Area Network (LAN) network architecture and a wireless WAN architecture.

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