DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is based on the Preliminary Amendment submitted on August 13, 2024. Claims 1-3, 5-13, 23-25, and 27-31 amended. Claims 14-22 and 32-36 cancelled. Claims 1-13 and 23-31 are pending.
Information Disclosure Statement
The information Disclosure Statement (IDS) filed on November 05, 2024 has been considered by the examiner.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3, 7-9, 11-12, 23, 28, and 30 are rejected under 35 U.S.C. § 103 as being unpatentable over Biacs et al. (US 10935663 B2, hereinafter “Biacs”), and further in view of Wachter et al. (US 20170251502 A1 , hereinafter “Wachter”).
Regarding Claim 1, Biacs teaches, a method in a network node configured to communicate with a plurality of wireless devices, WDs, “ In one embodiment, aspects of SVIM are implemented on a mobile device and/or a server to retrieve SVIM data from a field of crowdsourced mobile devices” [Col. 2, lines 41-44], and “server 120 maintains a crowdsourced GNSS integrity database 140 from the many mobile devices reporting integrity metrics” [Col. 3, lines 30-33], and “Data from mobile devices may be constantly provided to the server as mobile devices traverse particular geographic locations such that the server may have a nearly constant stream of integrity monitoring to process and analyze” [Col. 4, lines 6-10]
requesting the WD to provide GNSS positioning metrics with a location estimate, when a location estimate is available at the WD, “Server 120 may additionally send a request for more or less integrity data to AP 130 or BTS 135 for distribution to mobile devices within their respective operating range.” [Col. 4, lines 31-34], and “At block 305, the embodiment (e.g., a server in the SVIM) receives integrity metrics and an associated position from a mobile device” [Col. 10, lines 42-44], and “At block 210, the embodiment estimates a position of the mobile device. In some embodiments, the estimated position may be a PVT of the mobile device.” [Col. 9, lines 14-16], and “At block 220, the embodiment provides the position of the mobile device and the one or more satellite integrity metrics. In some embodiments, the mobile device automatically sends position and metrics to a respective server for combination and processing” [Col. 9, lines 21-25].
receiving from a plurality of WDs, local GNSS positioning metrics associated to the reported location estimate, “At block 305, the embodiment (e.g., a server in the SVIM) receives integrity metrics and an associated position from a mobile device. For example, the integrity metrics and associated position may be as described above with respect to FIG. 2. The server may receive multiple integrity metrics (e.g., metrics from individual mobile devices may be bundled or otherwise packaged into a dataset such that the server can associate/tag metrics to a particular source) and associated positions from one or more mobile devices in a crowdsourced network.” [Col. 10, lines 42-51]
determining local GNSS positioning metrics applicable to the plurality of WDs, “At block 310, the embodiment combines the integrity metrics and the associated mobile device position with pre-existing crowdsourced integrity metrics and associated positions” [Col. 10, lines 52-55], and “ In some embodiments the old and new reports may have different regional information and the different regional information may be combined.” [Col. 10, lines 60-63], and “server 120 creates or updates a reference crowdsourced integrity report from the combined integrity data of multiple sources.” [Col. 3, lines 23-25]
transmitting a set of local GNSS positioning metrics to be used by at least one WD, “The updated reference crowdsourced integrity report may be made available to mobile devices 105 so that mobile devices may achieve optimized positioning or location determination by avoiding or adjusting data from one or more SVs or constellations with questionable integrity” [Col. 3, lines 25-30], and “The server can combine reports to update the crowdsourced integrity report and can update mobile devices 105 as new data is determined” [Col. 4, lines 1-3], and “At block 315, the embodiment creates or updates a crowdsourced integrity report according to the combined data from block 310. For example, in some embodiments the server receives integrity metrics from the plurality of mobile devices and creates a reference crowdsourced integrity report as introduced above with FIG. 2. In some embodiments, one or more servers continuously receive crowdsourced integrity metrics from a plurality of mobile devices and update the crowdsourced integrity metrics as new information is received.” [Col. 11, lines 4-14]
However, Biacs does not explicitly teach obtaining a capability of the WD to provide GNSS positioning metrics
In the same field of endeavor, Wachter teaches obtaining a capability of the WD to provide GNSS positioning metrics, “producing a positioning method SUPL message, wherein the positioning method SUPL message includes a posmethod parameter, and wherein the posmethod parameter includes a positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer” [0007], and “receiving a positioning method Secure User Plane Location (SUPL) message from a SUPL Location Platform (SLP); determining that the positioning method SUPL message includes a posmethod parameter that includes a positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer; in response to the positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer, providing SET capability information to the SLP using the positioning protocol layer” [0011], and “The SET 12 may also receive signals from one or more navigation satellites 20 that form all or part of a Satellite Positioning System (SPS). The SPS may include or be part of a Global Navigation Satellite System (GNSS)” [0029].
It would have been obvious to a person of ordinary skill in the art to combine the teachings of Biacs and Wachter because both references are directed to GNSS positioning systems involving communication between a network entity and wireless devices for obtaining GNSS positioning information. Incorporating Wachter capability-identification procedure into Biacs would enable the network node to determine whether a wireless device supports the requested GNSS positioning measurements before requesting those measurements, thereby improving the efficiency and reliability of collecting GNSS positioning metrics with predictable results.
Regarding Claim 3, Biacs and Wachter disclose the limitations of claim 3 as recited above in the rejection of claim 1. In addition, Biacs further teaches, wherein the set of local GNSS positioning metrics include satellite signal quality information, “the one or more integrity metrics includes carrier phase metrics from the one or more satellites, signal strength for received satellite signals” [Col. 7, lines 5-7], and “For example SVIM can detect outliers and biases in over the air broadcast navigation parameters, signal quality, predicted and network assistance data” [Col. 5, lines 24-27], and “In one embodiment, the reference crowdsourced integrity report may include expected signal strength of a satellite signal.” [Col. 8, lines 48-50], and “In one embodiment, the reference crowdsourced integrity report may include expected accuracy of a satellite signal” [Col. 8, lines 53-55]
Regarding Claim 7, Biacs and Wachter disclose the limitations of claim 7 as recited above in the rejection of claim 1. In addition, Biacs further teaches, wherein the set of local GNSS positioning metrics include a geographical reference, the geographical reference including at least one of a cell, a beam, a tracking area, a location, a line segment and a polygon, “In one embodiment, the reference crowdsourced integrity report may include geographic area associated with one or more aspects of the reference integrity report. For example, geographic area may be determined from a source identifier of the reference crowdsourced integrity report, SV, constellation, mobile device, or server.” [Col. 8, line 64 to Col. 9, line 2], and “reference crowdsourced integrity reports can indicate which particular SVs, constellations, or geographic areas are of high integrity” [Col. 5, lines 34-36], and “a SVIM server can determine a particular geographic area is relatively sparsely populated by integrity metrics and may actively request mobile devices within the area to provide one or more particular metrics.” [Col. 3, lines 57-63]
Regarding Claim 8, Biacs and Wachter disclose the limitations of claim 8 as recited above in the rejection of claim 1. In addition, Biacs further teaches, wherein the set of local GNSS positioning metrics include metrics 4an indication of at least one of differential positioning assistance data, real time kinetic solution information and inertial measurement unit data, “the server can associate/tag metrics to a particular source) and associated positions from one or more mobile devices in a crowdsourced network.” [Col. 10, lines 49-51], and “In some embodiments, the estimated position may be a PVT of the mobile device. In some embodiments position may also include acceleration of the mobile device at a particular moment in time. PVT may be determined by AP based positioning, mobile sensor dead reckoning or other positioning methods in addition to or instead of GNSS based positioning.” [Col. 9, lines 15-21]
Regarding Claim 9, Biacs and Wachter disclose the limitations of claim 9 as recited above in the rejection of claim 1. In addition, Biacs further teaches, wherein the local GNSS positioning metrics are filtered based at least in part on a comparison of satellite signal measurements to at least one of a signal quality threshold and a signal power threshold, “In some embodiments, the server may prune its integrity data based on time of acquiring the data. For example, integrity data may age at the server such that after a configurable amount of time has passed, the data may not be as reliable as newly acquired integrity data.” [Col. 3, lines 60-65], and “In some embodiments, the server may produce updated reference crowdsourced integrity reports at set intervals, when incoming data meets a threshold, or other configurable parameter” [Col. 4, lines 10-13], and “the server simply deletes old data, or may mark older data with a reduced confidence or reliability tag.” [Col. 3, lines 65-67]
Regarding Claim 11, Biacs and Wachter disclose the limitations of claim 11 as recited above in the rejection of claim 1. In addition, Wachter further teaches, wherein the network node is a location server, “receiving a request at a Secure User Plane Location (SUPL) Location Platform (SLP) for location-related service” [0007], and “sending the positioning method SUPL message from the SLP to a SUPL Enabled Terminal (SET)” [0007], and “The H-SLP 16 is responsible for SUPL service management and position determination” [0031]
It would have been obvious to one of ordinary skill in the art to implement the network node of Biacs as the SUPL Location Platform (SLP)/H-SLP location server taught by Wachter because both references are directed to network-based GNSS positioning systems in which a network entity communicates with wireless devices to obtain positioning-related information. Using Wachter’s location sever in Biacs would have provided a known network architecture for collecting GNSS positioning information while yielding predictable results with a reasonable expectation of success.
Regarding Claim 12, Biacs teaches, a network node configured to communicate with a plurality of wireless devices, WDs, “ In one embodiment, aspects of SVIM are implemented on a mobile device and/or a server to retrieve SVIM data from a field of crowdsourced mobile devices” [Col. 2, lines 41-44] ], and “server 120 maintains a crowdsourced GNSS integrity database 140 from the many mobile devices reporting integrity metrics” [Col. 3, lines 30-33], and “Data from mobile devices may be constantly provided to the server as mobile devices traverse particular geographic locations such that the server may have a nearly constant stream of integrity monitoring to process and analyze” [Col. 4, lines 6-10]
request the WD to provide GNSS positioning metrics with a location estimate, when a location estimate is available at the WD, “In one embodiment, server 120 may retrieve monitoring data (e.g., integrity metrics such as integrity metrics in a dataset or other data package) or reference crowdsourced integrity reports from devices 105 and consolidate or combine known integrity data” [Col. 3, lines 15-23], and “At block 210, the embodiment estimates a position of the mobile device. In some embodiments, the estimated position may be a PVT of the mobile device.” [Col. 9, lines14-16], and “At block 220, the embodiment provides the position of the mobile device and the one or more satellite integrity metrics. In some embodiments, the mobile device automatically sends position and metrics to a respective server for combination and processing” [Col. 9, lines 21-25].
a radio interface in communication with the processing circuitry and configured to receive from a plurality of WDs, local GNSS positioning metrics associated to a reported location estimate, “At block 305, the embodiment (e.g., a server in the SVIM) receives integrity metrics and an associated position from a mobile device. For example, the integrity metrics and associated position may be as described above with respect to FIG. 2. The server may receive multiple integrity metrics (e.g., metrics from individual mobile devices may be bundled or otherwise packaged into a dataset such that the server can associate/tag metrics to a particular source) and associated positions from one or more mobile devices in a crowdsourced network.” [Col. 10, lines 42-51], and “mobile devices 105 may send or receive updated integrity reports or integrity metrics to/from server 120 or other mobile devices through AP 130.” [Col. 4, lines 27-29]
the processing circuitry being further configured to determine local GNSS positioning metrics applicable to the plurality of WDs, “At block 310, the embodiment combines the integrity metrics and the associated mobile device position with pre-existing crowdsourced integrity metrics and associated positions” [Col. 10, lines 52-55], and “ In some embodiments the old and new reports may have different regional information and the different regional information may be combined.” [Col. 10, lines 60-63], and “server 120 creates or updates a reference crowdsourced integrity report from the combined integrity data of multiple sources.” [Col. 3, lines 23-25]
the radio interface being further configured to transmit a set of local GNSS positioning metrics to be used by at least one WD, “The updated reference crowdsourced integrity report may be made available to mobile devices 105 so that mobile devices may achieve optimized positioning or location determination by avoiding or adjusting data from one or more SVs or constellations with questionable integrity” [Col. 3, lines 25-30], and “The server can combine reports to update the crowdsourced integrity report and can update mobile devices 105 as new data is determined” [Col. 4, lines 1-3], and “At block 315, the embodiment creates or updates a crowdsourced integrity report according to the combined data from block 310. For example, in some embodiments the server receives integrity metrics from the plurality of mobile devices and creates a reference crowdsourced integrity report as introduced above with FIG. 2. In some embodiments, one or more servers continuously receive crowdsourced integrity metrics from a plurality of mobile devices and update the crowdsourced integrity metrics as new information is received.” [Col. 11, lines 4-14]
processing circuitry configured to: obtain a capability of the WD to provide GNSS positioning metrics, Biacs teaches processing circuitry, “SVIM may be implemented as software, firmware, hardware, modules, or engines of a mobile device and/or server (e.g., see device hardware 400 below with respect to FIG. 4).” [Col. 7, lines 55-58]
However, Biacs does not explicitly teach obtain a capability of the WD to provide GNSS positioning metrics
In the same field of endeavor, Wachter teaches obtain a capability of the WD to provide GNSS positioning metrics, “producing a positioning method SUPL message, wherein the positioning method SUPL message includes a posmethod parameter, and wherein the posmethod parameter includes a positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer” [0007], and “receiving a positioning method Secure User Plane Location (SUPL) message from a SUPL Location Platform (SLP); determining that the positioning method SUPL message includes a posmethod parameter that includes a positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer; in response to the positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer, providing SET capability information to the SLP using the positioning protocol layer” [0011], and “The SET 12 may also receive signals from one or more navigation satellites 20 that form all or part of a Satellite Positioning System (SPS). The SPS may include or be part of a Global Navigation Satellite System (GNSS)” [0029].
It would have been obvious to a person of ordinary skill in the art to combine the teachings of Biacs and Wachter because both references are directed to GNSS positioning systems involving communication between a network entity and wireless devices for obtaining GNSS positioning information. Incorporating Wachter capability-identification procedure into Biacs would enable the network node to determine whether a wireless device supports the requested GNSS positioning measurements before requesting those measurements, thereby improving the efficiency and reliability of collecting GNSS positioning metrics with predictable results.
Regarding Claim 23, Biacs teaches, a method in a WD configured to communicate with a network node and a plurality of satellites, “ In one embodiment, aspects of SVIM are implemented on a mobile device and/or a server to retrieve SVIM data from a field of crowdsourced mobile devices” [Col. 2, lines 41-44], and “For example, a mobile device may monitor a SV and/or a constellation of SVs and determine integrity metrics for particular SVs and/or the constellation. The integrity metrics may be provided to a server (e.g., in an integrity metric dataset or other data package/arrangement)” [Col. 2, lines 44-48], and “mobile devices 105 may send or receive updated integrity reports or integrity metrics to/from server 120 or other mobile devices through AP 130.” [Col. 4, lines 27-29]
receiving a request from the network node to provide GNSS positioning metrics with a location estimate, when a location estimate is available at the WD, “Server 120 may additionally send a request for more or less integrity data to AP 130 or BTS 135 for distribution to mobile devices within their respective operating range.” [Col. 4, lines 31-34], and “a SVIM server can determine a particular geographic area is relatively sparsely populated by integrity metrics and may actively request mobile devices within the area to provide one or more particular metrics.” [Col. 3, lines 57-63], and “At block 210, the embodiment estimates a position of the mobile device. In some embodiments, the estimated position may be a PVT of the mobile device.” [Col. 9, lines14-16], and “At block 220, the embodiment provides the position of the mobile device and the one or more satellite integrity metrics. In some embodiments, the mobile device automatically sends position and metrics to a respective server for combination and processing” [Col. 9, lines 21-25]
determining local GNSS positioning metrics based at least in part on satellite signal measurements by the WD, “At block 215, the embodiment determines, at the mobile device, one or more satellite integrity metrics for the one or more satellites based at least on signals from the one or more satellites.” [Col. 9, lines 6-9], and “In some embodiments, the one or more integrity metrics includes determination of satellite signal integrity” [Col. 7, lines 27-28], and “In some embodiments, the one or more integrity metrics includes confidence rating for one or more other integrity metrics. For example, the confidence of any of the metrics herein (e.g., confidence in accuracy of the navigation message, pseudorange, pseudorange rate, unique identifier, carrier phase etc.) may have an associated rating which may be implemented in a variety of ways.” [Col. 7, lines 41-47], and “In one embodiment, the reference crowdsourced integrity report may include expected signal strength of a satellite signal.” [Col. 8, lines 48-50]
reporting the local GNSS positioning metrics with a location estimate when a location estimate is available at the WD, “At block 210, the embodiment estimates a position of the mobile device. In some embodiments, the estimated position may be a PVT of the mobile device.” [Col. 9, lines14-16], and “At block 220, the embodiment provides the position of the mobile device and the one or more satellite integrity metrics. In some embodiments, the mobile device automatically sends position and metrics to a respective server for combination and processing” [Col. 9, lines 21-25], and “At block 305, the embodiment (e.g., a server in the SVIM) receives integrity metrics and an associated position from a mobile device” [Col. 10, lines 42-44]
receiving GNSS positioning metrics from the network node, the GNSS positioning metrics being based at least in part on local GNSS positioning metrics received from a plurality of WDs, “mobile devices 105 may send or receive updated integrity reports or integrity metrics to/from server 120 or other mobile devices through AP 130.” [Col. 4, lines 27-29], and “The updated reference crowdsourced integrity report may be made available to mobile devices 105 so that mobile devices may achieve optimized positioning or location determination by avoiding or adjusting data from one or more SVs or constellations with questionable integrity” [Col. 3, lines 25-30], and “In some embodiments, one or more servers continuously receive crowdsourced integrity metrics from a plurality of mobile devices and update the crowdsourced integrity metrics as new information is received.” [Col. 11, lines 9-13], and “server 120 creates or updates a reference crowdsourced integrity report from the combined integrity data of multiple sources.” [Col. 3, lines 23-25]
determining a position of the WD based at least in part on the local and regional GNSS positioning metrics, “The updated reference crowdsourced integrity report may be made available to mobile devices 105 so that mobile devices may achieve optimized positioning or location determination by avoiding or adjusting data from one or more SVs or constellations with questionable integrity” [Col. 3, lines 25-30], and “A mobile device may determine on a case by case basis or by a configuration setting/parameter how particular SVs, constellations, or geographic areas which have low integrity should be treated when performing GNSS based positioning” [Col. 5, lines 37-41], and “In one embodiment, the quantity and quality of the crowdsourced GNSS integrity monitoring data from a large number of worldwide mobile devices can provide a flexible and extensive warning or control mechanism.” [Col. 5, lines 29-33]
However, Biacs does not explicitly teach transmitting to the network node a capability of the WD for providing GNSS positioning metrics.
In the same field of endeavor, Wachter teaches transmitting to the network node a capability of the WD for providing GNSS positioning metrics, “producing a positioning method SUPL message, wherein the positioning method SUPL message includes a posmethod parameter, and wherein the posmethod parameter includes a positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer” [0007], and “receiving a positioning method Secure User Plane Location (SUPL) message from a SUPL Location Platform (SLP); determining that the positioning method SUPL message includes a posmethod parameter that includes a positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer; in response to the positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer, providing SET capability information to the SLP using the positioning protocol layer” [0011], and “The SET 12 may also receive signals from one or more navigation satellites 20 that form all or part of a Satellite Positioning System (SPS). The SPS may include or be part of a Global Navigation Satellite System (GNSS)” [0029].
Therefore, it would have been obvious to modify Biacs to incorporate Wachter’s SET capability-transfer procedure because Wachter teaches providing ST capability information to the SLP using the positioning protocol layer before the positioning procedure, thereby enabling the network node to know the WD’s positioning capability before requesting GNSS positioning metrics from the WD.
Regarding Claim 28, Biacs and Wachter disclose the limitations of claim 28 as recited above in the rejection of claim 23. In addition, Biacs further teaches, wherein the local GNSS positioning metrics are based at least in part on comparisons of satellite signal measurements to at least one of a signal quality threshold and a signal power threshold, “In some embodiments, the server may prune its integrity data based on time of acquiring the data. For example, integrity data may age at the server such that after a configurable amount of time has passed, the data may not be as reliable as newly acquired integrity data.” [Col. 3, lines 60-65], and “In some embodiments, the server may produce updated reference crowdsourced integrity reports at set intervals, when incoming data meets a threshold, or other configurable parameter” [Col. 4, lines 10-13], and “the server simply deletes old data, or may mark older data with a reduced confidence or reliability tag.” [Col. 3, lines 65-67] The method of claim 23, wherein the local GNSS positioning metrics are based at least in part on comparisons of satellite signal measurements to at least one of a signal quality threshold and a signal power threshold.
Regarding Claim 30, Biacs teaches, a wireless device configured to communicate with a network node and a plurality of satellites, the WD comprising: “ In one embodiment, aspects of SVIM are implemented on a mobile device and/or a server to retrieve SVIM data from a field of crowdsourced mobile devices” [Col. 2, lines 41-44], and “For example, a mobile device may monitor a SV and/or a constellation of SVs and determine integrity metrics for particular SVs and/or the constellation. The integrity metrics may be provided to a server (e.g., in an integrity metric dataset or other data package/arrangement)” [Col. 2, lines 44-48], and “mobile devices 105 may send or receive updated integrity reports or integrity metrics to/from server 120 or other mobile devices through AP 130.” [Col. 4, lines 27-29], and “SVIM may be implemented as software, firmware, hardware, modules, or engines of a mobile device and/or server (e.g., see device hardware 400 below with respect to FIG. 4).” [Col. 7, lines 55-58]
Biacs teaches a wireless device including a radio interface for communicating with the network node. Specifically, Biacs teaches that “mobile devices 105 may send or receive updated integrity reports or integrity metrics to/from server 120 or other mobile devices through AP 130” [Col. 4, lines 27-29]
A person of the skill in the art would understand that communication between the mobile device and the server through AP 130 is performed using the wireless device’s radio interface.
receive a request from the network node to provide GNSS positioning metrics with a location estimate, when a location estimate is available at the WD, “Server 120 may additionally send a request for more or less integrity data to AP 130 or BTS 135 for distribution to mobile devices within their respective operating range.” [Col. 4, lines 31-34], and “a SVIM server can determine a particular geographic area is relatively sparsely populated by integrity metrics and may actively request mobile devices within the area to provide one or more particular metrics.” [Col. 3, lines 57-63], and “At block 210, the embodiment estimates a position of the mobile device. In some embodiments, the estimated position may be a PVT of the mobile device.” [Col. 9, lines14-16], and “At block 220, the embodiment provides the position of the mobile device and the one or more satellite integrity metrics. In some embodiments, the mobile device automatically sends position and metrics to a respective server for combination and processing” [Col. 9, lines 21-25]
processing circuitry in communication with the radio interface and configured to determine local GNSS positioning metrics based at least in part on satellite signal measurements by the WD, “SVIM may be implemented as software, firmware, hardware, modules, or engines of a mobile device and/or server (e.g., see device hardware 400 below with respect to FIG. 4).” [Col. 7, lines 55-58], and “At block 215, the embodiment determines, at the mobile device, one or more satellite integrity metrics for the one or more satellites based at least on signals from the one or more satellites.” [Col. 9, lines 6-9], and “In some embodiments, the one or more integrity metrics includes confidence rating for one or more other integrity metrics. For example, the confidence of any of the metrics herein (e.g., confidence in accuracy of the navigation message, pseudorange, pseudorange rate, unique identifier, carrier phase etc.) may have an associated rating which may be implemented in a variety of ways.” [Col. 7, lines 41-47], and “In one embodiment, the reference crowdsourced integrity report may include expected signal strength of a satellite signal.” [Col. 8, lines 48-50]
the radio interface being further configured to: report the local GNSS positioning metrics with a location estimate when a location estimate is available at the WD, “At block 210, the embodiment estimates a position of the mobile device. In some embodiments, the estimated position may be a PVT of the mobile device.” [Col. 9, lines14-16], and “At block 220, the embodiment provides the position of the mobile device and the one or more satellite integrity metrics. In some embodiments, the mobile device automatically sends position and metrics to a respective server for combination and processing” [Col. 9, lines 21-25], and “At block 305, the embodiment (e.g., a server in the SVIM) receives integrity metrics and an associated position from a mobile device” [Col. 10, lines 42-44]
receive GNSS positioning metrics from the network node, the GNSS positioning metrics being based at least in part on local GNSS positioning metrics received from a plurality of WDs, “mobile devices 105 may send or receive updated integrity reports or integrity metrics to/from server 120 or other mobile devices through AP 130.” [Col. 4, lines 27-29], and “The updated reference crowdsourced integrity report may be made available to mobile devices 105 so that mobile devices may achieve optimized positioning or location determination by avoiding or adjusting data from one or more SVs or constellations with questionable integrity” [Col. 3, lines 25-30], and “In some embodiments, one or more servers continuously receive crowdsourced integrity metrics from a plurality of mobile devices and update the crowdsourced integrity metrics as new information is received.” [Col. 11, lines 9-13], and “server 120 creates or updates a reference crowdsourced integrity report from the combined integrity data of multiple sources.” [Col. 3, lines 23-25]
the processing circuitry being further configured to determine a position of the WD based at least in part on the local and regional GNSS positioning metrics, “The updated reference crowdsourced integrity report may be made available to mobile devices 105 so that mobile devices may achieve optimized positioning or location determination by avoiding or adjusting data from one or more SVs or constellations with questionable integrity” [Col. 3, lines 25-30], and “A mobile device may determine on a case by case basis or by a configuration setting/parameter how particular SVs, constellations, or geographic areas which have low integrity should be treated when performing GNSS based positioning” [Col. 5, lines 37-41], and “In one embodiment, the quantity and quality of the crowdsourced GNSS integrity monitoring data from a large number of worldwide mobile devices can provide a flexible and extensive warning or control mechanism.” [Col. 5, lines 29-33]
Biacs teaches transmitting GNSS positioning metrics from a wireless device to the network node. For example, “mobile devices 105 may send or receive updated integrity reports or integrity metrics to/from server 120 or other mobile devices through AP 130” [Col. 4, lines 27-29], and “At block 220, the embodiment provides the position of the mobile device and the one or more satellite integrity metrics. In some embodiments, the mobile device automatically sends position and metrics to a respective server for combination and processing” [Col. 9, lines 21-25].
However, Biacs does not explicitly teach transmit to the network node a capability of the WD for providing GNSS positioning metrics.
In the same field of endeavor, Wachter teaches transmit to the network node a capability of the WD for providing GNSS positioning metrics, “producing a positioning method SUPL message, wherein the positioning method SUPL message includes a posmethod parameter, and wherein the posmethod parameter includes a positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer” [0007], and “receiving a positioning method Secure User Plane Location (SUPL) message from a SUPL Location Platform (SLP); determining that the positioning method SUPL message includes a posmethod parameter that includes a positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer; in response to the positioning protocol indicator indicating that SET capability transfer and positioning method selection are to be conducted in a positioning protocol layer, providing SET capability information to the SLP using the positioning protocol layer” [0011], and “The SET 12 may also receive signals from one or more navigation satellites 20 that form all or part of a Satellite Positioning System (SPS). The SPS may include or be part of a Global Navigation Satellite System (GNSS)” [0029].
a radio interface configured to: receive a request from the network node to provide GNSS positioning metrics with a location estimate, when a location estimate is available at the WD, “receiving or cause to receive a positioning measurement request from a positioning server” [Col. 15, lines 29-31]
Therefore, it would have been obvious to modify Biacs to incorporate Wachter’s SET capability transfer procedure because Wachter teaches providing SET capability information to the SLP using the positioning protocol later before the positioning procedure, thereby enabling the network node to know the WD’s positioning capability before requesting GNSS positioning metrics from the WD.
Claims 2, 4, 6, 13, 24-27, and 31 are rejected under 35 U.S.C. § 103 as being unpatentable over Biacs et al. (US 10935663 B2, hereinafter “Biacs”, in view of Wachter et al. (US 20170251502 A1 , hereinafter “Wachter”), and further in view of Irish et al. (US 10656282 B2, hereinafter “Irish”)
Regarding Claim 2, Biacs and Wachter disclose the limitations of claim 2 as recited above in the rejection of claim 1. However, Biacs and Wachter do not explicitly teach, wherein the local GNSS positioning metrics include, for each of at least one WD, a number of detected satellites and a number of satellites used for positioning.
In the same field of endeavor, Irish teaches, wherein the local GNSS positioning metrics include, for each of at least one WD, a number of detected satellites and a number of satellites used for positioning, “Nt represents the number of satellites in view” [Col. 7, lines 55-56], and “receiving global navigation satellite system (GNSS) fix data that represents GNSS calculated position of the user device, receiving signal strength data associated with each satellite communicating with the user device,” [Col. 32, lines 58-61]
It would have been obvious to one of ordinary skill in the art to incorporate Irish’s satellite count metrics into Biacs crowdsourced framework because satellite count is a fundamental, well-known GNSS quality indicator characterizing the local GNSS environment at a position – precisely the type of metric Biacs collects and aggregates – with predictable improvement in positioning quality and no inventive step required.
Regarding Claim 4, Biacs and Wachter disclose the limitations of claim 4 as recited above in the rejection of claim 3. However, Biacs and Wachter do not explicitly teach, wherein the satellite signal quality information includes an indication whether a satellite signal is line of sight.
In the same field of endeavor, Irish teaches, wherein the satellite signal quality information includes an indication whether a satellite signal is line of sight, “In GNSS and other wireless communication , line - of - sight ( LOS ) channels are characterized by statistically higher received power levels than those in which the LOS signal component is blocked ( e.g. , non - LOS or NLOS channels” [Col. 2, lines 13-17], and “higher SNR indicates that the path from the receiver to the satellite is likely LOS, while lower SNR indicates that the path from the receiver to the satellite is likely NLOS” [Col. 2, lines 27-30]
It would have been obvious to one of ordinary skill in the art to modify the crowdsourced GNSS integrity system of Biacs, as previously modified to incorporate the SET capability transfer procedure taught by Wachter, to further incorporate the LOS/NLOS determination taught by Irish. Biacs collects, aggregates, and distributes GNSS integrity metrics from multiple wireless devices to improve positioning performance, while Irish teaches determining LOS/NLOS information from satellite signal measurements as an indicator of satellite signal quality. Incorporating Irish’s LOS/NLOS determination into Biacs’ crowdsourced GNSS integrity framework would provide additional satellite signal quality information for generating more reliable GNSS integrity metrics and improving positioning accuracy. Such a combination merely applies a known satellite signal quality technique to Biacs’ existing crowdsourced GNSS integrity system using known techniques, yielding predictable results with a reasonable expectation of success.
Claim 5 is rejected under 35 U.S.C. § 103 as being unpatentable over Biacs et al. (US 10935663 B2, hereinafter “Biacs”, in view of Wachter et al. (US 20170251502 A1 , hereinafter “Wachter”), and further in view of Sun et al. (US 20150142311 A1, hereinafter “Sun”)
Regarding Claim 5, Biacs and Wachter disclose the limitations of claim 5 as recited above in the rejection of claim 1. However, Biacs and Wachter do not explicitly teach wherein the set of local GNSS positioning metrics include an average of satellite signal measurements.
Sun teaches that “Average Signal Strength Value of All Tracked Satellites in View ( C/N 0) 206.” [0055], and “average GPS signal strength of all tracked satellites C/N 0. “ [0059], and further explain “C/N0(N, ti) is the GPS signal strength (carrier to noise ratio) of the satellite N at time ti, and T is the average time period, Ns is the number of tracked satellites at time ti,”
Thus, Sun explicitly teaches that the local GNSS positioning metric include an average of satellite signal measurement, namely an average GPS signal strength (C/No) computed over tracked satellites.
It would have been obvious to one of ordinary skill in the art to incorporate Sun’s averaged satellite signal strength (C/No) metric into the crowdsourced GNSS positioning framework of Biacs because both references improve GNSS positioning using satellite-derived measurements. Incorporating Sun’s averaged satellite signal strength metric would provide a more robust and stable GNSS positioning metric by reducing the effects of short-term signal fluctuations while maintaining combability with Biacs’ collection and processing of GNSS positioning metrics, yielding predictable results with a reasonable expectation of success.
Regarding Claim 6, Biacs and Wachter disclose the limitations of claim 6 as recited above in the rejection of claim 1. However, Biacs and Wachter do not explicitly teach, wherein the set of local GNSS positioning metrics include a dilution of precision received from at least one WD of the plurality of WDs.
In the same field of endeavor, Irish teaches, wherein the set of local GNSS positioning metrics include a dilution of precision received from at least one WD of the plurality of WDs, “Typically, the GNSS location fix is given as yt=Hxt+et, where the covariance of the error et is estimated using standard Dilution of Precision computations.” [Col. 9, lines 38-40], and “the covariance is estimated using standard Dilution of Precision techniques” [Col. 9, lines 50-51]
It would have been obvious to further modify the crowdsourced GNSS integrity system of Biacs, as previously modified to incorporate the SET capability transfer procedure taught by Wachter and the LOS/NLOS determination taught by Irish, to further incorporate the DOP metric because Biacs collects, aggregates, and distributes GNSS positioning metrics from multiple wireless devices to improve GNSS positioning performance, while the DOP reference teaches dilution of precision as a recognized indicator of GNSS positioning geometry and positioning accuracy. Incorporating the DOP metric into Biacs’ crowdsourced GNSS integrity framework would provide additional GNSS quality information for evaluating the reliability and accuracy of the collected positioning metrics, thereby improving the integrity information generated by the network node. Such a modification merely applies a known GNSS quality metric to Biacs’ existing crowdsourced GNSS integrity system using known techniques, yielding predictable results with a reasonable expectation of success.
Regarding Claim 13, Biacs and Wachter disclose the limitations of claim 13 as recited above in the rejection of claim 12. However Biacs and Wachter do not explicitly teach, wherein the local GNSS positioning metrics includes, for each of at least one WD, a number of detected satellites and a number of satellites used for positioning.
In the same field of endeavor, Irish teaches, wherein the local GNSS positioning metrics includes, for each of at least one WD, a number of detected satellites and a number of satellites used for positioning, “mobile device 102 is capable of measuring an attribute of the GNSS signal provided each of the plurality of satellites 104.” [Col. 4, lines 32-34], and “mobile device 102 monitors the signal-to-noise ratio (SNR) of the received GNSS data” [Col. 4, lines 35-36]
It would have been obvious to further modify the crowdsourced GNSS integrity system of Biacs, as previously modified to incorporate the SET capability transfer procedure taught by Wachter, to further incorporate the satellite count information taught by Irish because the number of detected satellites and the number of satellite used for positioning are recognized indicators of GNSS positioning quality. Incorporating these metrics into Biacs’ crowdsourced GNSS integrity framework would improve the evaluation of positioning reliability using known GNSS quality metrics, yielding predictable results with a reasonable expectation of success.
Regarding Claim 24, Biacs and Wachter disclose the limitations of claim 24 as recited above in the rejection of claim 23. However, Biacs and Wachter do not explicitly teach, wherein the local GNSS positioning metrics include, for each of at least one WD, a number of detected satellites and a number of satellites used for positioning.
In the same field of endeavor, Irish teaches, wherein the local GNSS positioning metrics include, for each of at least one WD, a number of detected satellites and a number of satellites used for positioning, “mobile device 102 is capable of measuring an attribute of the GNSS signal provided each of the plurality of satellites 104.” [Col. 4, lines 32-34], and “mobile device 102 monitors the signal-to-noise ratio (SNR) of the received GNSS data” [Col. 4, lines 35-36]
It would have been obvious to further modify the crowdsourced GNSS integrity system of Biacs, as previously modified to incorporate the SET capability transfer procedure taught by Wachter, to further incorporate the satellite count information taught by Irish because the number of detected satellites and the number of satellite used for positioning are recognized indicators of GNSS positioning quality. Incorporating these metrics into Biacs’ crowdsourced GNSS integrity framework would improve the evaluation of positioning reliability using known GNSS quality metrics, yielding predictable results with a reasonable expectation of success.
Regarding Claim 25, Biacs, Wachter, and Irish disclose the limitations of claim 25 as recited above in the rejection of claim 23. In addition, Biacs further teaches, wherein the GNSS positioning metrics include satellite signal quality information, “For example SVIM can detect outliers and biases in over the air broadcast navigation parameters, signal quality, predicted and network assistance data” [Col. 5, lines 24-27], and “In one embodiment, the reference crowdsourced integrity report may include expected signal strength of a satellite signal.” [Col. 8, lines 48-50]
Regarding Claim 26, Biacs and Wachter disclose the limitations of claim 26 as recited above in the rejection of claim 25. However, Biacs and Wachter do not explicitly teach, wherein the satellite signal quality information includes an indication whether a satellite signal is line of sight.
In the same field of endeavor, Irish teaches, wherein the satellite signal quality information includes an indication whether a satellite signal is line of sight, “In GNSS and other wireless communication, line-of-sight (LOS) channels are characterized by statistically higher received power levels than those in which the LOS signal component is blocked (e.g., non-LOS or NLOS channels)” [Col. 2, lines 13-16], and “higher SNR indicates that the path from the receiver to the satellite is likely LOS, while lower SNR indicates that the path from the receiver to the satellite is likely NLOS.” [Col. 2, lines 27--30]
It would have been obvious to one of ordinary skill in the art to modify the crowdsourced GNSS integrity system of Biacs, as previously modified to incorporate the SET capability transfer procedure taught by Wachter, to further incorporate the LOS/NLOS determination taught by Irish. Biacs collects, aggregates, and distributes GNSS integrity metrics from multiple wireless devices to improve positioning performance, while Irish teaches determining LOS/NLOS information from satellite signal measurements as an indicator of satellite signal quality. Incorporating Irish’s LOS/NLOS determination into Biacs’ crowdsourced GNSS integrity framework would provide additional satellite signal quality information for generating more reliable GNSS integrity metrics and improving positioning accuracy. Such a combination merely applies a known satellite signal quality technique to Biacs’ existing crowdsourced GNSS integrity system using known techniques, yielding predictable results with a reasonable expectation of success.
Regarding Claim 27, Biacs and Wachter disclose the limitations of claim 27 as recited above in the rejection of claim 23. However, Biacs and Wachter do not explicitly teach, wherein the GNSS positioning metrics include a dilution of precision from at least one of the plurality of WDs.
In the same field of endeavor, Irish teaches, wherein the set of local GNSS positioning metrics include a dilution of precision received from at least one WD of the plurality of WDs, “Typically, the GNSS location fix is given as yt=Hxt+et, where the covariance of the error et is estimated using standard Dilution of Precision computations.” [Col. 9, lines 38-40], and “the covariance is estimated using standard Dilution of Precision techniques” [Col. 9, lines 50-51]
It would have been obvious to further modify the crowdsourced GNSS integrity system of Biacs, as previously modified to incorporate the SET capability transfer procedure taught by Wachter and the LOS/NLOS determination taught by Irish, to further incorporate the DOP metric because Biacs collects, aggregates, and distributes GNSS positioning metrics from multiple wireless devices to improve GNSS positioning performance, while the DOP reference teaches dilution of precision as a recognized indicator of GNSS positioning geometry and positioning accuracy. Incorporating the DOP metric into Biacs’ crowdsourced GNSS integrity framework would provide additional GNSS quality information for evaluating the reliability and accuracy of the collected positioning metrics, thereby improving the integrity information generated by the network node. Such a modification merely applies a known GNSS quality metric to Biacs’ existing crowdsourced GNSS integrity system using known techniques, yielding predictable results with a reasonable expectation of success.
Regarding Claim 31, Biacs and Wachter disclose the limitations of claim 31 as recited above in the rejection of claim 30. However, Biacs and Wachter do not explicitly teach, wherein the local GNSS positioning metrics include, for each of at least one WD, a number of detected satellites and a number of satellites used for positioning.
In the same field of endeavor, Irish teaches, wherein the local GNSS positioning metrics include, for each of at least one WD, a number of detected satellites and a number of satellites used for positioning, “mobile device 102 monitors the signal-to-noise ratio (SNR) of the received GNSS data” [Col. 4, lines 35-36], and “mobile device 102 communicates the received GNSS data and SNR data to a cloud-based localization server” [Col. 4, lines 35-46], and further “receiving global navigation satellite system (GNSS) fix data that represents GNSS calculated position of the user device, receiving signal strength data associated with each satellite communicating with the user device,” [Col. 32, lines 58-61]
It would have been obvious to one of ordinary skill in the art to incorporate Irish’s satellite count metrics into Biacs crowdsourced framework because satellite count is a fundamental, well-known GNSS quality indicator characterizing the local GNSS environment at a position – precisely the type of metric Biacs collects and aggregates – with predictable improvement in positioning quality and no inventive step required.
Claim 10 is rejected under 35 U.S.C. § 103 as being unpatentable over Biacs et al. (US 10935663 B2, hereinafter “Biacs”), in view of Wachter et al. (US 20170251502 A1 , hereinafter “Wachter”), and further in view of Muquet (US 10362556 B2, hereinafter “Muquet”)
Regarding Claim 10, Biacs and Wachter disclose the limitations of claim 10 as recited above in the rejection of claim 1. In addition, Biacs further teaches transmitting the crowdsourced GNSS integrity report to mobile devices, “The updated reference crowdsourced integrity report may be made available to mobile devices 105 so that mobile devices may achieve optimized positioning or location determination by avoiding or adjusting data from one or more SVs or constellations with questionable integrity” [Col. 3, lines 25-30], and “The server can combine reports to update the crowdsourced integrity report and can update mobile devices 105 as new data is determined” [Col. 4, lines 1-3]
However, Biacs does not explicitly teach that transmitting the set of local GNSS positioning metrics includes broadcasting or unicasting the set of local GNSS positioning metrics.
Muquet teaches transmitting GNSS positioning assistance information using broadcast and unicast transmission modes, wherein transmitting the set of local GNSS positioning metrics to at least one WD includes one of broadcasting and unicasting the set of local GNSS positioning metrics, “Assistance information is always unicast (sent to a unique UE) while it could be broadcast to all the UEs within a cell.” [Col. 2, lines 63-65]
It would have been obvious to one of ordinary skill in the art to modify Biacs’ transmission of crowdsourced GNSS positioning metrics with the broadcast or unicast transmission techniques taught by Muquet because both references related to network-assisted GNSS positioning. Muquest teaches broadcast and unicast as known alternative communication modes for delivering GNSS positioning assistance information, and applying either known transmission mode to Biacs’ distribution of GNSS positioning metrics would have been a routine design choice yielding predictable results and a reasonable expectation of success.
Claim 29 is rejected under 35 U.S.C. § 103 as being unpatentable over Biacs et al. (US 10935663 B2, hereinafter “Biacs”, in view of Wachter et al. (US 20170251502 A1 , hereinafter “Wachter”), and further in view of Ryden et al. (US 11153745 B2, hereinafter “Ryden”)
Regarding Claim 29, Biacs and Wachter disclose the limitations of claim 29 as recited above in the rejection of claim 23. In addition, Biacs further teaches multiple position estimate sources and associating or tagging collected positioning metrics with the source from which the corresponding position estimate was obtained, “the server can associate/tag metrics to a particular source) and associated positions from one or more mobile devices in a crowdsourced network.” [Col. 10, lines 49-51], and “In some embodiments, the estimated position may be a PVT of the mobile device. In some embodiments position may also include acceleration of the mobile device at a particular moment in time. PVT may be determined by AP based positioning, mobile sensor dead reckoning or other positioning methods in addition to or instead of GNSS based positioning” [Col. 9, lines 15-21]
Accordingly, Biacs teaches that collected GNSS positioning metrics are associated with the source of the corresponding position estimate and that position estimates may originate from different positioning methods, including GNSS positioning, AP-based positioning, and mobile sensor dead reckoning.
However, Biacs and Wachter do not explicitly teach that the position estimate classification includes an indication of inertial measurement unit (IMU) data, as recited in the claim.
Ryden teaches that wireless devices generate position estimates using an inertial measurement unit (IMU), “Most of the UEs in the market today are equipped with an Inertial Measurement Unit (IMU). The IMU may contain for example a 3-axis gyroscope and a 3-axis accelerometer… The measurements made by these sensors can be fused to form an estimate of UE's position.” [Col. 4, lines 11-19], and further “IMU, which is also referred to as an Inertial Navigation System (INS), is based on motion sensors such as accelerometers, rotation sensors such as gyroscopes), and occasionally magnetic sensors such as magnetometers. These sensors are able to continuously calculate, e.g. via so-called “dead reckoning”, the position, orientation, and velocity including direction and speed of movement, of the UE.” [Col. 4, lines 23-29], and “When sophisticated IMU sensors are used, this can aid in location estimation with respect to a reference position and a time when a GPS signal is lost.” [Col. 4, lines 59-62]
Accordingly, Ryden teaches generating position estimates using IMU data through dead reckoning.
Biacs teaches associating collected GNSS positioning metrics with the source of the corresponding position estimate and teaches that one such position source is mobile sensor dead reckoning. Ryden teaches that dead reckoning is performed using an IMU comprising accelerometers and gyroscopes to generate position estimate.
A person of ordinary skill in the art would have recognized the mobile sensor dead reckoning position source of Biacs as an IMU-based position source in view of the teachings of Ryden. Associating or tagging the collected GNSS positioning metrics with that IMU-based position source would have indicated that the corresponding position estimate was generated using inertial measurement unit data, thereby teaching the claimed position estimate classification including an indication of inertial measurement unit data.
It would have been obvious to a person of ordinary skill in the art to incorporate the IMU-based dead reckoning position source taught by Ryden into source-tagging framework of Biacs because both references relate to GNSS positioning system in which wireless devices generate position estimates using multiple positioning methods. Incorporating the known IMU-based dead reckoning position source in to Biacs would have enabled the server to distinguish position estimates generated from inertial navigation form those generated using other positioning methods, thereby improving interpretation and use of the collected GNSS positioning metrics while achieving predictable results with a reasonable expectation of success.
Conclusion
The prior art made of record not relied upon and considered pertinent to Applicant’s disclosure:
Bandi et al. (US 12656502 B2) Node-based Global Navigation Satellite System discloses a plurality of nodes distributed across a geographic area forming a mesh network of nodes. A node can be fixed or in motion and has its precisely determined position and AI capabilities, in any given geographical location. Each node receives GNSS signals from one or more GNSS satellites and distributes its own real-time emulated PNT signal to the other nodes and a user receiver, that may be used for PNT in the event that the GNSS satellites' signals become compromised or are unavailable.
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SANG PHUOC. LE
Examiner
Art Unit 2641
/SANG PHUOC LE/Examiner, Art Unit 2641
/CHARLES N APPIAH/Supervisory Patent Examiner, Art Unit 2641
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