DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 USC 102 and 103 (or as subject to pre-AIA 35 USC 102 and 103) is incorrect, any correction of the statutory basis 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.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-2 and 7-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sheynblat (US 2004/0203853 A1) in view of Smith (US 2016/0062949 A1).
In regard to claim 1, Sheynblat discloses a method for GNSS-based localization, comprising:
receiving GNSS satellite signals from at least one GNSS satellite and determining GNSS localization data using the received GNSS satellite signals (130a, 130b, 130c to 110, Fig. 1),
receiving cellular signals and determining cellular localization data using the received cellular signals (120a, 120b to 110, Fig. 1), and
evaluating a less accurate positioning subsystem using the more accurate positioning subsystem localization data to identify possible less accurate positioning subsystem source signal impairments (Fig. 2),
wherein receiving the more accurate positioning sub-system signals and determining the more accurate positioning sub-system localization data includes (i) determining a more accurate positioning sub-system-based object position using the more accurate positioning sub-system signals, and (ii) using the more accurate positioning sub-system-based object position to determine distance data describing a distance between the object and the at least one less accurate positioning subsystem source (220, 222, Fig. 2), and
wherein evaluating the less accurate positioning subsystem localization data includes comparing the distance data to less accurate positioning subsystem pseudo-range data determined from the GNSS localization data (220, Fig. 2; ¶44).
Sheynblat fails to disclose the more accurate positioning sub-system is a 5G cellular subsystem and the less accurate positioning sub-system is the GNSS subsystem.
Smith teaches a more accurate positioning sub-system is a 5G cellular subsystem and a less accurate positioning sub-system is a GNSS subsystem in a particular environment (p. 18, lines 6-9).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include this feature into the combination with a reasonable expectation of success in order to implement determining which positioning sub-system is the more accurate subsystem in different environments.
Additionally, this is a combining of prior art elements according to known methods to yield predictable results, the predictable result being that the subsystem that is the most accurate subsystem in the current environment is used to evaluate the less accurate subsystem for signal source impairments.
The Office takes Official Notice that one of ordinary skill in the art would have found it well known before the effective filing date of the invention for a cellular system to be implemented as a 5G cellular system.
The Office takes Official Notice that one of ordinary skill in the art would have found it well known before the effective filing date of the invention to perform location-finding on a vehicle.
In regard to claim 2, Sheynblat further discloses the GNSS localization data comprises at least GNSS pseudo-range data (216, 208, Fig. 2).
In regard to claim 7, Sheynblat further discloses information obtained with GNSS satellite signals and/or GNSS satellites to which an impairment has been identified is weighted or excluded from the GNSS-based localization for further processing purposes (¶47; ¶60).
In regard to claim 8, Sheynblat further discloses a computer program is configured to perform the for performing a method according to claim 1 (¶85).
In regard to claim 9, Sheynblat further discloses a non-transitory machine-readable storage medium on which the computer program according to claim 8 is stored (¶85).
In regard to claim 10, Sheynblat further discloses a localization device for an object configured so as to carry out a method according to claim 1 (Fig. 5).
In the combination, the object is a vehicle.
In regard to claim 11, Sheynblat further discloses receiving the cellular signals and determining the cellular localization data includes receiving the cellular signals from a plurality of cellular stations, each cellular signal comprises information of an absolute position of a respective cellular station of the plurality of cellular stations (120a, 120b to 110, Fig. 1; ¶31).
In the combination, the cellular data/signal/stations is 5G cellular data/signal/stations.
In regard to claim 12, Sheynblat further discloses receiving the cellular signals and determining the cellular localization data further includes using time-of-flight data of the cellular signals to determine a distance between the vehicle and each respective cellular station of the plurality of cellular stations (120a, 120b to 110, Fig. 1; ¶35-36).
In the combination, the cellular data/signals/stations is 5G cellular data/signals/stations.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sheynblat and Smith, as applied to claim 1, and further in view of Zhang (CN 110346816 A).
Sheynblat and Smith fail to teach evaluating the GNSS localization data includes identifying an impairment when a significant discrepancy between distance data and associated pseudo-range data are identified, and a discrepancy of more than 10% is considered the significant discrepancy.
Zhang teaches identifying an impairment when a significant discrepancy between distance data and associated pseudo-range data are identified, and a discrepancy of more than 10% is considered the significant discrepancy (p. 11, section ii) [where:
3 m is the discrepancy,
the error check is not passed with a discrepancy of 3 m,
the orbital altitude of a GPS satellite is 20,200 km,
the expected pseudorange should have approximately the value of the orbital altitude, or a greater value for a satellite not directly overhead,
3 m / 20,200,200 m = 1.49 x 10-7 = 1.49 x 10-5% is not sufficient to pass the error check, thus discrepancy percentages greater than that would not pass, which includes values greater than 10%, and thus the values within the scope of the claim are taught].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include this feature into the combination with a reasonable expectation of success in order to identify when a pseudorange is so incorrect that it is determined to be in error.
Additionally, this is a combining of prior art elements according to known methods to yield predictable results, the predictable result being that pseudoranges that are so incorrect that they are determined to be in error are identified.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sheynblat and Smith, as applied to claim 1, and further in view of Lee (US 2006/0267841 A1).
Sheynblat further discloses determining the position of the object using round trip delay (RTD) (¶35-36).
Sheynblat and Smith fail to teach triangulating a position of the vehicle using the determined distances between the vehicle and each respective 5G station of the plurality of 5G stations.
Lee teaches that determining a position using cellular signals based on triangulation/AOA is a known alternative to determining a position using cellular signals based on RTD (¶28).
Thus, these two elements were art-recognized equivalents at the time of the invention. One of ordinary skill in the art would have found it obvious before the effective filing date of the invention to substitute triangulation/AOA positioning for the RTD positioning of Sheynblat. Additionally, this is a simple substitution of one known, equivalent element for another to perform the same function and obtain predictable results. Because both elements are known techniques for determining the position of an object, it would have been obvious before the effective filing date of the invention to one of ordinary skill in the art to substitute one for the other to achieve the predictable result of determining the position of the object.
In the combination, the object is a vehicle.
In the combination, the cellular stations are 5G cellular stations.
The following reference(s) is/are also found relevant:
Wang (CN 110058281 A), which teaches not using a GNSS satellite when the corresponding pseudorange residual is greater that 3 m (p. 8, ¶3).
Gao (US 2014/0350885 A1), which teaches using a pseudorange residual to determine when GNSS satellite pseudoranges are of low accuracy or when then should be discarded (¶33-34).
Harper (US 2011/0287779 A1), which teaches a method for GNSS-based localization of a vehicle (¶30), comprising: a) receiving GNSS satellite signals from at least one GNSS satellite and determining GNSS localization data using the received GNSS satellite signals (1120, Fig. 11), b) receiving cellular signals and determining cellular localization data using the received 5G signals (1110, Fig. 11; ¶53), and c) evaluating GNSS localization data using the cellular localization data to identify possible GNSS satellite signal impairments (Fig. 6-9; 1130, 1140, Fig. 11). It is noted that 5G cellular signals are well known cellular signals.
Gum (US 2021/0333410 A1), which teaches that excluding an impaired satellite signal is a known alternative to weighting the satellite signal less (¶134, final sentence).
Deng (CN 112394383 A), which teaches a method for GNSS-based localization, comprising: a) receiving GNSS satellite signals from at least one GNSS satellite and determining GNSS localization data using the received GNSS satellite signals (satellites in upper left to receiver in lower left, Fig. 2; p. 2, ¶6; p. 7, ¶6), b) receiving 5G signals and determining 5G localization data using the received 5G signals (5G base stations to right to receiver in lower left, Fig. 2; p. 2, ¶6; p. 7, ¶6), and c) evaluating GNSS localization data using the 5G localization data to identify possible GNSS satellite signal impairments (p. 11, ¶3) [where when the first measurement error variance/satellite position system error is large, GNSS satellite signal impairments are large, and when the first measurement error variance/satellite position system error is small, GNSS satellite signal impairments are small].
van Diggelen '840 (US 2006/0111840 A1), which teaches a pseudorange residual is a difference between (a) a measured pseudorange and (b) a distance difference between a satellite position from satellite ephemeris and a computed approximate position (¶64).
Applicant is encouraged to consider these documents in formulating their response (if one is required) to this Office Action, in order to expedite prosecution of this application.
Response to Arguments
Applicant’s arguments on p. 6, with respect to the objection(s), have been fully considered and are persuasive. The objection(s) have been withdrawn.
Applicant’s arguments on p. 6-7, with respect to the 35 USC 101 and 112 rejection(s), have been fully considered and are persuasive. The rejection(s) have been withdrawn.
Applicant’s arguments on p. 7-11, with respect to the prior art rejection(s) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made.
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Fred H. Mull
Examiner
Art Unit 3645
/F. H. M./
Examiner, Art Unit 3645
/OLUMIDE AJIBADE AKONAI/Primary Examiner, Art Unit 3645