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 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.
Response to Amendment
The following addresses applicant’s remarks/amendments dated 20th February 2026.
Claims 1, and 6 were amended; claim 5 was cancelled; no new Claims were added; therefore, claims 1-4 and 6-20 are pending in current application and are addressed below.
Response to Arguments
Applicant’s arguments, see page 7-8, filed on 20th February 2026, with respect to the rejection(s) of claim(s) 1 under 35 U.S.C. 102 have been fully considered and are not persuasive.
In response to applicant’s arguments, see page 7-8, filed on 20th February 2026, that While Akhlaq’s “lattice points” (e.g., Qz) may correspond to integer vector wrapping variable candidates, there is no explicit teaching in Akhlaq that the projection mentioned by Akhlaq at 5207 as applied by the Office takes line segments and projects such segments in phase space to generate line segment points. Because Akhlaq does not disclose “generating a plurality of projected line segment points …..the plurality of unwrapped depths”, Akhlaq does not anticipate amended claim 1.
Examiner respectfully disagrees. As stated in Office Action dated on 24th November 2025, Akhlaq disclosed in Fig. 1, page 5206, right column, transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables); page 5207, right column, disclosed independent vectors from m-dimensional Euclidean space Rm with m ≥ n. The set of vectors (ꓥ = {u1b1+….+unbn; u1,…,un Є Z }) is called an n-dimensional lattice… Let H be an n-k dimensional (when k=1, then H is the n-1 dimensional subspace orthogonal to v) subspace of Rn (this is equivalent to project the generated line segment to n-1 dimensional subspace H to generate plurality of projected line segment points which corresponds with respect unwrapped depths) … The subspace Hꓕ contain the line of vectors {rv; r Є R} (page 5208, left column, first paragraph)… The closed Voronois cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point; Fig. 1, page 5208, further disclosed plurality of projected line segment points. Using equation 7 (wrapped phase (Yn) and unwrapped depth (ro)) with project method disclosed above to predictably get a plurality of projected line segment points wherein each of the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths. Furthermore, this can also be seen in page 5207, left column regarding how to estimate ζ of the wrapping variables by projection matrix onto the N-1 dimensional subspace orthogonal to w and I is the NxN identity matrix. Therefore, the projection mentioned by Akhlaq at 5207 is used to generating a plurality of projected line segment points which the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths is disclosed in Akhlaq page 5206-5029, Fig. 1. Thus the rejection is maintained.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 2, 4, 6 and 17-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Akhlaq et al. (“Selecting Wavelengths for Least Squares Range Estimation”, October 15 2016, Vol. 64, No. 20, IEEE Transactions on Signal Processing, hereinafter “Akhlaq”).
Regarding claim 1, Akhlaq teaches a method for phase unwrapping in time-of-flight systems, comprising:
determining a plurality of wrapped distance measurements at a respective plurality of frequencies, wherein each of the plurality of wrapped distance measurements corresponds to a respective phase (Akhlaq; page 5206, left column, section II, disclosed the estimation of the range (ro/2) from the signal y(t), where range is corresponds to phase Ө with respective frequency f (equation 1-3). Page 5206, right column, disclosed range ro and ro + kλ result in the same phase difference. For this reason the range is identifiable from the phase only if we assume ro to lie in some interval of length λ. To address this problem is to transmit multiple signals at multiple different frequencies and observe the phase at each; this implies that a plurality of wrapped distance measurement at a respective plurality of frequencies will be determined during the process);
generating a plurality of unwrapped depths for each of the plurality of wrapped distance measurements, based on the respective phase (Akhlaq; page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables));
generating a plurality of projected line segment points wherein each of the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths (Akhlaq; Fig. 1, page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables); page 5207, right column, disclosed independent vectors from m-dimensional Euclidean space Rm with m ≥ n. The set of vectors (ꓥ = {u1b1+….+unbn; u1,…,un Є Z }) is called an n-dimensional lattice… Let H be an n-k dimensional (when k=1, then H is the n-1 dimensional subspace orthogonal to v) subspace of Rn (this is equivalent to project the generated line segment to n-1 dimensional subspace H to generate plurality of projected line segment points which corresponds with respect unwrapped depths) … The subspace Hꓕ contain the line of vectors {rv; r Є R} (page 5208, left column, first paragraph)… The closed Voronois cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point; Fig. 1, page 5208, further disclosed plurality of projected line segment points. Using equation 7 (wrapped phase (Yn) and unwrapped depth (ro)) with project method disclosed above to predictably get a plurality of projected line segment points wherein each of the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths).
measuring a plurality of Voronoi vectors corresponding to the plurality of unwrapped depths (Akhlaq; Fig. 1, page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables); page 5207, right column, disclosed independent vectors from m-dimensional Euclidean space Rm with m ≥ n. The set of vectors (ꓥ = {u1b1+….+unbn; u1,…,un Є Z }) is called an n-dimensional lattice… Let H be an n-k dimensional (when k=1, then H is the n-1 dimensional subspace orthogonal to v) subspace of Rn (this is equivalent to project the generated line segment to n-1 dimensional subspace H to generate plurality of projected line segment points which corresponds with respect unwrapped depths) … The subspace Hꓕ contain the line of vectors {rv; r Є R} (page 5208, left column, first paragraph)… The closed Voronois cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point (see more detail calculation in page 5028 and Fig. 1); Fig. 1, page 5208, further disclosed plurality of projected line segment points. Using equation 7 (wrapped phase (Yn) and unwrapped depth (ro)) with project method disclosed above to predictably get a plurality of projected line segment points wherein each of the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths); and
determining a lattice of Voronoi cells, wherein each of the plurality of unwrapped depths corresponds to a respective Voronoi cell of the lattice (same as above; Akhlaq; Fig. 1, page 5208-5209, further define the Voronoi cell and how to find the closest lattice point when the measured distance has an noise component).
Regarding claim 2, Akhlaq teaches the method of claim 1, further comprising measuring a distance to an object, and identifying a corresponding Voronoi cell of the lattice for the measured distance (Akhlaq; Fig. 1, page 5208-5209, disclosed after defining Voronoi cell and related line vector, given a lattice ꓥ in Rm and a vector y Є Rm, to find a lattice point x Є ꓥ such that the squared Euclidean norm is minimized (called the closest lattice point problem). By identify the closest lattice point, predictably to find a measured distance, see more detail calculation in Page 5208-5209).
Regarding claim 4, Akhlaq teaches the method of claim 2, further comprising applying a transformation to the distance using a plurality of vectors (Akhlaq; Fig. 1, page 5208, disclosed the Voronoi cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point. If the lattice is full rank so that n=m then the volume of the Voronoi cell is equal to the volume of a fundamental parallelepiped. Otherwise, if m>n the Voronoi cell is unbounded in those directions orthogonal to the subspace spanned by the basis vectors b1,…, bn. Specifically, if x is contained in this orthogonal subspace, then y Є Vor ꓥ if and only if y + sx Є Vor ꓥ for all s Є R. In this case, the intersection of the Voronoi cell with the subspace spanned by b1, …, bn has n-dimensional volume equal to det ꓥ; Page 5209 disclosed the least squares range estimator first computes an estimate ζ Є Zn of the wrapping variables by minimizing the quadratic form (equation 10). And further determine the closest lattice point to Qy in the lattice ꓥ; see more detail in page 5208-5209).
Regarding claim 6, Akhlaq teaches the method of claim 5, wherein determining the lattice of Voronoi cells includes determining an area around each of the plurality of projected line segment points corresponding with the respective projected line segment point based on the plurality of Voronoi vectors (Akhlaq; Fig. 1, page 5207-5208, the closed Voronois cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point. If the lattice is full rank so that n=m then the volume of the Voronoi cell is equal to the volume of a fundamental parallelepiped, that is det ꓥ. Otherwise, if m>n the Voronoi cell is unbounded in those directions orthogonal to the subspace spanned by the basis vectors b1,…, bn. Specifically, if x is contained in this orthogonal subspace, then y Є Vor ꓥ if and only if y + sx Є Vor ꓥ for all s Є R. In this case, the intersection of the Voronoi cell with the subspace spanned by b1, …, bn has n-dimensional volume equal to det. See more detail in Fig. 1, page 5208).
Regarding claim 17, Akhlaq teaches a method for phase unwrapping in time-of-flight systems, comprising:
estimating a distance to an object and generating a corresponding measurement point (Akhlaq; page 5206, left column, section II, disclosed the estimation of the range (ro/2) from the signal y(t), where range is corresponds to phase Ө with respective frequency f (equation 1-3). Page 5206, right column, disclosed range ro and ro + kλ result in the same phase difference. For this reason the range is identifiable from the phase only if we assume ro to lie in some interval of length λ. To address this problem is to transmit multiple signals at multiple different frequencies and observe the phase at each; this implies that a plurality of wrapped distance measurement at a respective plurality of frequencies will be determined during the process; page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables));
applying a transformation to the measurement point using a plurality of vectors (Akhlaq; Fig. 1, page 5208, disclosed the Voronoi cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point. It the lattice is full rank so that n=m then the volume of the Voronoi cell is equal to the volume of a fundamental parallelepiped. Otherwise, if m>n the Voronoi cell is unbounded in those directions orthogonal to the subspace spanned by the basis vectors b1,…, bn. Specifically, if x is contained in this orthogonal subspace, then y Є Vor ꓥ if and only if y + sx Є Vor ꓥ for all s Є R. In this case, the intersection of the Voronoi cell with the subspace spanned by b1, …, bn has n-dimensional volume equal to det ꓥ; Page 5209 disclosed the least squares range estimator first computes an estimate ζ Є Zn of the wrapping variables by minimizing the quadratic form (equation 10). And further determine the closest lattice point to Qy in the lattice ꓥ; see more detail in page 5208-5209);
matching the measurement point to a Voronoi cell for a wrapped distance measurement based on the transformation, wherein the wrapped distance measurement is a projected line segment point (Akhlaq; Fig. 1, page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables); page 5207, right column, disclosed independent vectors from m-dimensional Euclidean space Rm with m ≥ n. The set of vectors (ꓥ = {u1b1+….+unbn; u1,…,un Є Z }) is called an n-dimensional lattice… Let H be an n-k dimensional (when k=1, then H is the n-1 dimensional subspace orthogonal to v) subspace of Rn (this is equivalent to project the generated line segment to n-1 dimensional subspace H to generate plurality of projected line segment points which corresponds with respect unwrapped depths) … The subspace Hꓕ contain the line of vectors {rv; r Є R} (page 5208, left column, first paragraph)… The closed Voronois cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point; Fig. 1, page 5208, further disclosed plurality of projected line segment points. Using equation 7 (wrapped phase (Yn) and unwrapped depth (ro)) with project method disclosed above to predictably get a plurality of projected line segment points wherein each of the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths); and
determining an unwrapped depth based on the projected line segment point (same as above; Akhlaq; Fig. 1, page 5208-5209, further define the Voronoi cell and how to find the closest lattice point when the measured distance has an noise component).
Regarding claim 18, Akhlaq teaches a method of claim 17, wherein applying the transformation includes using Voronoi vectors to identify the Voronoi cell (Akhlaq; Fig. 1, page 5208, disclosed the Voronoi cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point. It the lattice is full rank so that n=m then the volume of the Voronoi cell is equal to the volume of a fundamental parallelepiped. Otherwise, if m>n the Voronoi cell is unbounded in those directions orthogonal to the subspace spanned by the basis vectors b1,…, bn. Specifically, if x is contained in this orthogonal subspace, then y Є Vor ꓥ if and only if y + sx Є Vor ꓥ for all s Є R. In this case, the intersection of the Voronoi cell with the subspace spanned by b1, …, bn has n-dimensional volume equal to det ꓥ; Page 5209 disclosed the least squares range estimator first computes an estimate ζ Є Zn of the wrapping variables by minimizing the quadratic form (equation 10). And further determine the closest lattice point to Qy in the lattice ꓥ; see more detail in page 5208-5209).
Regarding claim 19, Akhlaq teaches a method of claim 18, wherein the measurement point is at most one Voronoi vector away from the projected line segment point (Akhlaq; page 5208, right column, disclosed to determine the closest lattice point. The closest lattice point problem and the Voronoi cell are related in that x Є ꓥ is a closest lattice point to y if and only if y-x Є Vorꓥ. The closest lattice point is not necessarily unique, this is there can be multiple lattice points that minimize. This occurs precisely when y-x lies on the boundary of Vorꓥ. If y-x is contained strictly in the interior of Vorꓥ, then x Є ꓥ is the unique closest lattice point to y. In particular, if y itself is in the interior of Vorꓥ, then the unique closest lattice point y is the origin 0).
Claim Rejections - 35 USC § 103
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.
Claim(s) 3, 9-14 are rejected under 35 U.S.C. 103 as being unpatentable over Akhlaq, modified in view of Perry et al. (US 20180011195 A1, hereinafter “Perry”).
Regarding claim 3, Akhlaq as modified above teaches the method as recited in claim 2, wherein identifying the corresponding Voronoi cell to map the distance to the corresponding Voronoi cell (Akhlaq; Fig. 1, page 5208-5209, disclosed after defining Voronoi cell and related line vector, given a lattice ꓥ in Rm and a vector y Є Rm, to find a lattice point x Є ꓥ such that the squared Euclidean norm is minimized (called the closest lattice point problem). By identify the closest lattice point, predictably to find a measured distance, see more detail calculation in Page 5208-5209).
Akhlaq does not teach, using a lookup table to map the distance.
Perry teaches, using a lookup table to map the distance (Perry; [0002], the TOF system includes a frequency unwrapping module configured to generate an input phase vector with M phases corresponding to M sampled signals reflected from an object, determine an M-1 dimensional vector of transformed phase values by applying a transformation matrix (T) to the input phase vector, determine an M-1 dimensional vector of rounded transformed phase value by rounding the transformed phase values to a nearest integer, and determine a one dimensional lookup table (LUT) index value by transforming the M-1 dimensional rounded transformed phase value. The index value is input into the one dimensional LUT to determine a range of the object; Fig. 5, Fig. 7, Fig. 8, [0052], operation 514, generates a one dimensional LUT by packing the M-1 dimensional domain of B into one dimensional using Tdeskew and additional transformations (transformation matrix (T)). The one-dimensional LUT may provide a number of range disambiguation).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of this invention to modify the method taught by Akhlaq to include using a lookup table to map the distance taught by Perry with a reasonable expectation of success. The reasoning for this is to store the index value in the one dimensional LUT such that can be used to determine a range of object (Perry; Fig. 5, Fig. 7, Fig. 8, [0002], [0052], [0064]).
Regarding claim 9, Akhlaq teaches a system for phase unwrapping, comprising:
a receiver configured to receive reflected frequencies (Akhlaq; page 5206, left column, section II, disclosed the estimation of the range (ro/2) from the signal y(t) (sent by a transmitter and received by a receiver), where range is corresponds to phase Ө with respective frequency f (equation 1-3)); and
determine a plurality of wrapped distance measurements at a respective plurality of frequencies, wherein each of the plurality of wrapped distance measurements corresponds to a respective phase (Akhlaq; page 5206, left column, section II, disclosed the estimation of the range (ro/2) from the signal y(t), where range is corresponds to phase Ө with respective frequency f (equation 1-3). Page 5206, right column, disclosed range ro and ro + kλ result in the same phase difference. For this reason the range is identifiable from the phase only if we assume ro to lie in some interval of length λ. To address this problem is to transmit multiple signals at multiple different frequencies and observe the phase at each; this implies that a plurality of wrapped distance measurement at a respective plurality of frequencies will be determined during the process),
generate a plurality of projected line segment points based on the plurality of wrapped distance measurements (Akhlaq; page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables); page 5207, right column, disclosed independent vectors from m-dimensional Euclidean space Rm with m ≥ n. The set of vectors (ꓥ = {u1b1+….+unbn; u1,…,un Є Z }) is called an n-dimensional lattice… Let H be an n-k dimensional (when k=1, then H is the n-1 dimensional subspace orthogonal to v) subspace of Rn (this is equivalent to project the generated line segment to n-1 dimensional subspace H to generate plurality of projected line segment points which corresponds with respect unwrapped depths)), and
determine a lattice of Voronoi cells, wherein each Voronoi cell corresponds to one of the plurality of projected line segment points (Akhlaq; Fig. 1, page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables); page 5207, right column, disclosed independent vectors from m-dimensional Euclidean space Rm with m ≥ n. The set of vectors (ꓥ = {u1b1+….+unbn; u1,…,un Є Z }) is called an n-dimensional lattice… Let H be an n-k dimensional (when k=1, then H is the n-1 dimensional subspace orthogonal to v) subspace of Rn (this is equivalent to project the generated line segment to n-1 dimensional subspace H to generate plurality of projected line segment points which corresponds with respect unwrapped depths) … The subspace Hꓕ contain the line of vectors {rv; r Є R} (page 5208, left column, first paragraph)… The closed Voronois cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point (see more detail calculation in page 5028 and Fig. 1); Fig. 1, page 5208, further disclosed plurality of projected line segment points. Using equation 7 (wrapped phase (Yn) and unwrapped depth (ro)) with project method disclosed above to predictably get a plurality of projected line segment points wherein each of the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths; Fig. 1, page 5208-5209, further define the Voronoi cell and how to find the closest lattice point when the measured distance has an noise component).
Akhlaq does not teach, a processor configured to:
Perry disclosed an example system 1000 (including processor unit 21) that may be useful in implementing the described TOF system with multi frequency unwrapping (Perry; Fig. 10, [0072]).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of this invention to modify a system taught by Akhlaq to include a processor taught by Perry with a reasonable expectation of success. The reasoning for this is to use an example system 1000 (including processor unit 21) that may be useful in implementing the described TOF system with multi frequency unwrapping (Perry; Fig. 10, [0072]).
Regarding claim 10, Akhlaq as modified above teaches the system as recited in claim 9, wherein the processor (Perry; Fig. 10, [0072]) is further configured to measure a plurality of Voronoi vectors, and wherein an area for each Voronoi cell of the lattice is determined based on Voronoi vectors (Akhlaq; Fig. 1, page 5207-5208, the closed Voronois cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point. If the lattice is full rank so that n=m then the volume of the Voronoi cell is equal to the volume of a fundamental parallelepiped, that is det ꓥ. Otherwise, if m>n the Voronoi cell is unbounded in those directions orthogonal to the subspace spanned by the basis vectors b1,…, bn. Specifically, if x is contained in this orthogonal subspace, then y Є Vor ꓥ if and only if y + sx Є Vor ꓥ for all s Є R. In this case, the intersection of the Voronoi cell with the subspace spanned by b1, …, bn has n-dimensional volume equal to det. See more detail in Fig. 1, page 5208).
Regarding claim 11, Akhlaq as modified above teaches the system as recited in claim 9, wherein the processor (Perry; Fig. 10, [0072]) is further configured to measure a distance to an object and identify a corresponding Voronoi cell of the lattice for the measured distance (Akhlaq; Fig. 1, page 5208-5209, disclosed after defining Voronoi cell and related line vector, given a lattice ꓥ in Rm and a vector y Є Rm, to find a lattice point x Є ꓥ such that the squared Euclidean norm is minimized (called the closest lattice point problem). By identify the closest lattice point, predictably to find a measured distance, see more detail calculation in Page 5208-5209).
Regarding claim 12, Akhlaq as modified above teaches the system as recited in claim 11, wherein the processor (Perry; Fig. 10, [0072]) is further configured to measure the distance based on the received reflected frequencies (Akhlaq; page 5206, left column, section II, disclosed the estimation of the range (ro /2) from the signal y(t), where range is corresponds to phase Ө with respective frequency f (a transmitter sends a signal (equation 1); the signal propagate to target and reflected back to receiver (equation 2); equation 3 disclosed the phase of the received signal). If the transmitter and receiver could be in the same location and the receiver obtains the signal after being reflected off a target, the range of the target would be ro/2; Page 5206, right column, disclosed range ro and ro +kλ result in the same phase difference. To address this problem is to transmit multiple signals at multiple different frequencies and observe the phase at each).
Regarding claim 13, Akhlaq as modified above teaches the system as recited in claim 9, wherein the processor (Perry; Fig. 10, [0072]) is further configured to generate a plurality of unwrapped depths for each of the plurality of wrapped distance measurements, based on the respective phase, and wherein each of the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths (Akhlaq; Fig. 1, page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables); page 5207, right column, disclosed independent vectors from m-dimensional Euclidean space Rm with m ≥ n. The set of vectors (ꓥ = {u1b1+….+unbn; u1,…,un Є Z }) is called an n-dimensional lattice… Let H be an n-k dimensional (when k=1, then H is the n-1 dimensional subspace orthogonal to v) subspace of Rn (this is equivalent to project the generated line segment to n-1 dimensional subspace H to generate plurality of projected line segment points which corresponds with respect unwrapped depths) … The subspace Hꓕ contain the line of vectors {rv; r Є R} (page 5208, left column, first paragraph)… The closed Voronois cell of an n-dimensional lattice ꓥ in Rm is the subset of Rm containing all points nearer or of equal distance to the lattice point at the origin than to any other lattice point; Fig. 1, page 5208, further disclosed plurality of projected line segment points. Using equation 7 (wrapped phase (Yn) and unwrapped depth (ro)) with project method disclosed above to predictably get a plurality of projected line segment points wherein each of the plurality of projected line segment points corresponds with a respective one of the plurality of unwrapped depths).
Regarding claim 14, Akhlaq as modified above teaches the system as recited in claim 9, further comprising an emitter configured to emit a plurality of frequencies and wherein at least a portion of the plurality of frequencies reflected and received at the receiver (Akhlaq; page 5206, left column, section II, a transmitter sends a signal (equation 1). The signal propagate to target and reflected back to receiver (equation 2). Page 5206, right column, disclosed range ro and ro +kλ result in the same phase difference. To address this problem is to transmit multiple signals at multiple different frequencies and observe the phase at each).
Claim(s) 7-8 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Akhlaq, modified in view of Xu (US 20210033731 A1, hereinafter “Xu”).
Regarding claim 7, Akhlaq teaches the method of claim 1.
Akhlaq does not teach, wherein each of the plurality of frequencies is a multiple of a base frequency.
Xu teaches, wherein each of the plurality of frequencies is a multiple of a base frequency (Xu; [0033], disclosed current existing unwrapping techniques are performed in the phase domain with number of limitations. For instance, the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of this invention to modify the method taught by Akhlaq to include wherein each of the plurality of frequencies is a multiple of a base frequency taught by Xu with a reasonable expectation of success. The reasoning for this is the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances (Xu; [0033]).
Regarding claim 8, Akhlaq as modified above teaches the method of claim 7.
Akhlaq does not teach, wherein the plurality of frequencies includes a first frequency at seventeen times the base frequency, a second frequency at nineteen times the base frequency, and a third frequency at twenty-two times the base frequency.
Xu teaches, wherein the plurality of frequencies includes a first frequency at seventeen times the base frequency, a second frequency at nineteen times the base frequency, and a third frequency at twenty-two times the base frequency (Xu; [0033], disclosed current existing unwrapping techniques are performed in the phase domain with number of limitations. For instance, the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of this invention to modify the method taught by Akhlaq to include wherein each of the plurality of frequencies is a multiple of a base frequency taught by Xu with a reasonable expectation of success. The reasoning for this is the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances (Xu; [0033]). It has been held in the case where the claimed ranges "overlap or lie inside ranges disclosed by the prior art" a prima facie case of obviousness exists (See MPEP § 2144.05(I)). Additionally, the instant application notes that “In various implementations, any multiplications of the base frequency can be used for the various phases [0084]”. Therefore, use of 18x of the base frequence instead of 19x would have a predictable result to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distance.
Regarding claim 20, Akhlaq teaches the method of claim 17, wherein the measurement point includes multiple signals at multiple different frequencies and observe the phase at each (Akhlaq; page 5206, left column, section II, disclosed the estimation of the range (ro /2) from the signal y(t), where range is corresponds to phase Ө with respective frequency f (a transmitter sends a signal (equation 1); the signal propagate to target and reflected back to receiver (equation 2); equation 3 disclosed the phase of the received signal). If the transmitter and receiver could be in the same location and the receiver obtains the signal after being reflected off a target, the range of the target would be ro/2. Page 5206, right column, disclosed range ro and ro +kλ result in the same phase difference. To address this problem is to transmit multiple signals at multiple different frequencies and observe the phase at each; page 5206, right column, disclosed transmit multiple signals at multiple different frequencies and observe the phase at each (equation 6). Equation 7 disclosed the relationship between wrapped phase (Yn) and unwrapped depth (ro) (ϵ: noise; ζ: wrapping variables)).
Akhlaq does not teach, a first measurement at a first frequency, a second measurement at a second frequency, and a third measurement at a third frequency.
Xu disclosed in paragraph [0033] that the current existing unwrapping techniques are performed in the phase domain with number of limitations. For instance, the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances (equivalent to a first measurement at a first frequency, a second measurement at a second frequency, and a third measurement at a third frequency).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of this invention to modify the method taught by Akhlaq to include wherein each of the plurality of frequencies is a multiple of a base frequency taught by Xu with a reasonable expectation of success. The reasoning for this is the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances (Xu; [0033]).
Claim(s) 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Akhlaq, modified in view of Perry, in view of Xu.
Regarding claim 15, Akhlaq as modified above teaches the method of claim 14.
Akhlaq does not teach, wherein each of the plurality of frequencies emitted by the emitter is a multiple of a base frequency.
Xu teaches, wherein each of the plurality of frequencies emitted by the emitter is a multiple of a base frequency (Xu; [0033], disclosed current existing unwrapping techniques are performed in the phase domain with number of limitations. For instance, the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of this invention to modify the method taught by Akhlaq to include a processor taught by Perry, include wherein each of the plurality of frequencies is a multiple of a base frequency taught by Xu with a reasonable expectation of success. The reasoning for this is the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances (Xu; [0033]).
Regarding claim 16, Akhlaq as modified above teaches the method of claim 15.
Akhlaq does not teach, wherein the plurality of frequencies emitted by the emitter includes a first frequency at seventeen times the base frequency, a second frequency at nineteen times the base frequency, and a third frequency at twenty-two times the base frequency.
Xu teaches, wherein the plurality of frequencies emitted by the emitter includes a first frequency at seventeen times the base frequency, a second frequency at nineteen times the base frequency, and a third frequency at twenty-two times the base frequency (Xu; [0033], disclosed current existing unwrapping techniques are performed in the phase domain with number of limitations. For instance, the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances).
It would have been obvious to one of ordinary skill in the art prior to the effective filling date of this invention to modify the method taught by Akhlaq to include a processor taught by Perry, include wherein each of the plurality of frequencies is a multiple of a base frequency taught by Xu with a reasonable expectation of success. The reasoning for this is the values of the multiple frequencies are constrained to have an integral relationship with a common denominator among the frequencies, (e.g., [153, 162, 198]/9=[17 18 22]) in order to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distances (Xu; [0033]). It has been held in the case where the claimed ranges "overlap or lie inside ranges disclosed by the prior art" a prima facie case of obviousness exists (See MPEP § 2144.05(I)). Additionally, the instant application notes that “In various implementations, any multiplications of the base frequency can be used for the various phases [0084]”. Therefore, use of 18x of the base frequence instead of 19x would have a predictable result to provide a repeatable phase cycle where all of the frequencies overlap periodically at known distance.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Perry et al. (US 20180011195 A1), disclosed in Fig. 3, paragraph [0034]-[0035], a graph 300 for this relation between two phase measurement Ө1 and Ө2. Specifically, line 302 illustrates the relation between the phase of measurements at frequencies f1, f2, corresponding to line 202 and 204 from origin until 214a (Fig. 2). At this point the relation moves to line 304, then to line 306, then to line 308, etc.; The identity of each of the lines 302, 304, 306 etc., encoded a range disambiguation tuple (n1, n2, … nM), that allows the calculation of disambiguated phase for any of the measurement frequencies plot. This allows the range determination module 60 to disambiguate range measurements out to range = C/(2xf0); If there is no factor common to all the relative frequencies m1, ,2, …mM. The range determination module 60 may further encode the identity of each of the lines 302, 304, 306, etc., by mapping onto a vector subspace that is the orthogonal complement of the vector. In the case of two frequencies, this may correspond to projecting onto a basis vector orthogonal to (m1, m2), giving a series of points referred to as “unwrapping points” that can be uniquely identified by single coefficient corresponding to the distance along a line (line 330 represents such a basis vector). For example, the identity of the line 302 is represented by point 330a along the line 330. Thus, the range determination module 60 reduces the dimensionality by one form two dimension as per graph 300 to one dimension of line 330. The one dimension of the basis vector is more clearly illustrated by 340.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/CHIA-LING CHEN/Examiner, Art Unit 3645 /YUQING XIAO/Supervisory Patent Examiner, Art Unit 3645
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