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 .
DETAILED OFFICE ACTION
Priority
Should applicant desire to obtain the benefit of foreign priority under 35 U.S.C. 119(a)-(d) prior to declaration of an interference, a certified English translation of the foreign application must be submitted in reply to this action. 37 CFR 41.154(b) and 41.202(e). Failure to provide a certified translation may result in no benefit being accorded for the non-English application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 2024-06-18 in compliance with the provisions of 37 CFR 1.97 has been considered by the examiner and made of record in the application file.
Claim Status
Claims 1-11 and 13-21 are pending in this application and are under examination in this Office Action. Claim 12 is canceled. No claims have been allowed.
Claim Rejections – 35 U.S.C. § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for the 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.
As reiterated by the Supreme Court in KSR, and as set forth in MPEP 2141 (R-01.2024), II, the factual inquiries of Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), applied for establishing a background for determining obviousness under 35 U.S.C. §103, are summarized as follows:
Determining the scope and content of the prior art;
Ascertaining the differences between the prior art and the claims at issue;
Resolving the level of ordinary skill in the pertinent art; and
Considering objective evidence indicative of obviousness or non-obviousness, if present.
This application currently names joint inventors. In considering patentability of the claims, the examiner presumes that the subject matter disclosed in the prior art was created by another (i.e., not by the inventive entity) unless proven otherwise. Applicant is advised of the obligation under 37 C.F.R. § 1.56 to point out the inventor and effective filing dates of each claim, and any evidence of common ownership/assignment as of the effective filing date, so that the examiner may properly consider the applicability of 35 U.S.C. § 102(b)(2)(C) for any potential 35 U.S.C. § 102(a)(2) prior art against the claimed invention(s).
Claims 1,13 and 14 are rejected under 35 U.S.C. §103 as being unpatentable over Rohde et al. (US20180034554A1) in view of Xu et al. (CN104426606A).
Claim 1
Rohde teaches a coherent optical receiver (COR) characterization method in which light from a coherent source is split and one path is frequency shifted by a frequency shift f, and performance parameters are computed using phase relationships between recorded output components “[0014] An aspect of the present disclosure provides a method for measuring GDV of a COR, the COR comprising an OS port, a local oscillator LO port, and one or more output ports, the method comprising: splitting light from a coherent light source into first and second lights; frequency shifting one of the first or second lights by a frequency shift f, modulating the first light in amplitude at a first modulation frequency F, that is greater than f and a second modulation frequency F2 in a phase - locked manner, wherein F2 > F, > f, providing one of the first and second lights into a signal port of the COR, and the other of the first and second lights into a local oscillator (LO) port of the COR; obtaining, from an output COR signal received from the one or more output ports of the COR, a first time - domain trace corresponding to a frequency component of the output signal at a first shifted modulation frequency (F + f) or (F1 - f), and a second time domain trace corresponding to a frequency component of the output signal at a second shifted modulation frequency (F2 + f) or (F2 - f); and, determining the GDV based on a phase shift between the first and second time - domain traces” [Rohde, ¶ [0014]].
Rohde further teaches that the frequency shift is provided by an optical frequency shifter “[0048] An optical frequency shifter (OFS) 109 may be disposed in the optical path 116 of the first light 106 to the first output optical port 111 and is operable to shift an optical frequency of light passing therethrough by a frequency shift f The OFS 109 may be embodied, for example , using an acousto - optic modulator , which is known in the art to shift the optical frequency of light it receives by a frequency of an acoustic wave generated therein . Other embodiments of the OFS 109 may also be envisioned, such as for example using an optical modulator followed by an optical filter. In another embodiment the OFS 109 may be disposed in the optical path 117 to the second output port 112 for coupling frequency - shifted light into the LO input port 152 of COR 150” [Rohde, ¶ [0048]].
Rohde does not expressly teach generating beat frequencies by scanning a signal close to the LO, acquiring receiver RF output waveforms using an oscilloscope. However, within analogous art, Xu teaches generating beat frequencies by scanning a signal close to the LO, acquiring receiver RF output waveforms using an oscilloscope, computing phase/frequency via FFT, and using a linear fit of phase versus frequency to calculate channel time delay and phase difference “[0006] a) through the to-be-tested optical coherence receiver input similar to the local oscillation signal frequency scanning signal light to form a beat frequency with the local oscillation signal; [0007] b) using the oscilloscope connection waiting optical coherence between any two radio frequency signal output channel of the receiver, detecting collecting all the beat frequency waveform data under the input scanning signal light of each wavelength; [0008] c) the beat frequency waveform data acquisition for eliminating noise dithering process, and calculating the frequency of phase and beat frequency waveform of the beat frequency under different wavelength input signal; [0009] d) drawing the frequency and phase through linear fitting relation curve, and using the frequency and phase relation curve to calculate the time delay and phase difference between the two output channels of the oscilloscope is connected between” [Xu, ¶ ¶ [0006]-[0009]].
Xu further teaches repeating the same delay/phase measurement procedure across different output-channel pairs by replacing the oscilloscope connections “[0010] Furthermore, further comprising step e) replacing the oscilloscope connection of output channel, repeating steps a) to d) are optical coherence of time delay and phase difference between each channel of the receiver” [Xu, ¶ [0010]].
Accordingly, Rohde in view of Xu teaches or at least renders obvious the limitations of claim 1, including: (i) acquiring coherent receiver output signals under a first frequency-shift test condition and under a second, different frequency-shift test condition (e.g., by selecting different frequency offsets/beat frequencies as taught by Xu in Rohde’s frequency-shift test setup), (ii) processing the first and second signal sets to obtain corresponding phase differences, and (iii) obtaining coherent receiver phase difference and time delay based on the phase differences (Xu’s linear fit phase–frequency relationship).
A person of ordinary skill in the art (POSITA) would have been motivated to apply Xu’s explicit FFT-based phase extraction and phase–frequency linear-fit delay/phase-difference computation technique to Rohde’s coherent receiver frequency-shift test platform because both references address the same objective accurately characterizing coherent receiver phase and delay parameters from measured receiver outputs. Xu provides a predictable way to compute delay as the slope of phase versus frequency and phase difference as the offset/phase relation between channels, while Rohde provides a known coherent receiver test configuration with a controllable frequency shift f. Combining these teachings would have been a straightforward use of prior art elements according to their established functions, yielding improved accuracy and repeatability with a reasonable expectation of success.
Claim 13
Claim 13 recites an apparatus including memory and a processor configured to execute instructions to perform the method of claim 1. Rohde teaches a recorder and controller that sample and process the coherent receiver output to determine phase response and delay characteristics. Rohde describes the recorder as a digital signal recorder with an ADC and digital processor “[0085] The output COR signal 144 received by the recorder 160 may be filtered to obtain a first time – domain trace Si (t) corresponding to a first frequency component which represents the modulation of the COR signal 144 at a shifted first modulation frequency (F1 - f) or (F] + f), and a second time - domain trace S (t) corresponding to a second frequency component which in this embodiment represents the modulation of the COR signal 144 at the second shifted modulation frequency (F,- f) or (F, + f) . The time domain trace S, (t) may be referred to herein as the first-time domain trace, and the time domain trace S, (t) may be referred to as the second time domain trace. Each of these traces may be obtained, for example, by applying a suitably narrow – band digital or analog filter to the recorded COR output signal 144, or to a signal obtain therefrom by a pre – processing operation. In one example embodiment, the recorder 160 is a digital signal recorder having at least one ADC 10 followed by the digital processor 20 at its input as illustrated in FIG. 9, wherein the processor 20 may be configured to perform the filtering operations using digital filters that may be implemented with software or hardware logic as known in the art. It will be appreciated that tunable analog RF filters may also be used to select the desired frequency components” [Rohde, ¶ [0085]].
Rohde does not expressly teach a testing system including an oscilloscope and a data processing unit for FFT processing. However, within analogous art, Xu teaches a testing system including an oscilloscope and a data processing unit for FFT processing and linear fitting to compute channel time delay and phase difference “The invention claims an optical coherent receiver time delay and phase difference test method, through the to-be-tested optical coherence receiver input close to the local oscillation signal frequency scanning signal light to generate beat frequencies, collecting the light to be detected with an oscilloscope coherent beat frequency information of receiver radio frequency output, and eliminating noise and calculates the phase and frequency of the beat frequency by FFT operation, finally the linear fitting phase and frequency relation curve, the curve to calculate the coherent optical time delay and phase difference between each channel of the receiver. further claims the method used for testing system, comprising a local oscillation signal source, a tunable scanning signal source, the optical coherent receiver, an oscilloscope and a data processing unit. The invention uses the beat frequency detection optical coherence of time delay and phase difference between each channel of the receiver, which is simple and feasible and can accurately test the phase difference and the time delay between channels, overcomes the defect of the conventional apparatus cannot directly test the difficulty of phase difference and time delay of between 25 GHz high speed signal channel, and repeatability of the test data is good” [Xu, Abstract].
Accordingly, Rohde in view of Xu teaches or renders obvious the processor/memory embodiment of the claim 1 method recited in claim 13.
A POSITA would have implemented the measurement and computation steps of claim 1 using processor-executed instructions stored in memory because both Rohde and Xu expressly rely on digitizing receiver outputs and performing computational processing (phase extraction, correlation/phase response calculations, and linear fitting) that are routinely implemented in software/firmware executed by a processor.
Claim 14
Claim 14 recites a non-transitory computer-readable storage medium storing computer executable instructions thereon, wherein after the instructions are executed by a processor, the method for detecting a phase difference and time delay of a coherent receiver (claim 1) is implemented. Rohde and XU teach or render obvious this computer-readable-medium embodiment because they disclose digitizing/storing receiver output signals in memory and performing processor-executed computations (phase extraction, phase comparisons, and delay/phase calculations).
Rohde expressly teaches a digital signal recorder having ADC(s) followed by a processor coupled to memory, and further teaches reading memory to compute spectra/phase characteristics “[0076] With reference to FIG. 9, in one embodiment the recorder 160 may be implemented using one or more analog - to - digital converters (ADC) 10 at its input, which is / are operatively followed by a processor 20, which is in turn coupled to a memory device 30. The processor 20 may be implemented, for example, using a digital signal processor, a suitable high - speed microcontroller, an FPGA, or an ASIC. The processor 20 may be configured to save sampled time - domain signal or signals received from the COR under test in memory 30. The sampling rate of the ADC 10 should be more than twice the modulation frequency F. The duration of the saved signal may be chosen to be sufficiently large to provide a desired signal to noise ratio, for example a few million sampling points. Although implementing the controller 160 using digital logic circuits and / or processors may be preferable, it will be appreciated that an analog implementation or a combination of analogue and digital circuitry is also possible and would also be within the confines of the present disclosure. [0078] The controller 170 may be programmed to receive the sampled time - domain traces from the recorder 160, for example by reading the content of memory 30, either directly or with the aid of processor 20, and to compute a spectrum S (0) thereof, where w represents frequency. The controller 170 may further be programmed to determine, from the computed spectrum, the strength PF = S (27F) of the direct detection component of the spectrum at the base modulation frequency relative to the spectral strength shift of the modulation component or components at the shifted modulation frequency, PS = S (20 (F + f)), and compute the CMRR based on the determined relative spectral strengths as described hereinabove” [Rohde, ¶ [0076], ¶ [0078]].
However, within analogous art, Xu teaches a testing system comprising an oscilloscope and a data processing unit, and teaches computing phase/frequency (e.g., by FFT) and using a linear fitting phase–frequency relationship to calculate time delay and phase difference between channels “[0011] step c) the cancellation noise dither processing, a calculation method of the phase and frequency comprises: firstly, each wavelength input signal corresponding to the collected beat frequency waveform data are divided into N sections, and then finding the single frequency signal with the highest amplitude of each small section number, returning the frequency fn and the phase phi n of each single frequency signal using FFT algorithm, at last, counting the frequency and phase of the single-frequency signal, respectively listed frequency histogram and the phase histogram, two histogram in each count value corresponding with the most frequency and phase corresponding to the wavelength of the input signal frequency and phase. [0018] the data processing unit includes an FFT operation noise and linear fitting calculation part, wherein the FFT operation noise elimination to eliminate the noise dithering and FFT operation processing and calculating the collected under different wavelength input signal of the phase and the frequency of the beat frequency of the beat frequency waveform information collected by the oscilloscope, linear fitting calculation part, calculating the result of the FFT operation cancelling unit, performing linear fitting, drawing the relation curve, frequency and phase and relation curve calculated optical coherent receiver time delay and phase difference” [Xu, ¶ [0011],¶ [0018]].
Accordingly, it would have been obvious to store the corresponding instructions on a non-transitory storage medium and execute them by a processor to implement the claimed method, because the prior art already acquires digitized data, stores it in memory, and performs computational processing steps that are routinely implemented as executable program code.
Implementing the known coherent receiver testing computations in software on a non-transitory computer-readable storage medium is a standard and predictable design choice, particularly where Rohde expressly discloses processor/memory operation (memory 30) and Xu expressly discloses a data processing unit performing FFT/linear fitting. This is a straightforward use of known computer-implemented signal processing to perform known measurement computations with a reasonable expectation of success under KSR.
Claims 2,3,4,5,11,15,16,17,18,19,20 and 21 are rejected under 35 U.S.C. §103 as being unpatentable over Rohde et al. in view of Xu et al., and further in view of Sun et al. (US6917031B1) and Nemer et al. (US20050135521A1).
Claim 2
With respect to claim 2, all limitations of claim 1 are taught by Rohde and Xu, except wherein claim 2 additionally requires obtaining the phase differences by performing cross-correlation operations on signal pairs and autocorrelation operations on a signal, and obtaining phase differences based on the correlation results. Added: “processing the second set of signals to obtain the second phase difference corresponding to the second set of signals, comprises: performing a cross-correlation operation on the third signal and the fourth signal to obtain a second cross correlation result; performing an autocorrelation operation on the third signal to obtain a second autocorrelation result; obtaining the second phase difference corresponding to the second set of signals based on the second cross correlation result and the second autocorrelation result.”
However, within analogous art, Sun expressly teaches obtaining a quadrature angle/phase error estimate using correlation between I and Q “……. An estimate of the quadrature angle error can be calculated by performing the time-averaged multiplication of the detected in-phase and quadrature Signals 52,54 as represented in Equation 1. The time-averaged multiplication of the detected in-phase and quadrature Signals 52.54 essentially amounts to a correlation function. Multiplying I(t) by I(t)sin (0) +Q(t)cos (0) and time-averaging results in a function that is equal to If(t)sin (0). The I(t)*Q(t)cos (0) term time-averages to Zero as I(t) and Q(t) are uncorrelated. Therefore, the time-averaged multiplication of the detected in-phase and quadrature signals 52.54 can be expressed as shown in Equation 2………” [Sun, Col.7-8].
Sun further teaches normalization using an I-branch power term (autocorrelation/energy) to isolate the phase term “……The Normalization of Equation 2 with respect to I^2(t) isolates the sin(θ) term…….” [Sun, Col.8].
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Additionally, Nemer expressly teaches determining a cross-correlation between two quadratures and filtering/normalizing it to estimate phase imbalance “[0036] At 504, a cross-correlation between the two quadratures is determined. The cross-correlation may be determined by multiplying the instantaneous values of the two quadratures. At 506, phase imbalance is corrected using the cross-correlation between the two quadratures. In one embodiment, the cross-correlation may be filtered and then normalized. The normalized cross-correlation may then be accumulated by an integrator to estimate the phase imbalance. A correction matrix may then be constructed using the estimated phase imbalance. The correction matrix may then be multiplied by the two quadratures to correct the phase imbalance” [Nemer, ¶ [0036]].
Accordingly, it would have been obvious to a POSITA to implement the phase-difference computation in Rohde/Xu using Sun’s and/or Nemer’s correlation-and-normalization technique because it is a known and predictable DSP method for extracting quadrature phase error from measured I/Q-type signals, improving robustness to noise and amplitude scaling with a reasonable expectation of success.
The combination is a straightforward substitution of known signal-processing techniques (correlation and normalization) for their known purpose (estimating phase difference/imbalance), consistent with KSR.
Claim 3
With respect to claim 3, all limitations of claim 2 are taught by Rohde, Xu, Sun, and Nemer, except wherein claim 3 additionally requires that the first phase difference and the second phase difference are computed in an explicit inverse-sine (sin⁻¹) form based on ratios of correlation results. Added: “φ1Q = sin⁻¹(XOR_IQ1/XOR_I1) ... and φ’1Q = sin⁻¹(XOR_IQ2/XOR_I2).”
However, within analogous art, Nemer expressly teaches computing phase imbalance using an arc sin function of a normalized cross-correlation term “[0020] The phase imbalance may be approximated as follows using the cross-correlation: Δθ ≈ arc sin(2*Rp)” [Nemer, ¶ [0020]].
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Accordingly, it would have been obvious to a POSITA to implement claim 2’s correlation-based phase extraction using Nemer’s explicit arc sin(normalized-correlation) relationship to directly compute the phase difference from the correlation ratio because Nemer provides a closed-form mapping from normalized correlation to phase imbalance that matches the mathematical form recited in claim 3.
The combination is a predictable use of a known mathematical relationship (inverse-sine of normalized correlation) within the known correlation framework of Sun/Nemer to obtain a phase estimate.
Claim 4
With respect to claim 4, all limitations of claim 3 are taught by Rohde, Xu, Sun, and Nemer, except wherein claim 4 additionally requires computing the coherent receiver phase difference (φ Hybrid) as a function of the two-phase differences and the two different frequency shifts (f1 and f2). Added: “φ Hybrid = (f2·φ1Q − f1·φ’1Q)/ (f2 − f1).”
However, within analogous art, Rohde teaches that group delay corresponds to the slope of phase response versus frequency “[0008] Another important parameter of a COR is the GDV. The GDV is a measure related to time distortion of a signal, and may be determined variation of the group delay of a signal in the COR with frequency. The group delay is a measure of the slope of the phase response at any given frequency, and is given by the following equation” [Rohde, ¶ [0008]].
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Additionally, Xu teaches obtaining a phase–frequency relationship by linear fitting and using that relationship to compute channel phase difference and time delay “[0009] d) drawing the frequency and phase through linear fitting relation curve, and using the frequency and phase relation curve to calculate the time delay and phase difference between the two output channels of the oscilloscope is connected between” [Xu, ¶ [0009]].
Accordingly, once two-phase values are obtained at two distinct frequency shifts (two points on the phase–frequency line) as taught by Xu and Rohde, solving for the constant phase term (intercept/offset) corresponding to the coherent receiver phase difference is an expected and routine algebraic operation. The claimed closed form φ Hybrid expression is a straightforward rearrangement of the same linear relationship taught by Xu (phase vs frequency) and Rohde (delay as slope).
A POSITA would have been motivated to compute the phase offset/intercept from two phase measurements because it directly yields the receiver phase difference while leveraging the same phase frequency relationship already used to compute delay, improving completeness and accuracy of receiver characterization with a reasonable expectation of success.
Claim 5
With respect to claim 5, all limitations of claim 3 are taught by Rohde, Xu, Sun, and Nemer, except wherein claim 5 additionally requires computing time delay τ as (φ’1Q − φ1Q)/ (f2 − f1). Added: “τ = (φ’1Q − φ1Q)/ (f2 − f1).”
As discussed above, Rohde teaches group delay as the slope of phase response versus frequency “[0008] Another important parameter of a COR is the GDV. The GDV is a measure related to time distortion of a signal, and may be determined variation of the group delay of a signal in the COR with frequency. The group delay is a measure of the slope of the phase response at any given frequency, and is given by the following equation” [Rohde, ¶ [0008]].
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Additionally, Xu teaches computing time delay from the linear phase frequency relationship “[0009] d) drawing the frequency and phase through linear fitting relation curve, and using the frequency and phase relation curve to calculate the time delay and phase difference between the two output channels of the oscilloscope is connected between” [Xu, ¶ [0009]].
Thus, computing τ as a two-point slope (difference in phase divided by difference in frequency) is directly suggested by the prior art and is an obvious implementation of the taught slope/linear-fit concept.
A POSITA would have been motivated to implement the slope calculation using two frequency points because it is the simplest, predictable way to obtain delay from two measured phase values, reducing computational burden while preserving accuracy, consistent with Rohde and Xu teachings.
Claim 11
With respect to claim 11, all limitations of claim 1 are taught by Rohde and Xu, except wherein claim 11 additionally requires that the first and second sets of signals are amplitude normalized signals. Added: “the first set of signals and the second set of signals are amplitude normalized signals.”
However, within analogous art, Sun teaches normalization of correlation equations with respect to an I-branch power (I^2(t)) term to isolate the phase term “……The Normalization of Equation 2 with respect to I^2(t) isolates the sin(θ) term…….” [Sun, Col.8].
Additionally, Nemer teaches that cross-correlation may be filtered and then normalized prior to estimating phase imbalance “[0036] At 504, a cross-correlation between the two quadratures is determined. The cross-correlation may be determined by multiplying the instantaneous values of the two quadratures. At 506, phase imbalance is corrected using the cross-correlation between the two quadratures. In one embodiment, the cross-correlation may be filtered and then normalized. The normalized cross-correlation may then be accumulated by an integrator to estimate the phase imbalance. A correction matrix may then be constructed using the estimated phase imbalance. The correction matrix may then be multiplied by the two quadratures to correct the phase imbalance” [Nemer, ¶ [0036]].
Accordingly, it would have been obvious to amplitude-normalize the acquired signal sets (or equivalently normalize the correlation/power quantities derived from them) because normalization is a known and predictable way to reduce sensitivity to amplitude scaling and improve repeatability of correlation-based phase estimation.
A POSITA would have been motivated to normalize because receiver output amplitudes vary with launch power, polarization alignment, and instrumentation gain, and normalization improves robustness and accuracy of phase/delay measurement.
Claim 15
With respect to claim 15, all limitations of claim 13 are taught by Rohde and Xu, except wherein claim 15 additionally requires that the apparatus processes the first set and second set of signals using (i) cross-correlation of each signal pair and (ii) autocorrelation of one signal of the pair, and obtains the corresponding phase difference based on the cross-correlation result and the autocorrelation result.
Added: “performing a cross-correlation operation on the first signal and the second signal to obtain a first cross-correlation result; performing an autocorrelation operation on the first signal to obtain a first autocorrelation result; obtaining the first phase difference corresponding to the first set of signals based on the first cross-correlation result and the first autocorrelation result; and the processing the second set of signals to obtain the second phase difference corresponding to the second set of signals, comprises: performing a cross-correlation operation on the third signal and the fourth signal to obtain a second cross correlation result; performing an autocorrelation operation on the third signal to obtain a second autocorrelation result; obtaining the second phase difference corresponding to the second set of signals based on the second cross correlation result and the second autocorrelation result.”
However, within analogous art, Sun expressly teaches obtaining quadrature phase error using a correlation operation: “time-averaged multiplication … amounts to a correlation function.” (Sun, p.8). Sun further teaches normalization using an I-branch power term (autocorrelation/energy) “……The Normalization of Equation 2 with respect to I^2(t) isolates the sin(θ) term…….” [Sun, Col.8].
Additionally, Nemer expressly teaches determining a cross-correlation between quadratures and filtering/normalizing it to estimate phase imbalance. “[0036] At 504, a cross-correlation between the two quadratures is determined. The cross-correlation may be determined by multiplying the instantaneous values of the two quadratures. At 506, phase imbalance is corrected using the cross-correlation between the two quadratures. In one embodiment, the cross-correlation may be filtered and then normalized. The normalized cross-correlation may then be accumulated by an integrator to estimate the phase imbalance. A correction matrix may then be constructed using the estimated phase imbalance. The correction matrix may then be multiplied by the two quadratures to correct the phase imbalance” [Nemer, ¶ [0036]].
Accordingly, it would have been obvious to a POSITA to implement the claim 13 apparatus’ phase-difference computations using the cross-correlation and autocorrelation/energy normalization processing taught by Sun and Nemer, because these are known and predictable DSP techniques for extracting quadrature phase difference/imbalance from measured I/Q-type receiver outputs, improving robustness to noise and amplitude scaling with a reasonable expectation of success.
A POSITA would have been motivated to use correlation-based processing in the coherent receiver test apparatus of Rohde/ Xu because correlation-and-normalization methods are computationally efficient, stable under varying amplitude conditions, and are widely used to estimate quadrature phase errors from digitized I/Q samples; thus, the modification is a straightforward substitution of known signal-processing techniques for their known purpose.
Claim 16
With respect to claim 16, all limitations of claim 15 are taught by Rohde, Xu, Sun, and Nemer, except wherein claim 16 additionally requires computing the phase differences using an explicit inverse-sine form based on the correlation ratio (e.g., φ1Q = sin⁻¹(XOR_IQ1/XOR_I1) and φ’1Q = sin⁻¹(XOR_IQ2/XOR_I2)).
Added: “the first phase difference is … sin⁻¹ (…) … and the second phase difference is … sin⁻¹ (…).”
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However, within analogous art, Nemer expressly teaches an arc sin relationship for phase imbalance based on normalized correlation “[0020] The phase imbalance may be approximated as follows using the cross-correlation: Δθ ≈ arc sin(2*Rp)” [Nemer, ¶ [0020]].
Accordingly, it would have been obvious to a POSITA to compute the phase differences in the correlation-based framework using Nemer’s explicit arc sin (normalized correlation) mapping, because it provides a closed-form phase estimate directly from the normalized correlation quantity, matching the mathematical form recited in claim 16 and yielding predictable phase estimation behavior.
A POSITA would have been motivated to use Nemer’s arc sin(correlation) computation because it reduces computational complexity (closed-form instead of iterative search), is directly derived from correlation statistics, and provides a predictable and accurate way to convert normalized correlation metrics into a phase/angle estimate in I/Q systems, consistent with Sun’s correlation-and-normalization framework.
Claim 17
With respect to claim 17, all limitations of claim 16 are taught by Rohde, Xu, Sun, and Nemer, except wherein claim 17 additionally requires computing the coherent receiver phase difference (φ Hybrid) as a function of f1, f2 and the two-phase differences (φ1Q, φ’1Q).
Added: “φ Hybrid = (f2·φ1Q − f1·φ’1Q)/ (f2 − f1).”
However, within analogous art, Rohde teaches that group delay corresponds to the slope of phase response versus frequency “[0008] Another important parameter of a COR is the GDV. The GDV is a measure related to time distortion of a signal, and may be determined variation of the group delay of a signal in the COR with frequency. The group delay is a measure of the slope of the phase response at any given frequency, and is given by the following equation” [Rohde, ¶ [0008]].
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Additionally, Xu teaches obtaining a phase–frequency relationship (via linear fitting) and using that relationship to compute phase difference between channels “[0009] d) drawing the frequency and phase through linear fitting relation curve, and using the frequency and phase relation curve to calculate the time delay and phase difference between the two output channels of the oscilloscope is connected between” [Xu, ¶ [0009]].
Accordingly, once a POSITA has two phase values at two distinct frequency shifts (two points on a phase–frequency line), solving for the intercept/offset phase term corresponding to coherent receiver phase difference is a routine and predictable algebraic operation. The claimed φ Hybrid expression is an explicit closed form of that intercept computation and is therefore taught or at least rendered obvious by Xu phase–frequency relation curve in view of Rohde’s phase-slope/delay framework.
A POSITA would have been motivated to compute the receiver phase difference (offset/intercept) from two phase measurements because it completes the receiver characterization using the same measurements already used to compute delay (slope), enabling accurate calibration/correction of hybrid non-orthogonality with a reasonable expectation of success.
Claim 18
With respect to claim 18, all limitations of claim 15 are taught by Rohde, Xu, Sun, and Nemer, except wherein claim 18 additionally requires computing the time delay τ of the coherent receiver in a two-point slope form based on the two-phase differences and the difference between the two frequency shifts.
Added: “τ = (φ’1Q − φ1Q)/ (f2 − f1).”
As set forth above, within analogous art, Rohde teaches group delay as the slope of phase response versus frequency “[0008] Another important parameter of a COR is the GDV. The GDV is a measure related to time distortion of a signal, and may be determined variation of the group delay of a signal in the COR with frequency. The group delay is a measure of the slope of the phase response at any given frequency, and is given by the following equation” [Rohde, ¶ [0008]].
Further, Xu teaches calculating time delay from the phase–frequency relation curve “[0009] d) drawing the frequency and phase through linear fitting relation curve, and using the frequency and phase relation curve to calculate the time delay and phase difference between the two output channels of the oscilloscope is connected between” [Xu, ¶ [0009]].
Thus, computing τ as (Δ phase)/ (Δ frequency) is directly suggested by the prior art’s “delay equals phase slope” principle and is a predictable implementation requiring only two frequency-shift test conditions.
A POSITA would have been motivated to compute τ using a two-point slope because it is the simplest discrete implementation of the known slope/linear-fit approach, reduces computational burden, and provides a predictable estimate of receiver delay from two measured phase values with a reasonable expectation of success.
Claim 19
With respect to claim 19, all limitations of claim 14 are taught by Rohde and Xu, except wherein claim 19 additionally requires that the stored instructions cause the processor to compute phase differences using cross-correlation of signal pairs and autocorrelation/energy normalization, analogous to claim 15.
Added: “performing a cross-correlation operation on the first signal and the second signal to obtain a first cross-correlation result; performing an autocorrelation operation on the first signal to obtain a first autocorrelation result; obtaining the first phase difference corresponding to the first set of signals based on the first cross-correlation result and the first autocorrelation result; and the processing the second set of signals to obtain the second phase difference corresponding to the second set of signals, comprises: performing a cross-correlation operation on the third signal and the fourth signal to obtain a second cross correlation result; performing an autocorrelation operation on the third signal to obtain a second autocorrelation result; obtaining the second phase difference corresponding to the second set of signals based on the second cross correlation result and the second autocorrelation result.”
However, within analogous art, Sun and Nemer teach correlation-and-normalization processing to estimate quadrature phase error from I/Q samples, as discussed for claim 15. “……The Normalization of Equation 2 with respect to I^2(t) isolates the sin(θ) term…….” [Sun, Col.8].
“[0036] At 504, a cross-correlation between the two quadratures is determined. The cross-correlation may be determined by multiplying the instantaneous values of the two quadratures. At 506, phase imbalance is corrected using the cross-correlation between the two quadratures. In one embodiment, the cross-correlation may be filtered and then normalized. The normalized cross-correlation may then be accumulated by an integrator to estimate the phase imbalance. A correction matrix may then be constructed using the estimated phase imbalance. The correction matrix may then be multiplied by the two quadratures to correct the phase imbalance” [Nemer, ¶ [0036]].
Accordingly, it would have been obvious to store and execute instructions that perform the correlation-based phase estimation in a non-transitory storage medium because the underlying operations are computational and are routinely implemented as software instructions executed by a processor on digitized signals.
A POSITA would have been motivated to implement the known correlation/normalization signal processing as stored instructions because Rohde and Xu already digitize and process receiver outputs using processors/data processing units; encoding the correlation operations as executable instructions is a standard software embodiment of known DSP methods.
Claim 20
With respect to claim 20, all limitations of claim 19 are taught by Rohde, Xu, Sun, and Nemer, except wherein claim 20 additionally requires computing the phase differences using an explicit sin⁻¹ form based on correlation ratios, analogous to claim 16.
Added: “φ1Q = sin⁻¹(XOR_IQ1/XOR_I1) … and φ’1Q = sin⁻¹(XOR_IQ2/XOR_I2).”
However, within analogous art, Nemer expressly teaches computing phase imbalance using an arc sin function of a normalized correlation term, as discussed for claim 16. “[0020] The phase imbalance may be approximated as follows using the cross-correlation: Δθ ≈ arc sin(2*Rp)” [Nemer, ¶ [0020]].
Accordingly, it would have been obvious to include the explicit inverse-sine computation within the stored instructions because it is a known mathematical mapping from normalized correlation to phase error and is directly compatible with the correlation framework taught by Sun/Nemer.
A POSITA would have been motivated to use the arc sin(correlation) computation in software because it provides a closed-form phase estimate that is efficient to compute and yields predictable behavior in correlation-based estimators, improving the speed and determinism of the measurement algorithm.
Claim 21
With respect to claim 21, all limitations of claim 20 are taught by Rohde, Xu, Sun, and Nemer, except wherein claim 21 additionally requires computing the coherent receiver phase difference φ Hybrid as a function of f1, f2 and the two-phase differences (φ1Q, φ’1Q), analogous to claim 17.
Added: “φ Hybrid = (f2·φ1Q − f1·φ’1Q)/ (f2 − f1).”
Rohde teaches that delay corresponds to the slope of the phase response versus frequency, which implies that phase can be modeled as linear with frequency over a measurement interval (phase = slope·frequency + intercept), and thus the intercept corresponds to a constant phase offset/phase-difference term “[0008] Another important parameter of a COR is the GDV. The GDV is a measure related to time distortion of a signal, and may be determined variation of the group delay of a signal in the COR with frequency. The group delay is a measure of the slope of the phase response at any given frequency, and is given by the following equation” [Rohde, ¶ [0008]].
Further, Xu teaches obtaining phase values at multiple beat frequencies and deriving a phase–frequency relationship via linear fitting, and using that relationship to compute phase difference between channels “[0009] d) drawing the frequency and phase through linear fitting relation curve, and using the frequency and phase relation curve to calculate the time delay and phase difference between the two output channels of the oscilloscope is connected between” [Xu, ¶ [0009]].
Accordingly, once the two-phase differences φ1Q and φ’1Q are obtained at two different frequency shifts f1 and f2 (as required by claim 20 and taught by the combination for claims 19–20), it would have been obvious to a POSITA to compute the coherent receiver phase difference φ Hybrid as the intercept/offset term derived from the two-point phase–frequency relationship. The claimed expression φ Hybrid = (f2·φ1Q − f1·φ’1Q)/ (f2 − f1) is the explicit closed-form solution for that intercept using two points (f1, φ1Q) and (f2, φ’1Q), and therefore is taught or at least rendered obvious by Xu linear-fit phase–frequency approach in view of Rohde’s slope-of-phase delay principle.
A POSITA would have been motivated to compute φ Hybrid as the phase offset/intercept from two phase measurements because it provides a direct calibration parameter for hybrid non-orthogonality using the same measurements already used to compute delay, improving completeness and accuracy of receiver characterization with a reasonable expectation of success.
Claims 6,7,8 and 9 are rejected under 35 U.S.C. §103 as being unpatentable over Rohde et al. in view of Xu et al., and further in view of Sun et al. and Nemer et al., and further in view of Zelensky et al. (US8687974B2).
Claim 6
With respect to claim 6, all limitations of claim 1 are taught by Rohde and Xu, except wherein claim 6 additionally requires acquiring additional phase differences (third and fourth phase differences) and obtaining the time delay based on the first, second, third, and fourth phase differences.
Added: “obtain a third phase difference corresponding to the first set of signals; processing the second set of signals to obtain a fourth phase difference corresponding to the second set of signals; and the obtaining the time delay of the coherent receiver based on the first phase difference and the second phase difference, comprises: obtaining the time delay of the coherent receiver based on the first phase difference, the second phase difference, the third phase difference, and the fourth phase difference.”
However, within analogous art, Xu expressly teaches repeating the same delay/phase measurement across different receiver output-channel pairs by replacing the oscilloscope connections, thereby obtaining multiple channel-pair delay/phase differences “[0055] and then through step e) replacing the oscilloscope connection of output channel, repeating steps a) to d), testing the tested optical coherence of time delay and phase difference between each channel of the receiver. namely, using said method can measure the optical coherent receiver output end of other port (such as CHl; and CH3, CH2 and CH3, CH3 and CH4 ...) between time delay and phase difference” [Xu, ¶ [0055]].
Additionally, within analogous art, Zelensky teaches using multiple correlation evaluations and trials to detect and compensate timing skew “Compensation for in-phase (I) and quadrature (Q) timing skew and offset in an optical signal may be achieved based on the correlation between derivatives of I and Q samples in the optical signal. The magnitude of the correlation between derivatives are measured to determine the presence of skew. Correlation between derivatives may be coupled with frequency offset information and/or with trials having additional positive and negative skew to determine presence of skew. Correlations are determined according to pre-defined time periods to provide for continued tracking and compensation for timing skew that may result from, for example, thermal drift” [Zelensky, Abstract]
Accordingly, it would have been obvious to a POSITA to obtain additional phase-difference measurements (third/fourth phase differences) using the same measurement framework (Xu’s repeat-across-channel-pairs approach) and to incorporate those additional phase differences into the delay estimate to improve accuracy/robustness, particularly in view of Zelensky’s teaching that correlation-based skew estimation can be refined using multiple trials and measurements.
A POSITA would have been motivated to use multiple phase/delay determinations because redundancy and cross-checking are known techniques to reduce noise and systematic measurement error, and Xu’s explicitly instructs repeating measurements across channel pairs while Zelensky supports multi-trial correlation-based skew estimation.
Claim 7
With respect to claim 7, all limitations of claim 6 are taught by Rohde, Xu, Sun, Nemer and Zelensky, except wherein claim 7 additionally requires obtaining a first-time delay from the first/second phase differences, obtaining a second time delay from the third/fourth phase differences, and determining a mean of the first- and second-time delays as the time delay.
Added: “Obtaining a first-time delay based on the first phase difference and the second phase difference; obtaining a second time delay based on the third phase difference and the fourth phase difference; determining a mean of the first-time delay and the second time delay as the time delay of the coherent receiver.”
However, within analogous art, Xu teaches obtaining delay/phase between different channel pairs by repeating the measurement and thereby obtaining multiple delay results “[0010] Furthermore, further comprising step e) replacing the oscilloscope connection of output channel, repeating steps a) to d) are optical coherence of time delay and phase difference between each channel of the receiver” [Xu, ¶ [0010]].
Averaging multiple independent delay estimates is a routine statistical technique to reduce random error and improve stability once multiple estimates are available, and is consistent with the measurement practice of repeating tests under different configurations to improve accuracy (Xu) and performing multiple correlation trials (Zelensky).
A POSITA would have been motivated to average the two delay estimates because averaging is a predictable, well-known method to improve repeatability and reduce measurement noise while preserving the underlying receiver delay value being estimated.
Claim 8
With respect to claim 8, all limitations of claim 6 are taught by Rohde, Xu, Sun, Nemer and Zelensky, except wherein claim 8 additionally specifies that the third phase difference is based on cross-correlation of the first and second signals and autocorrelation of the second signal (and similarly for the fourth phase difference using autocorrelation of the fourth signal).
Added: “cross-correlation operation on the first signal and the second signal to obtain a third cross-correlation result; performing an autocorrelation operation on the second signal to obtain a third autocorrelation result; obtaining the third phase difference based on the third cross-correlation result and the third autocorrelation result; and the processing the second set of signals to obtain a fourth phase difference corresponding to the second set of signals, comprises: performing a cross-correlation operation on the third signal and the fourth signal to obtain a fourth cross correlation result; performing an autocorrelation operation on the fourth signal to obtain a fourth autocorrelation result; obtaining the fourth phase difference based on the fourth cross-correlation result and the fourth autocorrelation result.”
However, within analogous art, Sun and Nemer teach correlation-based phase estimation and normalization using energy/power terms, and make clear that normalization can be formed using a quadrature power/energy term (i.e., either I-branch or Q-branch power/energy) depending on implementation “……The Normalization of Equation 2 with respect to I^2(t) isolates the sin(θ) term…….” [Sun, Col.8].
“[0036] At 504, a cross-correlation between the two quadratures is determined. The cross-correlation may be determined by multiplying the instantaneous values of the two quadratures. At 506, phase imbalance is corrected using the cross-correlation between the two quadratures. In one embodiment, the cross-correlation may be filtered and then normalized. The normalized cross-correlation may then be accumulated by an integrator to estimate the phase imbalance. A correction matrix may then be constructed using the estimated phase imbalance. The correction matrix may then be multiplied by the two quadratures to correct the phase imbalance” [Nemer, ¶ [0036]].
Additionally, within analogous art, Nemer expressly teaches estimating and using the quadrature energies (autocorrelation/energy) of both quadratures (I and Q) by squaring I and Q samples and filtering the squared values, i.e., explicitly obtaining Q-branch energy for normalization “[0022] FIG. 3 illustrates the amplitude correction block 200 in greater detail according to one embodiment of the invention. The amplitude correction is iterative feedback Scheme for estimating and correcting the amplitude imbalance. At each iteration instance of n, the instantaneous values of I and Q are Squared using one or more multipliers. One or more filters, such as 302 or 304, are used to filter the Squared values to provide an approximation of the long-term energy of each quadrature. In one embodiment, the filters are first order auto-regressive filters of the form” [Nemer, ¶ [0022]].
Nemer further expressly states that determining the difference between energies of two quadratures comprises “1. A method comprising: determining a difference between energies of two base band quadratures, correcting an amplitude imbalance using the difference between the energies of the two quadratures, determining a cross-correlation between the two quadratures, and correcting a phase imbalance using the cross-correlation between the two quadratures.
2. The method of claim 1, wherein determining a difference between energies of two quadratures comprises determining instantaneous energies of the two quadratures by Squaring instantaneous values of the two quadratures” [Nemer, ¶ [0037]].
Thus, the prior art explicitly teaches Q-branch autocorrelation/energy (Q^2) and also teaches using both I- and Q-based energies in the normalization framework, directly supporting claim 8’s use of autocorrelation on the second/fourth (Q) signal.
Accordingly, it would have been obvious to a POSITA to form the normalization/autocorrelation term using the second (or fourth) signal rather than the first (or third) signal because the quadrature signals are symmetric components of the coherent receiver output and selection of one or the other for normalization is a routine design choice yielding predictable equivalent results.
A POSITA would have been motivated to use the other quadratures autocorrelation/energy as the normalization term to enable cross-checking and multiple-estimate consistency while maintaining the known objective of amplitude normalization for robust phase estimation.
Claim 9
With respect to claim 9, all limitations of claim 1 are taught by Rohde and Xu, except wherein claim 9 additionally requires that the polarization state of the two split optical paths differs under the first frequency shift condition and also differs under the second frequency shift condition.
Added: “a polarization state of the one path of optical signal after splitting is different from that of another path of optical signal after splitting and then the first frequency shift; and a polarization state of the one path of optical signal after splitting is different from that of another path of optical signal after splitting and then the second frequency shift.”
However, within analogous art, Rohde expressly teaches performing measurements for different polarization states using a polarization rotator that is switchable between states to measure characteristics for two orthogonal polarizations “[0066] Although FIG. 1 shows a single differential output channel of COR 150 from a single optical mixer 130 , in other embodiments , such as those commonly used in coherent optical communications , the optical mixer 130 may be of the type known as 90° optical hybrid which has four output ports that connect to two differential photodetectors , so as to output in - phase ( I ) and quadrature ( Q ) signals as known in the art . Furthermore, for polarization diversity such a COR may use two optical hybrids, one for each of two orthogonal polarizations. [0067] Referring now to FIG. 5, there is schematically illustrated a block diagram of an embodiment of COR 150 in the form of a dual -polarization, dual - quadrature integrated coherent receiver (ICR) 250. ICR 250 includes a signal optical port 251 that connects to a polarization beam splitter (PBS) 254, which outputs are connected to one of two input ports of each of two 90° optical hybrids 230. A variable optical attenuator 253 may be connected between the signal input port 251 and the PBS 254, and a monitoring photodetector 237 coupled at the output thereof to monitor the optical signal power provided to the optical hybrids 230. An LO input port 252 connects to a polarization preserving beam splitter (PPS) 255, which outputs are connected to the remaining input ports of the optical hybrids 230. Each of the 90° hybrids 230 have four optical outputs that are pair – wise connected to two differential detectors 140. The two 90° hybrids 230 operate at orthogonal optical polarization com ponents of the input optical signal, and thus provide quadrature I and Q signals in two polarization channels or planes, which are referred to as X - and Y - (polarization) channels or X - and Y - polarization planes of the COR. Thus, ICR 250 has four output channels providing four output electrical signals Ix, Qx, Iy, and Qy that in FIG . 4 are labeled at 144, to 1442, respectively. The ICR 250 may be implemented in a single chip, and may be configured to have a receiver bandwidth of more than 10 GHz .[0068] Referring now to FIG . 6, there is illustrated an embodiment of the test apparatus 100, generally indicated at 400, that is configured for testing multi - channel polarization diversity coherent optical receivers of the type illustrated in FIG. 5 . The apparatus 400 includes all of the main components of the apparatus 100, but may additionally include a polarization rotator 115 in the arm of the apparatus that connects to the signal port 251 of OCR 250. A beam splitter 205 splits light from the coherent light source 101 into first and second lights 106, 107 to propagate along two optical paths, or arms, 116 and 117 of the apparatus, which terminate with the first and second output ports 111 and 112. The first output port 111 is configured to connect to the signal port 251 of ICR 250, and the second output optical port 112 is configured to connect to the LO port of ICR 250; accordingly, the first output port 111 may also be referred to as the signal output port of the apparatus 400, and the second output port 112 may also be referred to as the LO output port. The beam splitter 205 may be a polarization preserving beam splitter (PPS) that outputs the first and second lights 106, 107 of substantially the same polarization. The polarization rotator 115 may be configured to rotate the polarization of the received light by a desired angle, for example about 45°, so that the light received at the signal port 251……” [Rohde, ¶ ¶ [0066] – [0068]].
Accordingly, it would have been obvious to perform the claim 1 measurements under different polarization-state conditions because Rohde teaches two-step measurement with different polarization-rotator states for orthogonal polarizations, which predictably improves robustness and allows characterization of polarization-diverse coherent receivers.
A POSITA would have been motivated to vary polarization states during coherent receiver testing because coherent receiver outputs depend on polarization alignment; Rohde’s switchable polarization-rotator approach is a known and predictable technique to ensure sufficient SNR in both polarization planes and to characterize receiver behavior across polarization conditions.
Claim 10 is rejected under 35 U.S.C. §103 as being unpatentable over Rohde in view of Xu, and further in view of Pook et al. (DE 102013000312 B4), Hart et al. (US 5,721,689), and Huang et al. (CN101388001A).
Claim 10
With respect to claim 10, all limitations of claim 1 are taught by Rohde and Xu, except wherein claim 10 additionally requires that the sampling frequency for the acquired signal sets is an integer multiple of the respective frequency shift (or beat/offset frequency) used for the measurement.
Added: “The sampling frequency of the first set of signals is an integer multiple of the first frequency shift, and the sampling frequency of the second set of signals is an integer multiple of the second frequency shift.”
However, within analogous art, Pook expressly teaches selecting a sampling frequency that is an integer multiple of a desired spectral component “According to the invention, the sampling frequency is an integer multiple of the frequency of the desired discrete spectral component. In particular, the ratio of the sampling frequency to the frequency of the desired discrete spectral component is exactly one of the values 3, 4 and 6. For any ratio of the sampling frequency f .sub’s to the respective frequency of the desired discrete spectral component ƒ .sub.g of f .sub.s / ƒ .sub.g ≠ [3, 4, 6], the coefficient c.sub.re assumes a value from the range of the real numbers. The computational implementation for calculating the feedback quantity from the first state memory is a multiple sequence of multiplications and additions. In particular, the multiplications force a comparatively high computational effort. With a ratio of the sampling frequency f. sub. s to the respective frequency of the desired discrete spectral component ƒ. sub.g of f .sub.s / ƒ .sub.g = 3, the coefficient c .sub.re = -1. Thus, the state of the first state memory is fed back with an inverted sign. The computational implementation of inversion of the sign of magnitude is a bit operation that is performed in one computing step. With a ratio of the sampling frequency f. sub.s to the respective frequency of the desired discrete spectral component ƒ .sub.g of f .sub.s / ƒ .sub.g = 4, the coefficient c .sub.re = 0. Accordingly, the state of the first state memory is not fed back. This eliminates all calculation steps for calculating the feedback quantity from the first state memory without replacement. With a ratio of the sampling frequency f .sub.s to the respective frequency of the desired discrete spectral component ƒ .sub.g of f .sub.s / ƒ .sub.g = 6, the coefficient c .sub.re = 1. Accordingly, the state of the first state memory is correct-signed, ie unchanged, fed back” [Pook, p.3].
Hart likewise teaches that DFT-based phase estimation assumes an integer number of samples per cycle, resulting in sampling frequency being an integer multiple of the fundamental frequency “……...Note that the rms value requires division by a factor of the square root of 2. The above description of the DFT assumes an integer samples per cycle N., resulting in a sampling frequency f=(N*f), where f is the fundamental frequency, e.g., the expected operating frequency of the generator when fully energized. The fundamental frequency is related to the DFT window and may be an assumed value. With a sampling frequency of 60x32 Hz, the DFT calculation with a 32-sample window will have a fundamental frequency of 60 Hz. For the same At, a window of N=22 samples, the DFT fundamental frequency is 87.27 Hz. Thus, the sampling frequency is an integer multiple of the fundamental frequency. The actual generator frequency varies from the DFT fundamental frequency by an amount Af. Application of the DFT when f is not an integer of the fundamental will introduce an "error” in the phasor estimate. These errors used estimate the actual frequency using the deviation from fundamental frequency. Considering the signal defined by equation (1) where cois defined as 21c(f+Af), and f=(Nxf). Applying the DFT equation results in….” (Hart, Col.2).
Additionally, within analogous art, Huang teaches that when the integer-multiple relationship is not satisfied due to sampling frequency deviation, phase estimation becomes incorrect, highlighting the importance of the integer-multiple condition for accurate phase estimation “……. however, the Hilbert transform method has high requirement to the sampling frequency when the signal frequency A/s/N, phase of Thetaz +, the formula is measured accurately, once the sampling frequency deviation, making the relationship of the integer multiple is not satisfied, estimation of formula (I) is not correct, the method of anti-noise performance difference; besides, the method still can only estimate the single frequency signal. (3) the sine curve (7) John Kuffel provides sine curve fitting (7 ' 8), the method can get high estimation precision. It is divided into four parameters (frequency, amplitude, phase, and DC components are unknown) method and three-parameter method (except the frequency is known, the other 3 are unknown) two situations, document [9], four parameter curve fitting process is not a linear process is closed, there is no exact mathematical formula can directly calculate fitting parameter, if the improper selection of fitting the initial condition, it is easy to make the iterative process or converge to a local optimum, and fitting a lot of calculation time. In order to improve the efficiency, Document [9] provides first estimated frequency, sine curve fitting three parameters (a closed linear process, and absolute convergence). However, the method to the frequency estimation is very accurate, otherwise, a direct consequence is the frequency estimation error into the phase estimation, besides, the method still canonly single-frequency signals to phase estimation. (4) correlation method [1 to 11], Document [10 11] uses the correlation method for detecting phase, assuming reference sample sequence is 7 (/7) = C0S (2 i TRPI s/7), f 0, 1, ..., H, the sequence to be tested is f (/7) = (;05 (S 2:1/// trible. primary), 0, 1, ..., AM, is estimated y (n)…….” [Huang, p.3].
Accordingly, it would have been obvious to a POSITA to choose sampling frequencies as integer multiples of the beat/offset frequencies used in Xu’s FFT-based phase extraction in order to improve spectral-bin alignment and reduce estimation error, as explicitly taught by Pook/Hart/Huang.
A POSITA would have been motivated to apply the integer-multiple sampling condition because Xu relies on frequency-domain (FFT) phase estimation at beat frequencies, and Pook /Hart/ Huang provide explicit, well-known guidance that integer-multiple sampling improves discrete spectral component estimation accuracy; the modification is a predictable optimization with a reasonable expectation of success.
It is noted that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Conclusion
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/MOHAMMED ABDELRAHEEM/Examiner, Art Unit 2635
/DAVID C PAYNE/Supervisory Patent Examiner, Art Unit 2635