DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Specification
The disclosure is objected to because of the following informalities:
In [0087], line 8, “Fifth (e)” should be --Fifth (v)-- to be consistent in the numbering scheme and be consistent with FIG. 4.
Appropriate correction is required.
Claim Objections
Claims 1-11 are objected to because of the following informalities:
In claim 1, line 5, “magnetic noise and geomagnetic field data” should be --the magnetic noise and the geomagnetic field data-- to void creating another antecedent bases (see the preamble for the antecedent bases).
In claim 1, line 8, “the magnetic noise data” should be --the magnetic noise-- to avoid the issue of lack of antecedent basis.
In claim 5, lines 2-3, “the magnetic noise data” should be --the magnetic noise-- to avoid the issue of lack of antecedent basis.
In claim 6, line 5, “magnetic noise and geomagnetic field data” should be --the magnetic noise and the geomagnetic field data-- to void creating another antecedent bases (see the preamble for the antecedent bases).
In claim 6, lines 7-8, “the magnetic noise data” should be --the magnetic noise-- to avoid the issue of lack of antecedent basis.
In claim 11, line 3, “the magnetic noise data” should be --the magnetic noise-- to avoid the issue of lack of antecedent basis.
The other claim(s) not discussed above, or depending on the above claim(s), are objected to for inheriting the issue(s) from their linking claim(s).
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, it recites “analyzing a relative gain and phase of the representative detection signal in a time-frequency (TF) domain, if a noise signal of the representative detection signal is sparse in the TF domain then the relative gain and phase is found using cluster analysis” in lines 9-12. It appears that finding the relative gain and phase is contingent on a noise signal of the representative detection signal being sparse in the TF domain. However, it is unclear whether “analyzing a relative gain and phase of the representative detection signal in a time-frequency (TF) domain” is also contingent on a noise signal of the representative detection signal being sparse in the TF domain.
For examination purpose, --analyzing a relative gain and phase of the representative detection signal in a time-frequency (TF) domain, [[if]]wherein a noise signal of the representative detection signal is sparse in the TF domain and the relative gain and phase is found using cluster analysis-- is assumed.
In claim 5, it recites “each axis of the plurality of magnetometers” in lines 3-4. It is unclear whether it means “an axis of each of the plurality of magnetometers”, “each of a plurality of axes of the plurality of magnetometers”, or else.
For examination purpose, --an axis of each of the plurality of magnetometers-- is assumed.
Regarding claim 6, it recites “analyzing a relative gain and phase of the representative detection signal in a time-frequency (TF) domain, if a noise signal of the representative detection signal is sparse in the TF domain then the relative gain and phase is found using cluster analysis” in lines 9-12. It appears that finding the relative gain and phase is contingent on a noise signal of the representative detection signal being sparse in the TF domain. However, it is unclear whether “analyzing a relative gain and phase of the representative detection signal in a time-frequency (TF) domain” is also contingent on a noise signal of the representative detection signal being sparse in the TF domain.
For examination purpose, --analyzing a relative gain and phase of the representative detection signal in a time-frequency (TF) domain, [[if]]wherein a noise signal of the representative detection signal is sparse in the TF domain and the relative gain and phase is found using cluster analysis-- is assumed.
In claim 11, it recites “each axis of the plurality of magnetometers” in lines 4-5. It is unclear whether it means “an axis of each of the plurality of magnetometers”, “each of a plurality of axes of the plurality of magnetometers”, or else.
For examination purpose, --an axis of each of the plurality of magnetometers-- is assumed.
The other claim(s) not discussed above, or depending on the above claim(s), are rejected for inheriting the issue(s) from their linking claim(s).
Notes
Claims 1 and 6 distinguish over the closest prior art of record as discussed below.
Regarding claims 1 and 6, the closest prior art of record fails to teach the feature of claim 1 (as the representative): “analyzing a relative gain and phase of the representative detection signal in a time-frequency (TF) domain, if a noise signal of the representative detection signal is sparse in the TF domain then the relative gain and phase is found using cluster analysis, and separating a geomagnetic field data signal from a magnetic noise data signal using cluster centroids in compressive sensing based on the cluster analysis,” in combination with the rest of the claim limitations as claimed and defined by the Applicant. The method separates the noise signal by clustering data in TF domain and performing compressive sensing.
Carter et al. ("CORRECTING GOES-R MAGNETOMETER DATA FOR STRAY FIELDS" 2016 ESA Workshop on Aerospace EMC (Aerospace EMC), Valencia, Spain, 2016) teaches a method of separating stray magnetic noise from geomagnetic field data by using an algorithm to switch between using gradiometry or averaging measurements of magnetometers.
Ream et al. ("Magnetic gradiometry using frequency-domain filtering" Meas. Sci. Technol. 33 (2022) 015104; cited in IDS) teaches a gradiometry algorithm that detects stray magnetic field signals through differencing magnetometer measurements in the time-domain and suppressing them in the frequency-domain.
Constantinescu et al. ("Maximum-variance gradiometer technique for removal of spacecraft-generated disturbances from magnetic field data" Geosci. Instrum. Method. Data Syst., 9, 451-469, 2020) teaches an algorithm that transforms a dual-magnetometer measurements into a new coordinate system derived from principle component analysis, and performs gradiometry along the direction of maximum-variance.
SHEINKER et al. ("Adaptive Interference Cancelation Using a Pair of Magnetometers" IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS VOL. 52, NO. 1 FEBRUARY 2016) teaches an analytical blind source separation method to remove a single noise source using a pair of magnetometers.
Imajo et al. ("Signal and Noise Separation From Satellite Magnetic Field Data Through Independent Component Analysis: Prospect of Magnetic Measurements Without Boom and Noise Source Information" Journal of Geophysical Research: Space Physics, 126, e2020JA028790, 2021; cited in IDS) teaches a noise separation method by applying Independent Component Analysis to separate noise signal based on their statistical independence.
The above are the closest references that utilize two or more magnetometers to facilitate the separation of the noise signal. Still, none of the prior art of record teaches or suggests the above indicated feature as claimed.
Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
ZHU et al. (CN 110673206 A) teaches a satellite magnetic field data seismic abnormality detection method, involving decomposing magnetic field in time-frequency domain to separate components caused by earthquake and components caused by solar activity.
ZHANG et al. (CN 106842344 B) teaches a unmanned aerial vehicle navigation magnetic full-axis gradient magnetic interference compensation method, involving training a feedforward networking to take normalized wavelet transformation of flight magnetic data as input, and output magnetic interference compensation data; and compensating the magnetic field measurement using the compensation data.
KIM et al. (US 20180115874 A1) teaches a method for performing geomagnetic signal processing, involving converting obtained geomagnetic signal into a high frequency signal using a signal processing filter; extracting abnormal high frequency signal values; determining whether a sum of the extracted abnormal high frequency signal values converges into a critical range a preset time window; and correcting the geomagnetic signal based on the determining.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN C KUAN whose telephone number is (571)270-7066. The examiner can normally be reached M-F: 9:00AM-5:30PM.
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/JOHN C KUAN/Primary Examiner, Art Unit 2857
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