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 .
Claim Status
The status of claims 1-20 is:
Claims 1-20 are pending.
Claim Rejections - 35 USC § 101
Claims 18-20 claim a “computer storage medium” which would normally be rejected under 35 USC 101 as including signals per se. However, Applicant defined “computer storage media” in paragraph [0080] of the instant application when stating “As defined herein, computer storage media does not include communication media. Therefore, a computer storage medium is not a propagating signal. Propagated signals are not examples of computer storage media.” Therefore, no rejection under 35 USC 101 is made.
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 and 4 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Klein et al. (U.S. Patent Publication No 2020/0256978, hereinafter “Klein”).
Regarding claim 1, Klein discloses a system comprising:
a processor (Klein [0090]: “The present invention can be a system, a method, and/or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention”); and
a memory comprising computer program code (Klein [0090]: “The present invention can be a system, a method, and/or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention”), the memory and the computer program code configured to cause the processor to:
obtain synthetic aperture radar (SAR) data of a geographic area from a plurality of satellite passes by a satellite (Klein [0036]: “The spectral information received from the optical satellite can be used to identify the no vegetation areas (or bare land images) and can be used as reference SAR images that can be assumed to be the bare land image”; Klein [0037]: “A second SAR image is acquired when the crop has emerged in the springtime”);
calculate a coherence value for a SAR data subset pair including a first SAR data subset and a second SAR data subset, wherein the first SAR data subset is associated with a first satellite pass of the plurality of satellite passes and the second SAR data subset is associated with a second satellite pass of the plurality of satellite passes (Klein [0037]: “A differential phase image is created to assess change in the interferometry signal. The image is corrected for local topographical variation to access the change in vegetation. The change in height for the crop is tracked multiple times after planting (during a predetermined time period)”);
process the obtained SAR data into interferometric data using the calculated coherence value (Klein [0037]: “A differential phase image is created to assess change in the interferometry signal. The image is corrected for local topographical variation to access the change in vegetation. The change in height for the crop is tracked multiple times after planting (during a predetermined time period)”);
provide the coherence value and the interferometric data to a trained crop growth estimation model (Klein [0055]: “The classified SAR images go through backscattering extraction block 114 and are provided to a crop models block 116. The crop models block 116 includes creating, training, and updating crop models for determining at least crop growth rates of a plurality of different plants in a plurality of different fields”; Klein Fig. 4); and
generate, using the trained crop growth estimation model, a crop growth prediction associated with the geographic area (Klein [0085]: “In various exemplary embodiments, the crop models 116 can be used to estimate a crop height at the end of the season (or at harvest time). For instance, at time T=0, a seed 190 is detected. T=0 can correlate to the time of planting or seeding. At time T=1, a plant 192 might have grown to a first height. This can be, e.g., after a week. At time T=2, the plant 194 grew a bit bigger to a second height. This can be, e.g., after 3 weeks. The difference in heights between time periods T=1 and T=2 can be designated as H1. At T=3, the plant 196 has grown even further to a third height. This can be, e.g., after 6 weeks. The difference in heights between time periods T=3 and T=2 can be designated as H2. At T=4, the plant 198 has grown even further to a fourth height. This can be, e.g., after 8 weeks. The difference in heights between time periods T=4 and T=3 can be designated as H3. The crop models 116 can be used to estimate the crop growth at time T=5, which can be the harvest time. The estimated plant 200 is shown at T=5. The plant 200 can be estimated based on a number of factors or parameters or variables discussed above. The continuously collected data can be provided to a computing device 174 for further processing and for executing the crop models 116 (FIG. 4). Thus, the growth rate for a crop during a growing season can be calculated based on the generated SAR images received from satellites 12 and crop development during the growing season can be calculated”).
Regarding claim 4, Klein discloses the system, wherein the memory and the computer program code are configured to further cause the processor to:
process the obtained SAR data into additional processed SAR data (Klein [0054]: “Regarding the speckle filtering block 110, it is noted that SAR transmits a precise signal toward its target (e.g., crop field) and, when the reflected radiation returns, a SAR records not only the amplitude of that signal, but its phase as well”), wherein the additional processed SAR data includes at least one of the following: amplitude data or polarimetric SAR data (Klein [0021]: “SAR images include information about an amplitude and a phase of a signal acquired by geo-orbiting satellites”; Klein [0054]: “Regarding the speckle filtering block 110, it is noted that SAR transmits a precise signal toward its target (e.g., crop field) and, when the reflected radiation returns, a SAR records not only the amplitude of that signal, but its phase as well”); and
wherein the additional processed SAR data is provided to the trained crop growth estimation model (Klein [0055]: “The classified SAR images go through backscattering extraction block 114 and are provided to a crop models block 116. The crop models block 116 includes creating, training, and updating crop models for determining at least crop growth rates of a plurality of different plants in a plurality of different fields”).
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) 7 is rejected under 35 U.S.C. 103 as being unpatentable over Klein in view of Yang et al. (U.S. Patent Publication No 2022/0283295, hereinafter “Yang”).
Regarding claim 7, Klein discloses the system, wherein processing the obtained SAR data into the interferometric data includes:
converting the obtained SAR data into the interferometric data (Klein [0037]: “A differential phase image is created to assess change in the interferometry signal. The image is corrected for local topographical variation to access the change in vegetation. The change in height for the crop is tracked multiple times after planting (during a predetermined time period)”; Klein [0085]: “In various exemplary embodiments, the crop models 116 can be used to estimate a crop height at the end of the season (or at harvest time). For instance, at time T=0, a seed 190 is detected. T=0 can correlate to the time of planting or seeding. At time T=1, a plant 192 might have grown to a first height. This can be, e.g., after a week. At time T=2, the plant 194 grew a bit bigger to a second height. This can be, e.g., after 3 weeks. The difference in heights between time periods T=1 and T=2 can be designated as H1. At T=3, the plant 196 has grown even further to a third height. This can be, e.g., after 6 weeks. The difference in heights between time periods T=3 and T=2 can be designated as H2. At T=4, the plant 198 has grown even further to a fourth height. This can be, e.g., after 8 weeks. The difference in heights between time periods T=4 and T=3 can be designated as H3. The crop models 116 can be used to estimate the crop growth at time T=5, which can be the harvest time. The estimated plant 200 is shown at T=5. The plant 200 can be estimated based on a number of factors or parameters or variables discussed above. The continuously collected data can be provided to a computing device 174 for further processing and for executing the crop models 116 (FIG. 4). Thus, the growth rate for a crop during a growing season can be calculated based on the generated SAR images received from satellites 12 and crop development during the growing season can be calculated”); and
wherein the phase unwrapped interferometric is provided to the trained crop growth estimation model (Klein [0055]: “The classified SAR images go through backscattering extraction block 114 and are provided to a crop models block 116. The crop models block 116 includes creating, training, and updating crop models for determining at least crop growth rates of a plurality of different plants in a plurality of different fields”).
Klein does not explicitly disclose the system, wherein processing the obtained SAR data into the interferometric data includes:
applying a phase unwrapping algorithm to the interferometric data.
However, Yang teaches the system, wherein processing the obtained SAR data into the interferometric data includes:
applying a phase unwrapping algorithm to the interferometric data (Yang [0085]: “Preferably, during synthetic aperture radar interferometric imaging according to the long cross-track baseline and the short cross-track baseline D, the phase difference obtained from the interferogram is the phase principal value between [−π, π] after unknown integer periods of wind-up. The winding phases have to be restored to show their actual phase differences, and the process is called phase unwrapping. Preferably, the imaging and sensing device 300 obtains information about synchronization in terms of time and frequency based on the along-track baseline and the cross-track baseline in time series, thereby calibrating signals it receives. The imaging and sensing device 300 then performs phase compensation based on the calibrated information, and uses the short cross-track baseline to perform phase unwrapping on the long cross-track baseline, thereby further enhancing precision of terrain altitude measurement”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the phase unwrapping as taught by Yang with the system of Klein because it would restore the phases to show their actual phase differences (Yang [0085]). This motivation for the combination of Klein and Yang is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention and rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Claim(s) 8 is rejected under 35 U.S.C. 103 as being unpatentable over Klein in view of Lingner (Lingner, S. (2019). Dry mass estimation at linear forest objects via structure from motion (Doctoral dissertation, Christian-Albrechts Universität Kiel)., hereinafter “Lingner”).
Regarding claim 8, Klein does not explicitly disclose the system, wherein the generated crop growth prediction includes estimated parameters of a sigmoidal growth curve associated with crops growing in the geographic area.
However, Lingner teaches the system, wherein the generated crop growth prediction includes estimated parameters of a sigmoidal growth curve associated with crops growing in the geographic area (Lingner Page 84: “The smooth function of the GAM indicates that there is a small growth rate in the first 15 years. After this period the growth rate maximises until approximately 25 years and decreases again afterwards. This shape of the curve does not surprise since trees are expected to have a sigmoidal growth curve like all organisms (West, 1987; Weiner and Thomas, 2001). The growth is finally constrained by limited recourses like light”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the sigmoidal growth curve as taught by Lingner with the system of Klein because it would improve the accuracy of the prediction as all organisms follow a sigmoidal growth curve (Lingner Page 84). This motivation for the combination of Klein and Lingner is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention and rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Claim(s) 10 is rejected under 35 U.S.C. 103 as being unpatentable over Klein in view of Bowers et al. (U.S. Patent Publication No 2024/0103156, hereinafter “Bowers”).
Regarding claim 10, Klein discloses the system, wherein the trained crop growth estimation model generates the crop growth prediction based at least in part on the data received (Klein [0055]: “The classified SAR images go through backscattering extraction block 114 and are provided to a crop models block 116. The crop models block 116 includes creating, training, and updating crop models for determining at least crop growth rates of a plurality of different plants in a plurality of different fields”).
Klein does not explicitly disclose the system, wherein the obtained SAR data includes first frequency data associated with a first radar frequency and second frequency data associated with a second radar frequency; and
wherein the first frequency data and the second frequency data are provided to the trained crop growth estimation model.
However, Bowers teaches the system, wherein the obtained SAR data includes first frequency data associated with a first radar frequency and second frequency data associated with a second radar frequency (Bowers [0009]: “A satellite imaging system is provided. The system includes a first satellite, a trailing satellite, and a ground terminal. The first satellite is configured to: acquire synthetic aperture radar (SAR) image data in a first predetermined signal frequency band at a first imaging location, the first imaging location defined by first coordinates; and transmit the SAR image data to the ground terminal via a first downlink. The ground terminal is configured to: determine a second imaging location from the received SAR image data, the second imaging location defined by second coordinates; and transmit the second imaging location to the trailing satellite via a second uplink. The trailing satellite is configured to: acquire image data in a second predetermined signal frequency band at the second imaging location, the image data having a higher resolution than the SAR image data; and transmit the image data to the ground terminal via a second downlink”); and
wherein the first frequency data and the second frequency data are provided to the trained crop growth estimation model (Bowers [0009]: “A satellite imaging system is provided. The system includes a first satellite, a trailing satellite, and a ground terminal. The first satellite is configured to: acquire synthetic aperture radar (SAR) image data in a first predetermined signal frequency band at a first imaging location, the first imaging location defined by first coordinates; and transmit the SAR image data to the ground terminal via a first downlink. The ground terminal is configured to: determine a second imaging location from the received SAR image data, the second imaging location defined by second coordinates; and transmit the second imaging location to the trailing satellite via a second uplink. The trailing satellite is configured to: acquire image data in a second predetermined signal frequency band at the second imaging location, the image data having a higher resolution than the SAR image data; and transmit the image data to the ground terminal via a second downlink”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate using two different radar frequencies as taught by Bowers with the system of Klein because it would allow for the use of a second frequency that could capture an image with a higher resolution than the first frequency was able to capture (Bowers [0009]). This motivation for the combination of Klein and Bowers is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention and rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Claim(s) 18 is rejected under 35 U.S.C. 103 as being unpatentable over Klein in view of Ray (U.S. Patent Publication No 2023/0213648, hereinafter “Ray”).
Regarding claim 18, Klein discloses a computer storage medium has computer-executable instructions (Klein [0090]: “The present invention can be a system, a method, and/or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention”) that, upon execution by a processor, cause the processor to at least:
obtain synthetic aperture radar (SAR) data of a geographic area from a plurality of satellite passes by a satellite (Klein [0036]: “The spectral information received from the optical satellite can be used to identify the no vegetation areas (or bare land images) and can be used as reference SAR images that can be assumed to be the bare land image”), the obtained SAR data including amplitude data (Klein [0021]: “SAR images include information about an amplitude and a phase of a signal acquired by geo-orbiting satellites”; Klein [0054]: “Regarding the speckle filtering block 110, it is noted that SAR transmits a precise signal toward its target (e.g., crop field) and, when the reflected radiation returns, a SAR records not only the amplitude of that signal, but its phase as well”);
calculate a coherence value for a SAR data subset pair including a first SAR data subset and a second SAR data subset, wherein the first SAR data subset is associated with a first satellite pass of the plurality of satellite passes and the second SAR data subset is associated with a second satellite pass of the plurality of satellite passes (Klein [0037]: “A differential phase image is created to assess change in the interferometry signal. The image is corrected for local topographical variation to access the change in vegetation. The change in height for the crop is tracked multiple times after planting (during a predetermined time period)”);
process the obtained SAR data into interferometric data using the calculated coherence value (Klein [0037]: “A differential phase image is created to assess change in the interferometry signal. The image is corrected for local topographical variation to access the change in vegetation. The change in height for the crop is tracked multiple times after planting (during a predetermined time period)”);
provide the amplitude data, the coherence value, and the interferometric data to a trained crop growth estimation model (Klein [0055]: “The classified SAR images go through backscattering extraction block 114 and are provided to a crop models block 116. The crop models block 116 includes creating, training, and updating crop models for determining at least crop growth rates of a plurality of different plants in a plurality of different fields”; Klein Fig. 4); and
generate, using the trained crop growth estimation model, a crop growth prediction associated with the geographic area (Klein [0085]: “In various exemplary embodiments, the crop models 116 can be used to estimate a crop height at the end of the season (or at harvest time). For instance, at time T=0, a seed 190 is detected. T=0 can correlate to the time of planting or seeding. At time T=1, a plant 192 might have grown to a first height. This can be, e.g., after a week. At time T=2, the plant 194 grew a bit bigger to a second height. This can be, e.g., after 3 weeks. The difference in heights between time periods T=1 and T=2 can be designated as H1. At T=3, the plant 196 has grown even further to a third height. This can be, e.g., after 6 weeks. The difference in heights between time periods T=3 and T=2 can be designated as H2. At T=4, the plant 198 has grown even further to a fourth height. This can be, e.g., after 8 weeks. The difference in heights between time periods T=4 and T=3 can be designated as H3. The crop models 116 can be used to estimate the crop growth at time T=5, which can be the harvest time. The estimated plant 200 is shown at T=5. The plant 200 can be estimated based on a number of factors or parameters or variables discussed above. The continuously collected data can be provided to a computing device 174 for further processing and for executing the crop models 116 (FIG. 4). Thus, the growth rate for a crop during a growing season can be calculated based on the generated SAR images received from satellites 12 and crop development during the growing season can be calculated”).
Klein does not explicitly disclose the medium, the processor at least:
obtaining SAR data including polarimetric SAR data.
However, Ray teaches the medium, the processor at least:
obtaining SAR data including polarimetric SAR data (Ray [0003]: “In the airborne case, the direction of the electric field vector for horizontal polarization is parallel to the earth’s surface, and the vertical polarization is perpendicular to the surface. The same type of polarization transmission and reception is referred to as VV or HH (first letter of the pair is the transmitter, second is the receiver). The cross-polarization response is the transmission and reception of opposite orientations of the electric field (HV or VH). These additional methods enhance both clutter and man-made object detection. For example, polarimetric radar has been applied to power line detection where VV and HV returns are higher than HH at aspect angles away from normal incidence and for steeper grazing angles. VV and HV returns are also highly correlated and their product with averaging can increase the signal to clutter ratio versus VV alone. These distinguishing characteristics can more generally be applied to linear and axially symmetric features as man-made vehicles and objects would have”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the polarimetric SAR data as taught by Ray with the system of Klein because the different polarization are better at detecting different features (Ray [0003]) and so obtaining that data and providing it to the model would improve the models ability to make predictions based on the data. This motivation for the combination of Klein and Ray is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention and rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Allowable Subject Matter
Claims 11-17 are allowed.
Claims 2-3, 5-6, 9, and 19-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AIDAN KEUP whose telephone number is (703)756-4578. The examiner can normally be reached Monday - Friday 8:00-4:00.
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/AIDAN KEUP/ Examiner, Art Unit 2666 /Molly Wilburn/Primary Examiner, Art Unit 2666