DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Election/Restrictions
Applicant’s election without traverse of Group A (Claims 1-18) in the reply filed on 09/10/2025 is acknowledged. Claims 1-18 are currently examined.
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 of this title, 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.
Claims 1-4, 6-12 and 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over US 20220038172 A1 (Kargieman), in view of Li, Z., Shen, H., Weng, Q., Zhang, Y., Dou, P. and Zhang, L., 2022. Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects. ISPRS Journal of Photogrammetry and Remote Sensing, 188, pp.89-108. (Li).
Regarding Claims 1, 9 and 18:
A computing system of a satellite comprising: one or more sensors comprising a forward-looking sensor; one or more processors; and one or more tangible, non-transitory, computer-readable media storing instructions executable by the one or more processors to cause the computing system to perform operations, the operations comprising: obtaining image data from the forward-looking sensor of the satellite, wherein the satellite is traveling along a current trajectory; determining, using a model and based on the image data, an imaging target and cloud coverage associated with the imaging target; determining a comparison between the cloud coverage associated with the imaging target and a threshold level of cloud coverage; determining an updated trajectory for the satellite based on the current trajectory and the comparison between the cloud coverage associated with the imaging target and the threshold level of cloud coverage; and generating one or more command instructions to control a motion of the satellite based on the updated trajectory (Kargieman: Fig. 1, an satellite with on board image system 106 and control system 118; Figs. 2-4, the image system performs various AI-enabled image processing including object detection among others; Fig. 5 and par. 95, image data may go through a cloud detection algorithm to identify cloud coverage areas for potential obstruction of target areas; par. 28, 144, further set of instructions from the satellite system may “cause the satellite system to be repositioned. That is, as the satellite system analyzes the images and detects objects, it may make the determination to reposition itself. Repositioning may include changing its attitude, altitude, orbit”, i.e., changing the satellite trajectory based on image analysis, including cloud obstruction among others).
Kargieman teaches in par. 31-34, 40-44, Fig. 4 and par. 84-94 AI-assisted image processing capability on the satellite system. Kargieman does not teach explicitly on a threshold based cloud identification method. However, Li teaches (Li: e.g., 3.1., detection based on spectral features, which performs feature extraction and combine multiple physical spectral rules to perform a threshold segmentation of clouds and shadows; 4.1., Physical-rule based algorithms that sets rules for threshold segmentation based on the physical properties of clouds/cloud shadows to achieve their detection among others).
It would have been obvious for one of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Kargieman with comparing the a threshold based cloud identification method as further taught by Li. The advantage of doing so is to enable methods to obtain accurate remote sensing of cloudy and rainy areas to improve satellite imaging applications (Li: Abstract).
Regarding Claims 2 and 10, Kargieman as modified further teaches:
The computing system of claim 1, wherein the operations further comprise accessing metadata associated with one or more environmental conditions (Li: e.g., 4.1., temperature, brightness, color and etc.).
Regarding Claims 3 and 11, Kargieman as modified further teaches:
The computing system of claim 2, wherein the metadata comprises at least one of (i) a sensor temperature, (ii) a sun angle, (iii) an earth surface angle, or (iv) a slew angle (Li: e.g., 4.1., temperature, brightness, color and etc.).
Regarding Claims 4 and 12, Kargieman as modified further teaches:
The computing system of claim 1, wherein the operations further comprise receiving a request for imagery of a geographic region, the request for imagery associated with the imaging target and the threshold level of cloud coverage (Kargieman: par. 52-53, user requests for image data for a geographic area(s). It is noted that image data implies a certain degree of image quality, where image quality requirements determine threshold level of could coverage or other level obstructions).
Regarding Claims 6 and 15, Kargieman as modified further teaches:
The computing system of claim 1, wherein the model is a convolutional neural network (Kargieman: e.g., par. 124).
Regarding Claims 7 and 16, Kargieman as modified further teaches:
The computing system of claim 1, wherein the one or more sensors comprises at least one of (i) a VIS camera (ii), or (ii) a LWIR camera (Li: Table 2, e.g., Rossow and Garder use infrared and visible radiances; Ricciardelli et al. use visible and infrared image data).
Regarding Claims 8 and 17, Kargieman as modified further teaches:
The computing system of claim 1, wherein the updated trajectory is a slew trajectory (Kargieman: par. 28, 144, further set of instructions from the satellite system may “cause the satellite system to be repositioned. That is, as the satellite system analyzes the images and detects objects, it may make the determination to reposition itself. Repositioning may include changing its attitude, altitude, orbit”, i.e., changing the satellite trajectory based on image analysis, including cloud obstruction among others, where attitude and altitude are slew trajectory).
Regarding Claim 14, Kargieman as modified further teaches:
The computer-implemented method of claim 9 further comprising: controlling the motion of the satellite to pass over the imaging target, wherein passing over the imaging target is indicative of a nadir position or an off-nadir position; and obtaining, using a sensor of the one or more sensors, imagery of the imaging target (Kargieman: par. 52-53, user requests for image data for a geographic area(s). It is noted that image data implies a certain degree of image quality, where image quality requirements determine threshold level of could coverage or other level obstructions. It is noted that in a case that satellite takes users requests or orders, the satellite is at or if going to fly over the requested area(s), therefore, the images either be taken at a nadir or off-nadir position).
Allowable Subject Matter
The Claims 5 and 13 are objected to as being dependent upon a rejected base claim, but are potentially 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 ZHITONG CHEN whose telephone number is (571) 270-1936. The examiner can normally be reached on M-F 9:30am - 5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Yuwen Pan can be reached on 571-272-7855. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ZHITONG CHEN/
Primary Examiner, Art Unit 2649