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 .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 should not be negated by the manner in which the invention was made.
Claim(s) 1-3,6-8,11,17-20,26-40 are rejected under 35 U.S.C. 103 as being unpatentable over Hogasten et al (US 2014/0168445)in view of Ferris et al (Daytime GEO Tracking with “Aquila”: Approach and Results from a New Ground-Based SWIR Small Telescope System)
As to claim 1, Hogasten et al teaches a system for detecting space objects, the system comprising:
a camera system (100, figure 1) comprising one or more shortwave infrared (SWIR) sensors ( imaging sensor device 1402 may alternatively or additionally be implemented using imaging sensor arrays or modules adapted to capture non-thermal (e.g., including electromagnetic radiation in visible wavelengths, near-infrared (NIR) wavelengths, shortwave infrared (SWIR) wavelengths, paragraph [0208])
a computer system comprising one or more processors configured to execute one or more computer program instructions that, when executed by one or more processors, effectuate operations comprising:
(a) obtaining a stacked image by stacking SWIR images of a daytime sky (In block 505, infrared sensors 132 begin capturing image frames of a scene, paragraph [0109]), wherein the SWIR images are captured by the camera system(( imaging sensor device 1402 may alternatively or additionally be implemented using imaging sensor arrays or modules adapted to capture non-thermal (e.g., including electromagnetic radiation in visible wavelengths, near-infrared (NIR) wavelengths, shortwave infrared (SWIR) wavelengths, paragraph [0208]);
While Hogasten teaches the limitation above. Hogasten fails to teach “(b) processing the stacked image into an array of pixels to identify at least one cluster of pixels based at least in part on a signal intensity of a plurality of pixels of the array of pixels; (c) generating output data based at least in part on the at least one cluster of pixels, wherein the output data is indicative of a space object imaged by the camera system . “ However, Ferris et al teaches a frame stacking (temporal low-pass filtering) is not as effective on 1/F (temporally correlated) noise as white (temporally uncorrelated) noise. PRNU is the variability of each photosite’s signal with respect to incident light. Standard practice from camera manufacturers is to apply a 2-point NUC (dark and gain terms) or 3-point NUC (dark, gain, and power terms) to correct for this noise source. Such practices have been found to be insufficient when attempting to reduce spatial noise down to stacked temporal noise limits. Numerica has developed a custom calibration routine to fit an arbitrary, continuous, monotonic function to each photo site using hundreds of measurements ( section 3.2).It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect space object in order to demonstrate a responsive, robust, and affordable commercial deep-space tracking system. Therefore, the claimed invention would have been obvious to one of ordinary skill in the art at the time of the invention by applicant.
As to claim 2,Ferris et al teaches the system of claim 1, wherein: the camera system comprises: one or more thermoelectric coolers (TECs)( thermoelectric coolers (TECs), section 3.1.3rd paragraph )
As to claim 3, Ferris et al teaches the system of claim 1, wherein the SWIR images of the daytime sky correspond to a plurality of seconds of imaging of the daytime sky by the camera system. ( Aquila acquires and stacks frames at rates of 100 Hz or higher, depending on scene conditions, section 3.2 note that Ferris teaches ( Ideally stacking of N frames would produce an SNR improvement equal to √N ( page 9 lines 24-25; figure 8).).
As to claim 6, Ferris et al teaches the system of claim 1, wherein the operations further comprise: identifying one or more candidate space objects based at least in part on the at least one cluster of pixels; and identifying at least one false positive from the one or more candidate space objects (Frame stacking (temporal low-pass filtering) is not as effective on 1/F (temporally correlated) noise as white (temporally uncorrelated) noise. PRNU is the variability of each photosite’s signal with respect to incident light. Standard practice from camera manufacturers is to apply a 2-point NUC (dark and gain terms) or 3-point NUC (dark, gain, and power terms) to correct for this noise source. Such practices have been found to be insufficient when attempting to reduce spatial noise down to stacked temporal noise limits. Numerica has developed a custom calibration routine to fit an arbitrary, continuous, monotonic function to each photosite using hundreds of measurements, section 3.2).
As to claim 7,Hogastan et al teaches the system of claim 1, wherein generating the output data comprises: generating an output image comprising an indication of the space object figure 6 and paragraph [0132]).
As to claim 8, Hogastan et al et al teaches the system of claim 1, comprising: wherein the camera system further comprises one or more filters(high pass filter; paragraph[0128][0140])
As to claim 11, Ferris et al et al teaches the system of claim 1, wherein the operations comprise: computing a numerical value for each signal intensity of the plurality of pixels of array of pixels ( Ideally stacking of N frames would produce an SNR improvement equal to √N ( page 9 lines 24-25; figure 8).
As to claim 17, Hogasten et al teaches the system of claim 1, wherein the camera system: is configured to maintain dark currents less than or equal to 100 kilo-electrons per pixel per second; is configured to capture images with a framerate greater than 100 Hz ( other frame rates, paragraph [0156][0157]); and comprises an optical train having one or more lowpass filters having cutoff wavelengths selected between 0.9-1.7 microns and one or more infrared polarizers (paragraph [0156-0159]) .
As to claim 18, Hogasten et al teaches the system of claim 1, wherein the camera systems is a ground-based camera system ( the non-thermal images captured at imaging sensor device 1402 may be visible light images that include pixels having pixel values that may be indicative of irradiance levels of radiation in the visible light spectrum (e.g., luminance, brightness, or other quantity of visible light intensity; paragraph [0208]).
The limitation of claims 19-20, 26-40 has been addressed above, see Ferris section 3.2.
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NANCY . BITAR
Examiner
Art Unit 2664
/NANCY BITAR/Primary Examiner, Art Unit 2664
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