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 .
Response to Amendment
Applicant previously filed claims 1,3-12 and 14-20. Claims 1 and 20 have been amended. Accordingly, claims 1,3-12 and 14-20 remain pending in the current application.
Response to Arguments
Applicant's arguments filed 11/14/2025 have been fully considered but they are not persuasive.
Applicant argues that Carr fails to teach “refining timestamped geolocation data and then correcting the attitude filter parameters of the Kalman filter based on the secondary geolocation data”. However examiner respectfully disagrees. In Paragraph 7, Carr explains underlying basis for INR technology as follows: “INR technology enables the accurate location of an image's individual pixels with respect to geographical coordinates. INR systems rely on sophisticated instrumentation to determine the absolute location and attitude, or orientation, of the orbiting spacecraft. They may also take into account internal configurations such as telescope magnification, the location of a scan mirror which determines the position of the sensor relative to the detector frame, and various other optical alignments.” In Paragraph 8, Carr teaches “Currently, state of the art INR systems have the ability to create data products where image pixels are assigned geographic coordinates with errors on the order of the pixel resolution or better. INR systems such as these are used in the Geostationary Operational Environmental Satellites (GOES), operated by the United States National Environmental Satellite, Data and Information Service (NESDIS), and the Meteosat satellites, operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and are termed "exquisite" systems for their ability to geo-locate image pixels with extreme accuracy.” In Paragraph 10, Carr teaches “a need in the art exists for a low cost system capable of measuring orientation and pixel location with a high degree of accuracy. A system and method for low cost, high precision INR by transferring geo-referenced pixel knowledge from an exquisite system to a less sophisticated system is herein presented.” Thus it is made exceedingly clear that the system presented is concerned with providing geolocation information for timestamped target pixels. In Paragraph 31, Carr teaches “Accordingly, in step 200 according to the present invention, the system utilizes the reference imagery from the exquisite system operating over roughly the same geographic location as the system of the present invention to compare with imagery from the non-exquisite system. By way of example, the GOES-R satellite, scheduled to launch in 2016, will provide imagery of the Earth's western hemisphere from a geosynchronous orbit. It will be classified as an exquisite system with advanced geo-referencing capabilities. The GOES-R satellite will provide an output of image and measurement data in real-time every five (5) minutes. Thus, the GOES-R satellite product will refresh twelve (12) times during each TEMPO scan, which lasts for approximately one (1) hour. While reference imagery from any type of geosynchronous or highly elliptical, near-polar or similar orbital satellite with highly accurate INR can be utilized with the instant invention, imagery from geostationary systems is preferred due to the high refresh rate of those systems.” In Paragraph 23, Carr teaches “As seen in FIG. 2 the peripheral system instrumentation also includes a tracking ephemeris 3 to specify the location of the spacecraft/remote sensing instrument in space. The tracking ephemeris 3 derives ephemeris data either indirectly such as, for example, by conventional ground tracking of the satellite's orbit, or directly by the means of an onboard global positioning system (GPS) receiver. In either case, tracking ephemeris 3 specifies the location of the spacecraft/remote sensing instrument in space using ephemeris data and, optional almanac data, from ground or the onboard GPS receiver in a known manner. In addition, an onboard gyroscope 4, such as a three-axis gyroscope package, tracks changes in the attitude of the system relative to inertial space. Recall that gyroscopes on their own cannot determine absolute orientation (roll, pitch, yaw angles) but only changes in orientation.” In Paragraph 24, Carr teaches “As seen at right, measurements taken from tracking ephemeris 3 and gyroscope 4 are fed into an Image Navigation and Registration (INR) processing system 10 in accordance with the present invention, which uses them to observe orbital motion of the vehicle and perturbations in the attitude of the optical axes at the scan mirror as described above. The INR processing system 10 calculates the apparent pixel shift due to these effects in real-time, and maintains accurate referencing of the pixels with respect to the geographical coordinate frame with a high degree of accuracy in near real-time. To do this, the INR processing system 10 computes directions of the lines of sight for each detector in a known manner relative to the rigid body of the instrument based upon the known orientation of the scan mirror 2, which is measured by one or more scan encoder(s) for its two axes 6, 7 to measure orientation. This computation provides a line-of-sight (LOS) vector for each detector. Various other parameters relevant to telescope 1, such as magnification and other optical alignments, are also known, albeit not necessarily exactly. Based upon the foregoing combination of at least: 1) location data for the spacecraft/remote sensing instrument in space (from Tracking Ephemeris 3); and 2) attitude changes in the spacecraft/remote sensing instrument pitch, roll and yaw (from gyroscope 4) both input to the INR processing system 10, plus 3) LOS vectors for each detector computed by the INR processing system 10, the INR system 10 calculates the position and orientation of the spacecraft or remote sensing instrument, and the geographic locations of the detector footprints, at a given time, t, and at a later time, after the passage of an amount of time .DELTA.t, which time can be noted as 1+.DELTA.t.” In Paragraph 30, Carr teaches “The INR processing system 10 of the present invention applies a linear quadratic estimation over a series of input measurements observed over time to compensate for apparent pixel shift and other perturbations in real-time, using image-to-image registration of the hosted payload imagery versus exquisite system imagery as one input to improve the accuracy of the hosted payload INR processing system. One embodiment of the method according to the present invention involves the use of a Kalman Filter, an algorithm that keeps track of the estimated state of a system, and an associated covariance, or uncertainty, over a period of time. The Kalman Filter is depicted generally at step 201 in FIG. 3, which also shows the Kalman Filter 201 receiving the following inputs: landmark 210/tie-point 220 data from step 200, location data from the tracking ephemeris 3, attitude data from the gyroscope 4, orientation data from scan mirror 2 sensor(s) 6, 7, and possibly other data as a matter of design choice indicative of alignment, scanner, and optical characteristics (e.g., telescope magnification). The Kalman Filter algorithm 201 represents the state of the system mathematically as a state vector, which consists of orbital position and velocity states, instrument attitude states, and other states to represent alignment, scanner, and optical characteristics (e.g. telescope magnification). The Kalman Filter has two (2) steps, which are repeated indefinitely during its operation: updating at step 202 and propagating at step 203. The Kalman Filter 201 updates its state at 202 with each geometric measurement, such as a landmark, tie-point, or GPS or ephemeris datum. To include the data from, for example, tracking ephemeris 3, a new tracking ephemeris datum is treated as a measurement type that is input into the Kalman Filter 201. With respect to the location and orientation of the host spacecraft or rigid frame of the instrument, the Kalman Filter 201 therefore updates its state at each new landmark, tie-point, or ephemeris datum. One having ordinary skill in the art will understand that additional known forms of reference data can also be used as inputs to the Kalman Filter 201, such as data from a star sensor or star sighting made through the aperture of the instrument, if available. Moreover, one having ordinary skill in the art will understand that, although the instant invention is described here with reference to data from a tracking ephemeris 3, gyroscope 4, etc., it may be used with data from any type of instrument capable of providing absolute or relative position and/or orientation data for the remote sensing instrument or its host spacecraft. In between updates, the state is propagated at 202 using the known equations of motion and with gyroscope 4 telemetry with respect to the system attitude. However, as described above, the longer the propagation period, the more unreliable the attitude knowledge becomes due to the angle random walk of the gyroscope 4. In the case of an orbiting satellite, attitude knowledge becomes unreliable when the propagation period exceeds a few minutes with most gyroscopes.” Further, in Paragraph 32, Carr teaches “At each time of refresh of the exquisite system, the INR system 10 of the instant invention will upload the new reference imagery from the exquisite system to compare with imagery from the hosted payload system taken simultaneously or near-simultaneously as that from the exquisite system. Then, in real-time, the hosted INR system 10 will extract tie-points, or small templates, from the reference imagery at step 220, and remap them from the perspective of the exquisite system into the perspective of the hosted payload, and matches them at step 230 using a known algorithm such as the Normalized Cross-Correlation (NCC) as described, for example, in U.S. application 20080002878 and Zhao et al., "Image Matching by Normalized Cross - Correlation", IEEE International Conference on Acoustics, Speech and Signal Processing, Volume: 2 (2006). Because the exquisite system has highly accurate INR ability, the geographic location of the landmark or tie-point feature is known with precision in the reference imagery. The NCC algorithm measures the apparent position of that same feature in the hosted payload imagery, providing an external reference point for system attitude adjustment. In this way, knowledge of pixel geo-locations from an exquisite system is transferred to the hosted payload on a recurring basis. This information is fed into the Kalman Filter in step 201 as an additional external measurement type. The Kalman Filter 201 updates upon the receipt of each match of pixel geo-location from exquisite to hosted payload system, providing improved estimates of the overall state of the system. This state is used in the step represented in FIG. 3 as step 205, in which INR processing system 10 "locates", e.g., calculates momentary locations of all detector footprints and provides a real-time (R/T) location product. Based on the tie-point data from step 220, or on the updated system state from the Kalman Filter 201, the imaging device will be able to provide improved INR for all pixels in the instant hosted payload system imagery and moving forward.” In Paragraph 33, Carr et al. teaches “In an optional smoothing step 204, the Kalman Filter adds state smoothing (denoted "Smoother" in FIG. 3). This step is valuable in the case of an instrument that is only sensitive to visible light. Such an instrument will have an initialization transient at the start of each orbit day because the state of the system will have been propagated overnight with no external reference and, by dawn, will have become inaccurate. Initial real-time geo-location accuracy will be poor until the Kalman Filter reconverges. The smoother alleviates some of these inaccuracies by, in essence, running a Kalman Filter backwards in time, so that a reconverged state of the system could then be updated and propagated backwards to yield a more accurate estimate of the system state at the dawn of the orbit day. However, this smoothing operation would only be useful in the production of a non-real-time product 205 during the entire diurnal cycle. There are many choices for a Kalman Filter-Smoother 204 implementation, one of which is the Rauch-Tung-Striebel (RTS) algorithm. However, one having ordinary skill in the art would understand that any known smoothing method capable of achieving a more accurate location product may be used. The result of the smoothing function is shown in step 204 of FIG. 3 where the image location is updated after the smoothing operation, resulting in a non-real-time (Non-R/T) product. The residuals from the Kalman Filter-Smoother 204 also indicate the quality of the INR performance achieved by the INR processing system 10.” In Paragraph 34, it teaches “The simultaneous nature of the comparison of reference and hosted payload imagery will allow even clouds to be used as reference points in the comparison. However, it should be noted that in almost all cases, the INR processing system 10 will have to account for a parallax between the reference and hosted payload imagery due to the different vantage points from which the two systems are likely to view the Earth's surface at any given time. The parallax comes into play in step 200, wherein the INR processing system 10 remaps the reference imagery from the perspective of the exquisite system into the perspective of the hosted payload. Under clear skies, the system can remedy the parallax by using a topographic database pertaining to the three-dimensional tie-point. As can be understood by one of ordinary skill in the art, knowledge of the three-dimensional attributes of the tie-point will allow the INR processing system 10 to translate same from one perspective to another, and then based on that mathematical translation, to translate the remainder of the image. When clouds prevent the hosted payload from finding any clear-sky tie-points, one direction (that parallel to the baseline between the two satellites) should be down-weighted in the Kalman Filter update step, in step 203 of the present invention, in accordance with the uncertainty of the altitude and sensitivity to parallax at the site. The axis perpendicular to the baseline is unaffected.” Carr throughout its disclosure clearly and unambiguously teaches updating the data, which is interpreted to mean the exact same thing as “correcting” the data. The above teachings are interpreted to teach the limitations as filed.
Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
Applicant's arguments do not comply with 37 CFR 1.111(c) because they do not clearly point out the patentable novelty which he or she thinks the claims present in view of the state of the art disclosed by the references cited or the objections made. Further, they do not show how the amendments avoid such references or objections.
Applicant is reminded that although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In light of the above remarks, the claims are rejected using the same art as before.
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.
Claim(s) 1, 3-12 and 14-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Carr (US 20150211864 A1).
Regarding Claim 12, Carr teaches a spacecraft (Paragraphs 18-19), comprising:
an image sensor configured to provide timestamped images (Paragraphs 18-20);
one or more orbit sensors configured to provide orbit position data (Paragraphs 19-28);
one or more attitude sensors configured to provide attitude data (Paragraphs 23-26); and
one or more electronic circuits in communication with the image sensor, the one or more orbit sensors, and the one or more attitude sensors, wherein the one or more electronic circuits are configured to: generate timestamped ephemeris data for the spacecraft based on the orbit position data; generate, using a Kalman filter, timestamped attitude data for the spacecraft based on the attitude data; determine timestamped geolocation information for target pixel(s) in the respective images based on the timestamped ephemeris data and the timestamped attitude data (Paragraphs 7-10; Paragraphs 19-28; Paragraphs 30-38);
refine the timestamped geolocation information based on a digital construct to generate secondary geolocation data; correct attitude filter parameters of the Kalman filter based on the secondary geolocation data; generate, using the Kalman filter with the corrected attitude filter parameters, additional timestamped attitude data for the spacecraft based on the attitude data after correcting the attitude filter parameters; and determine additional timestamped geolocation data for target pixel(s) in the respective images based on the timestamped ephemeris data and the additional timestamped attitude data (Paragraphs 7-10; Paragraphs 19-28; Paragraphs 30-38).
Regarding Claim 14, Carr teaches the spacecraft of claim 12, wherein the one or more electronic circuits are further configured to: refine the timestamped geolocation information based on a digital construct to generate secondary geolocation data; correct orbit filter parameters based on the secondary geolocation data; generate additional timestamped ephemeris data for the spacecraft based on the orbit position data after correcting the orbit filter parameters; and determine additional timestamped geolocation information for target pixel(s) in the respective images based on the additional timestamped ephemeris data and the timestamped attitude data and/or the additional timestamped attitude data (Paragraphs 7-10; Paragraphs 19-28; Paragraphs 30-38).
Regarding Claim 15, Carr teaches the spacecraft of claim 12, wherein the one or more electronic circuits are further configured, in correcting the attitude filter parameters, to: receive attitude state information at the spacecraft from a ground station; and replace a current estimate of one or more states in an attitude state vector for the Kalman filter based on the attitude state information (Paragraphs 7-10; Paragraphs 19-28; Paragraphs 30-38).
Regarding Claim 16, Carr teaches the spacecraft of claim 12, wherein the one or more electronic circuits are further configured, in correcting the attitude filter parameters, to: receive attitude state information at the spacecraft from a ground station; and replace at least a portion of a current covariance matrix of a current estimate of an attitude state vector of the Kalman filter based on the attitude state information (Paragraphs 7-10; Paragraphs 19-28; Paragraphs 30-38).
Regarding Claim 17, Carr teaches the spacecraft of claim 12, wherein the one or more electronic circuits are further configured to: receive orbit state information at the spacecraft from a ground station; replace a current estimate of one or more states in an orbit state vector based on the orbit state information; generate additional timestamped ephemeris data for the spacecraft based on the orbit position data from the one or more orbit sensors after replacing the current estimate of the one or more states in the orbit state vector; and determine additional timestamped geolocation information for target pixel(s) in the respective images based on the additional timestamped ephemeris data and the timestamped attitude data and/or the additional timestamped attitude data (Paragraphs 7-10; Paragraphs 19-28; Paragraphs 30-38).
Regarding Claim 18, Carr teaches the spacecraft of claim 12, wherein the one or more electronic circuits are further configured, in correcting the attitude filter parameters, to: receive orbit state information at the spacecraft from a ground station; and replace at least a portion of a current covariance matrix of a current estimate of an orbit state vector of the Kalman filter based on the orbit state information (Paragraphs 7-10; Paragraphs 19-28; Paragraphs 30-38).
Regarding Claim 19, Carr teaches the spacecraft of claim 12, wherein the one or more electronic circuits are further configured to: provide the timestamped geolocation information for the target pixel(s) in respective images along with the respective images from the spacecraft to a ground station (Paragraphs 7-10; Paragraphs 19-28; Paragraphs 30-38).
Method Claims 1, 3, 4, 6-7, 9 and 11 are drawn to the method of using the corresponding apparatus of claims 12-19 and are rejected for the same reasons as uses above.
Regarding Claim 5, Carr teaches the method of claim 4, further comprising: receiving the attitude state information from a ground station by the one or more electronic circuits onboard the spacecraft, wherein the attitude state information is determined based on control point information not available at the spacecraft (Paragraphs 19-28; Paragraphs 30-38).
Regarding Claim 8, Carr teaches the method of claim 7, further comprising: receiving, by the one or more electronic circuits onboard the spacecraft, the orbit position state information at the spacecraft from a ground station, wherein the orbit state information is determined based on control point information not available at the spacecraft (Paragraphs 19-28; Paragraphs 30-38).
Regarding Claim 10, Carr teaches the method of claim 1, wherein determining, by the one or more electronic circuits onboard the spacecraft, timestamped geolocation data for one of the target pixel(s) in a particular image based on the timestamped ephemeris data and the timestamped attitude data comprises: mapping, by the one or more electronic circuits onboard the spacecraft, the one of the target pixel(s) in the particular image to a region of the image sensor; forming, by the one or more electronic circuits onboard the spacecraft, a ray from the region of the image sensor to a point on the Earth based on the timestamped attitude data and the timestamped ephemeris data; projecting, by the one or more electronic circuits onboard the spacecraft, a digital elevation model into the Earth; and determining, by the one or more electronic circuits onboard the spacecraft, where the ray intersect the digital elevation model (Paragraph 7; Paragraphs 19-28; Paragraphs 30-38).
Claim 20 has limitations that are substantially similar to claims 12 and 16 rejected above, and is rejected for the same reasons as used above. Carr further teaches that the attitude filter parameters including a covariance matrix of an attitude determination unit of the Kalman filter (Paragraph 7; Paragraphs 19-28; Paragraphs 30-38).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FARHAN MAHMUD whose telephone number is (571)272-7712. The examiner can normally be reached 10-7.
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/FARHAN MAHMUD/Primary Examiner, Art Unit 2483