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 .
Priority
Examiner acknowledges no foreign priority is claimed.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 12/2/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered if signed and initialed by the Examiner.
Claim Objections
Claim 1 recites “SAR” in line 7 of claim 1. Examiner suggests adding “SAR (Synthetic Aperture Radar)” in first occurrence of “SAR” in the claim.
Claim 11 recites “SAR” in line 9 of claim 11. Examiner suggests adding “SAR (Synthetic Aperture Radar)” in first occurrence of “SAR” in the claim.
Claim 12 recites “SAR” in line 9 of claim 11. Examiner suggests adding “SAR (Synthetic Aperture Radar)” in first occurrence of “SAR” in the claim.
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 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.
For applicant’s benefit portions of the cited reference(s) have been cited to aid in the review of the rejection(s). While every attempt has been made to be thorough and consistent within the rejection it is noted that the PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS. See MPEP 2141.02 VI.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-9 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Pincus et al. (“3D SAR coherent change detection for monitoring the ground under a forest canopy”, 2019, ISSN 1751-8784), and further in view of Bailer et al. (US 2024/0077607 A1).
Regarding claim 1, Pincus et al. discloses “a signal processing device (section 1 paragraph 8: Figure 2: SAR images acquired by multichannel radar system)”,
generate three-dimensional information with reliability including three-dimensional information constructed with estimated values of reflection intensity (section 1 paragraph 5: using three-dimensional (3D) SAR beamforming, also known as SAR tomography…although an ordinary 2D SAR image has no vertical resolution, it retains information about the heights of scattering contributions in both the projection geometry of the layover and the pixel phase…given multiple co-registered 2D images acquired at slightly different grazing angles, they can be coherently weighted and summed to produce a new image that is 3D in the sense that it is steered to one height, with scattering contributions from other heights suppressed…the technique is typically used either to characterize the vertical structure of a scene by scanning beams in height and plotting the variation in scattering intensity, which is analogous to direction-of-arrival estimation, or to detect hidden targets by suppressing the canopy interference and searching for anomalous responses on the ground underneath, assuming that the ground height is known…the first goal, in particular, requires a wide but well-sampled angular aperture to support a useful level of vertical resolution and a useful unambiguous vertical extent. Such an aperture must be synthesized by many (usually ten or more) images acquired on separate passes, which is an impractical collection burden and leads to a difficult phase calibration problem, particularly cross-pass motion compensation for airborne platforms) and
a phase at a three-dimensional position in a steady state reconstructed using an observed SAR image (section 2 paragraph 1: the complex speckle pattern in a SAR image is the pixel-to-pixel fluctuation in the net coherent response of many scattering elements in spatially distributed clutter…it arises because the elements are not individually resolved, i.e. each resolution cell contains many elements at slightly different propagation ranges, so their scattering responses have different phases and coherently interfere…although it is sometimes modelled as multiplicative noise, the speckle pattern is, in fact, a deterministic and repeatable signature of the landscape, given a particular wavelength and angular point of-view), and
information indicating reliability of the three-dimensional information, and generates a simulated SAR image which is a complex image representing the steady state suitable for an imaging condition of a SAR image to be analyzed, using the three-dimensional information and the imaging condition of the SAR image to be analyzed, and calculate reliability information representing the reliability of the simulated SAR image (section 9: the 3D SAR CCD concept shown in Fig. 2 was tested using RVOG clutter generated by the simulation demonstrated in Section 2 …the scene change is illustrated in Fig. 14, with the ground scatterers for the second pass in red overlaid on those for the first pass in blue…Fig. 15 shows the ordinary CCD obtained when the volume is absent… averaging window used to evaluate the coherence…the distortions in the letters are a direct consequence of the particular random shifts for this realization of scene change…for this coherence metric, this CCD is the best possible representation of the scene change…each raw radar dataset was first focused into a SAR image at ground height with ground-plane resolution…each resolution cell covered several scatterers, giving rise to fully developed speckle…the SAR intensity images from the first and second channels are shown in Fig. 16..the images of the RVOG scene appear to be nothing more than different realizations of some noise process, with no texture or structure, but in fact, each pixel is the net response due to the coherent superposition of the individual echoes from the ground and laid-over volume scattering elements at that location, and therefore each image exhibits the deterministic speckle pattern that results from its particular collection geometry… the resulting images are 3D in the sense that the input data are steered to ground height, so the complex ground clutter is preserved but the above-ground scattering from the volume is suppressed…the average coherence of the unchanged area in the middle of the scene, which agrees with the theoretical coherence for the RVOG model; Fig. 19 shows receiver operating characteristics for change detection using selected CCD images…each curve shows the locus of the probability of detection and the probability of false alarm as the coherence threshold used to classify the pixels as either changed or unchanged is varied between zero and one…the proposed 3D processing techniques significantly improve change detection performance for volume obscured scenes; Figure 9; Section 8 paragraph 3: high level of volume attenuation shown in Fig. 8 for one scene is, in fact, achievable over a wide range of scenes, as shown in Fig. 9…these curves were generated in the same way as in the previous figure, for a minimal three-channel system…the performance is determined by both the height of the volume's effective phase center and the effective width of the vertical structure: when there is little propagation loss, scattering contributions will be received from a wide range of heights, which the beamformer has a limited ability to suppress due to its small number of channels).”
Pincus et al. does not explicitly disclose the signal processing device, comprising “a memory storing software instructions, and one or more processors configured to execute the software instructions.”
Bailer et al. (‘607) relates to detecting and correcting angle offsets in a SAR image. Bailer et al. (‘607) teaches the signal processing device, comprising “a memory storing software instructions, and one or more processors configured to execute the software instructions (paragraph 48: computer-readable instructions (CRI) recorded in memory (M) of a control system (C), such as one or more digital computers or electronic control units, and executed by one or more processors (P). The memory (M) may include tangible, non-transitory memory…the processes may be embodied as CRI in the memory (M) and executed by the processor under control of the control system (C); paragraph 49: one or more processors (P) in FIG. 7).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the signal processing device of Pincus et al. with the teaching of Bailer et al. (‘607) for generating more reliable SAR image (Bailer et al. (‘607) – paragraph 4). In addition, both of the prior art references, Pincus et al. and Bailer et al. (‘607)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, SAR image matching.
Regarding claim 2, which is dependent on independent claim 1, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 1. Pincus et al. further discloses “the one or more processors are configured to execute the software instructions to calculate information indicating the reliability of the three-dimensional information by evaluating a discrepancy between a received signal and a predicted signal predicted from the generated three-dimensional information for each of the reflection intensity and the phase (section 1 paragraph 5: using three-dimensional (3D) SAR beamforming, also known as SAR tomography… given multiple co-registered 2D images acquired at slightly different grazing angles, they can be coherently weighted and summed to produce a new image that is 3D in the sense that it is steered to one height, with scattering contributions from other heights suppressed…the technique is typically used either to characterize the vertical structure of a scene by scanning beams in height and plotting the variation in scattering intensity, which is analogous to direction-of-arrival estimation, or to detect hidden targets by suppressing the canopy interference and searching for anomalous responses on the ground underneath, assuming that the ground height is known; section 2 paragraph 1: the complex speckle pattern in a SAR image is the pixel-to-pixel fluctuation in the net coherent response of many scattering elements in spatially distributed clutter…it arises because the elements are not individually resolved, i.e. each resolution cell contains many elements at slightly different propagation ranges, so their scattering responses have different phases and coherently interfere…although it is sometimes modelled as multiplicative noise, the speckle pattern is, in fact, a deterministic and repeatable signature of the landscape, given a particular wavelength and angular point of-view; section 7 paragraph 1: compare the performance of different radar designs and beamformers for different model scenes).”
Regarding claim 3, which is dependent on independent claim 1, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 1. Pincus et al. further discloses “the one or more processors are configured to execute the software instructions to evaluate how reliable each estimate in the reconstructed three-dimensional information is among the possible values (section 7.1 paragraphs 1-2: Define the RVOG beamformer
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as the optimal beamformer in (44) obtained when
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is populated with volume coherences predicted by (48) for each pair of channels according to the random volume model…requires estimated or assumed values of the random volume parameters
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together with the known multichannel collection geometry…the beamformer's performance depends on how closely the modelled volume matches the actual canopy…the assumptions are two-fold: firstly, that the canopy is well-modelled as a random volume, and secondly, that the canopy is well-modelled by the specific random volume used to generate
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·..it may be safer to employ
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instead of
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when it is difficult to obtain a reliable estimate of R, say due to a limited number of resolution cells to average over, because the random volume parameters are potentially more stable than the covariance matrix…mixed approach, whereby the adaptivity is constrained within reasonable RVOG bounds, may be possible).”
Regarding claim 4, which is dependent on claim 2, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 2. Pincus et al. further discloses “the one or more processors are configured to execute the software instructions to generate reliability information by statistical processing using the generated simulated SAR image and the information indicating reliability of the three-dimensional information (section 1 paragraph 6: critically, CCD requires an accurate estimate of the complex reflectivity of the ground, not just its scattering intensity, so we are
restricted to beamformers that preserve phase…this requirement is rare in the 3D SAR literature…the phenomenology of polarimetric scattering from the ground in a tropical forest at P-band by using conventional beamforming to combine several images from airborne passes [20, 21]…adaptive Capon beamforming [II]
(also known as minimum-variance distortion less response (MVDR) beamforming, to separate and estimate the polarimetric covariance matrices for the ground and canopy, assuming a dual-layer surface volume model of a forest [23, 24]… extended this scheme for multiple interleaved surface and volume layers in ice).”
Regarding claim 5, which is dependent on independent claim 1, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 1. Pincus et al. further discloses “the one or more processors are configured to execute the software instructions to calculate a function that expresses information about how reliable what values are as the intensity and the phase at each position in a three-dimensional space as the three- dimensional information with reliability (section 5: model the coherence for every pair of channels in (5) by the dual-layer expression in (17)…for all pairs within a pass, the ground coherence will be unity (assuming that the spatial frequency apertures of the SAR images have been trimmed to their common region…across passes, all pairs observe the same temporal decorrelation (i.e. scene change); let
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denote the common ground coherence, which is the indicator of change we seek. Given the assumption of constant component powers in (16), μ will be constant for all channels and
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constant for all pairs of distinct channels. Expressing the three sets of observed coherences in matrix form gives
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, where
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is a matrix of ground interferometric phasors,
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is a matrix of volume coherences,
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is a matrix whose leading diagonal is unity and all other elements are
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, 1 is an M x M matrix of ones and 0 indicates the Hadamard product).”
Regarding claim 6, which is dependent on claim 5, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 5. Pincus et al. further discloses “the one or more processors are configured to execute the software instructions to estimate multiple simulated complex signal candidates estimated from the three-dimensional information with reliability and likelihood of each simulated complex signal candidate, and select or generate a likely simulated complex signa as the reliability information (section 9 paragraph 5: the three complex SAR images from each pass were combined in three separate ways: using the conventional, MVDR and RVOG beamformers… the MVDR beamformer is adaptive in that it uses an estimate of the covariance matrix at each pixel position, as described in Section 6, whereas the RVOG beamformer is matched to the fixed parameters of the model scene, as described in Section 7. I…the resulting images are 3D in the sense that the input data are steered to ground height, so the complex ground clutter is preserved but the above-ground scattering from the volume is suppressed…from (44), the optimal level of volume attenuation for this three-channel configuration is 12.1 dB…Fig. 17 shows the output intensity after MVDR beamforming…there is still no visible difference across passes; Section 11: the images from each pass must be coherently combined using optimal 3D SAR bemoaning techniques to suppress the canopy backscatter and provide an accurate estimate of the complex reflectivity of the ground).”
Regarding claim 7, which is dependent on independent claim 1, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 1. Pincus et al. further discloses “the one or more processors are further configured to execute the software instructions to detect a change in an area in the SAR image to be analyzed by comparing the SAR image to be analyzed with the simulated SAR image, and wherein
the one or more processors are configured to execute the software instructions to exclude a pixel with low reliability represented by the reliability information from comparison target (section 8 paragraph 2: Fig. 8 shows the optimal volume attenuation that could be achieved by a matched RVOG beamformer for different collection parameters, given a typical RVOG scene…each point on each curve
was obtained by populating matrix r v with volume coherences from (48) for all channel pairs in the given configuration and then evaluating
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in (44)…the curves have been cropped to exclude cases where the condition number of r v is greater than 1015 …as the angular spacing
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decreases, the optimal performance improves despite the resolution
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in (37) of the conventional beamformer becoming coarser; this is because r v becomes more ill-conditioned as the spacing decreases and/or the number of channels increases…even with only three channels, choosing
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(matching the Inter map design [18]) would support volume attenuation around - 12 dB, which from (35) is sufficient to permit accurate ground coherence estimates when μ > - 2.5 dB (assuming
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= 0).”
Regarding claim 8, which is dependent on claim 7, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 7. Pincus et al. further discloses “the one or more processors are configured to execute the software instructions to detect the change by calculating a degree of similarity between the SAR image to be analyzed and the simulated SAR image (section 9 paragraph 8: Fig. 19 shows receiver operating characteristics for change detection using selected CCD images…each curve shows the locus of the probability of detection and the probability of false alarm as the coherence threshold used to classify the pixels as either changed or unchanged is varied between zero and one…the true change map is given by Fig. 14. In the ground-only reference case (blue), the characteristic is still not perfect ( certain detection with zero false alarms) because the resolution of the CCD is coarser than the size of the true scene changes - compare the line width of the letters in Figs. 14 and 15. For a false-alarm rate of, say, five per cent, the probability of detection is 0.86 for the ground-only reference case, 0.26 for the single-channel CCD (green), 0.69 for the 3D CCD obtained using the fixed RVOG beamformer (red), and 0.76 for the 3D CCD obtained using the adaptive MVDR beamformer (cyan)…the proposed 3D processing techniques significantly improve change detection performance for volume obscured scenes).”
Regarding claim 9, which is dependent on claim 8, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 8. Pincus et al. further discloses “the one or more processors are configured to execute the software instructions to calculate the degree of similarity using phase information indicated by the SAR image to be analyzed and phase information indicated by the simulated SAR image (section 1 paragraph 5: the layover problem can be overcome using three-dimensional (3D) SAR beamforming, also known as SAR tomography…although an ordinary 2D SAR image has no vertical resolution, retains information about the heights of scattering contributions in both the projection geometry of the layover and the pixel phase…given multiple co-registered 2D images acquired at slightly different grazing angles, they can be coherently weighted and summed to produce a new image that is 3D in the sense that it is steered to one height, with scattering contributions from other heights suppressed.; Figures 10-13).”
Regarding claim 10, which is dependent on claim 8, Pincus et al./Bailer et al. (‘607) discloses the signal processing device of claim 8. Pincus et al. further discloses “the one or more processors are configured to execute the software instructions to generate the simulated SAR image for each of the imaging conditions of the multiple SAR images to be analyzed, and the change detection means calculates calculate the degree of similarity between the SAR image to be analyzed and the simulated SAR image for each pair of the SAR image to be analyzed and the simulated SAR image, and detects the change using calculated multiple degrees of similarity (section 9 paragraphs 1: the 3D SAR CCD concept shown in Fig. 2 was tested using
RVOG clutter generated by the simulation demonstrated in Section 2…the 180 x 120 m scene consisted of 2.4-million-point scatterers arranged randomly in ground and volume layers; on average, there were ten per square meter on the ground and five per cubic meter in the volume…scatterer intensity was assigned according to height, accow1ting for propagation loss, such that the whole scene satisfied the RVOG model with h., = 20m, a~8 = 0. l dB/m and μ = 0dB. Six sets of raw radar echoes were synthesized to mimic the pulses acquired by two passes of a three-channel array fanned by two alternating L-band (2 = 22.7 cm) antennas with a 10 m across-track separation (recall Fig. 1)…the two flight-tracks were nominally at 35° grazing angle and 6200 ft altitude, with realistic offsets in
ground-range and altitude of a few meters, giving a grazing angle separation of I/lb - ljr0 = 0.3°. The resulting channel spacing within each pass was t:,.1/f = 0.05°. For the interferometric pair formed across passes by the two middle channels, the resulting volume coherence according to (48), and the total RVOG coherence magnitude given by (18); Section 9 paragraph 9: Fig. 19 shows receiver operating characteristics for change detection using selected CCD images. Each curve shows the locus of the probability of detection and the probability of false alarm as the coherence threshold used to classify the pixels as either changed or unchanged is varied between zero and one…the true change map is given by
Fig. 14…in the ground-only reference case (blue), the characteristic is still not perfect ( certain detection with zero false alarms) because the resolution of the CCD is coarser than the size of the true scene changes - compare the line width of the letters in Figs. 14 and 15. For a false-alarm rate of, say, five percent, the probability of detection is 0.86 for the ground-only reference case, 0.26 for the single-channel CCD (green), 0.69 for the 3D CCD obtained using the fixed RVOG beamformer (red), and 0.76 for the 3D CCD obtained using the adaptive MVDR beamformer(cyan). Hence, the proposed 3D processing techniques significantly improve change detection performance for volume obscured scenes).”
Regarding independent claim 11, which is a corresponding method claim of independent device claim 1, Pincus et al./Bailer et al. (‘607) discloses all the claimed invention as shown above for claim 1.
Regarding independent claim 12, which is a corresponding non-transitory computer readable storage medium claim of independent device claim 1, Pincus et al./Bailer et al. (‘607) discloses all the claimed invention as shown above for claim 1.
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Knaell Et al. (US 5,394,151) describes a method and apparatus capable of acquiring three-dimensional images without having to position an antenna at all element positions of a filled two-dimensional spatial array (column 2 lines 34-37); a frequency response may be obtained by stepped frequency measurements or by measurements with a linearly frequency modulated (chirp) pulse…the frequency response may be obtained in a time so short that the relative motion between target and radar during the measurement time can be neglected (but not during the time interval between frequency response measurements). Let the index i denote a particular frequency response. Let its samples be denoted by the index k and let its radar line-of-sight (LOS) direction as measured from the target center of coordinates to the radar phase center be denoted by the unit vector…a radar datum may be indicated (column 5 lines 19-40).
Calabrese (US 9,019,144 B2) describes a method for acquiring SAR images for interferometric processing (column 4 lines 19-21); acquiring SAR images for interferometric processing, a method for computing a height, a method for computing a digital elevation model, a method for computing an interferogram, a method for computing a coherence map, a SAR remote sensing system configured to implement said SAR image acquisition method, a software program product for implementing said method for computing a height, a software program product for implementing said method for computing a digital elevation model, a software program product for implementing said method for computing an interferogram, and a software program product for implementing said method for computing a coherence map (column 4 lines 28-40).
Benninghofen et al. (US 2012/0133550 A1) describes obtaining distance information from an SAR image proceeds as follows. In an SAR system, the range gate is set for the generation of images…this range gate determines the distance between the SAR sensor and the resolution cell on the ground that corresponds to the center of the SAR slant range image…this pixel is identified as the center pixel…once a pixel has been determined as the target, the distance to the resolution cell on the ground corresponding to the pixel can be calculated (paragraph 26).
Willey et al. (US 2008/0074313 A1) describes a method and apparatus for three dimensional sub-voxel position imaging, and more particularly, to a method and apparatus for determining three dimensional sub-voxel positions using synthetic aperture radar (paragraph 1); the at least four simultaneous SAR platforms in flight are replaced by four sequential flights of a single SAR platform such that the flight trajectories are distributed in range, cross-range, and height…the relative phases and relative positions between the SAR platforms between passes are estimated from--central reference points in the scene (paragraph 9).
Dominguez et al. “A Back Projection Tomographic Framework for VHR SAR Image Change Detection” (Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 57, Issue: 7, July 2019)) describes a three state Tomography SAR change detection approach where 2-D and 3-D methods are combined to overcome their respective weakness and take advantage of their strengths.
Contact Information
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/NUZHAT PERVIN/Primary Examiner, Art Unit 3648
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