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 .
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 06/28/2024 and 10/07/2025 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered by the examiner.
Claim Objections
Claim(s) 3-7, 12-16, and 18-21 is/are objected to because of the following informalities:
In Claim 3, lines 2, 4-5, and 10, the phrase “the each identification point” should be “each identification point”
In Claim 4, lines 2, 4, 5, 8, and 10-11, the phrase “the each identification point” should be “each identification point”
In Claim 5, line 6, the phrase “the each identification point” should be “each identification point”
In Claim 6, line 3, the phrase “the each identification point” should be “each identification point”
In Claim 7, lines 2-3, the phrase “the each identification point” should be “each identification point”
In Claim 7, lines 8-9, 10, and 12, the phrase “the each second target point” should be “each second target point”
In Claim 12, lines 2, 4-5, and 10, the phrase “the each identification point” should be “each identification point”
In Claim 13, lines 2, 4, 5, 8, and 10-11, the phrase “the each identification point” should be “each identification point”
In Claim 14, line 5, the phrase “the each identification point” should be “each identification point”
In Claim 15, line 3, the phrase “the each identification point” should be “each identification point”
In Claim 16, lines 2-3, the phrase “the each identification point” should be “each identification point”
In Claim 16, lines 8-9, 10, and 12, the phrase “the each second target point” should be “each second target point”
In Claim 18, lines 3, lines 2, 4-5, and 10, the phrase “the each identification point” should be “each identification point”
In Claim 19, lines 2, 4, 5, 8, and 10-11, the phrase “the each identification point” should be “each identification point”
In Claim 20, line 6, the phrase “the each identification point” should be “each identification point”
In Claim 21, line 3, the phrase “the each identification point” should be “each identification point”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims
particularly pointing out and distinctly claiming the subject matter which the
inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out
and distinctly claiming the subject matter which the applicant regards as his
invention.
Claim(s) 1-7 and 9-21 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claim 1, the claim recites the limitation “determining an algorithm parameter corresponding to each identification point of the at least one identification point.” The recitation of “an algorithm parameter” (singular) corresponding to “each identification point” renders the claim indefinite because it is unclear whether a single algorithm parameter corresponds to all of the identification points, or whether a separate algorithm parameter corresponds to each identification point. For examination purposes, and based on the specification ([0071-0072]), the limitation is interpreted as meaning at least one algorithm parameter is determined for each identification point. This rejection also applies to the corresponding limitations in Claims 9 and 10.
Regarding Claim 1, the claim recites the limitation “determining, according to the algorithm parameter and in combination with a set algorithm, an identified radar target according to an algorithm output result.” It is unclear which algorithm parameter “the algorithm parameter” refers to because the preceding limitation indicates there may be multiple algorithm parameters. Additionally, it is unclear how “the algorithm parameter,” “a set algorithm,” and “an algorithm output result” are related, e.g., do “the algorithm,” “a set algorithm,” and “an algorithm” refer to the same algorithm? For examination purposes the limitation is interpreted as meaning an identified radar target is determined based on each algorithm parameter (corresponding to each identification point) and on an output of a set algorithm. This rejection also applies to the corresponding limitations in Claims 9 and 10.
Regarding Claim 2, the claim recites the limitation “wherein the radar data comprises an amplitude and a detection distance.” Because the radar data is “of at least one identification point,” it is unclear whether the radar data comprises a single amplitude and a single detection distance, or an amplitude and a detection distance for each identification point. For examination purposes, the limitation is interpreted as requiring an amplitude and a detection distance for each identification point. This rejection also applies to the corresponding limitations in Claims 11 and 17.
Regarding Claim 3, the claim recites the limitation “wherein determining the algorithm parameter corresponding to the each identification point according to the radar data of the at least one identification point comprises…” This limitation renders the claim indefinite for the reasons stated above regarding Claim 1, i.e., the recitation of “an algorithm parameter” (singular) corresponding to “each identification point” renders the claim indefinite because it is unclear whether a single algorithm parameter corresponds to all of the identification points, or whether a separate algorithm parameter corresponds to each identification point. This rejection also applies to the corresponding limitations in Claims 12 and 18.
Regarding Claim 3, the claim recites the limitation “determining a first coefficient and a second coefficient that correspond to the each identification point according to the amplitude and the detection distance of the at least one identification point.” It is unclear whether a single first coefficient and a single second coefficient correspond to all of the identification points, or whether a first coefficient and a second coefficient is determined for each identification point. Additionally, “the amplitude” and “the detection distance” render the claim indefinite because it is unclear whether there is a single amplitude and a single detection distance, or an amplitude and a detection distance for each identification point. For examination purposes, the limitation is interpreted as meaning a first coefficient and a second coefficient are determined for each identification point according to the amplitude and the detection distance corresponding to that same detection point. This rejection also applies to the corresponding limitations in Claims 12 and 18.
Regarding Claim 3, the claim recites the limitation “acquiring an initial parameter value corresponding to the algorithm parameter.” It is unclear whether a single initial parameter value is acquired, or whether an initial parameter value is acquired for each of multiple algorithm parameters. For examination purposes, the limitation is interpreted as meaning an initial parameter value is acquired for each algorithm parameter. This rejection also applies to the corresponding limitations in Claims 12 and 18.
Regarding Claim 3, the claim recites the limitation “determining a sum of a product of the first coefficient and the initial parameter value and a product of the second coefficient and the initial parameter value as the algorithm parameter corresponding to the each identification point.” The limitation renders the claim indefinite for similar reasons as above, i.e., it is unclear whether a single sum is determined, or whether multiple sums are determined for each algorithm parameter. For examination purposes, the limitation is interpreted as meaning that each algorithm parameter is determined by summing the product of the first coefficient and the initial parameter value and a product of the second coefficient and the initial parameter value, all of which correspond to the same identification point. This rejection also applies to the corresponding limitations in Claims 12 and 18.
Regarding Claim 4, the claim recites the limitation “wherein determining the first coefficient and the second coefficient that correspond to the each identification point according to the amplitude and the detection distance of the at least one identification point comprises…” This limitation renders the claim indefinite for the reasons stated above regarding Claim 3, i.e., it is unclear whether a single first coefficient and a single second coefficient correspond to all of the identification points, or whether a first coefficient and a second coefficient is determined for each identification point, and “the amplitude” and “the detection distance” render the claim indefinite because it is unclear whether there is a single amplitude and a single detection distance, or an amplitude and a detection distance for each identification point. This rejection also applies to the corresponding limitations in Claims 13 and 19.
Regarding Claim 4, the claim recites the limitation “determining, for the each identification point, an amplitude and a detection distance that correspond to the each identification point.” Because the radar data is recited as being of “at least one” identification point, it is unclear how a maximum amplitude and a minimum amplitude can be determined among “amplitudes” (plural) if there is only one identification point. For examination purposes, the limitation is interpreted as requiring a plurality of identification points, and therefore a plurality of amplitudes, such that a maximum amplitude and a minimum amplitude can be determined. This rejection also applies to the corresponding limitations in Claims 13 and 19.
Regarding Claim 4, the claim recites the limitation “determining the first coefficient according to the amplitude corresponding to the each identification point, the maximum amplitude, and the minimum amplitude.” The phrase “the first coefficient” renders the claim indefinite because it is unclear whether a single first coefficient is determined, or whether multiple first coefficients are determined. For examination purposes, the limitation is interpreted as meaning for each algorithm parameter/identification point, the corresponding first coefficient is determined according to the amplitude corresponding to the identification point, the maximum amplitude, and the minimum amplitude. This rejection also applies to the corresponding limitations in Claims 13 and 19.
Regarding Claim 4, the claim recites the limitation “determining a product of the detection distance that corresponds to the each identification point and a set scaling factor as the second coefficient.” The phrase “the second coefficient” renders the claim indefinite because it is unclear whether a single second coefficient is determined, or whether multiple second coefficients are determined. For examination purposes, the limitation is interpreted as meaning for each algorithm parameter/identification point, the corresponding second coefficient is equal to the product of the detection distance that corresponds to the identification point and a set scaling factor. This rejection also applies to the corresponding limitations in Claims 13 and 19.
Regarding Claim 5, the claim recites the limitation “determining, according to the algorithm parameter and in combination with the set algorithm, the identified radar target according to the algorithm output result comprises…” This limitation renders the claim indefinite for the reasons stated above regarding Claim 1, i.e., it is unclear which algorithm parameter “the algorithm parameter” refers to because the preceding limitation indicates there may be multiple algorithm parameters, and it is unclear how “the algorithm parameter,” “a set algorithm,” and “an algorithm output result” are related. This rejection also applies to the corresponding limitations in Claims 14 and 20.
Regarding Claim 5, the claim recites the limitations “performing cluster analysis according to the algorithm parameter corresponding to the each identification point to determine a cluster output by the set algorithm” and “determining the cluster as the radar target.” Because there may be more than one identification point, the cluster analysis may output more than one cluster, and it is therefore unclear which cluster “the cluster” refers to. It is also unclear whether a single algorithm parameter is used for the cluster analysis, or whether multiple algorithm parameters are used. For examination purposes, the limitations are interpreted as meaning for each identification point, cluster analysis is performed according to the algorithm parameter corresponding to the identification point, the cluster analysis determines a cluster output using the set algorithm, and the cluster output corresponds to a radar target. This rejection also applies to the corresponding limitations in Claims 14 and 20.
Regarding Claim 6, the claim recites the limitation “performing cluster analysis according to the algorithm parameter corresponding to the each identification point to determine the cluster output by the set algorithm comprises…” This limitation renders the claim indefinite for the reasons stated above regarding Claim 5, i.e., it is unclear which cluster “the cluster” refers to, and it is unclear whether a single algorithm parameter is used for the cluster analysis, or whether multiple algorithm parameters are used. This rejection also applies to the corresponding limitations in Claims 15 and 21.
Regarding Claim 6, the claim recites the limitation “determining a final size of the cluster.” It is unclear what is meant by “final size.” Does “size” refer to a number of identification points, a spatial extent, or something else? And relative to what is the size “final?” For examination purposes, “final size” is interpreted as the number of identification points included in the cluster. This rejection also applies to the corresponding limitations in Claims 15 and 21.
Regarding Claim 6, the claim recites the limitation “determining any identification point other than the cluster as the first target point.” The cluster is interpreted as comprising multiple identification points, and it is therefore unclear which or how many identification points are determined “other than the cluster.” Additionally, because the claim previously recites determining an identification point “as a first target point,” it is unclear which point “the first target point” refers to. For examination purposes, the limitation is interpreted as meaning, after outputting the cluster, the cluster analysis selects, as a new first target point, an identification point that is not part of a previous cluster. This rejection also applies to the corresponding limitations in Claims 15 and 21.
Regarding Claim 7, the claim recites the limitation “the final size.” This limitation renders the claim indefinite for the reasons stated above regarding Claim 6, i.e., it is unclear what is meant by “final size.” This rejection also applies to the corresponding limitation in Claim 16.
Claim Rejections - 35 USC § 102
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 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) 1-2, 5, 9-11,14, 17, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Foroozan (US 2021/0117659).
Regarding Claim 1, Foroozan discloses:
A method for identifying a radar target, comprising:
acquiring radar data of at least one identification point ([0058]: “output of the radar point cloud”);
determining an algorithm parameter corresponding to each identification point of the at least one identification point according to the radar data of the at least one identification point ([0059]: “DBSCAN”; [0062]: “spatial-variable parameters for both search radius and number of observations: ε(x,y) and k(x,y)”; Examiner note: the DBSCAN algorithm requires distance/neighborhood radius and density/number of points as algorithm parameters. Paragraph [0062] discloses an embodiment where these parameters are varied for each point.); and
determining, according to the algorithm parameter and in combination with a set algorithm, an identified radar target according to an algorithm output result ([0059]: “After applying DBSCAN, the algorithm may calculate the centroid of each cluster and estimate the boundaries of the target.”).
Regarding Claim 9, Foroozan discloses: An electronic device, comprising:
at least one processor ([0030]); and
a memory communicatively connected to the at least one processor ([0030]);
wherein the memory stores a computer program executable by the at least one processor ([0030]), and the computer program is configured to, when executed by the at least one processor, cause the at least one processor to perform the following steps:
acquiring radar data of at least one identification point ([0058]: “output of the radar point cloud”);
determining an algorithm parameter corresponding to each identification point of the at least one identification point according to the radar data of the at least one identification point ([0059]: “DBSCAN”; [0062]: “spatial-variable parameters for both search radius and number of observations: ε(x,y) and k(x,y)”; Examiner note: the DBSCAN algorithm requires distance/neighborhood radius and density/number of points as algorithm parameters. Paragraph [0062] discloses an embodiment where these parameters are varied for each point.); and
determining, according to the algorithm parameter and in combination with a set algorithm, an identified radar target according to an algorithm output result ([0059]: “After applying DBSCAN, the algorithm may calculate the centroid of each cluster and estimate the boundaries of the target.”).
Regarding Claim 10, Foroozan discloses: A non-transitory computer-readable storage medium storing computer instructions ([0030]) that, when executed by a processor, cause the at least one processor to perform the following steps:
acquiring radar data of at least one identification point ([0058]: “output of the radar point cloud”);
determining an algorithm parameter corresponding to each identification point of the at least one identification point according to the radar data of the at least one identification point ([0059]: “DBSCAN”; [0062]: “spatial-variable parameters for both search radius and number of observations: ε(x,y) and k(x,y)”; Examiner note: the DBSCAN algorithm requires distance/neighborhood radius and density/number of points as algorithm parameters. Paragraph [0062] discloses an embodiment where these parameters are varied for each point.); and
determining, according to the algorithm parameter and in combination with a set algorithm, an identified radar target according to an algorithm output result ([0059]: “After applying DBSCAN, the algorithm may calculate the centroid of each cluster and estimate the boundaries of the target.”).
Regarding Claims 2, 11, and 17, Foroozan discloses: wherein the radar data comprises an amplitude and a detection distance ([0056]: “distance to the sensor (r)”; [0058]: “Cartesian coordinates, the amplitude of the reflection”).
Regarding Claims 5, 14, and 20, Foroozan discloses: wherein the set algorithm comprises a cluster algorithm ([0059]: “DBSCAN”), and determining, according to the algorithm parameter and in combination with the set algorithm, the identified radar target according to the algorithm output result comprises:
performing cluster analysis according to the algorithm parameter corresponding to the each identification point to determine a cluster output by the set algorithm ([0059]: “applying DBSCAN”; [0060]: “The DBSCAN algorithm for radar data can use a fixed density threshold for the creation of a cluster”; [0062]: “spatial-variable parameters”); and
determining the cluster as the radar target, wherein the cluster is in a one-to-one correspondence with the radar target ([0059]: “After applying DBSCAN, the algorithm may calculate the centroid of each cluster and estimate the boundaries of the target.”).
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 shall not be negated by the manner in
which the invention was made.
Claim(s) 3, 12, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Foroozan (US 2021/0117659), as applied to Claims 2, 11, and 17 above, and further in view of Chen (CN 102253375 A).
Regarding Claims 3, 12, and 18, Foroozan teaches acquiring radar data including amplitude and detection distance ([0056]; [0058]), acquiring initial parameter values ([0060]: “fixed density threshold”; “radial search radius E”), and determining variable algorithm parameters from the radar data ([0062]: “spatial-variable parameters”).
Foroozan does not explicitly teach “determining a first coefficient and a second coefficient … according to the amplitude and the detection distance” or “determining a sum of a product of the first coefficient and the initial parameter value and a product of the second coefficient and the initial parameter value as the algorithm parameter,” as recited in Claim 3.
However, Chen is in the field of radar target detection algorithms and teaches:
determining a first coefficient and a second coefficient according to the amplitude and the detection distance of a detection point (Chen [pg. 3]: Es=abs(EL-EDet) * e and Ds=abs(TDis-PDis) * b, where abs(EL-EDet) is the first coefficient according to amplitude where abs(TDis-PDis) is the second coefficient according to distance)
acquiring an initial parameter value corresponding to the algorithm parameter (Chen [pg. 3]: Es=(abs(EL-EDet) * e) and Ds=(abs(TDis-PDis) * b), where e and b are initial values); and
determining a sum of a product of the first coefficient and the initial parameter value and a product of the second coefficient and the initial parameter value as the algorithm parameter corresponding to the each identification point (Chen [pg. 5], where Zs[i] is computed by summing Es and Ds).
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 invention of Foroozan and determine the algorithm parameter as the sum of coefficients and initial values, where the coefficients are determined according the a target’s amplitude and detection distance, as taught by Chen, with a reasonable expectation of success. Applying Chen’s known product and summing technique to Foroozan’s spatial-variable algorithm parameters would yield the predictable result of improving clustering accuracy by allowing Foroozan’s algorithm parameters to account for differences in amplitude and distance.
Claim(s) 6-7, 15-16, and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Foroozan (US 2021/0117659), as applied to Claims 1, 9, and 10 above, and further in view of Yang (CN 115439484 A).
Regarding Claims 6, 15, and 21, Foroozan teaches: wherein the algorithm parameter comprises a neighborhood radius and a density threshold ([0060]; [0062]), and performing cluster analysis according to the algorithm parameter corresponding to the each identification point to determine the cluster output by the set algorithm comprises:
determining any identification point of the at least one identification point as a first target point ([0060]: “each observation is examined if there are at least k observations within a radial search radius E”);
acquiring a first neighborhood radius and a first density threshold that correspond to the first target point ([0060]; [0062]: “spatial-variable parameters for both search radius and number of observations: ε(x,y) and k(x,y)”), and in a case where a number of identification points within a range defined by the first neighborhood radius with the first target point as a center is greater than or equal to the first density threshold, establishing a cluster ([0060]: “creation of a cluster”); wherein the cluster comprises the first target point and the identification points within the range defined by the first neighborhood radius with the first target point as the center ([0060]: “DBSCAN”; “creation of a cluster”; Examiner note: in DBSCAN a cluster comprises a first point, or core point, and any other points withing the neighborhood radius); and
outputting the cluster ([0060]: “creation of a cluster”).
Foroozan does not explicitly teach:
determining a final size of the cluster according to a neighborhood radius and a density threshold that correspond to each identification point within the range defined by the first neighborhood radius with the first target point as the center; and
determining any identification point other than the cluster as the first target point, and returning to perform the step of acquiring the first neighborhood radius and the first density threshold that correspond to the first target point and in the case where the number of identification points within the range defined by the first neighborhood radius with the first target point as the center is greater than or equal to the first density threshold, establishing the cluster until all identification points are traversed.
However, Yang is in the field of radar clustering algorithms, and teaches:
wherein the algorithm parameter comprises a neighborhood radius and a density threshold (Yang [pg. 31]: “neighborhood radius”; “number of search points”);
determining any identification point of the at least one identification point as a first target point (Yang [pgs. 30-31]: “determine any point corresponding to the target 4D point cloud data as the target point”);
acquiring a first neighborhood radius and a first density threshold that correspond to the first target point (Yang [pg. 31]: “determine the neighborhood radius”; “determine the minimum number of search points”), and in a case where a number of identification points within a range defined by the first neighborhood radius with the first target point as a center is greater than or equal to the first density threshold, establishing a cluster (Yang [pg. 32]: “When the actual number is greater than the minimum number… the remaining search points are determined to form the target cluster”); wherein the cluster comprises the first target point and the identification points within the range defined by the first neighborhood radius with the first target point as the center ([pg. 31]: “Determine the points in the target 4D point cloud data whose distance from the target point is less than the neighborhood radius as search points”);
determining a final size of the cluster according to a neighborhood radius and a density threshold that correspond to each identification point within the range defined by the first neighborhood radius with the first target point as the center (Yang [pg. 56]: “After determining the target point, determine the neighborhood radius of the contour corresponding to the target cluster in the target 4D point cloud data based on the target point. Traverse all points within the neighborhood radius of the contour corresponding to the target cluster. If a point has not been visited during the search process, add the point to the target cluster… Continue until all points within the neighborhood radius of the contour corresponding to the target cluster have been visited”); and
outputting the cluster (Yang [pg. 56]: “Once a complete target cluster is obtained…”), determining any identification point other than the cluster as the first target point, and returning to perform the step of acquiring the first neighborhood radius and the first density threshold that correspond to the first target point and in the case where the number of identification points within the range defined by the first neighborhood radius with the first target point as the center is greater than or equal to the first density threshold, establishing the cluster until all identification points are traversed (Yang [pg. 56]: “continue repeating the above steps to traverse all points, thereby obtaining multiple target clusters.”).
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 invention of Foroozan and determine a final size of the cluster and repeat the clustering analysis steps until all points are traversed, as taught by Yang, with a reasonable expectation of success. Applying Yang’s known repeated clustering technique to Foroozan’s target detection method would yield the predictable result of allowing the system to distinguish multiple targets, thereby improving target detection.
Regarding Claims 7 and 16, Foroozan does not explicitly teach – but Yang teaches: wherein determining the final size of the cluster according to the neighborhood radius and the density threshold that correspond to the each identification point within the range defined by the first neighborhood radius with the first target point as the center comprises:
determining the identification points within the range defined by the first neighborhood radius with the first target point as the center as second target points (Yang [pg. 56]: “Traverse all points within the neighborhood radius of the contour corresponding to the target cluster.”; “continue repeating the above steps to traverse all points”); and
acquiring, for each second target point of the second target points, a second neighborhood radius and a second density threshold that correspond to the each second target point (Yang [pg. 31]: “determine the neighborhood radius”; “determine the minimum number of search points”), and in a case where a number of identification points within a range defined by the second neighborhood radius with the each second target point as a center is greater than or equal to the second density threshold, adding the identification points within the range defined by the second neighborhood radius with the each second target point as the center to the cluster until all the second target points are traversed (Yang [pg. 32]: “When the actual number is greater than the minimum number… the remaining search points are determined to form the target cluster”; [pg. 56]: “Traverse all points within the neighborhood radius”; “continue repeating the above steps to traverse all points”).
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 invention of Foroozan and determine the final size of the cluster by determining second target points and repeating the clustering analysis, as taught by Yang, with a reasonable expectation of success. Applying Yang’s known repeated clustering technique to Foroozan’s target detection method would yield the predictable result of allowing the system to distinguish multiple targets, thereby improving target detection.
Allowable Subject Matter
Claims, 4, 13, and 19 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Regarding Claims 4, 13, and 19, the claims require determining a first coefficient, which is used to determine an algorithm parameter. The claims specifically require determining an amplitude of a detection point, determining a maximum amplitude and a minimum amplitude from among detected amplitudes, and determining the first coefficient according to the amplitude of the detection point, the maximum amplitude, and the minimum amplitude.
Foroozan (US 2021/0117659) teaches a radar clustering algorithm that determines algorithm parameters, but does not teach determining a coefficient to determine the algorithm parameters ([0058-0062]).
Chen (CN 102253375 A) teaches determining algorithm parameters by determining a coefficient related to a detected amplitude, but does not teach determining the coefficient based on the amplitude of a detection point, a maximum amplitude, and a minimum amplitude.
Therefore, the prior art does not teach or render obvious to one of ordinary skill in the art at the time of filing the combination limitations of the claimed invention. Specifically, the prior art does not teach or render obvious determining the first coefficient according to the amplitude of the detection point, the maximum amplitude, and the minimum amplitude.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NOAH Y. ZHU whose telephone number is (571) 270-0170. The examiner can normally be reached Monday-Friday, 8AM-4PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire, can be reached on (571) 270-5144. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NOAH YI MIN ZHU/Examiner, Art Unit 3648
/BRADY W FRAZIER/Primary Examiner, Art Unit 3648
Prosecution Insights