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 .
Status of Claims
Claims 1-11 are currently pending and have been examined
Claim Objections
Claims 1, and 10 are objected to because of the following informalities:
Claims 1 and 10 recites, “for each transmitter class among a plurality of predetermined transmitter classes, each transmitter class of said plurality of predetermined transmitter classes being associated with at least one expected signature,” which is a typographical error of “for each transmitter class among a plurality of predetermined transmitter classes, wherein each transmitter class of said plurality of predetermined transmitter classes being associated with at least one expected signature,”
Appropriate correction is required.
Claim(s) 4 and 6 are objected to because of the following informalities:
Claim(s) 4 and 6 recite, “wherein the observed signature is further dependent on a distribution of all of the corresponding frequency of the set of corresponding received pulses, and for said each transmitter class,” which is a typographical error of ““wherein the determined observed signature is further dependent on a distribution of all of the corresponding frequency of the set of corresponding received pulses, and for said each transmitter class,”
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) 1-11 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.
Claims 1; 10; and 11 recite, “determining an observed signature of the radar transmitter based on a distribution of time gaps between consecutive times of arrival;”
It is unclear what is arriving between consecutive times of arrival. Paragraphs [0005]-[0006] of the specification explains that consecutive pulses received from a radar transmitter is essential to the applicant’s invention in order to identify a radar transmitter. The invention as claimed omits the determination is based off of received pulses from a radar transmitter. For examination purposes the examiner will interpret the limitation to recite, “determining an observed signature of the radar transmitter based on a distribution of time gaps between consecutive times of arrival of the set of received pulses;”
Claims 2-9 inherit the deficiency noted in claim 1.
Claim 10 recites “ A non-transitory computer program comprising...” It is unclear if the claim is directed to a non-transitory computer readable medium or if the claim is directed to a computer program. The term “non-transitory computer program” is not a term of art and the applicant’s specification has not provided a definition for the term. Furthermore, a computer program is software, which does not have a tangible form and cannot be considered to be non-transitory. For examination purposes, the examiner will interpret the claim to recite “A computer comprising of one or more processors that execute instructions that implement a method for....”
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1:
In the instant case, claims 1-9 are directed to a method, which is a process; claim 10 is directed to a computer, which is a machine. Claim 11 is directed to a system, which is a machine. Therefore, the claims fall in one of the four statutory categories.
Step 2a, Prong 1:
Claim 10 recites:
determining an observed signature of the radar transmitter based on a distribution of time gaps between consecutive times of arrival;
for each transmitter class among a plurality of predetermined transmitter classes, wherein said each transmitter class of said plurality of predetermined transmitter classes being associated with at least one expected signature,
calculating a proximity score between the observed signature and each expected signature of said at least one expected signature associated with said each transmitter class,
said each expected signature being a function of an expected distribution of time gaps between consecutive times of transmission for said each transmitter class, and for a predetermined pulse loss rate; and
assigning the radar transmitter to the each transmitter class associated with the expected signature that results in a best proximity score.
Therefore, the limitations recited above are directed to identifying a radar transmitter. This concept is considered both a method of organizing human activity and a mathematical concept. It is considered to be a method of organizing human activity because it manages personal behavior, where a person can assign a transmitter class of the radar transmitter based off of a score. Furthermore, since a score is calculated for each signature of each radar transmitter in order to determine the transmitter class, the claim is directed to a mathematical concept. Methods of organizing human activity and mathematical concepts both are categorized as abstract ideas. Therefore, the claim recites an abstract idea.
Step 2a, Prong 2:
This judicial exception is not integrated into a practical application because claim 10 recites the following element(s): “A computer comprising of one or more processors that execute instructions that implement a method for”. This additional element does not integrate the exception into a practical application because they do no more than apply the abstract idea on a computer (see MPEP 2106.05(f)). Accordingly, the additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Claim 10 is directed to an abstract idea.
Step 2b:
Claim 10 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to integration of the abstract idea into practical application, the additional element(s) individually or in combination do no more than apply the abstract idea on a computer, which does not render a claim as being significantly more than the abstract idea. Accordingly claim 10 is ineligible.
Claim 1 is parallel in nature to claim(s) 10. Accordingly claim 1 is rejected as being directed towards ineligible subject matter based upon the same analysis above. Examiner notes no additional elements are recited in claim 1. Therefore, the abstract idea is not integrated into an abstract idea and is not considered to be significantly more than the abstract idea. Furthermore, dependent claims 2-9 further limit the abstract idea. Therefore, claims 2-9 are ineligible.
Claim 11 is parallel in nature to claim 10. Accordingly claim 11 is rejected as being directed towards ineligible subject matter based upon the same analysis as above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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
Claim(s) 1-7, 10 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US. 7034738 B1) in view of Szajnowski et al. (US 20080192864 A1).
Regarding Claim 1, Wang discloses,
the computer-implemented method comprising:
determining an observed signature of the radar transmitter based on a distribution of time gaps between consecutive times of arrival; (Col. 5, Line 53-59 “Table A, threat gen n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang),
for each transmitter class among a plurality of predetermined transmitter classes, each transmitter class of said plurality of predetermined transmitter classes being associated with at least one expected signature, (Col 3, Line 53-54; “Step 1: Specify various clustering parameters, as follows: K=number of cluster centers desired;”; col. 7, Line 44-58 “By matching the clusters against stored table 27, the latter containing identifications of known radars (threats and/or non-threats), the radars may be classified and identified.” of Wang)
calculating a proximity score between the observed signature and each expected signature of said at least one expected signature associated with said each transmitter class, (Col 1, Line 54-57; “ (c) sorting the multi-dimensional samples into a plurality of data clusters, based on their respective proximity to the data clusters, each data cluster representing a classification of a radar emitter.”; and col.3, Line 62-63 “Step 2: Distribute the N samples among the present cluster centers” of Wang)
said each expected signature being a function of an expected distribution of time gaps between consecutive times of transmission for said each transmitter class; and (Col. 2, Line 63-67, “The method first defines a measure of pattern similarity and establishes a rule for assigning individual samples to the domain of a specific cluster center.”; col. 5, Line 53-58 “Table A, threat_gen_n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs). The snapshot includes PDW mixes from multiple radar threats, as they may be intercepted by wideband receiver 21,”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang)
assigning the radar transmitter to the each transmitter class associated with the expected signature that results in a best proximity score. (Col 7, Line 54-58; “By matching the clusters against stored table 27, the latter containing identifications of known radars (threats and/or non-threats), the radars may be classified and identified.” of Wang)
Wang does not disclose the limitation below, but Szajnowski teaches,
said each expected signature being a function…for a predetermined pulse loss rate; (See paragraph [0031] “a sufficient number of pulses are aligned, then it is assumed that these pulses and the selected candidate pulse form a coherent group.”; and paragraph [0072] “The continuity criterion A may also take into account missing single pulses” of Szajnowski)
Wang and Szajnowski are analogous art as both disclose a radar method that use radar emitter identification and signal processing to classify pulse trains from radar signals.
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 process of classifying radar emitters using a proximity score, signatures, and pulse characterization as disclosed by Wang to include pulse loss rate as taught by Szajnowski. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Wang in order to detect and classify radar pulses that have too much noise or missing pulses within the signal. (see Paragraph [0028] of Szajnowski).
Regarding Claim 2, Wang in view of Szajnowski discloses the method of Claim 1. Wang further discloses:
wherein, for said each expected signature, the proximity score is a function of an optimal transport distance between the observed signature and said each expected signature, (Col 3, Line 9-12; “The Euclidean distance measure, D, lends itself to this procedure, because it is a good measure of proximity. However, because the proximity of two patterns is a relative measure of similarity,” of Wang) the radar transmitter being assigned to the each transmitter class associated with the expected signature for which the optimal transport distance that is calculated is smallest. (Col 3, Line 53-54; “Step 1: Specify various clustering parameters, as follows: K=number of cluster centers desired;”; col. 7, Line 44-58 “By matching the clusters against stored table 27, the latter containing identifications of known radars (threats and/or non-threats), the radars may be classified and identified.” of Wang)
Regarding Claim 3, Wang in view of Szajnowski, discloses the method of Claim 1. Wang further discloses:
wherein said each received pulse is further associated with a corresponding frequency, and said each transmitter class is associated with at least one transmission frequency, the observed signature further depending on the corresponding frequency of said each received pulse, (Col. 5, Line 53-59 “Table A, threat gen n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”) and see (Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang)
Regarding Claim 4, Wang in view of Szajnowski, discloses the method of claim 3. Wang further discloses,
wherein the determined observed signature is further dependent on a distribution of all of the corresponding frequency of the set of corresponding received pulses, and for said each transmitter class,; (See Col. 5, Line 53-59 “Table A, threat_gen_n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang) and
for said each transmitter class, the each expected signature corresponding thereto depending on the expected distribution associated therewith, repeated at each transmission frequency of the at least one transmission frequency of the each transmitter class. (See Col. 2, Line 63-67, “The method first defines a measure of pattern similarity and establishes a rule for assigning individual samples to the domain of a specific cluster center.” ; Col. 5, Line 53-58 “Table A, threat_gen_n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang)
Wang does not disclose the limitation below; however, Szajnowski teaches,
for each loss rate of said predetermined pulse loss rate of said each expected signature, the each expected signature corresponding thereto depending on the expected distribution associated therewith, repeated at each transmission frequency of the at least one transmission frequency of the each transmitter class. (See paragraph [0031] “a sufficient number of pulses are aligned, then it is assumed that these pulses and the selected candidate pulse form a coherent group.”; and paragraph [0072] “The continuity criterion A may also take into account missing single pulses” of Szajnowski)
Wang and Szajnowski are analogous art as both disclose a radar method that u se radar emitter identification and signal processing to classify pulse trains from radar signals.
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 process of classifying radar emitters using a proximity score, signatures, and pulse characterization as disclosed by Wang to include pulse loss rate as taught by Szajnowski. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Wang in order to detect and classify radar pulses that have too much noise or missing pulses within the signal. (see Paragraph [0028] of Szajnowski).
Regarding Claim 5, Wang in view of Szajnowski discloses, the method of Claim 4. Wang further discloses:
wherein said each received pulse is further associated with a corresponding duration and said each transmitter class is associated with at least one transmitted pulse duration, the observed signature further depending on the at least one transmitted pulse duration of said each received pulse, and for said each transmitter class, said each expected signature further depending on said at least one transmitted pulse duration associated therewith. (Col. 5, Line 53-59 “Table A, threat gen n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang)
Regarding Claim 6, Wang in view of Szajnowski, discloses the method of claim 5. Wang further discloses,
wherein the observed signature is further dependent on a distribution of the corresponding duration of the received pulses, and for said each transmitter class, (See Col. 5, Line 53-59 “Table A, threat gen n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang)
the expected signature corresponding therewith depending on the expected distribution associated therewith, repeated at said each pulse duration of the each transmitter class. (See Col. 2, Line 63-67, “The method first defines a measure of pattern similarity and establishes a rule for assigning individual samples to the domain of a specific cluster center.”; Col. 5, Line 53-59 “Table A, threat_gen_n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang)
Wang does not disclose the limitation below; however, Szajnowski teaches,
wherein the observed signature is further dependent on a distribution of the corresponding duration of the received pulses.... and for said each loss rate, (See Paragraph [0031] “a sufficient number of pulses are aligned, then it is assumed that these pulses and the selected candidate pulse form a coherent group.”; and paragraph [0072] “The continuity criterion A may also take into account missing single pulses” of Szajnowski)
Wang and Szajnowski are analogous art as both disclose a radar method that use radar emitter identification and signal processing to classify pulse trains from radar signals.
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 process of classifying radar emitters using a proximity score, signatures, and pulse characterization as disclosed by Wang to include pulse loss rate as taught by Szajnowski. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Wang in order to detect and classify radar pulses that have too much noise or missing pulses within the signal. (see Paragraph [0028] of Szajnowski).
Regarding Claim 7, Wang in view of Szajnowski discloses, the method of Claim 1. Wang does not disclose the limitation below. However,
Szajnowski further discloses,
wherein the predetermined pulse loss rate is less than 0.5. (Paragraph [0073] “for example, when only eight pulses are expected to occur within a burst and in total three pulses are allowed to be missing, the selected value of MN will be four (i.e., CP>4).” of Szajnowski)
Wang and Szajnowski are analogous art as both disclose a radar method that use radar emitter identification and signal processing to classify pulse trains from radar signals.
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 process of classifying radar emitters using a proximity score, signatures, and pulse characterization as disclosed by Wang to include pulse loss rate less than o.5 as taught by Szajnowski. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Wang in order to detect and classify radar pulses that have too much noise or missing pulses within the signal. (see Paragraph [0028] of Szajnowski).
Regarding Claim 10, Wang discloses,
A computer comprising of one or more processors that execute instructions that implement a method for identifying a radar transmitter from a set of corresponding received pulses, each received pulse of said set of corresponding received pulses being associated with a respective time of arrival, the computer-implemented method comprising:
determining an observed signature of the radar transmitter based on a distribution of time gaps between consecutive times of arrival; (Col. 5, Line 53-59 “Table A, threat gen n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang),
for each transmitter class among a plurality of predetermined transmitter classes, each transmitter class of said plurality of predetermined transmitter classes being associated with at least one expected signature, (Col 1, Line 42-44” based on their respective proximity to the data clusters, each data cluster representing a classification of a radar emitter.”) and (Col 3, Line 53-54; “Step 1: Specify various clustering parameters, as follows: K=number of cluster centers desired;”)
calculating a proximity score between the observed signature and each expected signature of said at least one expected signature associated with said each transmitter class, (Col 1, Line 54-57; “ (c) sorting the multi-dimensional samples into a plurality of data clusters, based on their respective proximity to the data clusters, each data cluster representing a classification of a radar emitter.”; and col.3, Line 62-63 “Step 2: Distribute the N samples among the present cluster centers” of Wang)
said each expected signature being a function of an expected distribution of time gaps between consecutive times of transmission for said each transmitter class, (Col. 2, Line 63-67, “The method first defines a measure of pattern similarity and establishes a rule for assigning individual samples to the domain of a specific cluster center.”; col. 5, Line 53-58 “Table A, threat_gen_n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs). The snapshot includes PDW mixes from multiple radar threats, as they may be intercepted by wideband receiver 21,”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.” of Wang)
assigning the radar transmitter to the each transmitter class associated with the expected signature that results in a best proximity score. (Col 7, Line 54-58; “By matching the clusters against stored table 27, the latter containing identifications of known radars (threats and/or non-threats), the radars may be classified and identified.” of Wang)
Wang does not disclose the limitation below; however, Szajnowski teaches,
said each expected signature being a function of an expected distribution of time gaps.... and for a predetermined pulse loss rate; and (See paragraph [0031] “a sufficient number of pulses are aligned, then it is assumed that these pulses and the selected candidate pulse form a coherent group.”; and paragraph [0072] “The continuity criterion A may also take into account missing single pulses” of Szajnowski)
Wang and Szajnowski are analogous art as both disclose a radar method that use radar emitter identification and signal processing to classify pulse trains from radar signals.
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 process of classifying radar emitters using a proximity score, signatures, and pulse characterization as disclosed by Wang to include pulse loss as taught by Szajnowski. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Wang in order to detect and classify radar pulses that have too much noise or missing pulses within the signal. (see Paragraph [0028] of Szajnowski).
Regarding Claim 11, Wang discloses,
An identification system that identifies a radar transmitter from a set of corresponding received pulses, each received pulse of said set of corresponding received pulses being associated with a respective time of arrival, the identification system comprising:
a processor configured to (Col. 7, Line 46-50; “Also included is processor 26, coupled to wideband receiver 21, for generating each PDW using PDW generator 22, normalizing each PDW using PDW normalizer 23 and clustering each normalized PDW into a respective cluster using ISODATA module 24.”)
determine an observed signature of the radar transmitter based on a distribution of time gaps between consecutive times of arrival; (Col. 5, Line 53-59 “Table A, threat gen n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs).”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.”),
for each transmitter class from among a plurality of predetermined transmitter classes, said each transmitter class being associated with at least one expected signature, (Col 3, Line 53-54; “Step 1: Specify various clustering parameters, as follows: K=number of cluster centers desired;”; col. 7, Line 44-58 “By matching the clusters against stored table 27, the latter containing identifications of known radars (threats and/or non-threats), the radars may be classified and identified.”)
calculate a proximity score between the observed signature and each expected signature of said at least one expected signature associated with said each transmitter class, (Col 1, Line 54-57; “ (c) sorting the multi-dimensional samples into a plurality of data clusters, based on their respective proximity to the data clusters, each data cluster representing a classification of a radar emitter.”; and col.3, Line 62-63 “Step 2: Distribute the N samples among the present cluster centers”)
said each expected signature being a function of an expected distribution of time gaps between consecutive times of transmission for said each transmitter class, (Col. 2, Line 63-67, “The method first defines a measure of pattern similarity and establishes a rule for assigning individual samples to the domain of a specific cluster center.”; col. 5, Line 53-58 “Table A, threat_gen_n.m, lists a program for generating a snapshot of the radars pulse descriptive words (PDWs). The snapshot includes PDW mixes from multiple radar threats, as they may be intercepted by wideband receiver 21,”; Col 7, Line 34-38; “Each PDW, which is a vector, is composed of four components, describing an intercepted radar pulse, as follows: (1) time of intercept (or arrival), TOA, (2) radio frequency, RF, (3) pulse width, PW, and (4) pulse amplitude, PA.”)
assign the radar transmitter to the each transmitter class associated with the each expected signature that results in a best proximity score. (Col 7, Line 54-58; “By matching the clusters against stored table 27, the latter containing identifications of known radars (threats and/or non-threats), the radars may be classified and identified.” )
Wang does not disclose the limitation below; however, Szajnowski teaches,
said each expected signature being a function of an expected distribution of time gaps.... and for a predetermined pulse loss rate; and (See paragraph [0031] “a sufficient number of pulses are aligned, then it is assumed that these pulses and the selected candidate pulse form a coherent group.”; and paragraph [0072] “The continuity criterion A may also take into account missing single pulses” of Szajnowski)
Wang and Szajnowski are analogous art as both disclose a radar method that use radar emitter identification and signal processing to classify pulse trains from radar signals.
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 process of classifying radar emitters using a proximity score, signatures, and pulse characterization as disclosed by Wang to include pulse loss as taught by Szajnowski. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Wang in order to detect and classify radar pulses that have too much noise or missing pulses within the signal. (see Paragraph [0028] of Szajnowski).
Allowable Subject Matter
Claim(s) 8 and 9 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 and 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VICTOR OLEKANMA whose telephone number is 571-272-8978. The examiner can normally be reached M-TH between 7:00 AM and 3:00 PM.
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/VICTOR IKECHUKWU OLEKANMA/Examiner, Art Unit 3648
/RESHA DESAI/Supervisory Patent Examiner, Art Unit 3648
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