Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The following is a final office action in response to the communication filed on 01/27/2026. Claims 1-4, 6-11, and 13-20 have been amended. Claims 1-20 are currently pending and have been examined.
Response to Arguments
Applicant’s arguments and remarks filed on 01/27/2026 have been fully considered. Examiner thanks Applicant for the clear and detailed remarks.
Applicant’s amendments overcome the 35 U.S.C. §112(b) rejection of claims 1-20.
Applicant’s arguments provided for the 35 U.S.C. §103 rejections of claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claims 3-4, 10-11 and 17-18 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 3, line 1 on page 2 recites “an estimated power variance”. An estimated power variance was introduced in claim 1, line 8, and it is unclear whether the estimated power variance of claim 3 is the same or different from claim 1. For purposes of examination, claim 3 will be read as “the estimated power variance”.
Regarding claim 4, lines 2-3 recites “the an estimated power variance”. An estimated power variance was introduced in claim 1, line 8, and it is unclear whether the estimated power variance of claim 4 is the same or different from claim 1. For purposes of examination, claim 4 will be read as “the estimated power variance”.
Regarding claim 10, line 6 recites “an estimated power variance”. An estimated power variance was introduced in claim 8 (page 3, line 1), and it is unclear whether the estimated power variance of claim 10 is the same or different from claim 8. For purposes of examination, claim 10 will be read as “the estimated power variance”.
Regarding claim 11, line 3 recites “an estimated power variance”. An estimated power variance was introduced in claim 8 (page 3, line 1), and it is unclear whether the estimated power variance of claim 11 is the same or different from claim 8. For purposes of examination, claim 11 will be read as “the estimated power variance”.
Regarding claim 17, page 5, line 4 recites “an estimated power variance”. An estimated power variance was introduced in claim 15, line 8, and it is unclear whether the estimated power variance of claim 17 is the same or different from claim 15. For purposes of examination, claim 17 will be read as “the estimated power variance”.
Regarding claim 18, line 3 recites “an estimated power variance”. An estimated power variance was introduced in claim 15, line 8, and it is unclear whether the estimated power variance of claim 18 is the same or different from claim 15. For purposes of examination, claim 18 will be read as “the estimated power variance”.
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.
Claims 1-3, 8-10 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Nakanishi (US-20080094274-A1; hereinafter, Nakanishi) in view of Kojima (US-20130342383-A1; hereinafter, Kojima).
Regarding claim 1, Nakanishi discloses [Note, what Nakanishi fails to disclose is strike-through]:
A method performed by a radar sensor system (see at least Fig. 1 and [0028]; “FIG. 1 is a block diagram showing a configuration of the entirety of a radar according to a first embodiment.”), the method comprising:
receiving time-domain analog-to-digital converted (ADC) samples (see at least [0048]; “An AD converter 8 converts the signal into a sampling data sequence, and supplies the sampling data sequence to a DSP (digital signal processor) 17.”) of a received radar signal (see at least Fig. 1 and [0047]; “The antenna 5 transmits the FM-modulated continuous wave transmission signal supplied from the VCO 1 and receives the signal reflected from the same direction.”);
identifying power magnitudes for the time-domain ADC samples (see at least [0051]; “A standard deviation computing unit 13 determines a standard deviation of amplitude on the basis of amplitude data items of the input sampling data sequence during a predetermined period (interval).”);
calculating an estimated power variance of the power magnitudes of the time-domain ADC samples in the given ramp (see at least [0051]; “A standard deviation computing unit 13 determines a standard deviation of amplitude on the basis of amplitude data items of the input sampling data sequence during a predetermined period (interval).”);
identifying a time-domain ADC sample having a power magnitude above a power threshold (see at least [0052]; “An interference detecting unit 14 determines whether or not each sampling data item (amplitude) in the sampling interval, which is clipped from the input sampling data sequence in order to determine a frequency spectrum, exceeds a threshold.”); and
However, Nakanishi does not explicitly teach calculating a mean power value for the time-domain ADC samples in a given ramp of the received radar signal or adjusting the power magnitude of the identified time-domain ADC sample to generate an adjusted time-domain ADC sample.
Nakanishi discloses detecting interference in radar signals, and Kojima is directed a radar interference rejection device for use with pulse compression radar Kojima teaches:
A method performed by a radar sensor system (see at least Fig. 1, compression radar device 10), the method comprising:
receiving time-domain analog-to-digital converted (ADC) samples of a received radar signal (see at least Fig. 1, A/D converter 41);
identifying power magnitudes for the time-domain ADC samples (see at least [0070]; “The amplitude calculator 61 calculates and outputs the absolute values (I2+Q2) of the complex signals I and Q obtained by the quadrature detector 42.”);
calculating a mean power value for time-domain ADC samples in a given interval of the received radar signal (see at least [0071] – [0075]; “The HPF 62 attenuates the frequency band lower than a specific cutoff frequency in order to make it easier to detect change in the amplitude of the portion where the radar interference is superposed over the echo signal…The moving deviation calculator 63 calculates the moving deviation in the distance direction of the output of the HPF 62. The distance of the sweep corresponds to the time it takes from transmission to reception of a modulated pulse signal at the antenna 20, and the distance direction corresponds to the time axis…The moving deviation calculator 63 receives the output of all seven of these registers 631 to 637 and the output of the HPF 62, and the standard deviation calculator 638 calculates the standard deviation of the eight sets of data. The standard deviation calculator 638 calculates a moving mean M from the output of the seven registers 631 to 637 and the output of the HPF 62.”);
calculating an estimated power variance of the power magnitudes of the time-domain ADC samples in the given interval (see at least [0075]; “Then, the square of the differences between the moving mean M and the output of the registers 631 to 637 and the output of the HPF 62 is found, the square root of a value obtained by averaging the square of the differences thus found is found, and this is outputted as the standard deviation.”);
identifying a time-domain ADC sample having a power magnitude above a power threshold (see at least[0077] – [0078]; “The moving deviation comparator 65 compares the moving deviation of the target distance of the target sweep with the moving deviation at the same distance over the plurality of continuous sweeps. If the moving deviation of the target distance of the target sweep is prominent with respect to the moving deviation of the adjacent sweeps, it is concluded that radar interference is superposed over the target distance of the target sweep…A variety of methods can be used to determine whether or not the moving deviation of the target distance of the target sweep is prominent with respect to the data of the sweeps adjacent to the target sweep. For instance, The deviation σn of the target distance of the target sweep is compared with the average value (σn-1+σn+1)/2 of the deviation values (σn-1 and σn+1) for the sweeps before and after at the same distance. If the deviation value σn of the target distance of the target sweep is greater than the product obtained by multiplying this average value by an interference detection coefficient co, it is concluded that the radar interference is superposed.”); and
adjusting the power magnitude of the identified time-domain ADC sample to generate an adjusted time-domain ADC sample (see at least [0066]; “The echo interpolator 432 replaces data for which the radar interference has been detected in the interference detection device 60 with data that does not include the radar interference. For instance, data for which the radar interference has been detected is replaced by the echo interpolator 432 with data at the same distance in an adjacent sweep. For example, an average is taken for data at the same distance in sweeps before and after the target sweep to find intermediate data between the two, and an offset is added to the intermediate data so that the data in the target sweep will be smoothly linked.”).
Both Nakanishi and Kojima teach detecting radar interference in time-domain radar samples by calculating the standard deviation of the signal amplitudes. Kojima explicitly calculates the mean signal value as part of calculating the standard deviation, and the formula for standard deviation includes the mean value of the sample set. Therefore, it would have been obvious to one of ordinary skill in the art at the time of the claimed invention to calculate the mean power value for the ADC samples as an intermediate step in calculating the variance in the method of Nakanishi. Furthermore, it would have been obvious to one of ordinary skill to replace data in which interference has been detected, as taught by Kojima. Nakanishi teaches detecting interference, but does not explicitly teach mitigating the interference. Replacing data subject to interference, as taught by Kojima, would have the advantage of removing the effect of the interference, and would have a reasonable likelihood of success, as both methods are performed in the time domain at an intermediate (medium) frequency.
Regarding claim 2, Nakanishi in view of Kojima discloses the method of claim 1. Nakanishi further teaches:
wherein the power threshold is a multiple of the estimated power variance of the power magnitudes of the time-domain ADC samples in the given ramp (see at least Fig. 6(A) and associated description in [0061]: “As shown, the amplitude of the beat signal generally does not exceed the standard deviation times 2, but the spike noise SPN sometimes exceeds the standard deviation times 2. Accordingly, as shown in this example, the value obtained by multiplying the standard deviation of amplitude of the beat signal, which is determined from the input beat signal, by 2 is used as the threshold. If the data item exceeding the threshold exists, the data is considered as the spike noise, and thus it is possible to determine that ‘interference exists’.”).
Regarding claim 3, Nakanishi in view of Kojima discloses the method of claim 1. Nakanishi further teaches:
wherein the radar signal comprises a plurality of ramps (see at least [0055]; “In a transmission signal TX, a frame F, constituted by an up-modulation interval in which the frequency increases and a down-modulation interval in which the frequency decreases, is repeated.”),
However, Nakanishi does not explicitly teach:
on a per-sample basis, calculating a difference between the absolute value of the power magnitude of a given ADC sample and the mean power magnitude for the ramp from which the given ADC sample was taken; and
calculating the estimated power variance of the power magnitudes by averaging the absolute values of the calculated differences.
Kojima teaches:
on a per-sample basis, calculating a difference between the absolute value of the power magnitude of a given ADC sample and the mean power magnitude for the interval from which the given ADC sample was taken; and
estimated power variance of the power magnitudes by averaging the absolute values of the calculated differences (see at least Formulas 5 and 6 in paragraph [0103] for average deviation, which match the formula described in claim 3. The variables are defined in [0077]. See also [0102]; “The average deviation, the moving root mean square, the moving variance, the moving mean square, or the moving mean value can be used as an index of variance instead of the moving standard deviation in the distance direction.”).
Nakanishi and Kojima both detect radar interference by comparing the standard deviation of an interval of ADC values to a threshold. Kojima teaches that alternative calculations can also be used as indexes of variance, including the average deviation. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that any of the indices of variance used for detecting radar interference in Kojima would be applicable in Nakanishi for detecting radar interference. Such a change would represent substitution of one known element for another to achieve predictable results.
Regarding claim 8, Nakanishi discloses [Note, what Nakanishi fails to disclose is strike-through]:
A radar sensor system (see at least Fig. 1 and [0028]; “FIG. 1 is a block diagram showing a configuration of the entirety of a radar according to a first embodiment.”) comprising:
a receive antenna that receives a radar return (see at least Fig. 1, antenna 5 receives a return signal from the target); and
circuitry (see at least Fig. 1, digital signal processor 17) configured to perform acts comprising:
receiving time-domain analog-to-digital converted (ADC) samples (see at least [0048]; “An AD converter 8 converts the signal into a sampling data sequence, and supplies the sampling data sequence to a DSP (digital signal processor) 17.”) of a received radar signal (see at least Fig. 1 and [0047]; “The antenna 5 transmits the FM-modulated continuous wave transmission signal supplied from the VCO 1 and receives the signal reflected from the same direction.”);
identifying power magnitudes for the time-domain ADC samples (see at least [0051]; “A standard deviation computing unit 13 determines a standard deviation of amplitude on the basis of amplitude data items of the input sampling data sequence during a predetermined period (interval).”);
calculating an estimated power variance of the power magnitudes of the time-domain ADC samples in the given ramp (see at least [0051]; “A standard deviation computing unit 13 determines a standard deviation of amplitude on the basis of amplitude data items of the input sampling data sequence during a predetermined period (interval).”);
identifying a time-domain ADC sample having a power magnitude above a power threshold (see at least [0052]; “An interference detecting unit 14 determines whether or not each sampling data item (amplitude) in the sampling interval, which is clipped from the input sampling data sequence in order to determine a frequency spectrum, exceeds a threshold.”); and
However, Nakanishi does not explicitly teach calculating a mean power value for the time-domain ADC samples in a given ramp of the received radar signal or adjusting the power magnitude of the identified time-domain ADC sample to generate an adjusted time-domain ADC sample.
Nakanishi discloses detecting interference in radar signals, and Kojima is directed a radar interference rejection device for use with pulse compression radar Kojima teaches:
receiving time-domain analog-to-digital converted (ADC) samples of a received radar signal (see at least Fig. 1, compression radar device 10 and A/D converter 41);
identifying power magnitudes for the time-domain ADC samples (see at least [0070]; “The amplitude calculator 61 calculates and outputs the absolute values (I2+Q2) of the complex signals I and Q obtained by the quadrature detector 42.”);
calculating a mean power value for time-domain ADC samples in a given interval of the received radar signal (see at least [0071] – [0075]; “The HPF 62 attenuates the frequency band lower than a specific cutoff frequency in order to make it easier to detect change in the amplitude of the portion where the radar interference is superposed over the echo signal…The moving deviation calculator 63 calculates the moving deviation in the distance direction of the output of the HPF 62. The distance of the sweep corresponds to the time it takes from transmission to reception of a modulated pulse signal at the antenna 20, and the distance direction corresponds to the time axis…The moving deviation calculator 63 receives the output of all seven of these registers 631 to 637 and the output of the HPF 62, and the standard deviation calculator 638 calculates the standard deviation of the eight sets of data. The standard deviation calculator 638 calculates a moving mean M from the output of the seven registers 631 to 637 and the output of the HPF 62.”);
calculating an estimated power variance of the power magnitudes of the time-domain ADC samples in the given interval (see at least [0075]; “Then, the square of the differences between the moving mean M and the output of the registers 631 to 637 and the output of the HPF 62 is found, the square root of a value obtained by averaging the square of the differences thus found is found, and this is outputted as the standard deviation.”);
identifying a time-domain ADC sample having a power magnitude above a power threshold (see at least[0077] – [0078]; “The moving deviation comparator 65 compares the moving deviation of the target distance of the target sweep with the moving deviation at the same distance over the plurality of continuous sweeps. If the moving deviation of the target distance of the target sweep is prominent with respect to the moving deviation of the adjacent sweeps, it is concluded that radar interference is superposed over the target distance of the target sweep…A variety of methods can be used to determine whether or not the moving deviation of the target distance of the target sweep is prominent with respect to the data of the sweeps adjacent to the target sweep. For instance, The deviation σn of the target distance of the target sweep is compared with the average value (σn-1+σn+1)/2 of the deviation values (σn-1 and σn+1) for the sweeps before and after at the same distance. If the deviation value σn of the target distance of the target sweep is greater than the product obtained by multiplying this average value by an interference detection coefficient co, it is concluded that the radar interference is superposed.”); and
adjusting the power magnitude of the identified time-domain ADC sample to generate an adjusted time-domain ADC sample (see at least [0066]; “The echo interpolator 432 replaces data for which the radar interference has been detected in the interference detection device 60 with data that does not include the radar interference. For instance, data for which the radar interference has been detected is replaced by the echo interpolator 432 with data at the same distance in an adjacent sweep. For example, an average is taken for data at the same distance in sweeps before and after the target sweep to find intermediate data between the two, and an offset is added to the intermediate data so that the data in the target sweep will be smoothly linked.”).
Both Nakanishi and Kojima teach detecting radar interference in time-domain radar samples by calculating the standard deviation of the signal amplitudes. Kojima explicitly calculates the mean signal value as part of calculating the standard deviation, and the formula for standard deviation includes the mean value of the sample set. Therefore, it would have been obvious to one of ordinary skill in the art at the time of the claimed invention to calculate the mean power value for the ADC samples as an intermediate step in calculating the variance in the method of Nakanishi. Furthermore, it would have been obvious to one of ordinary skill to replace data in which interference has been detected, as taught by Kojima. Nakanishi teaches detecting interference, but does not explicitly teach mitigating the interference. Replacing data subject to interference, as taught by Kojima, would have the advantage of removing the effect of the interference, and would have a reasonable likelihood of success, as both methods are performed in the time domain at an intermediate (medium) frequency.
Regarding claim 9, Nakanishi in view of Kojima discloses the radar sensor system of claim 8. The remaining limitations of claim 9 are analogous to those of claim 2 and are rejected for similar reasons.
Regarding claim 10, Nakanishi in view of Kojima discloses the radar sensor system of claim 8. The remaining limitations of claim 10 are analogous to those of claim 3 and are rejected for similar reasons.
Regarding claim 15, Nakanishi discloses [Note, what Nakanishi fails to disclose is strike-through]:
A hardware logic component (see at least Fig. 1, digital signal processor 17), comprising:
one or more processors configured to perform acts (see at least Fig. 1, digital signal processor 17) comprising:
receiving time-domain analog-to-digital converted (ADC) samples (see at least [0048]; “An AD converter 8 converts the signal into a sampling data sequence, and supplies the sampling data sequence to a DSP (digital signal processor) 17.”) of a received radar signal (see at least Fig. 1 and [0047]; “The antenna 5 transmits the FM-modulated continuous wave transmission signal supplied from the VCO 1 and receives the signal reflected from the same direction.”);
identifying power magnitudes for the time-domain ADC samples (see at least [0051]; “A standard deviation computing unit 13 determines a standard deviation of amplitude on the basis of amplitude data items of the input sampling data sequence during a predetermined period (interval).”);
calculating an estimated power variance of the power magnitudes of the time-domain ADC samples in the given ramp (see at least [0051]; “A standard deviation computing unit 13 determines a standard deviation of amplitude on the basis of amplitude data items of the input sampling data sequence during a predetermined period (interval).”);
identifying a time-domain ADC sample having a power magnitude above a power threshold (see at least [0052]; “An interference detecting unit 14 determines whether or not each sampling data item (amplitude) in the sampling interval, which is clipped from the input sampling data sequence in order to determine a frequency spectrum, exceeds a threshold.”); and
However, Nakanishi does not explicitly teach calculating a mean power value for the time-domain ADC samples in a given ramp of the received radar signal or adjusting the power magnitude of the identified time-domain ADC sample to generate an adjusted time-domain ADC sample.
Nakanishi discloses detecting interference in radar signals, and Kojima is directed a radar interference rejection device for use with pulse compression radar Kojima teaches:
receiving time-domain analog-to-digital converted (ADC) samples of a received radar signal (see at least Fig. 1, compression radar device 10 and A/D converter 41);
identifying power magnitudes for the time-domain ADC samples (see at least [0070]; “The amplitude calculator 61 calculates and outputs the absolute values (I2+Q2) of the complex signals I and Q obtained by the quadrature detector 42.”);
calculating a mean power value for time-domain ADC samples in a given interval of the received radar signal (see at least [0071] – [0075]; “The HPF 62 attenuates the frequency band lower than a specific cutoff frequency in order to make it easier to detect change in the amplitude of the portion where the radar interference is superposed over the echo signal…The moving deviation calculator 63 calculates the moving deviation in the distance direction of the output of the HPF 62. The distance of the sweep corresponds to the time it takes from transmission to reception of a modulated pulse signal at the antenna 20, and the distance direction corresponds to the time axis…The moving deviation calculator 63 receives the output of all seven of these registers 631 to 637 and the output of the HPF 62, and the standard deviation calculator 638 calculates the standard deviation of the eight sets of data. The standard deviation calculator 638 calculates a moving mean M from the output of the seven registers 631 to 637 and the output of the HPF 62.”);
calculating an estimated power variance of the power magnitudes of the time-domain ADC samples in the given interval (see at least [0075]; “Then, the square of the differences between the moving mean M and the output of the registers 631 to 637 and the output of the HPF 62 is found, the square root of a value obtained by averaging the square of the differences thus found is found, and this is outputted as the standard deviation.”);
identifying a time-domain ADC sample having a power magnitude above a power threshold (see at least[0077] – [0078]; “The moving deviation comparator 65 compares the moving deviation of the target distance of the target sweep with the moving deviation at the same distance over the plurality of continuous sweeps. If the moving deviation of the target distance of the target sweep is prominent with respect to the moving deviation of the adjacent sweeps, it is concluded that radar interference is superposed over the target distance of the target sweep…A variety of methods can be used to determine whether or not the moving deviation of the target distance of the target sweep is prominent with respect to the data of the sweeps adjacent to the target sweep. For instance, The deviation σn of the target distance of the target sweep is compared with the average value (σn-1+σn+1)/2 of the deviation values (σn-1 and σn+1) for the sweeps before and after at the same distance. If the deviation value σn of the target distance of the target sweep is greater than the product obtained by multiplying this average value by an interference detection coefficient co, it is concluded that the radar interference is superposed.”); and
adjusting the power magnitude of the identified time-domain ADC sample to generate an adjusted time-domain ADC sample (see at least [0066]; “The echo interpolator 432 replaces data for which the radar interference has been detected in the interference detection device 60 with data that does not include the radar interference. For instance, data for which the radar interference has been detected is replaced by the echo interpolator 432 with data at the same distance in an adjacent sweep. For example, an average is taken for data at the same distance in sweeps before and after the target sweep to find intermediate data between the two, and an offset is added to the intermediate data so that the data in the target sweep will be smoothly linked.”).
Both Nakanishi and Kojima teach detecting radar interference in time-domain radar samples by calculating the standard deviation of the signal amplitudes. Kojima explicitly calculates the mean signal value as part of calculating the standard deviation, and the formula for standard deviation includes the mean value of the sample set. Therefore, it would have been obvious to one of ordinary skill in the art at the time of the claimed invention to calculate the mean power value for the ADC samples as an intermediate step in calculating the variance in the method of Nakanishi. Furthermore, it would have been obvious to one of ordinary skill to replace data in which interference has been detected, as taught by Kojima. Nakanishi teaches detecting interference, but does not explicitly teach mitigating the interference. Replacing data subject to interference, as taught by Kojima, would have the advantage of removing the effect of the interference, and would have a reasonable likelihood of success, as both methods are performed in the time domain at an intermediate (medium) frequency.
Regarding claim 16, Nakanishi in view of Kojima discloses the hardware logic component of claim 15. The remaining limitations of claim 16 are analogous to those of claim 3 and are rejected for similar reasons.
Regarding claim 17, Nakanishi in view of Kojima discloses the hardware logic component of claim 15. The remaining limitations of claim 17 are analogous to those of claim 4 and are rejected for similar reasons.
Claims 4, 11 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Nakanishi in view of Kojima, further in view of Meissner et al. (US-20200379081-A1; hereinafter, Meissner).
Regarding claim 4, Nakanishi in view of Kojima discloses the method of claim 3. Nakanishi further teaches:
wherein the radar signal comprises a plurality of frames comprising ramps (see at least [0055]; “In a transmission signal TX, a frame F, constituted by an up-modulation interval in which the frequency increases and a down-modulation interval in which the frequency decreases, is repeated.”),
Both Nakanishi and Meissner detect radar interference by comparing the standard deviation or variance in a chirp or ramp to a threshold. Meissner teaches:
further comprising calculating the mean power variance by averaging the mean power variances calculated by a moving window (see at least Eq. 11 in [0050], where the standard deviations computed for multiple instances of a moving window are averaged).
Nakanishi calculates the standard deviation in a preset interval and creates a interference-detecting threshold as a multiple of this standard deviation (see [0061]). Meissner calculates the standard deviation of a moving window of radar data and similarly compares the computed value to a threshold to detect interference. The threshold of Meissner is determined using an average value of the standard deviations found by the moving window. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to compute the threshold used in Nakanishi using an average of the computed standard deviation values, as taught by Meissner. Such a calculation in the case of Nakanishi would comprise averaging the mean power variances of ramps in a given frame.
Regarding claim 11, Nakanishi in view of Kojima discloses the radar sensor system of claim 10. The remaining limitations of claim 11 are analogous to those of claim 4 and are rejected for similar reasons.
Regarding claim 18, Nakanishi in view of Kojima discloses the hardware logic component of claim 17. The remaining limitations of claim 18 are analogous to those of claim 4 and are rejected for similar reasons.
Claims 5-6, 12-13 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Nakanishi in view of Kojima, further in view of Nakamura (US-20230350007-A1; hereinafter, Nakamura).
Regarding claim 5, Nakanishi in view of Kojima discloses the method of claim 1. However, Nakanishi does not explicitly teach:
wherein adjusting the power magnitude of the identified sample comprises multiplying the identified sample power magnitude by zero.
Nakanishi discloses detecting interference in radar signals, and Nakamura is directed to detecting interference in radar signals and generating an interference-removed signal. Nakamura teaches:
wherein adjusting the power magnitude of the identified sample comprises multiplying the identified sample power magnitude by zero (see at least Fig. 4 and related description in [0037]; “The lower part of FIG. 4 shows an example of spectrum of the modified sample signal Ts2 generated by multiplying the sample signal Ts by the reduction signal Ti. As shown in FIG. 4, in this embodiment, the sample signal Ts is multiplied by the reduction signal Ti in step S110, so as to generate the modified sample signal Ts2, in which the signal intensity is zero in the range Ri1 corresponding to the interference range Ri, and the signal intensity in the other range is similar to the sample signal Ts.”).
Nakanishi teaches detecting interference, but does not explicitly teach mitigating the interference. 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 interference detection used in Nakanishi to include multiplying the regions affected by interference to zero, as taught by Nakamura. Replacing data subject to interference, as taught by Nakamura, would have the advantage of removing the effect of the interference, and would have a reasonable likelihood of success, as both methods are performed in the time domain at an intermediate frequency.
Regarding claim 6, Nakanishi in view of Kojima discloses the method of claim 1. However, Nakanishi does not explicitly teach:
wherein adjusting the power magnitude of the identified sample comprises attenuating the identified sample power magnitude to a level within the mean power variance for the ramp from which the identified sample was taken.
Nakanishi discloses detecting interference in radar signals, and Nakamura is directed to detecting interference in radar signals and generating an interference-removed signal. Nakamura teaches:
wherein adjusting the power magnitude of the identified sample comprises attenuating the identified sample power magnitude to a level within the mean power variance for the ramp from which the identified sample was taken (see at least Fig. 4 and related description in [0037]; “The lower part of FIG. 4 shows an example of spectrum of the modified sample signal Ts2 generated by multiplying the sample signal Ts by the reduction signal Ti. As shown in FIG. 4, in this embodiment, the sample signal Ts is multiplied by the reduction signal Ti in step S110, so as to generate the modified sample signal Ts2, in which the signal intensity is zero in the range Ri1 corresponding to the interference range Ri, and the signal intensity in the other range is similar to the sample signal Ts.” Examiner notes that attenuating the identified samples to a level of zero will be within the mean power variance of the ramp for any ramp comprising non-zero values. Nakamura teaches the use of ramp signals in [0025]).
Nakanishi teaches detecting interference, but does not explicitly teach mitigating the interference. 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 interference detection used in Nakanishi to include multiplying the regions affected by interference to zero, as taught by Nakamura. Replacing data subject to interference, as taught by Nakamura, would have the advantage of removing the effect of the interference, and would have a reasonable likelihood of success, as both methods are performed in the time domain at an intermediate frequency.
Regarding claim 12, Nakanishi in view of Kojima discloses the radar sensor system of claim 8. The remaining limitations of claim 12 are analogous to those of claim 5 and are rejected for similar reasons.
Regarding claim 13, Nakanishi in view of Kojima discloses the radar sensor system of claim 8. The remaining limitations of claim 13 are analogous to those of claim 6 and are rejected for similar reasons.
Regarding claim 19, Nakanishi in view of Kojima discloses the hardware logic component of claim 15. The remaining limitations of claim 19 are analogous to those of claim 5 and are rejected for similar reasons.
Regarding claim 20, Nakanishi in view of Kojima discloses the hardware logic component of claim 15. The remaining limitations of claim 20 are analogous to those of claim 6 and are rejected for similar reasons.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Nakanishi in view of Kojima, further in view of Li et al. (US-11536801-B1; hereinafter, Li).
Regarding claim 7, Nakanishi in view of Kojima discloses the method of claim 1. However, Nakanishi does not explicitly teach:
further comprising generating a point cloud using the ADC samples and the adjusted ADC sample.
Nakanishi discloses detecting interference in radar signals, and Li is directed to enhancing radar sensing using non-uniform FMCW chirps. Li teaches:
further comprising generating a point cloud using the ADC samples (see at least Fig. 6, where radar chirps shown in 252 are processed into a point cloud in 282).
Both Nakanishi and Li teach radar systems using frequency ramps. Nakanishi teaches detecting the radar data affected by interference. Li teaches processing the radar data into a point cloud. 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 system used in Nakanishi to include computing a point cloud as taught by Li. Such a modification would have a reasonable expectation of success because both system use frequency ramped signals, and the modification would represent applying a known technique to a known method ready for improvement to yield predictable results.
Regarding claim 14, Nakanishi in view of Kojima discloses the radar sensor system of claim 8. The remaining limitations of claim 14 are analogous to those of claim 7 and are rejected for similar reasons.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ashley B. Raynal whose telephone number is (703)756-4546. The examiner can normally be reached Monday - Friday, 8 AM - 4 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire can be reached at (571) 270-5144. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ASHLEY BROWN RAYNAL/Examiner, Art Unit 3648
/VLADIMIR MAGLOIRE/Supervisory Patent Examiner, Art Unit 3648