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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/04/2026 has been entered. Claims 1-4, 8-11, 13, 15-18 and 20 have been amended. Claims 1-20 are currently pending and have been examined.
Response to Arguments
Applicant’s arguments and remarks filed on 06/04/2024 have been fully considered.
Applicant’s amendments overcome the 35 U.S.C. §112(b) rejections of claims 3, 10 and 17. However, indefiniteness issues remain in claims 4, 11 and 18, as discussed below in the 35 U.S.C. §112 section.
Applicant’s arguments provided for the 35 U.S.C. §103 rejections of claims 1-3, 5, 7-10, 12, 14-17 and 19 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.
Applicant’s arguments provided for the prior art rejection of claims 4, 11 and 18 is convincing, and the prior art rejection for those claims has been overcome.
Applicant’s arguments provided for the 35 U.S.C. §103 rejections of claims 6, 13 and 20 have been considered but are not persuasive.
(A) Applicant argues, “Claims 6, 13, and 20 are patentable for the same reasons and for an additional reason. The AA states that Nakamura's zeroing operation reads on the attenuation limitation because, according to the AA, a value of zero will always be within the estimated power variance. Applicant respectfully disagrees. The dependent claims do not merely recite setting a value to zero in the abstract. They require attenuating the identified time-domain ADC sample power magnitude to a level within the estimated power variance of the power magnitudes for the ramp from which the identified time- domain ADC sample was taken. That limitation depends on the ramp-specific estimated power variance required by the amended independent claims. Nakamura's Paragraph [0037] describes multiplying a sample signal by a reduction signal that is zero in an interference range, and Paragraph [0025] describes generating chirp signals. Neither paragraph teaches or suggests using an estimated power variance for the ramp from which the identified time-domain ADC sample was taken as the relevant attenuation bound.
The AA's mathematical observation regarding zero also does not supply the missing claim relationship. The claims require attenuation to a level within the estimated power variance for the ramp from which the identified sample was taken; they do not merely require that the final value be numerically zero. The rejection does not identify where Nakamura teaches or suggests the claimed ramp-specific estimated power variance, much less attenuation tied to that ramp-specific variance. Thus, Nakamura does not cure the deficiencies of the base Nakanishi and Kojima combination and does not teach the additional limitations of Claims 6, 13, and 20. The rejection of Claims 5, 6, 12, 13, 19, and 20 should therefore be withdrawn,” (from remarks pages 16-17).
Applicant further argues, “Applicant also acknowledges the AA's comments regarding Claims 6, 13, and 20. The AA states that Nakamura's setting of a sample value to zero reads on the attenuation limitation because, according to the AA, a value of zero will always be within the estimated power variance. Applicant respectfully disagrees. The claims do not merely recite setting a value to zero in the abstract. Claims 6, 13, and 20 depend from independent claims that require ramp-specific mean and variance calculations, and the attenuation limitation is tied to the estimated power variance for the ramp from which the identified sample was taken. Thus, the claimed attenuation is part of a ramp-specific interference mitigation process based on the claimed estimated power variance. A reference that sets a sample to zero for reasons unrelated to the claimed ramp-specific estimated power variance does not teach or suggest attenuating the identified sample power magnitude to a level within the estimated power variance for the ramp from which the identified sample was taken.
Moreover, the asserted mathematical observation regarding zero does not supply the missing claim relationship. The dependent claims require more than the numerical fact that zero may be less than or equal to a nonnegative variance value. They require attenuation of the identified sample power magnitude to a level within the estimated power variance associated with the ramp from which that identified sample was taken. The rejection does not identify where Nakamura teaches or suggests using the claimed ramp-specific estimated power variance as the relevant attenuation bound, nor does Nakamura remedy the deficiencies in the relied-upon teachings of Nakanishi and Kojima regarding the ramp-based mean and variance calculations now expressly recited in the independent claims,” (from remarks pages 10-11).
As to point (A), Examiner respectfully disagrees. Applicant asserts that the combination of Nakanishi and Kojima do not teach the limitation of claims 6, 13 and 20 of “attenuating the identified sample power magnitude to a level within the estimated power variance of the power magnitudes of the ramp from which the identified sample was taken”. Examiner respectfully notes that the claims require estimating the power variance of the ramp. The claims further require that the identified sample be attenuated to a level within the estimated power variance of the ramp. Nothing further is required by the claims. Nakanishi teaches calculating the estimated power variance. Nakamura teaches setting the identified sample to zero, a value which mathematically guaranteed to be within the estimated power variance. Therefore, the combination of Nakanishi and Nakamura teach all limitations of claims 6, 13 and 20, and the rejection is maintained.
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 4, 11 and 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.
Claim 4 recites the limitation "the estimated power variance" in line 3. There is insufficient antecedent basis for this limitation in the claim. In parent claim 1 “an estimated power variance for the given ramp” is introduced in line 11. The “estimated power variance” of parent claim 3 is interpreted to have antecedent basis in the quoted section of claim 1. However, “the estimated power variance” of claim 4 is explicitly taught to be for multiple ramps, not for a single given ramp. Therefore, this “estimated power variance” of claim 4 must be different from those recited in claims 1 and 3, meaning that it lacks antecedent basis.
Claims 11 and 18 are analogous to claim 4 and are rejected for similar reasons.
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), as evidenced by Jansen et al. (US-20200072941-A1; hereinafter, Jansen).
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, using the mean power value for the given interval and the power magnitudes identified for all the time-domain ADC samples in the given interval, an estimated power variance for the given interval (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 the variance for a given ramp, calculating a mean power value, or adjusting the power magnitude of the identified samples.
Nakanishi teaches calculating the variance over a predetermined period or interval, but does not give specific teachings or embodiments about the length of this interval. Nakanishi further teaches transmitting ramps and receiving ramp echoes (see Fig. 2). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to set the predetermined period of Nakanishi to be for a ramp, as evidenced by Jansen, who teaches calculating a mean power value of a given ramp (see at least Fig. 8, block 304 and associated text in [0074]; “Then, at 304, the power is calculated for the current chirp from the high pass filtered samples for each chirp, as illustrated by block 376. For the current chirp, the power P for the lth chirp can be calculated from the k.sup.th high pass filtered sample, s.sub.filt…”. Examination of the equation in [0074] shows that it calculates the average power for the chirp). Thus, calculating statistical parameters over the length of a ramp is known in the art.
Furthermore, it would have been obvious to one of ordinary skill in light of the teachings of Nakanishi to calculate the mean power value over the same interval as the variance is calculated, because the mean value is required in calculations of variance. By definition, the formula for variance,
σ
2
=
1
N
∑
(
x
i
-
μ
)
2
, requires and includes the mean value, µ.
However, Nakanishi does not teach adjusting the power magnitude of the identified samples.
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, using the power magnitudes identified for all of the time-domain ADC samples in a given interval of the received radar signal, a mean power value of the given interval (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, using the mean power value for the given interval and the power magnitudes identified for all of the time-domain ADC samples in the given interval, an estimated power variance for 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. 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 interval (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’.”).
It would have been obvious for the interval to be a ramp for the reasons given regarding claim 1.
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 value 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 value for the interval 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 (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.
It would have been obvious for the interval to be a ramp for the reasons given regarding claim 1.
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 the variance for a given ramp, calculating a mean power value, or adjusting the power magnitude of the identified samples.
Nakanishi teaches calculating the variance over a predetermined period or interval, but does not give specific teachings or embodiments about the length of this interval. Nakanishi further teaches transmitting ramps and receiving ramp echoes (see Fig. 2). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to set the predetermined period of Nakanishi to be for a ramp, as evidenced by Jansen, who teaches calculating a mean power value of a given ramp (see at least Fig. 8, block 304 and associated text in [0074]; “Then, at 304, the power is calculated for the current chirp from the high pass filtered samples for each chirp, as illustrated by block 376. For the current chirp, the power P for the lth chirp can be calculated from the k.sup.th high pass filtered sample, s.sub.filt…”. Examination of the equation in [0074] shows that it calculates the average power for the chirp). Thus, calculating statistical parameters over the length of a ramp is known in the art.
Furthermore, it would have been obvious to one of ordinary skill in light of the teachings of Nakanishi to calculate the mean power value over the same interval as the variance is calculated, because the mean value is required in calculations of variance. By definition, the formula for variance,
σ
2
=
1
N
∑
(
x
i
-
μ
)
2
, requires and includes the mean value, µ.
However, Nakanishi does not teach adjusting the power magnitude of the identified samples.
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, using the power magnitude identified for all of the time-domain ADC samples in a given interval of the received radar signal, a mean power value for the given ramp (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. 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, using the mean power value for the given interval and the power magnitudes identified for all the time-domain ADC samples in the given interval, an estimated power variance for the given interval (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 the variance for a given ramp, calculating a mean power value, or adjusting the power magnitude of the identified samples.
Nakanishi teaches calculating the variance over a predetermined period or interval, but does not give specific teachings or embodiments about the length of this interval. Nakanishi further teaches transmitting ramps and receiving ramp echoes (see Fig. 2). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to set the predetermined period of Nakanishi to be for a ramp, as evidenced by Jansen, who teaches calculating a mean power value of a given ramp (see at least Fig. 8, block 304 and associated text in [0074]; “Then, at 304, the power is calculated for the current chirp from the high pass filtered samples for each chirp, as illustrated by block 376. For the current chirp, the power P for the lth chirp can be calculated from the k.sup.th high pass filtered sample, s.sub.filt…”. Examination of the equation in [0074] shows that it calculates the average power for the chirp). Thus, calculating statistical parameters over the length of a ramp is known in the art.
Furthermore, it would have been obvious to one of ordinary skill in light of the teachings of Nakanishi to calculate the mean power value over the same interval as the variance is calculated, because the mean value is required in calculations of variance. By definition, the formula for variance,
σ
2
=
1
N
∑
(
x
i
-
μ
)
2
, requires and includes the mean value, µ.
However, Nakanishi does not teach adjusting the power magnitude of the identified samples.
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, using the power magnitudes identified for all of the time-domain ADC samples in a given interval of the received radar signal, a mean power value of the given interval (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, using the mean power value for the given interval and the power magnitudes identified for all of the time-domain ADC samples in the given interval, an estimated power variance for 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. 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 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
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/ASHLEY BROWN RAYNAL/Examiner, Art Unit 3648
/OLUMIDE AJIBADE AKONAI/Primary Examiner, Art Unit 3648
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