Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on the following dates: 7/2/2023, 1/18/2025 and 7/16/2025 have been reconsidered by the examiner.
The information disclosure statement (IDS) submitted on the following date: 12/11/2025 has been considered by the examiner and initialed copy of the IDS is hereby attached.
Response to Arguments
Applicant’s arguments with respect to claims 1, 7 and 15 under 35 USC 102(a)(1) have been fully considered and are not deemed persuasive as thus:
Regarding claim 1, the Applicant asserts that Meissner fails to disclose: “Meissner fails to disclose or suggest determining a dispersion of a phase characteristic of the representation corresponding to a specified range bin, as in claim 1, particularly in combination with the other features recited in claim 1. As such, claim 1 is patentable over Meissner” However, Meissner, discloses: determine a frequency domain representation of the interference-corrupted combined signal (Meissner, para [0058], Prior to a more detailed explanation of various examples of approximation, the signal processing chain from the analog-digital conversion through to the range-Doppler analysis will be explained in detail based on the example block diagram from FIG. 12. FIG. 12 essentially illustrates the preprocessing of a radar data field Y[n, m] in the time domain prior to the transformation into the frequency domain in the course of the range-Doppler analysis) and (para [0066], One finding from the above analysis is that the scaling factor c used in the approximation is frequency-dependent. This applies regardless of the specific method used to calculate the approximation. The frequency in turn depends on the velocity of the radar target and is consequently a priori unknown. In order to be able to calculate the approximation (e.g. according to equation (8)), the velocity of the radar target would already have to be known, but this is not normally the case at this stage in the processing (before the Fourier transform). In order to solve this problem, according to the example implementations described here, the signal sequences y.sub.n[m] are split into a plurality of sub-bands using a filter bank for the purpose of calculating the approximation. This splitting (decomposition) provides a corresponding number of sub-band signal sequences y.sub.n,s[m], wherein s denotes the respective sub-band (s=1, 2, . . . ). A center frequency can be assigned to each sub-band. Adjacent sub-bands can adjoin or slightly overlap one another. The filters of the filter bank are normally designed in such a way that the upper limit frequency (cut-off frequency) of one sub-band is equal to the lower limit frequency of the next sub-band. Together, the sub-bands can cover the entire baseband (in relation to the slow time axis, e.g. the Doppler frequency domain) of the radar system. In one example implementation, the signal sequences sub-band signal sequences y.sub.n[m] are split in each case into sixteen sub-band signal sequences y.sub.n,s[m]. The specific number of sub-bands depends on the respective application and can also be smaller or larger than sixteen)
determine a dispersion of a phase characteristic of the representation corresponding to a specified range bin (Meissner, paras [0058] and [0066])
Regarding claims 7 and 15, the Applicant assertions have been fully considered and overcome the rejection on record.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-5, 7-9, and 11-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Meissner et al (US 20200191911 A1), hereinafter Meissner.
Regarding claim 1, Meissner discloses:
A radar system having a first transceiver unit (Meissner, para [0031], FIG. 5 illustrates in more detail an example implementation of a radar transceiver 1 according to the example from FIG. 3. In the present example, particularly the RF frontend 10 of the radar transceiver 1 and the RF frontend 10′ of a different (interfering) radar sensor 1′ are shown. It should be noted that FIG. 5 represents a simplified circuit diagram in order to indicate the basic structure of the RF frontend 10 with one transmit channel (TX channel) and one receive channel (RX channel). Actual implementations which may be highly dependent on the specific application are normally more complex and have a plurality of TX and/or RX channels),
the radar system to mitigate interference caused by a signal transmitted by a second transceiver unit of another radar system, the radar system comprising (Meissner, para [0005], A method is described below which can be used in a radar system. According to one example implementation, the method comprises providing a digital baseband signal using a radar receiver. The baseband signal comprises a plurality of segments, wherein each segment is assigned to a chirp of an emitted chirp sequence and each segment comprises a specific number of samples. For each signal sequence of n samples of the segments, where n in each case denotes a specific sample position within the respective segment, the method comprises the following: detecting interference-affected samples of the signal sequence; splitting the signal sequence into two or more sub-band signal sequences, wherein each sub-band signal sequence is assigned in each case to a frequency sub-band; replacing interference-affected samples in the two or more sub-band signal sequences in each case with a value which is based on adjacent samples in order to obtain corrected sub-band signal sequences; and determining a corrected signal sequence of n samples of the segments based on the corrected sub-band signal sequences) and (para [0012], FIG. 5 is a circuit diagram illustrating a simplified example of a radar transceiver, and also a further radar transceiver which causes interference):
the first transceiver unit to (Meissner, para [0012]):
transmit a first signal toward a target (Meissner, para [0014], FIG. 7 shows a time diagram of a transmit signal of a radar sensor and a transmit signal causing the interference (interfering signal) of a further radar sensor (interferer), wherein the signal characteristics (frequency over time) of these signals partially overlap one another.
[0015] FIG. 8 shows a time diagram of an example of a signal characteristic of a radar signal (following conversion into the baseband) which contains a radar echo from a radar target and an interfering signal (interference));
and receive an interference-corrupted combined signal including an echo signal from the, target in response to the transmitted first signal and a second signal transmitted by the second transceiver unit (Meissner, paras [0012] and [0014-0015]),
wherein the first transceiver unit and the second transceiver unit have corresponding transmit parameters (Meissner, para [0024], FIG. 2 illustrates by way of example the aforementioned frequency modulation of the signal s.sub.RF(t). As shown in FIG. 2 (upper diagram), the emitted RF signal s.sub.RF(t) is composed of a set of chirps, e.g. the signal s.sub.RF(t) comprises a sequence of sinusoidal signal characteristics (waveforms) with increasing frequency (up-chirp) or decreasing frequency (down-chirp). In the present example, the instantaneous frequency f(t) of a chirp increases beginning at a start frequency f.sub.START within a time period T.sub.RAMP linearly to a stop frequency f.sub.STOP (see lower diagram in FIG. 2). Such chirps are also referred to as linear frequency ramps. FIG. 2 shows three identical linear frequency ramps. It should be noted, however, that the parameters f.sub.START, f.sub.STOP, T.sub.RAMP as well as the pause between the individual frequency ramps may vary. The frequency variation also does not necessarily have to be linear (linear chirp). Depending on the implementation, transmit signals with exponential or hyperbolic frequency variation (exponential or hyperbolic chirps), for example, can also be used) Examiner notes transmit parameters may include chirp timing and waveform i.e. linear;
and a processor to detect synchronous interference in the interference-corrupted combined signal (Meissner, para [0024]),
the processor to (Meissner, para [0002], The present description relates to the field of radar sensors, and to signal processing methods used in radar sensors which enable a suppression of disruptive interference):
determine a frequency domain representation of the interference-corrupted combined signal (Meissner, paras(Meissner, para [0058], Prior to a more detailed explanation of various examples of approximation, the signal processing chain from the analog-digital conversion through to the range-Doppler analysis will be explained in detail based on the example block diagram from FIG. 12. FIG. 12 essentially illustrates the preprocessing of a radar data field Y[n, m] in the time domain prior to the transformation into the frequency domain in the course of the range-Doppler analysis) and (para [0066], One finding from the above analysis is that the scaling factor c used in the approximation is frequency-dependent. This applies regardless of the specific method used to calculate the approximation. The frequency in turn depends on the velocity of the radar target and is consequently a priori unknown. In order to be able to calculate the approximation (e.g. according to equation (8)), the velocity of the radar target would already have to be known, but this is not normally the case at this stage in the processing (before the Fourier transform). In order to solve this problem, according to the example implementations described here, the signal sequences y.sub.n[m] are split into a plurality of sub-bands using a filter bank for the purpose of calculating the approximation. This splitting (decomposition) provides a corresponding number of sub-band signal sequences y.sub.n,s[m], wherein s denotes the respective sub-band (s=1, 2, . . . ). A center frequency can be assigned to each sub-band. Adjacent sub-bands can adjoin or slightly overlap one another. The filters of the filter bank are normally designed in such a way that the upper limit frequency (cut-off frequency) of one sub-band is equal to the lower limit frequency of the next sub-band. Together, the sub-bands can cover the entire baseband (in relation to the slow time axis, e.g. the Doppler frequency domain) of the radar system. In one example implementation, the signal sequences sub-band signal sequences y.sub.n[m] are split in each case into sixteen sub-band signal sequences y.sub.n,s[m]. The specific number of sub-bands depends on the respective application and can also be smaller or larger than sixteen);
determine a dispersion of a phase characteristic of the representation corresponding to a specified range bin (Meissner, para [0046], In a first step, a first FFT (normally referred to as a range FFT) is applied to each chirp. The Fourier transform is calculated for each column of the field Y[n, m]. In other words, the field Y[n, m] is Fourier-transformed along the fast time access, and a two-dimensional field R[k, m] of spectra, referred to as a range map, is obtained as a result, wherein each of the M columns of the range map in each case contains N (complex-value) spectral values. The “fast” time axis becomes the frequency axis due to the Fourier transform; the row index k of the range map R[k, m] corresponds to a discrete frequency and is therefore also referred to as a frequency bin. Each discrete frequency corresponds to a range according to equation (4), and for this reason the frequency axis is also referred to as the range axis) and (para [0054]), Examiner notes that FFT across the samples of each chirp yields range bins and helps with the identification of synchronous interference;
and based on the dispersion, assign the specified range bin as exhibiting synchronous interference (Meissner, para [0057], The approaches described below for suppressing the interference-induced disturbances aim to replace the individual samples which have been defined as errored (corrupted) in the signal sequences y.sub.n[m] of a radar data field (for n=0, . . . , N−1) with an approximation of the “true” value. This approximation can be calculated e.g. using interpolation based on the (e.g. immediately) adjacent samples. The chirps in which interference-induced disturbances occur are identified before the aforementioned approximation, which can be achieved, for example, using a comparison with a threshold value. The result of this identification is a list of indices of chirps with errored samples, in the example from FIG. 11 this is e.g. {m.sub.0, m.sub.1, m.sub.2, m.sub.3, m.sub.4, m.sub.5, m.sub.6, m.sub.7, m.sub.8, m.sub.9 } plus the associated index values on the fast time axis) and (paras [0058] and [0066]) Examiner notes that synchronous interference corresponds with the range bins.
Regarding claim 2, Meissner discloses:
the radar system of claim 1 (Meissner, paras [0014-0015]),
wherein to, based on the dispersion, assign the specified range bin as exhibiting synchronous interference (Meissner, para [0057]),
the processor is further to (Meissner, para [0002]):
compare the dispersion to a threshold (Meissner, para [0005]), Examiner notes that within the mitigation interference system that comparison of dispersion to a threshold is an essential aspect in order for said system to actively detect and mitigate interference; otherwise, there would not be the ability to distinguish between a true target return to distorted reflection.
Regarding claim 3, Meissner discloses:
the radar system of claim 1 (Meissner, paras [0012] and [0014-0015]),
the processor further to (Meissner, para [0002]):
determine multiple metrics of the phase characteristic of the representation corresponding to a specified range bin (Meissner, para [0039], As previously explained with reference to FIG. 6, a chirp sequence comprises a plurality of chirps; in the present case, the number of chirps of a sequence is denoted M. Depending on the application, a sequence can also contain chirps with different parameters (start frequency and stop frequency, duration and modulation pause). During a modulation pause between two consecutive chirps, the frequency may, for example, be equal to the stop frequency of the preceding chirp or the start frequency of the following chirp (or equal to a different frequency). The chip duration can be in the range from a few microseconds to a few milliseconds, for example in the range from 20 μs to 2 ms. The actual values may be greater or smaller, depending on the application. The number M of chirps in a sequence can correspond to a power of two, e.g. M=256), Examiner interprets the counting of the number of chirps in a burst that have power above a threshold may be considered metrics related to phase characteristics.
Regarding claim 4, Meissner discloses:
the radar system of claim 1 (Meissner, paras [0014-0015]),
the processor further to (Meissner, para [0002]):
determine multiple dispersions of the phase characteristic of the representation corresponding to multiple range bins (Meissner, para [0055], FIG. 11 illustrates, similarly in a contour plot, the impact of interference-induced disturbances (interference bursts), such as those shown e.g. in FIGS. 7 and 8, in the radar data field Y[n, m]. If a specific chirp is examined, e.g. the chirp with the index m=m.sub.8, groups with a plurality of consecutive samples (e.g. in the index range from n.sub.0 to n.sub.1) along the fast access may then be errored (corrupted) due to the aforementioned interference-induced disturbances, wherein the amount (magnitude) of the errored samples concerned is normally significantly higher than the amount of the samples not affected by interference) Examiner interprets interference bursts as high phase dispersions.
Regarding claim 5, Meissner discloses:
the radar system of claim 1 (Meissner, paras [0014-0015]),
wherein the dispersion includes a standard deviation (Meissner, paras [0055]) and (para [0062], The function block 43 represents the suppression/elimination of the interference-induced disturbances (interference mitigation) using approximation of the (unknown) true value. In other words, the samples y.sub.n[i] identified as errored are replaced with an approximation y.sub.n′[i] (for all i∈I, see equation (6)). As mentioned, this interference suppression is carried out for each signal sequence y.sub.n[m] (e.g., for n=0, . . . , N−1). The resulting corrected signal sequences y.sub.n'[m] form the corrected radar data field Y′[n, m] on the basis of which, for example, a range-Doppler analysis (function block 44) can then be carried out for the detection of radar targets), Examiner interprets errored samples as standard deviation
Regarding claim 6, Miessner discloses:
the radar system of claim 1 (Meissner, paras [0014-0015]),
wherein the frequency domain representation includes a discrete Fourier Transform representation (FFT) (Miessner, para [0045], According to one example implementation, the calculation of a range-Doppler map comprises two steps, wherein a plurality of Fourier transforms are calculated in each step (e.g. using an FFT algorithm). According to the present example, the baseband signal y(t) (cf. FIG. 5) is sampled in such a way that, for a chirp sequence with M chirps, N×M sampling values (samples) are obtained, e.g. M segments, each having N samples. This means that the sampling time interval T.sub.SAMPLE is selected in such a way that each of the M segments (chirp echoes in the baseband) is represented by a sequence of N samples. As shown in diagram (c) in FIG. 9, these M segments can each be arranged into N samples in a two-dimensional field (array) Y[n, m] (radar data field). Each column of each field Y[n, m] represents one of the M considered segments of the baseband signal y(t), and the n-th row of the field Y[n, m] contains the n-th sample of the M chirps. The row index n (n=0, 1, . . . N−1) can therefore be considered as a discrete time n.Math.T.sub.SAMPLE (within a chirp) on a “fast” time axis. The column index m (m=0, 1, . . . M−1) can equally be considered as a discrete time m.Math.T.sub.CHIRP on a “slow” time axis. The column index m corresponds to the number of chirps in a chirp sequence) .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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 7-9 and 11-19 are rejected under 35 U.S.C. 103 as being unpatentable over Meissner et al (US 20200191911 A1), hereinafter Meissner in view of Amihood et al (US 20210190902 A1), hereinafter Amihood.
Regarding claim 7, Meissner discloses:
a radar system having a first transceiver unit, the radar system to mitigate interference caused by a signal transmitted by a second transceiver unit of another radar system, the radar system comprising (Meissner, paras [0005] and [0012]):
the first transceiver unit to (Meissner, paras [0014-0015]):
transmit a first signal toward a target (Meissner, paras [0014-0015]);
and receive an interference-corrupted combined signal including an echo signal from the target in response to the transmitted signal and a second signal transmitted by the second transceiver unit (Meissner, paras [0012] and [0014-0015]),
wherein the first transceiver unit and the second transceiver unit have non-identical transmit parameters (Meissner, para [0023], FIG. 1 illustrates in a schematic diagram the use of a frequency-modulated continuous-wave radar system, usually referred to as an FMCW radar system, as a sensor for measuring ranges and velocities of objects which are normally referred to as radar targets. In the present example, the radar device 1 has separate transmit (TX) and receive (RX) antennas 5 or 6 (bistatic or pseudo-monostatic radar configuration). It should be noted, however, that one or more antennas can also be used which simultaneously serve as transmit antennas and receive antennas (monostatic radar configuration). In the present example, the transmit antenna 5 emits a continuous radio-frequency (RF) signal s.sub.RF(t) which is frequency-modulated, for example, with a type of sawtooth signal (periodic, linear frequency ramp). In some implementations, the RF signal is within the frequency band between 76 and 81 GHz. The emitted signal s.sub.RF(t) is backscattered at the radar target T and the backscattered/reflected signal y.sub.RF(t) is received by the receive antenna 6. FIG. 1 shows a simplified example; in practice, radar sensors are systems equipped with a plurality of transmit (TX) and receive (RX) channels in order to be able also to define the Direction of Arrival (DoA) of the backscattered/reflected signal y.sub.RF(t) and thus locate the radar target T more precisely) Examiner notes that FMCW relates to non-identical parameters in that the waveform aids with differentiating signals across transmitters;
and a processor to mitigate asynchronous interference in the interference corrupted combined signal, the processor to (Meissner, para [0037, p.4, lines 10-19], In the present example, the interference occurs three times during the chip duration of 60 μs, e.g. at approximately 7 μs, 28 μs and 42 μs. As mentioned, the power of the interfering signal may be higher than the power of the radar echoes from real targets. Furthermore, apart from the exceptions not considered here, the interfering signals and the transmit signal of the considered radar sensor 1 are uncorrelated and for this reason the interference can be regarded as noise (in the sense of a broadband interference) and thus increases the noise floor) and (para [0054], Various techniques are known for detecting interference. These techniques make it possible to detect that a measurement has been affected by interference and the measurement results are therefore unreliable. Other approaches aim to suppress the noise signals or reduce them using filter techniques. The example implementations described below relate to a possible approach for suppressing interfering signal components (cf. equation (3)), signal y.sub.RF,I(t) using a special filter technique already in the time domain (e.g. before a Fourier transform into the frequency domain is performed) and (para [0055]), Examiner interprets the uncorrelated and burst interference are alternative terms used to describe asynchronous:
determine whether interference is present in a time-domain representation of the interference-corrupted combined signal (Meissner, paras [0023] and [0055]), Examiner notes that FMCW radar transmits a chirp signal over time, and interference burst may be considered a combined signal due to an overlap of the desired signal (i.e. chirp) and composite (i.e. noise, jammed, etc.) signal as an example of time-domain representation;
;
Amihood discloses:
suppress samples corresponding to the interference to create a masked signal from a mask (M) (Amihood, para [0024], Due to the vibrations, the radar system observes one or more interference artifacts within a received radar signal. To the radar system, the interference artifact can appear to be one or more moving objects. It can be challenging for the radar system to distinguish between an object of interest (e.g., a desired object) within the external environment and the interference artifact. As such, the radar system may generate one or more false detections based on the interference artifact, which increases the radar system's false-alarm rate and degrades the performance of the radar system. Sometimes the interference artifact can mask the desired object and prevent the radar system from detecting the object.
[0025] In other cases, the radar system observes objects that are vibrating. These objects can be internal or external to the electronic device. Sometimes multipath causes the radar system to observe an interference artifact associated with the vibrating object at a range that is farther than the range to the vibrating object. The interference artifact associated with the vibrating object can similarly result in a false detection and mask other desired objects);
and construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M) (Amihood, para [0029], Symmetric Doppler interference mitigation exploits the symmetric amplitude contributions of the interference artifact across the Doppler spectrum to attenuate the interference artifact. This filtering operation incorporates the interference artifact within the noise floor, without significantly attenuating reflections from the desired object. Symmetric Doppler interference mitigation can be performed on each radar frame (e.g., each chirp) without a priori knowledge about the frequency or amplitude of the vibration. In this way, the radar system can filter interference artifacts that are generated from a variety of different types of vibrations. An ability of the symmetric Doppler interference mitigation to attenuate the interference artifact is also independent of the Doppler sampling frequency and whether or not aliasing occurs. By filtering the interference artifacts, the radar system produces fewer false detections in the presence of vibrations and can detect objects that would otherwise be masked by the interference artifact)
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify Meissner with Amihood to incorporate the features of: suppress samples corresponding to the interference to create a masked signal from a mask (M), and construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M) . Both arts are considered analogous arts as they both disclose signal interference, frequency-domain and time-domain representation and dispersion; however, Meissner fails to disclose suppress samples corresponding to the interference to create a masked signal from a mask (M), and construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M) as disclosed by Amihood. The modification would render the predictable results improved reduction of interference power, improved detection performance, improved effective signal-to-noise ratio, and improved clutter/interference separation.
Regarding claim 8, Meissner discloses:
the radar system of claim 7 (Meissner, paras [0012] and [0014-0015]),
wherein to determine whether the interference is present in the time-domain representation of the combined signal, the processor further to (Meissner, paras [0044], In the examples shown here, the calculations for determining range-Doppler maps are carried out by a digital computing unit, such as e.g. a signal processor (cf. FIG. 5, DSP 40). In other example implementations, other computing units can also be used additionally or alternatively to a signal processor in order to carry out the calculations. Depending on the implementation, calculations can be carried out by various software and hardware entities or combinations thereof. The term computing unit can typically be understood to mean any combination of software and hardware which is able and designed to carry out the calculations described in connection with the example implementations explained here) and (para [0055]), Examiner interprets FMCW radar that transmits a chirp signal over time, and interference burst may be considered a combined signal due to an overlap of the desired signal (i.e. chirp):
based on an amplitude of the frequency-domain representation of the combined signal (Meissner, paras [0054-0055] and [0060], A detection algorithm is applied to the radar data field Y[n, m] in order to identify samples which are corrupted, e.g. due to interference-induced disturbances. As already mentioned, these corrupted samples can be detected using a comparison with a threshold value, e.g. a specific sample is detected as corrupted if its magnitude |Y[n, m]| or its energy or a different suitable criterion exceeds a specific threshold value. The energy of a sample can be represented e.g. by Y[n, m].sup.2.) Examiner interprets energy used to describe amplitude (i.e. signal strength) as frequency-domain representation,
assign a time interval as exhibiting asynchronous interference (Meissner, paras [0054-0055] and [0060])
Regarding claim 9, Meissner discloses:
the radar system of claim 7 (Meissner, paras [0012] and [0014-0015]),
the processor further to (Meissner, para [0002]):
assign zero values in the time domain to the samples corresponding to the interference (Meissner, para [0057]).
Amihood discloses:
wherein to suppress samples corresponding to the interference to create a masked signal (Amihood, paras [0024-0025]).
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify Meissner with Amihood to incorporate the features of: wherein to suppress samples corresponding to the interference to create a masked signal. Both arts are considered analogous arts as they both disclose signal interference, frequency-domain and time-domain representation and dispersion; however, Meissner fails to disclose suppress samples corresponding to the interference to create a masked signal from a mask (M), and construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M) as disclosed by Amihood. The modification would render the predictable results improved reduction of interference power, improved detection performance, improved effective signal-to-noise ratio, and improved clutter/interference separation.
Regarding claim 11, Meissner discloses:
the radar system of claim 7 (Meissner, paras [0012] and [0014-0015]),
the processor further to downweight values, in the time domain to the samples corresponding to the interference (Meissner, paras [0002]) and (para [0066], One finding from the above analysis is that the scaling factor c used in the approximation is frequency-dependent. This applies regardless of the specific method used to calculate the approximation. The frequency in turn depends on the velocity of the radar target and is consequently a priori unknown. In order to be able to calculate the approximation (e.g. according to equation (8)), the velocity of the radar target would already have to be known, but this is not normally the case at this stage in the processing (before the Fourier transform). In order to solve this problem, according to the example implementations described here, the signal sequences y.sub.n[m] are split into a plurality of sub-bands using a filter bank for the purpose of calculating the approximation. This splitting (decomposition) provides a corresponding number of sub-band signal sequences y.sub.n,s[m], wherein s denotes the respective sub-band (s=1, 2, . . . ). A center frequency can be assigned to each sub-band. Adjacent sub-bands can adjoin or slightly overlap one another. The filters of the filter bank are normally designed in such a way that the upper limit frequency (cut-off frequency) of one sub-band is equal to the lower limit frequency of the next sub-band. Together, the sub-bands can cover the entire baseband (in relation to the slow time axis, e.g. the Doppler frequency domain) of the radar system. In one example implementation, the signal sequences sub-band signal sequences y.sub.n[m] are split in each case into sixteen sub-band signal sequences y.sub.n,s[m]. The specific number of sub-bands depends on the respective application and can also be smaller or larger than sixteen) Examiner notes that a filter bank breaks down a signal into multiple frequency sub-bands.
Amihood discloses:
wherein to suppress samples corresponding to the interference to create a masked signal (Amihood, paras [0024-0025]).
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify Meissner with Amihood to incorporate the features of: wherein to suppress samples corresponding to the interference to create a masked signal. Both arts are considered analogous arts as they both disclose signal interference, frequency-domain and time-domain representation and dispersion; however, Meissner fails to disclose suppress samples corresponding to the interference to create a masked signal from a mask (M). The modification would render the predictable results improved reduction of interference power, improved detection performance, improved effective signal-to-noise ratio, and improved clutter/interference separation.
Regarding claim 12, Meissner discloses:
the radar system of claim 7 (Meissner, paras [0012] and [0014-0015]),
the processor to perform a 2-dimensional Fast Fourier Transform (Meissner, para [0046]).
Regarding claim 13, Meissner discloses:
the radar system of claim 7 (Meissner, paras [0012] and [0014-0015]),
the processor to perform a 1-dimensional Fast Fourier Transform (Meissner, para [0046]).
Regarding claim 14, Meissner discloses:
the radar system of claim 7 (Meissner, paras [0012] and [0014-0015]),
wherein the first transceiver unit includes a first receive channel and a second receive channel, the processor further to (Meissner, paras [0002] and [0044]):
initialize a candidate-corrected frequency-domain representation (X) of the interference- corrupted combined signal of the first receive channel using a signal from the second receive channel (Meissner, para [0046], In a first step, a first FFT (normally referred to as a range FFT) is applied to each chirp. The Fourier transform is calculated for each column of the field Y[n, m]. In other words, the field Y[n, m] is Fourier-transformed along the fast time access, and a two-dimensional field R[k, m] of spectra, referred to as a range map, is obtained as a result, wherein each of the M columns of the range map in each case contains N (complex-value) spectral values. The “fast” time axis becomes the frequency axis due to the Fourier transform; the row index k of the range map R[k, m] corresponds to a discrete frequency and is therefore also referred to as a frequency bin. Each discrete frequency corresponds to a range according to equation (4), and for this reason the frequency axis is also referred to as the range axis) and (para [0053], As with all measurement data, the spectral values in a range map or a range-Doppler map contain noise. The detectability of the aforementioned local maxima and the reliability of the detection depend on the noise floor of the radar system. Various noise sources can contribute to the noise floor, in particular the phase noise of the local oscillator (see FIG. 4, LO 101). The interference effects discussed above due to other, interfering radar sensors can have a negative impact on the detection of radar targets and on the robustness and reliability of the measurement results. The aforementioned interference can increase the noise floor at least temporarily to such an extent that a detection of radar targets becomes impossible or at least susceptible to error) Examiner interprets spectral values as frequency domain representation).
Regarding claim 15, Meissner discloses:
a radar system having a first transceiver unit (Meissner, Fig. 5, transceiver 1, para [0031]),
the radar system to mitigate interference caused by a signal transmitted by a second transceiver unit of another radar system, the radar system comprising (Meissner, para [0005]):
the first transceiver unit to (Meissner, para [0031]):
transmit a first signal toward a target (Meissner, para [0023], FIG. 1 illustrates in a schematic diagram the use of a frequency-modulated continuous-wave radar system, usually referred to as an FMCW radar system, as a sensor for measuring ranges and velocities of objects which are normally referred to as radar targets. In the present example, the radar device 1 has separate transmit (TX) and receive (RX) antennas 5 or 6 (bistatic or pseudo-monostatic radar configuration). It should be noted, however, that one or more antennas can also be used which simultaneously serve as transmit antennas and receive antennas (monostatic radar configuration). In the present example, the transmit antenna 5 emits a continuous radio-frequency (RF) signal s.sub.RF(t) which is frequency-modulated, for example, with a type of sawtooth signal (periodic, linear frequency ramp). In some implementations, the RF signal is within the frequency band between 76 and 81 GHz. The emitted signal s.sub.RF(t) is backscattered at the radar target T and the backscattered/reflected signal y.sub.RF(t) is received by the receive antenna 6. FIG. 1 shows a simplified example; in practice, radar sensors are systems equipped with a plurality of transmit (TX) and receive (RX) channels in order to be able also to define the Direction of Arrival (DoA) of the backscattered/reflected signal y.sub.RF(t) and thus locate the radar target T more precisely);
and receive an interference-corrupted combined signal including an echo signal from the target in response to the transmitted first signal and a second signal transmitted by the second transceiver unit (Meissner, Fig. 7, paras [0014-0015]);
and a processor to detect synchronous interference in the combined signal (Meissner, paras [0024] and [0057]),
the processor to (Meissner, paras [0002] and [0044]):
determine a frequency domain representation of the combined signal (Meissner, paras [0054-0055]);
determine a dispersion of a phase characteristic of the representation corresponding to a specified range bin (Meissner, paras [0046] and [0054]);
and based on the dispersion, assign the specified range bin as exhibiting synchronous interference (Meissner, paras [0024] and [0057]);
the processor to mitigate asynchronous interference in the interference corrupted combined signal, the processor to (Meissner, paras [0037] and [0055]):
determine whether interference is present in a time-domain representation of the interference-corrupted combined signal (Meissner, paras [0055] and[0057]),
(Meissner, paras [0054] and[0062]).
Amihood discloses:
suppress samples corresponding to the interference to create a masked signal from a mask (M) (Amihood, paras [0024-0025]),
and construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M) (Amihood, para [0029])
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify Meissner with Amihood to incorporate the features of: wherein to suppress samples corresponding to the interference to create a masked signal. Both arts are considered analogous arts as they both disclose signal interference, frequency-domain and time-domain representation and dispersion; however, Meissner fails to disclose suppress samples corresponding to the interference to create a masked signal from a mask (M), and construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M) as disclosed by Amihood. The modification would render the predictable results improved reduction of interference power, improved detection performance, improved effective signal-to-noise ratio, and improved clutter/interference separation.
Claim 16 is rejected under the same analysis as claim 2.
Claim 17 is rejected under the same analysis as claim 5.
Claim 18 is rejected under the same analysis as claim 8.
Claim 19 is rejected under the same analysis as claim 9.
Claims 10 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Meissner et al (US 20200191911 A1), hereinafter Meissner in view of Amihood et al (US 20210190902 A1), hereinafter Amihood in further view of Stettiner et al (US 20210156982 A1), hereinafter, Stettiner.
Regarding claim 10, Meissner discloses:
the radar system of claim 7 (Meissner, paras [0012] and [0014-0015]),
wherein to construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M),
minimize a difference between a masked candidate corrected frequency-domain representation (X) of the interference-corrupted combined signal and the masked interference- corrupted corrected time-domain representation of the combined signal (Y) by applying a sparsity regularizer
Amihood discloses:
wherein to construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M) (Amihood, para [0029]),
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify Meissner with Amihood to incorporate the features of: wherein to construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M). Both arts are considered analogous arts as they both disclose signal interference, frequency-domain and time-domain representation and dispersion; however, Meissner fails to disclose wherein to construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M). The modification would render the predictable results improved reduction of interference power, improved detection performance, improved effective signal-to-noise ratio, and improved clutter/interference separation. However, the combination of Meissner and Amihood fails to disclose: minimize a difference between a masked candidate corrected frequency-domain representation (X) of the interference-corrupted combined signal and the masked interference- corrupted corrected time-domain representation of the combined signal (Y) by applying a sparsity regularizer
Stettiner discloses:
minimize a difference between a masked candidate corrected frequency-domain representation (X) of the interference-corrupted combined signal and the masked interference- corrupted corrected time-domain representation of the combined signal (Y) by applying a sparsity regularizer (Stettiner, paras [0164], A model for 3D random sparse sampling will now be provided. Note this model can be extended to 4D without difficulty. A simplified 3D version of the problem is presented, assuming the dimensions of the radar image are range, doppler and elevation, and subsampling is done only on the range and elevation dimensions); (para [0167], For this case the signal precisely matches the DFT frequencies thus the transform of the rectangular window function is sampled at the nulls and at other frequencies outside the target frequency to obtain noise, proportional to number of pulses. [0168] In general, the 3D random sparse sampling can be approximated as follows where [AltContent: rect].sub.3 is a three dimensional fourier transform:
PNG
media_image1.png
59
340
media_image1.png
Greyscale
PNG
media_image2.png
160
341
media_image2.png
Greyscale
Examiner notes that this is done within a range-Doppler map system wherein the two domains relate to time and frequency. Additionally, Discrete Fourier Transform (DFT) in minimizing the differences between the time and frequencies domains.
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify the combination of Meissner and Amihood with Stettiner to incorporate the features of: minimize a difference between a masked candidate corrected frequency-domain representation (X) of the interference-corrupted combined signal and the masked interference- corrupted corrected time-domain representation of the combined signal (Y) by applying a sparsity regularizer. The three arts disclose signal interference, frequency-domain and time-domain representation and dispersion; however, Meissner fails to disclose wherein to construct a corrected frequency-domain representation (X*) of the interference-corrupted combined signal using the time-domain representation of the interference-corrupted combined signal (Y) and using the mask (M). The combination of Meissner and Amihood fails to disclose: minimize a difference between a masked candidate corrected frequency-domain representation (X) of the interference-corrupted combined signal and the masked interference- corrupted corrected time-domain representation of the combined signal (Y) by applying a sparsity regularizer. The modification would render the predictable results of the sparsity constraints leading more interpretable, less noisy and focused signals, and there may be improved signal recovery when interference may not be as evident in both the time and frequency domains.
Claim 20 is rejected under the same analysis as claim 10.
References Cited But Not Relied Upon
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure as thus:
Meissner at al US 20200124699 A1 discloses an FMCW radar with interference signal suppression (Abstract)
Kelly et al US 20060125682 A1 discloses a radar return signal processing method for detecting a vehicle processing time samples to detect interference signals in samples
Kirsch et al US 20240036183 A1 discloses a radar method for phase-coherent analysis and a plurality of superimposed interference-afflicted (received) signals (para [0043]), sparse asymptotic minimum variance technique para [0045])
Gottinger et al US 20220404456 A1 discloses a method for reducing interference effects in radar system (Abstract)
Gulden et al US 20220334217 A1 discloses interference variables such as phase noise, nonlinearities, time offset and unknown starting phases (para [0006])
Bayram US 20220087618 A1 discloses decomposition of composite signals (Abstract)
Himmelstoss et al US 20150168539 A1 discloses an FMCW radar system and interference recognition method for FMCW radar systems (Abstract)
Dobrev et al US 20190107614 A1 discloses a radar system comprising a plurality of transceivers considered to be asynchronous (non-synchronized) (para [0021]), and holography interference (paras [0026-0027])
Schuman et al US 20230059452 A1 discloses an airborne look-down radar system
Himmelstoss et al US 20150168539 A1 discloses an FMCW radar system and interference recognition method
Levitan et al US 20210278521 A1 discloses a radar system and range-doppler maps wherein rows correspond with range-bins, weaker targets are masked, and interference suppression
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KIMBERLY JENKINS whose telephone number is (571)272-0404. The examiner can normally be reached Monday - Friday 8a-5p EST.
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 517.270.5144. 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.
/KIMBERLY JENKINS/ Examiner, Art Unit 3648
/VLADIMIR MAGLOIRE/ Supervisory Patent Examiner, Art Unit 3648