DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
The action is in reply to the amendment received on May 14th, 2024.
Claims 1-20 are currently pending and have been examined.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. KR10-2023-0039751, filed on March 27th, 2023.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on March 18th, 2024 has been considered by the examiner and an initialed copy of the IDS is hereby attached.
Specification
Applicants’ amendments to the specification filed May 14th, 2026, with respect to informalities indicated in the previous office action, have been fully considered and are acceptable. The objection to the specification has been rescinded.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 4-10, 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over Schiffmann et al. (US 10114106 B2), hereinafter Schiffman, in view of van Meurs (US 2022026887 A1), hereinafter Meurs.
Regarding claim 1, Schiffmann discloses [Note: What Schiffmann fails to clearly disclose is strike-through]
1. A radar device comprising (See Figs. 1 and 3, further column 1 lines 28 “In accordance with one embodiment, a radar system”): and
one or more processors (Fig. 1, further column 3 lines 62 – 65 “The system 10 also includes a controller 34 in communication with the radar-sensor 14 and the speed-sensor 30. The controller 34 may include a processor (not specifically shown) such as a microprocessor or other control circuitry”)
memory configured to store instructions which, when executed by the one or more processors, cause the one or more processors to perform operations (Column 3, line 65 through Column 4 line 7 “The controller 34 may include memory (not specifically shown), including non-volatile memory, such as electrically erasable programmable read-only memory (EEPROM) for storing one or more routines, thresholds, and captured data. The one or more routines may be executed by the processor to perform steps for determining error correction factors or offsets to auto-align the radar-sensor 14 based on signals received by the controller 34 as described herein.”) comprising:
detect stationary objects (Column 2, lines 27-30 “The auto-alignment algorithm described herein is for use on a host-vehicle as it observes or tracks stationary objects or targets as the host-vehicle travels along a road.”);
determine a relative speed of each of the stationary objects with respect to the host vehicle (Fig. 1, Item 22, further Column 3 lines 25-28 “The radar-sensor 14 is operable to determine or measure various values or variable from the returned radar-signal reflected by the objects 20 including, but not limited to, a measured-range-rate 22 (dRm)”);
determine a speed of the host vehicle by using a sensor of the host vehicle (Figure 1, item 32, Column “The system also includes a speed-sensor used to indicate or determine a measured-speed (Sm) of the host-vehicle”) ;
(Schiffmann teaches an algorithm by which the difference between vehicle sensor speed and measured relative speeds of the surrounding stationary objects are formulated into a least-squares problem to solve for said coefficients, see Eq. 1, Eq. 2, Eq. 5. Further, Column 6 lines 6-11 “As noted above, relative motion between the radar-sensor and stationary targets is necessary, hence the actual-longitudinal speed of the radar-sensor is assumed to be nonzero. Combining Eqs. 1-4 produces Eq. 5, from which the errors Bs, Ba, and Be can be determined using… “. Here, Ba and Be are defined to be the azimuthal and elevation angle alignment errors respectively.; and
determine an angle for compensating for misalignment of the radar device using the linear regression coefficient of the speed sensor errors and compensate an angle of a target using the angle determined using the linear regression coefficient of the speed sensor errors. (Column 7, lines 43-44 “For the Q. 10, a least squares problem leading to a batch solution could take the form of Eq. 18, where...”. The constants Ba and Be as cited in the previous limitation are the desired compensation angles.)
Meurs discloses,
determine whether a host vehicle is driving in a straight line (Paragraph 0057 “ In order to reduce the chances of outliers due to non-straight vehicle travel, buffering of the K sensor heading estimations can be triggered using an external trigger signal. The external trigger signal can be provided by, for example, a sensor determining when the steering wheels of the vehicle are straight, or near straight, or a signal provided during a factory-environment calibration process. “);
It would have been obvious to someone with ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the features as disclosed by Meurs into the invention of Schiffmann. Both Meurs and Schiffmann are considered analogous arts to the claimed invention as they disclose a device and method for the correction of a radar device misalignment, where the relative velocities of nearby stationary objects as measured by the radar device are used as inputs. Schiffmann states (Column 9, lines 1-5) “The auto-alignment algorithm is most accurate when run under conditions where the lateral and vertical components of relative-to-Earth velocity of the radar-sensor are nearly zero. Thus, ideal conditions are a straight trajectory on smooth asphalt.” The combination of Schiffmann and Meurs would be obvious with a reasonable expectation of success in order to ensure that the vehicle is traveling in a straight line before performing the alignment correction described in Schiffmann.
Regarding claim 4, Schiffmann discloses
The radar device of claim 1, wherein the one or more processors are configured to determine the speed sensor errors for the estimation angles of the stationary objects by calculating a difference between an absolute value of a velocity component in a driving direction of the host vehicle among relative velocity vectors of the stationary objects and an absolute value of the speed of the host vehicle (Column 6 lines 52-55, “To solve Eq. 5, the following signals or values are needed: A) Radar measurements dRm(i), Am(i) and Em(i), which are provided by radar-sensor, and B) Host velocity components Um(i) and Vm(i)” Column 5 lines 13-29: Here, dRm(i) is defined as the measured range-rate of the i-th object detected, Am(i) is the measured azimuthal angle of the i-th object detected, Em(i) is the measured elevation angle of the i-th object detection, Um(i) is the measured longitudinal velocity of the vehicle, and Vm(i) is the measured vertical velocity of the vehicle.).
Regarding claim 5, Schiffmann discloses
The radar device of claim 1, wherein the one or more processors are configured to determine a coefficient representing reliability of the linear regression coefficient,
wherein the linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects is determined if the coefficient representing the reliability of the linear regression coefficient is equal to or greater than a threshold coefficient (A specific coefficient based on the least-squares minimization problems is discussed to determine confidence in the estimation. Column 9, lines 29-40 “The algorithm 18 described herein is most useful if it includes a confidence indication, in addition to the miss-alignment estimates. This confidence indicator signals to the consumer of the miss-alignment estimates whether or not they are ready to be used and trusted. The algorithm generally will start out by providing somewhat erroneous estimates of the desired quantities, but the error in the estimates should rapidly decrease to a steady-state level. Once this steady-state level is achieved, the algorithm should signal high confidence in the estimates. If something goes wrong and the estimates don't appear to be converging to useful values, then a low confidence should be signaled”.)
Regarding claim 6, Schiffmann discloses
The radar device of claim 5, wherein the estimation angles of the stationary objects are estimated azimuths (Fig. 1, Column 2, lines 25 – 30 , “The radar-sensor 14 is operable to determine or measure various values or variable from the returned radar-signal reflected by the objects 20 including, but not limited to, a measured-range-rate 22 (dRm), a measured-azimuth-angle 24 (Am), and a measured-elevation-angle 26 (Em) to the objects.”), and the angle for compensating for the misalignment of the radar device is a compensation value for the estimated azimuths of the target (Eq. 1, Column 5 lines 35-38 “Ba: bias error in measured azimuth angle, i.e. the azimuth-misalignment 38; Be: bias error in measured elevation angle, i.e. the elevation-misalignment”).
Regarding claim 7, Schiffmann discloses
The radar device of claim 5, wherein the estimation angles of the stationary objects are estimated elevation angles, and the angle compensating for the misalignment of the radar device is a compensation value for the estimated elevation angles of the target (Eq. 1, Column 5 lines 35-38 “Ba: bias error in measured azimuth angle, i.e. the azimuth-misalignment 38; Be: bias error in measured elevation angle, i.e. the elevation-misalignment”).
Regarding claim 8, Schiffmann discloses [Note: What Schiffmann fails to clearly disclose is strike-through]
The radar device of claim 1, ;
Meurs discloses,
wherein the one or more processors are configured to determine whether the host vehicle is driving in the straight line based on a yaw rate of the host vehicle (Paragraph 0057 “ In order to reduce the chances of outliers due to non-straight vehicle travel, buffering of the K sensor heading estimations can be triggered using an external trigger signal. The external trigger signal can be provided by, for example, a sensor determining when the steering wheels of the vehicle are straight, or near straight, or a signal provided during a factory-environment calibration process. “);
It would have been obvious to someone with ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the features as disclosed by Meurs into the invention of Schiffmann. Both Meurs and Schiffmann are considered analogous arts to the claimed invention as they disclose a device and method for the correction of a radar device misalignment, where the relative velocities of nearby stationary objects as measured by the radar device are used as inputs. Schiffmann states (Column 9, lines 1-5) “The auto-alignment algorithm is most accurate when run under conditions where the lateral and vertical components of relative-to-Earth velocity of the radar-sensor are nearly zero. Thus, ideal conditions are a straight trajectory on smooth asphalt.” The combination of Schiffmann and Meurs would be obvious with a reasonable expectation of success in order to ensure that the vehicle is traveling in a straight line before performing the alignment correction described in Schiffmann.
Regarding claim 9, Schiffmann discloses
9. The radar device of claim 1, wherein the linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects is determined if a number of the detected stationary objects is equal to or greater than a threshold number (See summary, further column 3, lines 30-34 “ As will be described in more detail below, the algorithm 18 needs at least three (3) instances of the objects 20 to perform the auto-alignment, so each of at least three (3) instances of the objects 20 must be present in the field-of-view 16.” Further, column 9, lines 13-18 “ It has been found that the observability condition is satisfied if there are at least three detections having sufficient azimuth and elevation angle diversity. )
Regarding claim 10, Schiffmann discloses
10. An angle compensation method for a radar device, comprising:
determining whether a host vehicle drives in a straight line;
detecting stationary objects around the host vehicle;
determining a relative speed of each of the stationary objects with respect to the host vehicle;
determining a speed of the host vehicle by using a sensor of the host vehicle;
if the host vehicle is driving in the straight line, determining speed sensor errors by calculating a difference between the relative speed of each of the stationary objects with respect to the host vehicle and the speed of the host vehicle determined using the sensor;
determining a linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects; and
determining an angle for compensating for misalignment of the radar device using the linear regression coefficient of the speed sensor errors, and compensating an angle of a target using the angle determined using the linear regression coefficient of the speed sensor errors.
Regarding claim 10, the same cited section and rationale as claim 1 is applied.
Regarding claim 13, Schiffmann discloses
13. The angle compensation method of claim 10, wherein the speed sensor errors for the estimation angles of the stationary objects are determined by calculating a difference between an absolute value of a velocity component in a driving direction of the host vehicle among relative velocity vectors of the stationary objects and an absolute value of the speed of the host vehicle.
Regarding claim 13, the same cited section and rationale as claim 4 is applied.
Regarding claim 14, Schiffmann discloses
14. The angle compensation method of claim 10, further comprising determining a coefficient representing reliability of the linear regression coefficient,
wherein the determining of the linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects is performed if the coefficient representing the reliability of the linear regression coefficient is greater than or equal to a threshold coefficient.
Regarding claim 14, the same cited section and rationale as claim 5 is applied.
Regarding claim 15, Schiffmann discloses
15. The angle compensation method of claim 14, wherein the estimation angles of the stationary objects are estimated azimuths, and the angle for compensating for the misalignment of the radar device is a compensation value for the estimated azimuths of the target.
Regarding claim 15, the same cited section and rationale as claim 6 is applied.
Regarding claim 16, Schiffmann discloses
16. The angle compensation method of claim 14, wherein the estimation angles of the stationary objects are estimated elevation angles, and the angle compensating for the misalignment of the radar device is a compensation value for the estimated elevation angles of the target.
Regarding claim 16, the same cited section and rationale as claim 7 is applied.
Regarding claim 17, Schiffmann discloses
17. The angle compensation method of claim 10, wherein the determining of the linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects is performed if a number of the detected stationary objects is equal to or greater than a threshold number.
Regarding claim 17, the same cited section and rationale as claim 8 is applied.
Regarding claim 18, Schiffmann discloses [Note: What Schiffmann fails to clearly disclose is strike-through]
18. A radar device (Abstract) comprising:
detect stationary objects around a host vehicle (Column 2 lines 27-30 “The auto-alignment algorithm described herein is for use on a host-vehicle as it observes or tracks stationary objects or targets as the host-vehicle travels along a road.”)
determine a relative speed of each of the stationary objects with respect to the host vehicle (Fig. 1, Item 22, further Column 3 lines 25-28 “ The radar-sensor 14 is operable to determine or measure various values or variable from the returned radar-signal reflected by the objects 20 including, but not limited to, a measured-range-rate 22 (dRm)”) and a speed of the host vehicle (Figure 1, item 32, Column “The system also includes a speed-sensor used to indicate or determine a measured-speed (Sm) of the host-vehicle”) ;,
determine a linear regression coefficient of speed sensor errors by calculating a difference between the relative speed of each of the stationary objects and the speed of the host vehicle (Schiffmann teaches an algorithm by which the difference between vehicle sensor speed and measured relative speeds of the surrounding stationary objects are formulated into a least-squares problem to solve for said coefficients, see Eq. 1, Eq. 2, Eq. 5. Further, Column 6 lines 6-11 “As noted above, relative motion between the radar-sensor and stationary targets is necessary, hence the actual-longitudinal speed of the radar-sensor is assumed to be nonzero. Combining Eqs. 1-4 produces Eq. 5, from which the errors Bs, Ba, and Be can be determined using… “. Here, Ba and Be are defined to be the azimuthal and elevation angle alignment errors respectively.) ,
determine an angle for compensating for misalignment of the radar device using the linear regression coefficient of the speed sensor errors, and
compensate an angle of the target using the angle determined using the linear regression coefficient of the speed sensor errors (Column 7, lines 43-44 “For the Q. 10, a least squares problem leading to a batch solution could take the form of Eq. 18, where...”. The constants Ba and Be as cited in the previous limitation are the desired compensation angles.)
Meurs discloses
an antenna unit including a transmission antenna unit including one or more transmission antennas and a reception antenna unit including one or more reception antennas (Fig. 1, Fig. 3, Claim 1. “A radar system comprising: a plurality of radar transmitters, a plurality of radar receivers”);
a transceiver configured to transmit a transmission signal through the transmission antenna unit and receive a reception signal through the reception antenna unit (Fig. 1, Fig. 3, Claim 1. “A radar system comprising: a plurality of radar transmitters, a plurality of radar receivers”)
one or more processors configured to:
estimate an angle of a target by processing the transmission signal and the reception signal (Fig. 3 Paragraph 0017 “ A radar chirp signal is transmitted by the radar system 100 (310). In a multiple-input, multiple-output radar system, a chirp signal can be transmitted by each antenna 110 during a chirp sequence interval. Chirp reflection signals can be subsequently received by one or more of receiving antennas 120 (320). The received chirp signals are then processed by radar MCU 130 to determine the presence of targets (330). Such processing can include, for example, fast Fourier transform (FFT) to determine range and doppler information, constant false alarm rate (CFAR) to determine whether a signal is representative of a physical target, and target plotting and tracking. “ );
It would have been obvious to someone with ordinary skill in the art prior to the effective filing date of the claimed invention to incorporate the features as disclosed by Meurs into the invention of Schiffmann. Both Meurs and Schiffmann are considered analogous arts to the claimed invention as they disclose a device and method for the correction of a radar device misalignment, where the relative velocities of nearby stationary objects as measured by the radar device are used as inputs. Schiffmann teaches (Fig. 1, Column 3 lines 22-30 “Continuing to refer to FIG. 1, the radar-sensor 14 is used to detect instance of objects 20 present in a field-of-view 16 proximate to the host-vehicle 12 on which the radar-sensor 14 is mounted. The radar-sensor 14 is operable to determine or measure various values or variable from the returned radar-signal reflected by the objects 20 including, but not limited to, a measured-range-rate 22 (dRm), a measured-azimuth-angle 24 (Am), and a measured-elevation-angle 26 (Em) to the objects 20.”). It does not cite any particular radar device or antenna configuration, just that it is capable of performing the required measurements of the nearby stationary objects. It is the position of the examiner that a radar system such as the one described in the instant application inherently requires a transmitting and receiving antenna. For example, Meurs teaches a particular transmitter and receiver combination to achieve this. The combination of Schiffmann and Meurs would be obvious with a reasonable expectation of success in order to determine the relative velocities of nearby stationary objects as described in Schiffmann.
Regarding claim 19, Schiffmann discloses
The radar device of claim 18, wherein the one or more processors are configured to determine the angle for compensating for the misalignment of the radar device differently depending on a sign and an absolute value of the linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects.
Regarding claim 16, the same cited section and rationale as claim 12 is applied.
Regarding claim 20, Schiffmann discloses
The radar device of claim 18, wherein the one or more processors are configured to determine the speed sensor errors for the estimation angles of the stationary objects by calculating a difference between an absolute value of a velocity component in a driving direction of the host vehicle among relative velocity vectors of the stationary objects and an absolute value of the speed of the host vehicle.
Regarding claim 20, the same cited section and rationale as claim 4 is applied.
Claim(s) 2-3, and 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Schiffmann in view of Meurs as applied to claims 1 and 10 above, and further in view of Ru et al. (US 20190187250 A1), hereafter Ru.
Regarding claim 2, Schiffmann discloses [Note: What Schiffmann fails to clearly disclose is strike-through]
The radar device of claim 1, wherein the angle for compensating for the misalignment of the radar device is determined by the one or more processors
The art taught by Schiffmann does not explicitly require that a minimum threshold misalignment angle is required for the application of the misalignment correction. However, such threshold behavior is not considered novel by one of ordinary skill in the art. For example, in a radar misalignment detection method described in Ru, a minimum sensor misalignment is required before sending a signal to a user (Ru et al., specification paragraph 14 “ In some exemplary embodiments, if at least one of the absolute misalignment angle of the first radar sensor and the absolute misalignment angle of the second radar sensor exceeds a threshold angle, then an alert is issued”).
Regarding claim 3, Schiffmann discloses
The radar device of claim 2, wherein the one or more processors (Fig. 1, further column 3 lines 62 – 65 “The system 10 also includes a controller 34 in communication with the radar-sensor 14 and the speed-sensor 30. The controller 34 may include a processor (not specifically shown) such as a microprocessor or other control circuitry”) are configured to determine the angle for compensating for the misalignment of the radar device differently depending on the absolute value and a sign of the linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects (Eqs. 16,
P
=
t
r
a
n
s
B
s
B
a
B
e
where the quantity P is equivalent to the linear regression coefficient and contains the desired misalignment angles Ba and Be).
Regarding claim 11, Schiffmann discloses
The angle compensation method of claim 10, wherein the determining of the angle for compensating for misalignment of the radar device is performed if an absolute value of the linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects is greater than or equal to a threshold value.
Regarding claim 11, the same cited section and rationale as claim 2 is applied.
Regarding claim 12, Schiffmann discloses
The angle compensation method of claim 11, wherein the determining of the angle for compensating for the misalignment of the radar device comprises determining the angle for compensating for the misalignment of the radar device differently depending on the absolute value and a sign of the linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects.
Regarding claim 12, the same cited section and rationale as claim 3 is applied.
Response to Arguments
Applicant's arguments received May 14th, 2026, with respect to 35 U.S.C. § 103. With regard to claims 1, 4-10, and 13-20, applicant makes the following arguments: (1) Neither Schiffmann or Meurs discloses, teaches, or suggests the limitation “determine a relative speed of each of the stationary objects with respect to the host vehicle” as recited in claim 1. (2) The disclosure of Schiffman does not disclose, teach, or suggest, “calculating a difference between the relative speed of each of the stationary objects with respect to the host vehicle and the speed of the host vehicle determined using the sensor”. (3) Neither Schiffman nor Meurs discloses, teaches, or suggests, “determine a linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects; and determine a linear regression coefficient of the speed sensor errors and compensate an angle of a target using the angle determined using the linear regression coefficient of the speed sensor errors” as recited in claim 1. All arguments have been fully considered, and are not found persuasive.
In response to the argument (1) of claims 1, 4-10, and 13-20, the Examiner respectfully disagrees. Applicant’s argument contends that the cited section in Schiffman, column 3 lines 25-28 “measured -range-rate 22 (dRm)” does not disclose or teach the determination of the relative speeds of each of the stationary objects with respect to the host vehicle. Within the art, it is known that the quantity “range-rage” (dRm in Schiffman) refers to the relative speed between an object and a radar sensor. An example of a dictionary definition of range rate is given in section 2.1.2 of Bizup, David Francis, “Improving radar target tracking with the range rate measurement”, University of Virginia, (2003):
Range rate, also known as the radial or Doppler velocity, is missing from the estimator. The reason is that the Kalman filter assumes a linear system. Range rate is highly non-linear in Cartesian space, as seen in the following expression for range rate as a function of the state space for a radar at the origin:
r
˙
=
x
x
˙
+
y
y
˙
x
2
+
y
2
(Eq. 2.8)
In light of this definition, the disclosure of a “measure range-rate” of each of the stationary objects is identical to the determination of a relative speed of each of the measured objects. Therefore, the Examiner maintains that the combination of Schiffmann in view of Meurs teaches the claimed limitation.
In response to argument (2), Applicant further argues that none of Eqs. 1 to 5 of Schiffman calculate the difference between the relative speed of each of the stationary objects with respect to the vehicle and the speed of the host vehicle as determined using a sensor. Schiffman defines the quantities in Eqs. 1 to 5 as (Schiffman column 5, bold for emphasis on relevant definitions):
Definitions of the ‘actual’ (i.e. the measurement-error-free value) variable names or symbols, and the ‘measured’ (i.e. indicated by measurements made by the radar-sensor 14) variable names or symbols used herein are defined as follows: dRa(i), dRm(i): actual-range-rate 48 and measured-range-rate 22 of the i-th object detection; Aa(i), Am(i): actual-azimuth-angle 44 and measured-azimuth-angle 24 of the i-th detection; Ea(i), Em(i): actual-elevation-angle 46 and measured-elevation-angle 26 of the i-th detection; Ua(i), Va(i), Wa(i): actual-longitudinal, actual-lateral, and actual-vertical components of the actual velocity vector or the radar-sensor 14 relative to Earth at the time the i-th detection is observed; Um(i), Vm(i), Wm(i): measured-longitudinal, measured-lateral, and measured-vertical components of measured velocity vector of the radar-sensor 14 relative to Earth at the time the i-th detection is observed; Ut(i), Vt(i), Wt(i): longitudinal, lateral, vertical of indicated velocity vectors relative to Earth of the i-the object (i.e. target) detection; Ys(i): side-slip-angle 50 of the host-vehicle 12 at the time the i-th object detection is observed, where the slide-slip-angle is the angle between the horizontal host-vehicle velocity vector (i.e. the vector [Ua Va 0]) and the x-axis; Ba: bias error in measured azimuth angle, i.e. the azimuth-misalignment 38; Be: bias error in measured elevation angle, i.e. the elevation-misalignment 40; and Bs: speed-scaling-error 36 in host vehicle speed.
By these definitions, the quantity of interest would be
d
R
m
i
-
U
m
i
, which indeed does not appear explicitly in Schiffman. Instead, this is formulated slightly, as shown in Schiffman Eq. 5.
d
R
m
i
+
U
m
i
cos
A
m
i
*
cos
E
m
i
+
V
m
i
sin
A
m
*
cos
E
m
i
=
…
(See. Eq. 5)
Assuming that one is traveling in a straight line, i.e. there is only a longitudinal velocity component of the vehicle sensor (As motivated by Schiffman Col. 6, lines 35-38 “Eq. 10 is a simplified version of Eq. 5 that is suitable for conditions of operation in which the host vehicle is traveling in a straight line”), this reduces to (Schiffman Eq. 10):
d
R
m
i
+
U
m
i
cos
A
m
(
i
)
cos
E
m
i
=
U
m
i
F
i
,
1
F
i
,
2
F
i
,
3
*
B
s
B
a
B
e
T
Further, using the condition of the claimed invention which assumes that the road objects are in-plane, (i.e.
E
m
i
=
0
), this expression reduces to:
d
R
m
i
+
U
m
i
cos
A
m
(
i
)
=
U
m
i
cos
A
m
i
,
-
sin
A
m
i
,
-
c
o
s
[
A
m
i
]
*
B
s
B
a
B
e
T
If one only considers the azimuthal plane
(
B
e
=
0
)
, as in the claimed invention, this further reduces to:
d
R
m
i
+
U
m
i
cos
A
m
(
i
)
=
B
s
U
m
(
i
)
cos
[
A
m
(
i
)
]
-
B
a
U
m
i
sin
A
m
(
i
)
The specification of the claimed invention only requires the longitudinal component of the measured range-rate (Specification [0123] “the velocity component
v
r
→
of the object in the driving direction of the host vehicle”). The measured range-rate
d
R
m
i
of the prior art and
v
r
→
as defined in the instant application may be related as follows (assuming the vehicle is moving in the positive y- direction and objects are stationary):
d
R
m
i
=
y
y
˙
x
2
+
y
2
=
R
cos
[
A
m
(
i
)
]
y
˙
R
,
d
R
m
i
c
o
s
[
A
m
]
=
y
˙
=
v
r
→
Similarly, the equation above of the prior art, reduced to just the longitudinal component, would be the following:
d
R
m
i
+
U
m
i
cos
A
m
(
i
)
=
B
s
U
m
(
i
)
cos
[
A
m
(
i
)
]
-
B
a
U
m
i
sin
A
m
(
i
)
d
R
m
i
c
o
s
[
A
m
]
=
B
s
U
m
i
-
B
a
U
m
tan
A
m
-
U
m
i
d
R
m
i
c
o
s
[
A
m
]
=
v
r
→
=
-
U
m
i
(
B
a
U
m
tan
A
m
+
1
+
B
s
)
d
R
m
i
c
o
s
[
A
m
]
=
v
r
→
=
-
U
m
i
-
B
a
tan
A
m
i
U
m
i
-
B
s
U
m
(
i
)
This is analogous Applicant’s Eq. 4, i.e. the definition of a “speed sensor error”, noting that the longitudinal sensor velocity
v
→
in Applicant’s invention is equivalent to
U
m
i
in Shiffman:
S
S
E
=
v
r
→
-
U
m
i
=
B
a
tan
A
m
i
U
m
i
+
B
s
U
m
(
i
)
Note what Applicant specifies as the “normal case”, i.e. Applicant Eq. 4 (Specification [0148]) for case of no angular misalignment (
B
a
=
0
)
, is precisely reproduced:
S
S
E
=
S
S
E
=
v
r
→
-
U
m
i
=
B
s
U
m
i
=
β
0
Applicant equation 5 for the “tilted case” (Specification [0159]) is reproduced by defining
x
=
t
a
n
[
A
m
i
]
:
S
S
E
=
v
r
→
-
U
m
i
=
B
a
U
m
i
x
+
B
s
U
m
i
=
β
1
x
+
β
0
While the applicant’s form of this equation uses a cosine rather than a tangent, the difference is considered obvious to those of ordinary skill in the art and is simply a different formulation of the same problem that leads to the same result. Thus, the quantities defined by the applicant are known to be implicit to specific limiting cases of the invention of Schiffman, which clearly fall within the scope of the disclosure. Therefore, Examiner maintains that Schiffman teaches the claimed limitation.
In response to argument (3), Applicant further argues that neither Schiffman nor Meurs discloses, teaches, or suggests, “determine a linear regression coefficient of the speed sensor errors for the estimation angles of the stationary objects; and determine a linear regression coefficient of the speed sensor errors and compensate an angle of a target using the angle determined using the linear regression coefficient of the speed sensor errors” as recited in claim 1. It is well-known within the art that a system of linear equations, Eq. 18 of Schiffman, may be formulated as a batch least-squares linear algebra problem (Schiffman Col. 7, lines 10-20). Linear regression is a visualized batch least-linear squares optimization, which when written in matrix notation takes the form
y
i
=
X
T
β
+
ϵ
i
, where
X
T
is the transpose of a matrix of independent variables,
β
is a column vector of optimization parameters, and
ϵ
i
is a column vector known as the error term (Wikipedia contributors. "Linear regression." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 28 Jun. 2019.). In the formulation of Schiffman, the optimization parameters are contained within
P
=
B
s
B
a
B
e
T
, which is optimized through a least-squares regression of the speed sensor errors (See response to argument (2)). In the case of the present invention, the relevant parameter is
B
a
, which is an angular offset of the radar sensor in the azimuthal plane. Therefore, examiner maintains that the combination of Schiffman in view of Meurs teaches the claimed limitation.
In regard to claim 10 and 18, applicant argues these claims are allowable based on similar arguments to those used for claim 1. As stated in the arguments above, the examiner is maintaining the rejection for claim 1, and therefore claims 10 and 18 remain rejected.
In regard to claims 2-9, 11-17, and 19-20, applicant argues these claims are allowable due to their dependency on claims 1, 10, and 18. As stated in the arguments above, the examiner is maintaining the rejection for claims 1, 10, and 18, and therefore claims 2-9, 11-17, and 19-20 remain rejected.
Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
Examiner notes that holding citation to a dictionary was not tantamount to the assertion of a new ground of rejection "where such a reference is a standard work, cited only to support a fact judicially noticed and, as here, the fact so noticed plays a minor role, serving only to fill in the gaps which might exist in the evidentiary showing made by the Examiner to support a particular ground for rejection." (emphasis and internal quotations omitted)). See MPEP § 1207.03 Section III.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. These citations are a result of further search after receipt of applicant’s arguments, but are not pertinent to said arguments. Rozewicz et al. (US 20210341599 A1) discloses a computer implemented method for determining the alignment parameters of a radar sensor, including azimuthal, elevation, and roll misalignment angles. Jeannin et al. (US 20230384418 A1) discloses a method for determine a correction vector for an automotive radar based on the positions and velocities of stationary objects versus the vehicle velocity vector.
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner
should be directed to THOMAS JAMES HALLORAN whose telephone number is (571)272-8643. The
examiner can normally be reached Mon-Fri. 7:30am-5pm.
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,
Resha H. Desai can be reached at (571) 270-7792. 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.
/T.J.H./Examiner, Art Unit 3648
/RESHA DESAI/Supervisory Patent Examiner, Art Unit 3648
Prosecution Insights