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 .
Response to Amendment
1 This action is in response to the amendment filed on 02/05/2026. Claims 1, 3-4, and 15 have been amended, claims 17-18 were added, and the abstract was amended to overcome an objection. Claims 1-16 remain rejected, and claims 17-18 are rejected.
Response to Arguments
2 Applicant’s arguments with respects to claims 1 and 15 filed on 2/05/2026, with respect to the rejection under 35 U.S.C. 103 regarding that the prior art does not teach the following but not limited to “wherein the LIDAR simulation circuit is configured to simulate at least one current scan signal of the LIDAR device based on the at least one characteristic parameter, wherein the LIDAR simulation circuit is configured to simulate at least one future scan signal of the LIDAR device based on the at least one characteristic parameter”. This arguments has been considered, but are moot due to similar and new grounds of rejection.
3 Regarding arguments to claims 2-14 and 16, they directly/indirectly depend on independent claims 1 and 15 respectively. Applicant does not argue anything other than independent claims 1 and 15. The limitations in those claims, in conjunction with combination, was mostly previously established as explained, with a few changes with the amended dependent claims.
4 Claims 17 and 18 are new claims that were added, and is dependent of the independent claims 1 and 15. They are considered, but are moot under similar grounds of rejection.
Claim Rejections - 35 USC § 103
5 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.
6 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.
7 Claim(s) 1-3, 5, 7, 11-13, and 15-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Werschnik et al. (DE 102019106129 A1) in view of Safira et al. (US 20220058309 A1) and Li et al. (US 20210356561 A1).
8 Regarding claim 1, Werschnik teaches a LIDAR target simulation system for testing a LIDAR device ([0001] reciting “The present invention relates to a test unit and a method for testing a LIDAR unit for a vehicle and to a computer program.”), the LIDAR target simulation system comprising a scenario generation circuit ([0028] reciting “In response thereto, for example, the computer unit 155 can then read out a parameter 162 from a memory 165, wherein this parameter 162 represents a predefined time duration which corresponds to a travel time duration which the light beam 110 emitted by the LIDAR unit 100 brown in order to be reflected at an object which is located in an optical axis between the LIDAR unit 100 and the position of the receiving unit 145 a, and would occur again at the receiver 120 as a reflected light beam 115…Taking into account this parameter 162, which now represents the predefined time period, a transmission signal 170 is now generated and output to the transmitting unit 140 a, which then emits the light beam 115 to the LIDAR unit 100 or the receiver 120 of the LIDAR unit 100 and thereby simulates an object which is at that position of the transmitting unit 140 or at that position of the transmitting unit 140 a.”), a pattern detector ([0028] reciting “The computer unit 155 is connected in a signal-transmitting manner to the transmitting units 140 (i.e. at least one transmitting unit 140 a) and receiving units 145 (i.e. at least one receiving unit 145 a) of the respective transmitting unit-receiving unit pairs 135.”), a LIDAR simulation circuit ([0028] reciting “By selecting the parameter 162 representing the defined time period, a defined delay of the output of the light beam 115 by the transmitting unit 140 can thus be achieved, such that the LIDAR unit 100 can simulate the presence of an object in front of the LIDAR-100 at a predefined distance.”), and a signal response generator ([0051] reciting “The method 600 further comprises a step 620 of determining a transmission signal for output to a transmission unit in a computer unit, wherein the transmission signal is output after a defined period of time in response to the reception signal.”),
wherein the scenario generation circuit is configured to generate a test scenario for testing the LIDAR device ([0027] reciting “In order now to avoid the aforementioned disadvantages in checking the functionality of LIDAR unit 100, it is now proposed to provide a test unit 130 in front of LIDAR unit 130 instead of a real test environment. The test unit 130 can be positioned directly in front of the LI DAR unit 100 and has transmitter-receiver unit pairs 135.”; [0028] reciting “In this context, a period of time should still be taken into account which is caused by a travel time of the light 110 or 115 by a distance between the LIDAR unit 100 and the test unit 130.”),
wherein the pattern detector includes circuitry configured to receive at least one scan signal generated by the LIDAR device to be tested ([0028] reciting “This means that the computer unit 155 can receive a reception signal 160 a, for example, from a reception unit 145 a, which signal represents an incidence from a light beam 110 emitted by the LIDAR unit 100 onto the reception unit 145 a.”), wherein the pattern detector further includes circuitry configured to determine at least one characteristic parameter of the received scan signal, wherein the at least one characteristic parameter is associated with properties of the at least one scan signal ([0028] reciting “In response thereto, for example, the computer unit 155 can then read out a parameter 162 from a memory 165, wherein this parameter 162 represents a predefined time duration which corresponds to a travel time duration which the light beam 110 emitted by the LIDAR unit 100 brown in order to be reflected at an object which is located in an optical axis between the LIDAR unit 100 and the position of the receiving unit 145 a, and would occur again at the receiver 120 as a reflected light beam 115.”),
and
wherein the signal response generator includes circuitry configured to generate a response signal to be received by the LIDAR device to be tested, wherein the signal response generator includes circuitry configured to generate the response signal based on the at least one simulated scan signal of the LIDAR device and based on the test scenario ([Abstract] reciting “Furthermore, the test unit (130) comprises a transmitting unit (140a, 140b, 140c) for transmitting light (115) to the LIDAR unit (100) in response to a transmitted signal (170a, 170b, 170c), wherein the transmitting unit (140a, 140b, 140c) is arranged at a predetermined distance from the receiving unit (145a, 145b, 145c) on the sensor screen (150). Finally, the test unit (130) comprises a computer unit (155) which is designed to output the transmission signal (170a, 170b, 170c) to the transmission unit (140a, 140b, 140c) after a defined period of time in response to the reception signal (160a, 160b, 160c).”).
9 Werschnik does not explicitly teach wherein the LIDAR simulation circuit is configured to simulate at least one current scan signal of the LIDAR device based on the at least one characteristic parameter, wherein the LIDAR simulation circuit is configured to simulate at least one future scan signal of the LIDAR device based on the at least one characteristic parameter.
10 Safira teaches wherein the LIDAR simulation circuit is configured to simulate at least one current scan signal of the LIDAR device based on the at least one characteristic parameter ([0043] reciting “The object detection system 232 can be configured to detect objects in the simulated environment in a way that is similar to how the object detection system 132 recognizes the detected objects in an actual driving environment 110. The object detection system 232 can analyze simulated images of the simulated environment as if captured by the physical camera(s) of the optical detection system 120… The object detection system 232 can also receive and process the simulated LiDAR data and can use the simulated LiDAR data in combination with the simulated images of the environment.”; [0070] reciting “The generated simulated strengths of beams can be based on a distance from the autonomous vehicle to the respective simulated object. For example, based on the current distances from the autonomous vehicle to various simulated objects and angles at which the simulated objects are seen from the vantage point of the autonomous vehicle, the computing device (e.g., implementing the optical data simulator 210) can determine characteristics of the LiDAR sensing signals incident on the simulated objects. The characteristics of the sensing signals can include the angles of incidence, polarizations, amplitudes, and so on.”)…
11 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Werschnik) to incorporate the teachings of Safira to provide a method that is able to simulate a type of current scan signal based on the parameters, utilizing the LIDAR scans that are provided by the teachings of Werschnik. Doing so would all certain simulators to determine characteristics of the LiDAR sensing signals incident on the simulated objects as stated by Safira ([0070] recited).
Werschnik in view of Safira does not explicitly teach … wherein the LIDAR simulation circuit is configured to simulate at least one future scan signal of the LIDAR device based on the at least one characteristic parameter.
12 Li teaches … wherein the LIDAR simulation circuit is configured to simulate at least one future scan signal of the LIDAR device based on the at least one characteristic parameter ([0015] reciting “According to various embodiments, a drive emulation system is able to emulate echo signals responsive to detection and ranging electromagnetic signal transmissions (e.g., radar and lidar signals) from multiple sensors on a vehicle under test, such as an automobile or other autonomous vehicle. The embodiments provide cost-effective, high performance target emulation in a scene simulation that scales well with an increased number of sensors…A prediction model executed by echo signal emulators will be used to project the target information to a time in the near future when the target information is presented to the autonomous vehicle through emulated echo signals. When the vehicle's sensors are actively probing the simulated environment, the prediction model is used to project the target information to the precise time when the sensors are generating their probing signals (e.g., at the start of radar chirp frames).”; [0036] reciting “The prediction model 115 is programmed to predict the emulated target list that will be used by the first, second and y.sup.th echo signal emulators 111, 112 and 113 to provide the emulated echo signals at a future time…The timing of the predicted time point being determined for the near future therefore depends on specific characteristics of the electromagnetic signal, although as a practical matter, the near future will be in the milliseconds level, for example, for most types of electromagnetic signals.”).
13 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Werschnik in view of Safira) to incorporate the teachings of Li to provide a method to have the LIDAR system or device taught by Werschnik in view of Safira to incorporate a type of simulation, that could be related to time, of a scan that happens in the future that is based on certain and different types of parameters. Doing so would allow their system to emulate echo signals responsive to LIDAR signals as stated by Li ([0015] recited).
14 Regarding claim 2, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 1 (see claim 1 rejection above), wherein the at least one characteristic parameter comprises a pulse shape of the at least one scan signal, an angle of departure of the at least one scan signal, a time of detection of the at least one scan signal (Werschnik; [0028] reciting “By selecting the parameter 162 representing the defined time period, a defined delay of the output of the light beam 115 by the transmitting unit 140 can thus be achieved, such that the LIDAR unit 100 can simulate the presence of an object in front of the LIDAR-100 at a predefined distance.”), pulse rate of the at least one scan signal, a pulse position of the at least one scan signal, a line rate of the at least one scan signal, a column rate of the at least one scan signal (Werschnik; [0032] reciting “In particular, by means of the arrangement of the transmitter-receiver unit pairs 135 in, for example, M rows and N columns, it is thus possible to achieve an MxN-matrix-like structure of the sensor screen 150, in which delay paths for the delayed output of the "reflected" light beam 150 to the receiver 120 of the LIDAR unit 100 are provided in order to specify different test scenarios in suitable resolution of the LIDAR unit 100 to be tested…”), and/or a repetition rate of the at least one scan signal.
15 Regarding claim 3, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 1 (see claim 1 rejection above), wherein the LIDAR simulation circuit is configured to simulate the at least one current scan signal (Safira; [0043] reciting “The object detection system 232 can be configured to detect objects in the simulated environment in a way that is similar to how the object detection system 132 recognizes the detected objects in an actual driving environment 110. The object detection system 232 can analyze simulated images of the simulated environment as if captured by the physical camera(s) of the optical detection system 120… The object detection system 232 can also receive and process the simulated LiDAR data and can use the simulated LiDAR data in combination with the simulated images of the environment.”; [0070] reciting “The generated simulated strengths of beams can be based on a distance from the autonomous vehicle to the respective simulated object. For example, based on the current distances from the autonomous vehicle to various simulated objects and angles at which the simulated objects are seen from the vantage point of the autonomous vehicle, the computing device (e.g., implementing the optical data simulator 210) can determine characteristics of the LiDAR sensing signals incident on the simulated objects. The characteristics of the sensing signals can include the angles of incidence, polarizations, amplitudes, and so on.”) and the at least one future scan signal of the LIDAR device based on a state space model of the LIDAR device (Li; [0015] reciting “According to various embodiments, a drive emulation system is able to emulate echo signals responsive to detection and ranging electromagnetic signal transmissions (e.g., radar and lidar signals) from multiple sensors on a vehicle under test, such as an automobile or other autonomous vehicle. The embodiments provide cost-effective, high performance target emulation in a scene simulation that scales well with an increased number of sensors…A prediction model executed by echo signal emulators will be used to project the target information to a time in the near future when the target information is presented to the autonomous vehicle through emulated echo signals. When the vehicle's sensors are actively probing the simulated environment, the prediction model is used to project the target information to the precise time when the sensors are generating their probing signals (e.g., at the start of radar chirp frames).”; [0036] reciting “The prediction model 115 is programmed to predict the emulated target list that will be used by the first, second and y.sup.th echo signal emulators 111, 112 and 113 to provide the emulated echo signals at a future time…The timing of the predicted time point being determined for the near future therefore depends on specific characteristics of the electromagnetic signal, although as a practical matter, the near future will be in the milliseconds level, for example, for most types of electromagnetic signals.”) based on a state space model of the LIDAR device (Werschnik; [0028] “Taking into account this parameter 162, which now represents the predefined time period, a transmission signal 170 is now generated and output to the transmitting unit 140 a, which then emits the light beam 115 to the LIDAR unit 100 or the receiver 120 of the LIDAR unit 100 and thereby simulates an object which is at that position of the transmitting unit 140 or at that position of the transmitting unit 140 a.”).
16 Regarding claim 5, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 3 (see claims 1 and 3 rejections above), wherein the pattern detector includes circuitry configured to receive at least one further scan signal generated by the LIDAR device during testing of the LIDAR device (Werschnik; [0017] reciting “An embodiment of the approach proposed here is particularly advantageous in which the computer unit is designed to output the transmission signal to the transmission unit in order to control a modulation of the output of light from the transmission unit to the LIDAR unit…As a result, a further plausibility check of the distance detected by the LIDAR unit can thus be carried out not only from the light travel time but also, for example, from the reduction of an amplitude of the light received by the LIDAR unit.”) wherein the pattern detector further includes circuitry configured to determine at least one updated characteristic parameter of the LIDAR device based on the at least one further scan signal (Werschnik; [0029] reciting “It is also conceivable that the parameter 162, which presents the defined time duration, is variable or actually varied, so that for example, at a first point in time a first parameter 162 is used for determining the transmission signal 170 after reception of the reception signal 160 a, which parameter corresponds to a (first) time duration, whereas at a later second point in time a second parameter 162 is used for determining the transmission signal 170 after reception of the reception signal 160 a, which parameter corresponds to a second time duration.”) and wherein the LIDAR simulation circuit is configured to update parameters of the state space model based on the at least one updated characteristic parameter (Werschnik; [0028] reciting “This distance of the object in front of the LIDAR unit 100 can be determined or simulated in the LIDAR unit 100 essentially by evaluating the time-of-flight difference between the emission of the light beam 11 0 by the transmitter 105 and the reception of the "reflected" light beam 115 by setting the parameter 162 representing the time duration and, if appropriate, by taking into account the time-of-flight of the light of the light beams 110 or 115, the presence of an object at a certain distance in front of the LIDAR unit 100 can thus be flexibly predetermined or simulated.”).
17 Regarding claim 7, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 1 (see claim 1 rejection above), wherein the signal response generator comprises an analog pulse responder, and wherein the analog pulse responder includes circuitry configured to generate the response signal to be received by the LIDAR device (Werschnik; [0026] reciting “Arranged in the LIDAR unit 100 is now a receiver 120, which can receive the reflected light beam 115 and, from the determination of the difference in time between the emission of the emitted light beam 110 and the incidence of the reflected light beam 115 (taking account of the light velocity), can make an estimation of the distance of the object from the LIDAR unit 100 at which the emitted light beam 110 was reflected and detected by the reflected light beam 115 at the receiver 120. Alternatively or additionally, further parameters of the emitted light beam 110 can also be evaluated, for example in relation to corresponding parameters in reflected light beam 115, such as an amplitude or phase, in order to obtain further information relating to the object at which the emitted light beam 110 was reflected.”).
18 Regarding claim 11, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 1 (see claim 1 rejection above), wherein the signal response generator includes circuitry configured to generate the response signal with a predetermined time delay (Werschnik; [0028] reciting “By selecting the parameter 162 representing the defined time period, a defined delay of the output of the light beam 115 by the transmitting unit 140 can thus be achieved, such that the LIDAR unit 100 can simulate the presence of an object in front of the LIDAR-100 at a predefined distance.”).
19 Regarding claim 12, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 11 (see claims 1 and 11 rejections above), wherein the predetermined time delay depends on the at least one simulated scan signal of the LIDAR device and/or on the test scenario (Werschnik; [0028] reciting “By selecting the parameter 162 representing the defined time period, a defined delay of the output of the light beam 115 by the transmitting unit 140 can thus be achieved, such that the LIDAR unit 100 can simulate the presence of an object in front of the LIDAR-100 at a predefined distance.”; [0048] reciting “Via the MxN delay paths with suitable resolution, any test situation with spatial arrangements of objects of different reflections can be offered to the LIDAR to be tested.”).
20 Regarding claim 13, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 1 (see claim 1 rejection above), wherein the test scenario is a three-dimensional test scenario and/or wherein the test scenario comprises at least one object, wherein a simulated distance of the at least one object is smaller than a length corresponding to the speed of light times a processing time of the signal response generator (Werschnik; [0005] reciting “In the present case, a test unit can be understood to mean, for example, a compact unit which can be placed in front of the LIDAR unit at a certain distance, which can also be very small, for example.”; [0048] reciting “D-scenes may be mimicked by parameterization. Via the MxN delay paths with suitable resolution, any test situation with spatial arrangements of objects of different reflections can be offered to the LIDAR to be tested. The distance is achieved by phase and reflectance by amplitude parameterization. The structure is compact and designed for end-of-line testing.”).
21 Claim 15 has similar limitations as of Claim 1, therefore it is rejected under the same rationale as Claim 1.
22 Claim 16 has similar limitations as of Claim 3, therefore it is rejected under the same rationale as Claim 3.
23 Regarding claim 17, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 1 (see claim 1 rejection above), wherein the scenario generation circuit is independent of the LIDAR simulation circuit such that the generated test scenario and the simulated scan signals are uncorrelated (Werschnik; [0010] reciting “Such an embodiment offers the advantage of being able to simulate a distance of an object from the LIDAR unit in a very flexible manner, sucl1 that the LIDAR unit can be checked with very many different test scenarios.”; [0030] reciting “If, on the other hand, a parameter 162 is used for determining the second transmission signal 170 b, which parameter represents a different time period and thus a different distance of the object in front of the LIDAR unit 100, the LIDAR unit 100 can simulate the presence of two different objects at different distances at different positions of the LIDAR unit 100 or else the presence of a large, spatially extended object, such that the LIDAR unit 100 can possibly even detect the dimensions of the object in different directions.”).
24 Claim 18 has similar limitations as of claim 17, therefore it is rejected under the same rationale as claim 17.
25 Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Werschnik et al. (DE 102019106129 A1) in view of Safira et al. (US 20220058309 A1) and Li et al. (US 20210356561 A1) as of claims 1 and 3, further in view of Ahn et al. (US 20210272466 A1).
26 Regarding claim 4, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 3 (see claims 1 and 3 rejections above), to simulate the at least one current scan signal (Safira; [0043] reciting “The object detection system 232 can be configured to detect objects in the simulated environment in a way that is similar to how the object detection system 132 recognizes the detected objects in an actual driving environment 110. The object detection system 232 can analyze simulated images of the simulated environment as if captured by the physical camera(s) of the optical detection system 120… The object detection system 232 can also receive and process the simulated LiDAR data and can use the simulated LiDAR data in combination with the simulated images of the environment.”; [0070] reciting “The generated simulated strengths of beams can be based on a distance from the autonomous vehicle to the respective simulated object. For example, based on the current distances from the autonomous vehicle to various simulated objects and angles at which the simulated objects are seen from the vantage point of the autonomous vehicle, the computing device (e.g., implementing the optical data simulator 210) can determine characteristics of the LiDAR sensing signals incident on the simulated objects. The characteristics of the sensing signals can include the angles of incidence, polarizations, amplitudes, and so on.”) and the at least one future scan signal of the LIDAR device based on the state space model of the LIDAR device (Li; [0015] reciting “According to various embodiments, a drive emulation system is able to emulate echo signals responsive to detection and ranging electromagnetic signal transmissions (e.g., radar and lidar signals) from multiple sensors on a vehicle under test, such as an automobile or other autonomous vehicle. The embodiments provide cost-effective, high performance target emulation in a scene simulation that scales well with an increased number of sensors…A prediction model executed by echo signal emulators will be used to project the target information to a time in the near future when the target information is presented to the autonomous vehicle through emulated echo signals. When the vehicle's sensors are actively probing the simulated environment, the prediction model is used to project the target information to the precise time when the sensors are generating their probing signals (e.g., at the start of radar chirp frames).”; [0036] reciting “The prediction model 115 is programmed to predict the emulated target list that will be used by the first, second and y.sup.th echo signal emulators 111, 112 and 113 to provide the emulated echo signals at a future time…The timing of the predicted time point being determined for the near future therefore depends on specific characteristics of the electromagnetic signal, although as a practical matter, the near future will be in the milliseconds level, for example, for most types of electromagnetic signals.”).
27 Werschnik in view of Safira and Li does not explicitly teach wherein the LIDAR simulation circuit comprises a Kalman filter and/or a machine-learning circuit wherein the Kalman filter and/or the machine-learning circuit is configured…
28 Ahn teaches wherein the LIDAR simulation circuit comprises a Kalman filter and/or a machine-learning circuit wherein the Kalman filter and/or the machine-learning circuit is configured ([0054] reciting “In order to verify an algorithm for estimating the velocity of the obstacle, which is realized with the Kalman filter, a simulation for detection of the obstacle and estimation of the velocity thereof is realized. The simulation is realized in such a manner that performance of the algorithm in terms of LiDAR accuracy and performance of the algorithm in terms of the horizontal-axis LiDAR resolution are comparable.”)…
29 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Werschnik in view of Safira and Li) to incorporate the teachings of Ahn to provide the usage of a Kalman filter to go with the LIDAR and state space model teachings of Werschnik in view of Safira and Li, which the Kalman filter can be in place of the prediction models taught by Werschnik in view of Safira and Li. Doing so would allow the verification of an algorithm for estimating certain velocities as stated by Ahn ([0054] recited).
30 Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Werschnik et al. (DE 102019106129 A1) in view of Safira et al. (US 20220058309 A1) and Li et al. (US 20210356561 A1) as of claims 1, 3, and 5, further in view of Hoffmann et al. (DE 102019118039 A1).
31 Regarding claim 6, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 5 (see claims 1, 3, and 5 rejections above), but does not explicitly teach wherein the LIDAR simulation circuit is configured to update the parameters of the state space model by a closed-loop control technique.
32 Hoffmann teaches wherein the LIDAR simulation circuit is configured to update the parameters of the state space model by a closed-loop control technique ([0011] reciting “Consequently, optical signals emitted by the measuring device, for example a LIDAR measuring device, can be received and optical response signals dependent thereon, which in turn are received by the optical measuring device, can be emitted.”; [0012] reciting “A closed loop thus results. The response signals may be amplitude varying signals. Furthermore, an angular resolution of the measuring device can be checked via the matrix of transceiver pairs.”).
33 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Werschnik in view of Safira and Li) to incorporate the teachings of Hoffmann to provide a closed loop technique for the LIDAR signals’ parameters provided by Werschnik in view of Safira and Li. Doing so would provide a check on an angular resolution of a measuring device as stated by Hoffmann ([0012] recited).
34 Claim(s) 8-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Werschnik et al. (DE 102019106129 A1) in view of Safira et al. (US 20220058309 A1) and Li et al. (US 20210356561 A1) as of claims 1 and 7, further in view of Lee et al. (US 20200033481 A1) and Schwarz et al. (US 20160306032 A1).
35 Regarding claim 8, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 7, wherein the analog pulse responder (see claims 1 and 7 rejections above)…, but does not explicitly teach wherein the analog pulse responder comprises an analog integrator, wherein the analog integrator includes circuitry configured to integrate a constant voltage signal, thereby obtaining an integrated voltage signal, and wherein the analog pulse responder includes circuitry configured to generate the response signal when the integrated voltage signal reaches a predefined threshold.
36 Lee teaches wherein the analog pulse responder comprises an analog integrator, wherein the analog integrator includes circuitry configured to integrate a voltage signal, thereby obtaining an integrated voltage signal, and wherein the analog pulse responder includes circuitry configured to generate the response signal when the integrated voltage signal reaches a predefined threshold ([0043] reciting “The modulation signal may also be a sinewave, gated or pulsed sinewave, chirped sinewave, or a frequency-modulated (FM) sinewave, or an amplitude-modulated (AM) sinewave, or a pulse-width-modulated (PWM) series of pulses.”; [0316] reciting “The lidar system may further include: a trans impedance amplifier configured to convert a current input from the activated pixels into a voltage and amplify the voltage; an integrator configured to integrate an output signal of the trans impedance amplifier; a noise remover configured to remove noise from an output signal of the integrator; an analog to digital converter configured to convert the output signal of the noise remover into a digital signal”).
37 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Werschnik in view of Safira and Li) to incorporate the teachings of Lee to provide a method to incorporate a type of analog integrator for a certain type of response or output signals using the pulse responders that are taught by Werschnik in view of Safira and Li. Doing so would allow the detector configured to analyze the digital signal to generate depth information for each scan angle as stated by Lee ([0316] recited).
38 Werschnik in view of Safira, Li, and Lee does not explicitly teach wherein the analog integrator includes circuitry configured to integrate a constant voltage signal…
39 Schwarz teaches wherein the analog integrator includes circuitry configured to integrate a constant voltage signal ([0013] reciting “In a further embodiment, a method of operating a LiDAR sensor is provided. An electromagnetic pulse can be emitted to cause a reflected electromagnetic pulse. The reflected pulse can be received and a signal indicative of a time derivative or slope of the intensity of the pulse can be produced. The signal indicative of the time derivative or slope can be compared with a reference slope, and a peak detected signal can be outputted when the signal indicative of the time derivative or slope passes the reference slope.”; [0017] reciting “It can be advantageous for LiDAR sensors to keep their avalanche photodiode(s) operating with a constant gain. For example, LiDAR sensors can use the amplitude of the electric pulse provided by the avalanche photodiode to infer information about a target surface of an object, primarily related to the surface's reflectance.”; [0019] recited “In the embodiments described herein, a LiDAR sensor optionally can directly determine the avalanche photodiode's gain relationship to its bias voltage and enable its gain to be held constant.”)…
40 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Werschnik in view of Safira, Li, and Lee) to incorporate the teachings of Schwarz to provide a method that can allow the voltage signal taught by Werschnik in view of Safira, Li, and Lee to be constant. Doing so would avoid suspending the sensor’s range measurements as stated by Schwarz ([0019] recited).
41 Regarding claim 9, Werschnik in view of Safira, Li, Lee, and Schwarz teaches the LIDAR target simulation system of claim 8 (see claims 1 and 7-8 rejections above), wherein the signal response generator includes circuitry configured to adjust a magnitude of the constant (Schwarz; See claim 8 for “constant”) voltage signal and/or the predefined threshold based on the at least one simulated scan signal of the LIDAR device and/or based on the test scenario (Lee; [0297] reciting “As shown in FIG. 21, the dynamic threshold may vary according to the magnitude of the input signal, like TH0 and TH1. The dynamic threshold may vary in proportion to the magnitude of the input signal of the noise remover 330. For example, as shown in FIG. 21, when the magnitude of the received signal increases, the dynamic threshold increases from TH0 from TH1. On the other hand, the dynamic threshold may be lowered when the magnitude of the received signal decreases.”).
42 Regarding claim 10, Werschnik in view of Safira, Li, Lee, and Schwarz teaches the LIDAR target simulation system of claim 8 (see claims 1 and 7-8 rejections above), wherein the analog integrator includes circuitry configured to start integrating the constant (Schwarz; See claim 8 for “constant”) voltage signal upon detection of the at least one scan signal (Lee; [0316] reciting “The lidar system may further include: a trans impedance amplifier configured to convert a current input from the activated pixels into a voltage and amplify the voltage; an integrator configured to integrate an output signal of the trans impedance amplifier; a noise remover configured to remove noise from an output signal of the integrator; an analog to digital converter configured to convert the output signal of the noise remover into a digital signal; and a detector configured to analyze the digital signal to generate depth information for each scan angle.”).
43 Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Werschnik et al. (DE 102019106129 A1) in view of Safira et al. (US 20220058309 A1) and Li et al. (US 20210356561 A1) as of claim 1, further in view of Hoffmann et al. (DE 102019118039 A1).
44 Regarding claim 14, Werschnik in view of Safira and Li teaches the LIDAR target simulation system according to claim 1 (see claim 1 rejection above), but does not explicitly teach wherein the LIDAR device is a flash LIDAR device.
45 Hoffmann teaches wherein the LIDAR device is a flash LIDAR device ([0005] reciting “LIDAR systems can be designed as flash LIDAR, wherein a single, very strong pulse is emitted on the transmission side.”; [0017] reciting “The LIDAR can be a flash LIDAR, a scan LIDAR or also a multibeam LIDAR. As a rule, the number and resolution of the transceiver pairs in the matrix must be adapted for this purpose.”).
46 It would have been obvious to one with ordinary skill before the effective filing date of the claimed invention, to have modified the method (taught by Werschnik in view of Safira and Li) to incorporate the teachings of to provide Hoffmann to have the LIDAR device taught by Werschnik in view of Safira and Li to be a flash LIDAR device that can deal with similar pulse methods. Doing so would allow more optical signals emitted by the measuring device as stated by Hoffmann ([0017] recited).
Conclusion
47 Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
48 Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNY TRAN LE whose telephone number is (571)272-5680. The examiner can normally be reached Mon-Thu: 7:30am-5pm; First Fridays Off; Second Fridays: 7:30am-4pm.
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/JOHNNY T LE/Examiner, Art Unit 2614
/KENT W CHANG/Supervisory Patent Examiner, Art Unit 2614
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