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 .
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-7, 9-17, and 18-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sun et al.(US 2023/0366993 A1).
Regarding claim 1, Sun teaches
A lidar system comprising: (The present invention is directed to LiDAR systems and methods. (paragraph 0004))
a laser source configured to generate a pulsed laser at a first time, the pulsed laser being characterized by a first pulse width; (The laser source generates a pulsed laser, When the received pulse energy is low (less than the second threshold), the pulse width is used for matching. (paragraph 0005 and 0039) the laser source is generating the pulse laser with a pulse width)
an optical module configured receiving a reflected laser signal; (the optical module receives the reflected laser signal. (paragraph 0005))
a pixel circuit configured to generate electrical outputs based on the reflected laser signal, the pixel circuit comprising m pixels (The pixel circuit generates an electrical output based on the reflected signal, Lidar system 700 is configured to reconstruct images, with distance information, using a SPAD array that includes many SPAD pixels. (paragraph 0005 and 0098 Fig. 5) This shows the pixel circuit also called the SPAD Sensor or SPAD array generates the electrical outputs based on the reflected signal and comprises of multiple pixels)
a time-to-digital converter (TDC) configured to generate m histogram data corresponding to m pixels, each of the m histogram data comprising n intensity values corresponding to n time bins; (The output of TDC 750 is stored at a memory as a histogram data structure. For example, in a histogram data structure, memory blocks correspond to predefined time bins, and each of the memory blocks stores an intensity value (e.g., number of photons received within a predefined time interval). (paragraph 0103))
a memory device configured to store the histogram data; (The output of TDC 750 is stored at a memory as a histogram data structure (paragraph 0103))
and a processor module configured to: generate a first data array comprising m values corresponding to the m pixels, each of the m values being a function of a sum corresponding n time bin values; (The output of TDC 750 is stored at a memory as a histogram data structure. For example, in a histogram data structure, memory blocks correspond to predefined time bins, and each of the memory blocks stores an intensity value (e.g., number of photons received within a predefined time interval). (paragraph 0103 and Fig. 5) The TDC in the prior art is generating histogram data i.e. first data array. This function could also be completed by the processor.)
generate a second data array comprising m entries corresponding to the m pixels, each of m entries comprising one or more total peak values; (The output of TDC 750 is stored at a memory as a histogram data structure. For example, in a histogram data structure, memory blocks correspond to predefined time bins, and each of the memory blocks stores an intensity value (e.g., number of photons received within a predefined time interval). (paragraph 0103 and Fig. 5) The TDC in the prior art is generating histogram data i.e. first data array. This function could also be completed by the processor. The prior art teaches of only one set of array data i.e. histogram data. This second data array is a subset of the first data array. The prior arts histogram data contains both information of the first and second data array.)
determine a first vector using the first data array; (Obtain N1 peaks based on histogram data. (paragraph 0046 Fig. 2) The N1 peaks are equivalent to the first vector using the histogram data. The first vector is an array of values that come from the first data array. The N1 peaks are also an array of values.)
determine a second vector using the second data array; (Select N2 peaks as candidate peaks, with N1>N2. (paragraph 0047 Fig. 2) The N2 peaks are equivalent to the second vector and use the histogram data. The second vector is an array of values that come from the second data array. The N2 peaks are also an array of values.)
remove one or more artifact peaks from the second data array using a similarity function; (In various embodiments, peaks can be derived from histogram data, and signal peaks can be acquired through a single filtering process. The target peak can subsequently be obtained using a matching function. By employing a two-stage filtering approach, invalid peaks can be effectively removed, (paragraph 0095) The target peak is being identified using a matching function and then being removed.)
and determine a target object distance using at least the second data array. (The processor module calculates the preliminary peak location, compares it to a threshold value, and calculates the time of flight (TOF) value to determine the target object distance (paragraph 0008))
Regarding claim 2, Sun teaches
The lidar system of claim 1, wherein the processor module is further configured to identify a preliminary peak location using at least the second data array. (The processor module identifies multiple peaks and selects at least a first peak associated with a preliminary peak location and characterized by a second pulse width. (paragraph 0101))
Regarding claim 3, Sun teaches
• The lidar system of claim 2, wherein the processor module is further configured to calculate a time of flight (TOF) value using the first time and a second time, the second time being based on the preliminary peak location. (The processor module identifies multiple peaks and selects at least a first peak associated with a preliminary peak location and characterized by a second pulse width. It also associates an artifact type to at least a second and third peak from the plurality of peaks, with the second peak being characterized by a variance. Using the histogram data, the processor module calculates the preliminary peak location and compares it to a threshold value to determine the target object distance by calculating the time of flight (TOF) value. Additionally, the output of splitter 722 provides the timing of the outgoing light signal, and this timing information is later used in ToF calculations. (paragraph 0010 and 0099) The processor uses multiple peaks to calculate the TOF value. Each peak has an associated time value that is being used to calculate TOF. The prior art teaches of the first peak being the preliminary peak location. The second peak could be associated to the preliminary peak location to achieve the same result.)
Regarding claim 4, Sun teaches
• The lidar system of claim 1, wherein the pixel circuit comprise a SPAD sensor array. (a SPAD array that includes many SPAD pixels. (paragraph 0098))
Regarding claim 5, Sun teaches
• The lidar system of claim 1, the optical module comprises multiple lens elements, the one or more artifact peaks being associated with an internal reflection attributed to the multiple lens elements. (It is understood that lens 720 refers to an optical module that may include multiple optical and/or mechanical elements. In certain implementations, lens 720 includes diffractive optical elements to create a desired output optical pattern. Lens 720 may include focusing and optical correction elements, configured in multiple lens elements. Glare results from light reflections within the lens (paragraph 0042 and 0098))
Regarding claim 6, Sun teaches
• The lidar system of claim 1, wherein the one or more artifact peaks is associated with a glare caused by a secondary light source. (glare problem caused by fully exposed or dispersed light source locations. (paragraph 0101))
Regarding claim 7, Sun teaches
• The lidar system of claim 1, wherein the one or more artifact peak is associated with a semitransparent object. (In various embodiments, the variance is associated with dust particle locations or glass reflections. Additionally, the processor module may evaluate a matching function using at least the first and second peaks or using the second pulse width (paragraph 0011))
Regarding claim 9, Sun teaches
• The lidar system of claim 8, wherein the one or more artifact peaks are associated with low similarity values. (Glass identification. The reflectivity of glass varies significantly. If the reflectivity scale coefficient across multiple frames is generally small and there are image points, it can be determined that the point is likely a glass point. (paragraph 0043))
Regarding claim 10, Sun teaches
• A lidar system comprising: (The present invention is directed to LiDAR systems and methods. (paragraph 0004))
a laser source configured to generate a pulsed laser at a first time, the pulsed laser being characterized by a first pulse width; (The laser source generates a pulsed laser, When the received pulse energy is low (less than the second threshold), the pulse width is used for matching. (paragraph 0005 and 0039) the laser source is generating the pulse laser with a pulse width)
an optical module configured receiving a reflected laser signal; (the optical module receives the reflected laser signal. (paragraph 0005))
a pixel circuit configured to generate electrical outputs based on the reflected laser signal, the pixel circuit comprising m pixels (The pixel circuit generates an electrical output based on the reflected signal, Lidar system 700 is configured to reconstruct images, with distance information, using a SPAD array that includes many SPAD pixels. (paragraph 0005 and 0098 Fig. 5) This shows the pixel circuit also called the SPAD Sensor or SPAD array generates the electrical outputs based on the reflected signal and comprises of multiple pixels)
a time-to-digital converter (TDC) configured to generate m histogram data corresponding to m pixels, each of the m histogram data comprising n intensity values corresponding to n time bins; (The output of TDC 750 is stored at a memory as a histogram data structure. For example, in a histogram data structure, memory blocks correspond to predefined time bins, and each of the memory blocks stores an intensity value (e.g., number of photons received within a predefined time interval). (paragraph 0103))
a memory device configured to store the histogram data; (The output of TDC 750 is stored at a memory as a histogram data structure (paragraph 0103))
and a processor module configured to: identify l histograms from the m histogram data, the l histograms comprising a first histogram and a second histogram; (The output of TDC 750 is stored at a memory as a histogram data structure. For example, in a histogram data structure, memory blocks correspond to predefined time bins, and each of the memory blocks stores an intensity value (e.g., number of photons received within a predefined time interval). (paragraph 0103) This processor module is identifying the same data the TDC has already generated.)
identify a first peak from the first histogram at a first bin location; (Obtain N1 peaks based on histogram data. (paragraph 0046 Fig. 2) The N1 peaks involve obtaining a first peak which would correspond with a first bin location)
identify a second peak from the second histogram at a second bin location corresponding to the first bin location; (Select N2 peaks as candidate peaks, with N1>N2. (paragraph 0047 Fig. 2) The N2 peaks would be at a second bin location that could correspond to the first bin.)
calculate a ratio between a first intensity of the first peak and a second intensity of the second peak; (Another approach to processing LiDAR data involves calculating the signal-to-noise ratio (SNR) for each peak, (paragraph 0023) The signal to noise ratio is a comparison of peaks to determine if a peak is considered a useable peak or artifact peak)
determine whether the second peak is an artifact peak based on the ratio; (Another approach to processing LiDAR data involves calculating the signal-to-noise ratio (SNR) for each peak, (paragraph 0023) The signal to noise ratio is a comparison of peaks to determine if a peak is considered a useable peak or artifact peak)
determine a target object distance using at least the first peak. (The processor module identifies and selects peaks from the histogram data, calculates a preliminary peak location associated with the target object distance, and compares it to a threshold value. The processor module then calculates the time of flight (TOF) value and determines the target object distance. Various embodiments of the system include configurations for removing additional peaks, handling non-linear responses, using SPAD sensors, and comparing peak values to different threshold values for various scenarios such as high reflection, glare, glass reflection, and dust particles. The processor module may also identify additional peaks and determine location differences in some embodiments. (paragraph 0006))
Regarding claim 11, Sun teaches
• The system of claim 10, wherein the artifact peak is associated with a glare caused by a secondary light source. (glare problem caused by fully exposed or dispersed light source locations. (paragraph 0101) This indicates the glare can be caused by a secondary light source.)
Regarding claim 12, Sun teaches
• The system of claim 10, wherein the processor module is further configured to remove the second peak. (In various embodiments, peaks can be derived from histogram data, and signal peaks can be acquired through a single filtering process. The target peak can subsequently be obtained using a matching function. By employing a two-stage filtering approach, invalid peaks can be effectively removed, resulting in a higher elimination rate of invalid peaks compared to a single filtering method. (paragraph 0095) This involves removing multiple peaks which can include two peaks.)
Regarding claim 13, Sun teaches
• The system of claim 10, wherein the processor module is further configured to identify and remove a third peak. (In various embodiments, peaks can be derived from histogram data, and signal peaks can be acquired through a single filtering process. The target peak can subsequently be obtained using a matching function. By employing a two-stage filtering approach, invalid peaks can be effectively removed, resulting in a higher elimination rate of invalid peaks compared to a single filtering method. (paragraph 0095) This involves removing multiple peaks which can include three peaks.)
Regarding claim 14, Sun teaches
• The system of claim 10, wherein the first histogram is associated with a first SPAD pixel and the second histogram is associated with a second SPAD pixel. (In various embodiments, the SPAD sensor 740 is implemented as a macro pixel, commonly referred to as a digital silicon photomultiplier (dSiPM). The TDC 750 consists of a number of TDCs (e.g., equal to the number of SPAD pixels) configured to process the arrival time of multiple pulses generated by the SPAD sensor 740. For instance, the TDCs in block 750 may be individually connected to their corresponding SPAD pixels in block 740 for efficient signal processing. (paragraph 0102))
Regarding claim 15, Sun teaches
• A lidar system comprising: (The present invention is directed to LiDAR systems and methods. (paragraph 0004))
a laser source configured to generate a pulsed laser at a first time, the pulsed laser being characterized by a first pulse width; (The laser source generates a pulsed laser, When the received pulse energy is low (less than the second threshold), the pulse width is used for matching. (paragraph 0005 and 0039) the laser source is generating the pulse laser with a pulse width)
a control module configured to process the first time; (Control module 730 manages operations and various aspects of lidar system 700. As shown, control module 730 is coupled to laser 710 and splitter 722, along with other components. Depending on the embodiment, control module 130 can be implemented using one or more microprocessors. For example, control module 730 may include a microprocessor that can be used for timing control of input and output and power control of laser 710. (paragraph 0099))
an optical module configured receiving a reflected laser signal; (the optical module receives the reflected laser signal. (paragraph 0005))
a pixel circuit configured to generate electrical outputs based on the reflected laser signal, the pixel circuit comprising m pixels; (The pixel circuit generates an electrical output based on the reflected signal, Lidar system 700 is configured to reconstruct images, with distance information, using a SPAD array that includes many SPAD pixels. (paragraph 0005 and 0098 Fig. 5) This shows the pixel circuit also called the SPAD Sensor or SPAD array generates the electrical outputs based on the reflected signal and comprises of multiple pixels)
a time-to-digital converter (TDC) configured to generate m histogram data corresponding to m pixels, each of the m histogram data comprising n intensity values corresponding to n time bins; (The output of TDC 750 is stored at a memory as a histogram data structure. For example, in a histogram data structure, memory blocks correspond to predefined time bins, and each of the memory blocks stores an intensity value (e.g., number of photons received within a predefined time interval). (paragraph 0103))
a memory device configured to store the histogram data; (The output of TDC 750 is stored at a memory as a histogram data structure (paragraph 0103))
and a processor module configured to: generate a first data array comprising m values corresponding to the m pixels, each of the m values being a function of a sum corresponding n time bin values; (The output of TDC 750 is stored at a memory as a histogram data structure. For example, in a histogram data structure, memory blocks correspond to predefined time bins, and each of the memory blocks stores an intensity value (e.g., number of photons received within a predefined time interval). (paragraph 0103 and Fig. 5) The TDC in the prior art is generating histogram data i.e. first data array. This function could also be completed by the processor.)
generate a second data array comprising m entries corresponding to the m pixels, each of m entries comprising one or more total peak values; (The output of TDC 750 is stored at a memory as a histogram data structure. For example, in a histogram data structure, memory blocks correspond to predefined time bins, and each of the memory blocks stores an intensity value (e.g., number of photons received within a predefined time interval). (paragraph 0103 and Fig. 5) The TDC in the prior art is generating histogram data i.e. first data array. This function could also be completed by the processor. The prior art teaches of only one set of array data i.e. histogram data. This second data array is a subset of the first data array. The prior arts histogram data contains both information of the first and second data array.)
determine a first vector using the first data array; (Obtain N1 peaks based on histogram data. (paragraph 0046 Fig. 2) The N1 peaks are equivalent to the first vector using the histogram data. The first vector is an array of values that come from the first data array. The N1 peaks are also an array of values.)
determine a second vector using the second data array; (Select N2 peaks as candidate peaks, with N1>N2. (paragraph 0047 Fig. 2) The N2 peaks are equivalent to the second vector and use the histogram data. The second vector is an array of values that come from the second data array. The N2 peaks are also an array of values.)
identify a first peak from the second data array using a similarity function. (In various embodiments, peaks can be derived from histogram data, and signal peaks can be acquired through a single filtering process. The target peak can subsequently be obtained using a matching function. By employing a two-stage filtering approach, invalid peaks can be effectively removed, (paragraph 0095) The target peak is being identified using a matching function and then being removed.)
Regarding claim 16, Sun teaches
• The system of claim 15, wherein the first peak is associated with a glare artifact. (The left peak might be caused by glare. If conventional technology is used, i.e., selecting the highest peak as the effective peak of the target object, (paragraph 0074))
Regarding claim 17, Sun teaches
• The system of claim 15, further comprising an optical splitter configured to direct a portion of the pulsed laser to the control module. (Control module 730 manages operations and various aspects of lidar system 700. As shown, control module 730 is coupled to laser 710 and splitter 722, along with other components. Depending on the embodiment, control module 130 can be implemented using one or more microprocessors. For example, control module 730 may include a microprocessor that can be used for timing control of input and output and power control of laser 710. Components such as TDC 750 and digital signal processor (DSP) 760 as shown are functional blocks that are—on the chip layer—implemented with the same processor(s) for the control module 730. In addition to providing control signal signals to laser 710, control module 730 also receives the output of the laser 710 via splitter 722. (paragraph 0099))
Regarding claim 18, Sun teaches
The system of claim 15, wherein the processor module is further configured to calculate similarity coefficients using the similarity function. (In various embodiments, peaks can be derived from histogram data, and signal peaks can be acquired through a single filtering process. The target peak can subsequently be obtained using a matching function. By employing a two-stage filtering approach, invalid peaks can be effectively removed, (paragraph 0095) Since a matching function i.e. similarity function is being used a similarity coefficient is inherent to the function)
Regarding claim 19, Sun teaches
• The system of claim 15, wherein the processor module is further configured to calculate a second time based on a second peak being selected using at least the second data array. (The processor module identifies multiple peaks and selects at least a first peak associated with a preliminary peak location and characterized by a second pulse width. It also associates an artifact type to at least a second and third peak from the plurality of peaks, with the second peak being characterized by a variance. Using the histogram data, the processor module calculates the preliminary peak location and compares it to a threshold value to determine the target object distance by calculating the time of flight (TOF) value. (paragraph 0010) Each of the peaks has a peak location that corresponds to a certain time)
Regarding claim 20, Sun teaches
• The system of claim 19, wherein the processor module is further configured determine a distance based on a difference between the first time and the second time. (lidar system 700 measures distance by calculating the time differences between transmitted light signals and the corresponding received signals. (paragraph 0097))
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.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sun et al. (US Appl. No 18/315297) in view of Yates et al. (US Patent 10725157 B1).
Regarding claim 8, Sun teaches all of the elements of claim 1 as previously stated. Yates teaches of wherein the processor module is further configured to calculate a Pearson correlation coefficient using at least the first data array and the second data array. (Once the two data sets have been obtained, analysis component 318 can perform correlation analysis on the two data sets to determine whether the two data sets demonstrate a degree of correlation in excess of a correlation threshold indicative of cross-correlation between the two pixels 414a and 414b. In this regard, analysis component 318 can use any suitable technique for determining correlation or non-correlation of the two data sets, including but not limited to Pearson's correlation coefficient (paragraph111)).
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 disclosed in Yates into the invention of Sun. Both references are considered analogous art to the claimed invention as they both disclose a time of flight sensor for distance measurements. The combination would be obvious with a reasonable expectation of success in order to use the Pearson correlation coefficient to compare data to get an increase in accuracy for object distance.
Conclusion
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/ETHAN JAKOB SLAUGHTER/Examiner, Art Unit 3648
/VLADIMIR MAGLOIRE/Supervisory Patent Examiner, Art Unit 3648