Abstract: A light detection and ranging apparatus (LIDAR) includes at least one waveguide including a first cladding layer having a first refractive index and a second cladding layer having multiple second refractive indexes to expand an optical mode of an optical beam propagating within the waveguide. The second refractive indexes include a gradient of refractive indexes and the first refractive index is less than the second refractive indexes.

Abstract: A set of POIs of a point cloud are received at a first filter, where each POI of the set of POIs comprises one or more points. Each POI of the set of POIs is filtered. A set of neighborhood points of a POI is selected. A metric for the set of neighborhood points is computed based on a property of the set of neighborhood points and the POI, wherein the property comprises a velocity. Based on the metric, whether to accept the POI, modify the POI, reject the POI, or transmit the POI to a second filter, to extract at least one of range or velocity information related to the target is determined. Provided the POI is not accepted, modified, or rejected, the POI is transmitted to the second filter to determine whether to accept, modify, or reject the POI to extract the at least one of range or velocity information related to the target.

Abstract: A method of compensation in a light detection and ranging (LIDAR) system. The method includes applying a first frequency shift to a target signal to compensate for doppler shift in the target signal and performing a phase impairment correction on the target signal to produce a corrected target signal. The method further includes undoing the first frequency shift on the corrected target signal.

Abstract: A method of singulating a die of a wafer includes etching a trench on a first surface of a wafer comprising a die and performing a cut on a second surface of the wafer, wherein the cut overlaps with the trench on the first surface of the wafer to separate the die from the wafer.

Abstract: A method of determining range and velocity information of a target in a light detection and ranging (LiDAR) system, includes determining a set of signal power density spectrums in a frequency domain based on an optical signal returned from a target, wherein a number of the set of signal power density spectrums is determined based on an expected mirror Doppler shift associated with the optical signal returned from the target. The method further includes averaging the set of signal power density spectrums to generate a compensated signal power density spectrum and detecting a peak value in the compensated signal power density spectrum to determine range and velocity information related to a target based on a corresponding frequency of the peak value of compensated signal power density spectrum.

Abstract: A light detection and ranging (LIDAR) system includes a processor and a memory. The memory stores a plurality of data points and stores instructions that cause the LIDAR system to: generate the plurality of data points associated with one or more return beams corresponding to one or more optical beams transmitted towards a target; perform a plurality of processing operations on the plurality of data points to generate a point cloud corresponding to the target, wherein a first processing operation of the plurality of processing operations is configured to output a pair of indices as input to a second processing operation of the plurality of processing operations, the pair of indices referring to memory locations of a first data point and a second data point of the plurality of data points, respectively; and calculate a range and a velocity of the target based on the point cloud.

Abstract: A method of operating a light detection and ranging (LiDAR) system is provided that includes performing a scene measurement using a LiDAR sensor capable of measuring Doppler per point. The method also includes estimating a velocity of the LiDAR sensor with respect to static points within the scene based on the scene measurement. The method may also include compensating for the velocity of the LiDAR sensor and compensating for a Doppler velocity of the LiDAR sensor.

Abstract: A method of operating a frequency-modulated continuous wave (FMCW) light detection and ranging (LIDAR) system is provided. The method includes transmitting a beam of co-propagating, cross-polarized light to a target. The method includes receiving return light reflected from the target by at least one detector. The method further includes transforming a polarization state of the beam at a transformation rate faster than a data collection rate from the at least one detector.

Abstract: A method generates first points based on a first scan of an environment that includes one or more moving objects. The method transforms the first points into a first static frame, which includes removing one or more of the first points corresponding to the one or more moving objects. The method generates second points based on a second scan of the environment that includes the one or more moving objects. The method transforms the second points into a second static frame, which includes removing one or more of the second points corresponding to the one or more moving objects. The method combines the first static frame and the second static frame into an accumulated static frame, which has an increase in resolution compared with the first static frame. The method then loads the accumulated static frame into a point cloud.

Abstract: A light detection and ranging (LIDAR) system transmits, towards a target, a set of chirp signals. The LIDAR system receives from the target, a set of adjusted chirp signals. The LIDAR system then determines, based on the set of adjusted chirp signals, a degree of ghosting mitigation to compensate for a ghost target appearing in a point cloud at a location where no real target exists.

Abstract: A system uses range and Doppler velocity measurements from a lidar system and images from a video system to estimate a six degree-of-freedom trajectory of a target. The system estimates this trajectory in two stages: a first stage in which the range and Doppler measurements from the lidar system along with various feature measurements obtained from the images from the video system are used to estimate first stage motion aspects of the target (i.e., the trajectory of the target); and a second stage in which the images from the video system and the first stage motion aspects of the target are used to estimate second stage motion aspects of the target. Once the second stage motion aspects of the target are estimated, a three-dimensional image of the target may be generated.

Abstract: Systems and methods for controlling camera settings of a camera to improve detection of faces in an uncontrolled environment are described. A first image is received from the camera, where the first image is captured by the camera at a first set of camera settings. A face is detected in the first image. The camera is adjusted to a second set of camera settings based on the detected face, where the second set of camera settings different from the first set of camera settings. A second image is received from the camera, where the second image is captured by the camera at the second set of camera settings. The face is detected in the second image. A quality metric of the face in the second image is determined where the quality metric is indicative of an image quality of the face in the second image.

Abstract: A frequency modulated continuous wave (FMCW) light detection and ranging (LIDAR) system includes a processor and a memory. The memory stores instructions that, when executed by the processor, cause the system to: generate subbands in a frequency domain based on a range-dependent time domain baseband signal, classify each subband into a subband type, select processing parameters for each subband based on the respective subband type, and process each of the subbands using the selected processing parameters for the subband.

Abstract: A system and method for detecting a potential match between a candidate facial image and a dataset of facial images is described. Some implementations of the invention determine whether a candidate facial image (or multiple facial images) of a person taken, for example, at point of entry corresponds to one or more facial images stored in a dataset of persons of interest (e.g., suspects, criminals, terrorists, employees, VIPs, “whales,” etc.). Some implementations of the invention detect potential fraud in a dataset of facial images. In a first form of potential fraud, a same facial image is associated with multiple identities. In a second form of potential fraud, different facial images are associated with a single identity, as in the case, for example, of identity theft. According to various implementations of the invention, spectral clustering techniques are used to determine a likelihood that pairs of facial images (or pairs of facial image sets) correspond to the person or different persons.

Abstract: A system including an optical scanner to transmit an optical beam towards an object. The system includes a first optical element to receive a returned reflection having a lag angle; and direct the returned reflection to generate a first directed beam. The system includes a beam directing unit to receive the first directed beam; and direct, based on a first array voltage, the first directed beam to generate a second directed beam at a first location on a different optical element. The beam directing unit to direct, based on a second array voltage, the second steered beam from the first location on the different optical element to a second location on the different optical element to compensate for the lag angle.

Abstract: Free-space optics for use in a light detection and ranging (LIDAR) apparatus include a polarization beam-splitter (PBS) to direct an optical beam in a first direction toward a target environment and to propagate a portion of the optical beam in a second direction for receipt by a photodetector (PD), a polarization wave plate (PWP) to convert the optical beam from a first polarization to a second polarization, and to convert the target return signal from a third polarization to a fourth polarization, and a lens system coupled between the PBS and the PWP to magnify the optical beam. The propagated portion of the optical beam comprises a local oscillator (LO) signal to mix with a target return signal to generate target information.

Abstract: A method includes transmitting a plurality of optical beams towards a plurality of targets, receiving a plurality of return signals based on reflections of the plurality of optical beams from the plurality of targets, and generating a first plurality of peaks each associated with a different up-chirp frequency of the plurality of optical beams and a second plurality of peaks each associated with a different down-chirp frequency of the plurality of optical beams. The method further includes determining peak shape similarities between each of the first plurality of peaks and the second plurality of peaks, pairing each peak of the first plurality of peaks with a peak of the second plurality of peaks based on the peak shape similarities, and identifying the plurality of targets based on the pairing.

Abstract: A light detection and ranging (LIDAR) system is provided that includes a first optical source and a second optical source configured to emit respectively a first optical beam and a second optical beam that are nondegenerate and are chirped antiphase, lensing optics to direct the first and second optical beams toward a target, and collect a first return signal and a second return signal, and a first optical detector and a second optical detector configured to generate a first signal from the first return signal mixed with a first local oscillator and a second signal from the second return signal mixed with the second local oscillator.

Abstract: A light detection and ranging (LIDAR) system including a processor to receive a return signal from a target based on an optical beam transmitted towards the target and receive a baseband signal in a time domain based on the return signal. The processor of the LIDAR system further to produce a comparison of signal peaks of the baseband signal with an estimate of LIDAR system noise in the frequency domain, and identify targets based on the comparison.

Abstract: A return signal from a target is received based on an optical beam from an optical source of a LiDAR system. The return signal is sampled and converted to a frequency domain, where the return signal comprises a first frequency waveform. A matched filter is selected, where the matched filter comprises a second frequency waveform to match the first frequency waveform. The matched filter is updated by updating a set of coefficients of the second frequency waveform. The return signal is filtered by the updated matched filter to generate a filtered return signal to extract range and velocity information of the target.