Abstract: This document describes techniques and systems to vary waveforms across frames in lidar systems. The described lidar system transmits signals with different waveforms for the same pixel of consecutive frames to avoid a return signal overlapping with a noise spike or a frequency component of another return signal. The different waveforms can be formed using different frequency modulations, different amplitude modulations, or a combination thereof for the same pixel of consecutive frames. The lidar system can change the waveform of the transmit signal for the same pixel of a subsequent frame automatically or in response to determining that a signal-to-noise ratio of the return signal of an initial frame is below a threshold value. In this way, the lidar system can increase the signal-to-noise ratios in return signals. These improvements allow the lidar system to increase its accuracy in determining the characteristics of objects that reflected the return signals.

Abstract: This document describes techniques and systems to resolve return signals among pixels in lidar systems. The described lidar system transmits signals with different waveforms for consecutive pixels to associate return signals with their corresponding pixels. During a detection window, the lidar system receives a return signal and compares it in the frequency domain to at least two template signals. The template signals include the waveform of an initial pixel and a subsequent pixel of two consecutive pixels, respectively. The lidar system then determines, based on the comparison to the template signals, the pixel to which the return signal corresponds and determines a characteristic of an object that reflected the return signal. In this way, the lidar system can confidently resolve detections to reduce the time between pixels. This improvement allows the described lidar system to operate at faster scanning speeds and realize a faster reaction time for automotive applications.

Abstract: Techniques and apparatuses are described that implement a low-cost readout module for a lidar system. The low-cost readout module includes a timing readout path and an intensity readout path, which are coupled to a receive channel of the lidar system. The timing readout path generates time-sensitive information using a threshold-triggered timing circuit, which can include a time-to-digital converter. The intensity readout path generates non-time-sensitive information using a hold-and-sample circuit, which can include a hold circuit and an analog-to-digital converter. By utilizing the threshold-triggered timing circuit to provide time-sensitive data and the hold-and-sample circuit to provide non-time-sensitive information, the readout module can have a lower cost than other readout modules that utilize a high-performance analog-to-digital converter for each receive channel.

Abstract: This document describes techniques and systems to resolve return signals among pixels in lidar systems. The described lidar system transmits signals with different waveforms for consecutive pixels to associate return signals with their corresponding pixels. During a detection window, the lidar system receives a return signal and compares it in the frequency domain to at least two template signals. The template signals include the waveform of an initial pixel and a subsequent pixel of two consecutive pixels, respectively. The lidar system then determines, based on the comparison to the template signals, the pixel to which the return signal corresponds and determines a characteristic of an object that reflected the return signal. In this way, the lidar system can confidently resolve detections to reduce the time between pixels. This improvement allows the described lidar system to operate at faster scanning speeds and realize a faster reaction time for automotive applications.

Abstract: This document describes techniques and systems to increase the dynamic range of time-of-flight (ToF) lidar systems. The described lidar system adjusts, based on the energy of a first return pulse, the bias voltage of a photodetector for other return pulses of the object pixel. The bias voltage can be adjusted down for highly-reflective or close-range objects. Similarly, the bias voltage can be increased for low-reflectivity or long-range objects. The ability of the described lidar system to adjust the bias voltage of the photodetector for each object pixel increases the dynamic range of the lidar system without additional hardware or a complex readout. The increased dynamic range allows the described lidar system to maintain a long-range capability, while accurately measuring return-pulse intensity for detecting close-range or highly-reflective objects.

Abstract: An illustrative example object detection system includes a sensor having a field of view. The sensor is configured to emit radiation and to detect at least some of the radiation reflected by an object within the field of view. A panel in the field of view allows the radiation to pass through the panel. The panel being is configured to be set in a fixed position relative to a vehicle coordinate system. A plurality of reflective alignment markers are situated on the panel in the field of view. The reflective alignment markers reflect radiation emitted by the sensor back toward the sensor. A processor is configured to determine an alignment of the sensor with the vehicle coordinate system based on an indication from the sensor regarding radiation reflected by the reflective alignment markers and detected by the sensor.

Abstract: An illustrative example object detection system includes a sensor having a field of view. The sensor is configured to emit radiation and to detect at least some of the radiation reflected by an object within the field of view. A panel in the field of view allows the radiation to pass through the panel. The panel being is configured to be set in a fixed position relative to a vehicle coordinate system. A plurality of reflective alignment markers are situated on the panel in the field of view. The reflective alignment markers reflect radiation emitted by the sensor back toward the sensor. A processor is configured to determine an alignment of the sensor with the vehicle coordinate system based on an indication from the sensor regarding radiation reflected by the reflective alignment markers and detected by the sensor.

Abstract: This document describes analysis of a functional architecture under the Safety of Intended Functionality of System (SOTIF) standard through construction of Bayesian networks that model performance of the functional architecture. The Bayesian networks model performance of the functional architecture given triggering conditions that result in at least some possible hazards. Constructed based on estimated probability data or probability data collected, the Bayesian networks quantify uncertainty of the system performance using conditional probabilities representing causal relationships between modules or components of the functional architecture. This allows inference and other probabilistic algorithms to be performed by the Bayesian network to calculate an overall hazard-rate of the functional architecture as well as identifying weaknesses in the functional architecture. A hazard-rate-of-occurrence can be estimated for many different system configurations and use cases to prove whether SOTIF is achieved.

Abstract: This document describes techniques and systems to vary waveforms across frames in lidar systems. The described lidar system transmits signals with different waveforms for the same pixel of consecutive frames to avoid a return signal overlapping with a noise spike or a frequency component of another return signal. The different waveforms can be formed using different frequency modulations, different amplitude modulations, or a combination thereof for the same pixel of consecutive frames. The lidar system can change the waveform of the transmit signal for the same pixel of a subsequent frame automatically or in response to determining that a signal-to-noise ratio of the return signal of an initial frame is below a threshold value. In this way, the lidar system can increase the signal-to-noise ratios in return signals. These improvements allow the lidar system to increase its accuracy in determining the characteristics of objects that reflected the return signals.

Abstract: This document describes techniques and systems to resolve return signals among pixels in lidar systems. The described lidar system transmits signals with different waveforms for consecutive pixels to associate return signals with their corresponding pixels. During a detection window, the lidar system receives a return signal and compares it in the frequency domain to at least two template signals. The template signals include the waveform of an initial pixel and a subsequent pixel of two consecutive pixels, respectively. The lidar system then determines, based on the comparison to the template signals, the pixel to which the return signal corresponds and determines a characteristic of an object that reflected the return signal. In this way, the lidar system can confidently resolve detections to reduce the time between pixels. This improvement allows the described lidar system to operate at faster scanning speeds and realize a faster reaction time for automotive applications.

Abstract: This document describes techniques and systems to increase the dynamic range of time-of-flight (ToF) lidar systems. The described lidar system adjusts, based on the energy of a first return pulse, the bias voltage of a photodetector for other return pulses of the object pixel. The bias voltage can be adjusted down for highly-reflective or close-range objects. Similarly, the bias voltage can be increased for low-reflectivity or long-range objects. The ability of the described lidar system to adjust the bias voltage of the photodetector for each object pixel increases the dynamic range of the lidar system without additional hardware or a complex readout. The increased dynamic range allows the described lidar system to maintain a long-range capability, while accurately measuring return-pulse intensity for detecting close-range or highly-reflective objects.

Abstract: Techniques and apparatuses are described that implement a low-cost readout module for a lidar system. The low-cost readout module includes a timing readout path and an intensity readout path, which are coupled to a receive channel of the lidar system. The timing readout path generates time-sensitive information using a threshold-triggered timing circuit, which can include a time-to-digital converter. The intensity readout path generates non-time-sensitive information using a hold-and-sample circuit, which can include a hold circuit and an analog-to-digital converter. By utilizing the threshold-triggered timing circuit to provide time-sensitive data and the hold-and-sample circuit to provide non-time-sensitive information, the readout module can have a lower cost than other readout modules that utilize a high-performance analog-to-digital converter for each receive channel.