Abstract: A computer-implemented method and a system for at least partially removing intrinsic static noise from data obtained by an optical time-of-flight sensor using full-waveform analysis. The method includes receiving a plurality of calibration traces, the calibration traces being obtained in a controlled environment wherein no object is present in a field of view of the optical time-of-flight sensor; determining a noise template using the calibration traces by performing a statistical analysis on the calibration traces to determine a shape and an amplitude of the intrinsic static noise in the calibration traces; receiving a normal operation trace, the normal operation trace being obtained in an uncontrolled environment wherein a presence of the object in the field of view is unknown; subtracting the noise template from the normal operation trace, obtaining and outputting a denoised signal.

Abstract: Computer-implemented methods and systems for at least partially removing extrinsic static noise from data obtained by an optical time-of-flight sensor using full-waveform analysis. The method comprises finding a mathematical representation of the electromagnetic crosstalk present in victim calibration traces and caused by aggressor photosensitive element using aggressor calibration traces and victim calibration traces, determining a predetermined threshold for the amplitude of the aggressor calibration trace at which the electromagnetic crosstalk is present in the victim calibration traces, predicting the extrinsic static noise generated by the aggressor signal on the synchronized victim operation trace using the mathematical representation to generate a predicted crosstalk signal, removing the predicted crosstalk signal from the synchronized victim operation trace to output a denoised signal.

Abstract: A computer-implemented method and a system for at least partially removing intrinsic static noise from data obtained by an optical time-of-flight sensor using full-waveform analysis. The method includes receiving a plurality of calibration traces, the calibration traces being obtained in a controlled environment wherein no object is present in a field of view of the optical time-of-flight sensor; determining a noise template using the calibration traces by performing a statistical analysis on the calibration traces to determine a shape and an amplitude of the intrinsic static noise in the calibration traces; receiving a normal operation trace, the normal operation trace being obtained in an uncontrolled environment wherein a presence of the object in the field of view is unknown; subtracting the noise template from the normal operation trace, obtaining and outputting a denoised signal.

Abstract: Computer-implemented methods and systems for at least partially removing extrinsic static noise from data obtained by an optical time-of-flight sensor using full-waveform analysis. The method comprises finding a mathematical representation of the electromagnetic crosstalk present in victim calibration traces and caused by aggressor photosensitive element using aggressor calibration traces and victim calibration traces, determining a predetermined threshold for the amplitude of the aggressor calibration trace at which the electromagnetic crosstalk is present in the victim calibration traces, predicting the extrinsic static noise generated by the aggressor signal on the synchronized victim operation trace using the mathematical representation to generate a predicted crosstalk signal, removing the predicted crosstalk signal from the synchronized victim operation trace to output a denoised signal.

Abstract: A method for detecting a vehicle comprising: providing a multi-channel scannerless full-waveform lidar system operating in pulsed Time-Of-Flight operation oriented towards a surface of the roadway to cover the detection zone; providing at least one initialization parameter; emitting pulses at an emission frequency; receiving reflections of the pulses from the detection zone; and acquiring and digitalizing a series of individual complete traces at each channel of system; identifying at least one detection in at least one of the traces; obtaining a height and an intensity for the detection; determining a nature of the detection to be one of an environmental particle detection, a candidate object detection and a roadway surface detection; if the nature of the detection is the candidate object detection, detecting a presence of a vehicle in the detection zone.

Abstract: A method for tracking and characterizing a plurality of vehicles simultaneously in a traffic control environment, comprising: providing a 3D optical emitter; providing a 3D optical receiver with a wide and deep field of view; driving the 3D optical emitter into emitting short light pulses; receiving a reflection/backscatter of the emitted light, thereby acquiring an individual digital full-waveform LIDAR trace for each detection channel of the 3D optical receiver; using the individual digital full-waveform LIDAR trace and the emitted light waveform, detecting a presence of a plurality of vehicles, a position of at least part of each vehicle and a time at which the position is detected; assigning a unique identifier to each vehicle; repeating the steps of driving, receiving, acquiring and detecting, at a predetermined frequency; tracking and recording an updated position of each vehicle and an updated time at which the updated position is detected.

Abstract: A method for detecting a vehicle comprising: providing a multi-channel scannerless full-waveform lidar system operating in pulsed Time-Of-Flight operation oriented towards a surface of the roadway to cover the detection zone; providing at least one initialization parameter; emitting pulses at an emission frequency; receiving reflections of the pulses from the detection zone; and acquiring and digitalizing a series of individual complete traces at each channel of system; identifying at least one detection in at least one of the traces; obtaining a height and an intensity for the detection; determining a nature of the detection to be one of an environmental particle detection, a candidate object detection and a roadway surface detection; if the nature of the detection is the candidate object detection, detecting a presence of a vehicle in the detection zone.

Abstract: A method for tracking and characterizing a plurality of vehicles simultaneously in a traffic control environment, comprising: providing a 3D optical emitter; providing a 3D optical receiver with a wide and deep field of view; driving the 3D optical emitter into emitting short light pulses; receiving a reflection/backscatter of the emitted light, thereby acquiring an individual digital full-waveform LIDAR trace for each detection channel of the 3D optical receiver; using the individual digital full-waveform LIDAR trace and the emitted light waveform, detecting a presence of a plurality of vehicles, a position of at least part of each vehicle and a time at which the position is detected; assigning a unique identifier to each vehicle; repeating the steps of driving, receiving, acquiring and detecting, at a predetermined frequency; tracking and recording an updated position of each vehicle and an updated time at which the updated position is detected.

Abstract: A method for tracking and characterizing a plurality of vehicles simultaneously in a traffic control environment, comprising: providing a 3D optical emitter; providing a 3D optical receiver with a wide and deep field of view; driving the 3D optical emitter into emitting short light pulses; receiving a reflection/backscatter of the emitted light, thereby acquiring an individual digital full-waveform LIDAR trace for each detection channel of the 3D optical receiver; using the individual digital full-waveform LIDAR trace and the emitted light waveform, detecting a presence of a plurality of vehicles, a position of at least part of each vehicle and a time at which the position is detected; assigning a unique identifier to each vehicle; repeating the steps of driving, receiving, acquiring and detecting, at a predetermined frequency; tracking and recording an updated position of each vehicle and an updated time at which the updated position is detected.