A laser distance measuring device, a laser distance measuring method, and a movable platform are provided. The laser distance measuring device includes a transmitting module and a receiving module. The transmitting module includes a transmitting circuit and an optical transmitting system, the transmitting circuit is configured to transmit laser pulses, and the optical transmitting system is configured to disperse the laser pulse, to make the laser pulses cover a designated field-of-view area. The receiving module includes a receiving circuit and an optical receiving system, the receiving circuit includes an APD array operating in a linear mode and is configured to receive at least some of returning laser pulses upon the laser pulses being reflected back by a measured object, and convert the at least some of the returning laser pulses into an electrical signal.

A method of detecting a lane line based on lidar data can include detecting, by a processor, points each estimated as a lane line in a lidar data, performing, by the processor, an estimation operation of estimating parameters of a mathematical model using the detected points, and performing, by the processor, a setting operation of calculating distances between each of the detected points and the mathematical model in which the parameters are estimated and setting the calculated distances as scores. The method can further include performing, by the processor, a summation operation of summing the scores, and setting, by the processor, the mathematical model determined according to the summation score as a lane line.

A method of detecting a lane line based on lidar data can include detecting, by a processor, points each estimated as a lane line in a lidar data, performing, by the processor, an estimation operation of estimating parameters of a mathematical model using the detected points, and performing, by the processor, a setting operation of calculating distances between each of the detected points and the mathematical model in which the parameters are estimated and setting the calculated distances as scores. The method can further include performing, by the processor, a summation operation of summing the scores, and setting, by the processor, the mathematical model determined according to the summation score as a lane line.

Techniques to adjust a gain of an analog-to-digital converter circuit (ADC) and/or an ADC full scale from one sample to the next of an analog input signal to compensate for the signal loss over distance, which can increase an effective dynamic range of the system. The benefit of compensating for the signal loss due to distance is that a data interface between the ADC of the receiver of the LIDAR system and a signal processor no longer needs to support the dynamic range from the range specification.

Autonomously driven vehicles operate in rain, snow and other adverse weather conditions. An on-board vehicle sensor has a beam with a diameter that is only intermittently blocked by rain, snow, dust or other obscurant particles. This allows an obstacle detection processor is to tell the difference between obstacles, terrain variations and obscurant particles, thereby enabling the vehicle driving control unit to disregard the presence of obscurant particles along the route taken by the vehicle. The sensor may form part of a LADAR or RADAR system or a video camera. The obstacle detection processor may receive time-spaced frames divided into cells or pixels, whereby groups of connected cells or pixels and/or cells or pixels that persist over longer periods of time are interpreted to be obstacles or terrain variations. The system may further including an input for receiving weather-specific configuration parameters to adjust the operation of the obstacle detection processor.

Autonomously driven vehicles operate in rain, snow and other adverse weather conditions. An on-board vehicle sensor has a beam with a diameter that is only intermittently blocked by rain, snow, dust or other obscurant particles. This allows an obstacle detection processor is to tell the difference between obstacles, terrain variations and obscurant particles, thereby enabling the vehicle driving control unit to disregard the presence of obscurant particles along the route taken by the vehicle. The sensor may form part of a LADAR or RADAR system or a video camera. The obstacle detection processor may receive time-spaced frames divided into cells or pixels, whereby groups of connected cells or pixels and/or cells or pixels that persist over longer periods of time are interpreted to be obstacles or terrain variations. The system may further including an input for receiving weather-specific configuration parameters to adjust the operation of the obstacle detection processor.

A laser detection and ranging system and method for operating thereof. In some embodiments, the method includes: transmitting a plurality of laser pulses, each at a respective one of a plurality of pulse transmission times; detecting a plurality of return pulses, each at a respective one of a plurality of return pulse times; and estimating a range or a range rate of a target based on the pulse transmission times and the return pulse times. Each of the pulse transmission times may be offset from a corresponding nominal pulse transmission time by a respective pulse position modulation offset, the nominal pulse transmission times being uniformly spaced with a period corresponding to a pulse repetition frequency, the pulse repetition frequency being greater than 500 kHz.

A method for providing a detection-signal for objects to be detected—at least a first and second light-beam including different frequencies being generated with a first optical non-linear 3-wave-process from a light-beam of a light-source including an output-frequency, and the first light-beam including a reference-frequency being detected, and the second light-beam including an object-frequency being emitted and received after reflection on an object, and the light-beam including the output-frequency and the second light-beam including the object-frequency being superposed, and a reference-beam including a reference-frequency being generated with a second optical non-linear 3-wave-process from the two superposed light-beams including the output-frequency and including the object-frequency, and a detection-signal being generated so that the object-distance is determinable due to the aforementioned superposition based on the time-difference between the detection of the first light-beam including the reference-frequency and a detection of a change of the reference-beam including the reference-frequency.

Methods and systems for performing three dimensional LIDAR measurements with an integrated LIDAR measurement device are described herein. In one aspect, a return signal receiver generates a pulse trigger signal that triggers the generation of a pulse of illumination light and data acquisition of a return signal, and also triggers the time of flight calculation by time to digital conversion. In addition, the return signal receiver also estimates the width and peak amplitude of each return pulse, and samples each return pulse waveform individually over a sampling window that includes the peak amplitude of each return pulse waveform. In a further aspect, the time of flight associated with each return pulse is estimated based on a coarse timing estimate and a fine timing estimate. In another aspect, the time of flight is measured from the measured pulse due to internal optical crosstalk and a valid return pulse.

Various implementations disclosed herein include a method for operating a LIDAR sensor, comprising repeatedly performing measurements in a respective measurement time window (M), at the beginning of which at least one measurement light pulse (A) having at least one predefined wavelength is emitted by the LIDAR sensor, and determining whether a light pulse (A′) having the at least one predefined wavelength is detected by the LIDAR sensor within the measurement time window (M), wherein a time interval (D1, D2, D3) between two consecutive measurement time windows (M) is varied.