A ranging system includes: a source generating a wideband incident wave that is transmitted toward a target and that is reflected by the target to form a reflected wave; a feedback detector to detect the reflected wave to generate a detected signal; an operator configured to perform low-pass filtering on the detected signal at an adjustable filtering bandwidth to generate a filtered signal, and calculate cross-correlation of a feedback signal that originates from the filtered signal and a reference signal that corresponds to the incident wave to generate a cross-correlation result; and a controller calculating a distance to the target based on an operation output that originates from the cross-correlation result.

A light detection and ranging (LIDAR) system includes an optical receiver to generate a plurality of data points associated with one or more return beams from a target of the LIDAR system, a processor, and a memory. The memory stores the plurality of data points and stores instructions that cause the LIDAR system to: perform a processing operation on a first data point of the plurality of data points to determine a second data point of the plurality of data points with which to modify the first data point; generate, as output of the processing operation, a first index to a first memory location of the first data point and a second index to a second memory location of the second data point; and generate a point cloud corresponding to the target based on the first data point as modified by the second data point.

A light detection and ranging (LIDAR) system includes an optical receiver to generate a plurality of data points associated with one or more return beams from a target of the LIDAR system, a processor, and a memory. The memory stores the plurality of data points and stores instructions that cause the LIDAR system to: perform a processing operation on a first data point of the plurality of data points to determine a second data point of the plurality of data points with which to modify the first data point; generate, as output of the processing operation, a first index to a first memory location of the first data point and a second index to a second memory location of the second data point; and generate a point cloud corresponding to the target based on the first data point as modified by the second data point.

A light detection and ranging (lidar) receiver may include a first photodiode, a first amplifier connected to the first photodiode, and a first analog-to-digital converter (ADC) connected to an output of the first amplifier. The lidar receiver may include a second photodiode, a second amplifier connected to the second photodiode, and a second ADC connected to the second amplifier. The lidar may include a processor connected to an output of the first ADC and an output of the second ADC and a direct-current-to-direct-current converter connected to an output of the processor and to the first photodiode and the second photodiode. The processor may determine, based on the output of the first ADC and the output of the second ADC, a first bias to apply to the first photodiode and a second bias to apply to the second photodiode.

A light detection and ranging (lidar) receiver may include a first photodiode, a first amplifier connected to the first photodiode, and a first analog-to-digital converter (ADC) connected to an output of the first amplifier. The lidar receiver may include a second photodiode, a second amplifier connected to the second photodiode, and a second ADC connected to the second amplifier. The lidar may include a processor connected to an output of the first ADC and an output of the second ADC and a direct-current-to-direct-current converter connected to an output of the processor and to the first photodiode and the second photodiode. The processor may determine, based on the output of the first ADC and the output of the second ADC, a first bias to apply to the first photodiode and a second bias to apply to the second photodiode.

Examples are disclosed relating to performing denoising and adaptive precision control on time-of-flight sensor data using noise metrics. One example provides a computing system, comprising, a logic machine, and a storage machine holding instructions executable by the logic machine to obtain time-of-flight (ToF) image data comprising a plurality of pixels, for each pixel of the ToF image data, determine one or more noise metrics by applying a spatial kernel, segment the ToF image data based on the one or more noise metrics to obtain differently classified pixels, during a denoising phase, process pixels of a first classification differently than pixels of a second classification, after the denoising phase, determine a depth image, and output the depth image.

A LIDAR system is adapted for performing anemometrical measurements relating to a focusing zone of a laser beam which is emitted by the system. The system includes a temporal control device for the laser beam, which is adapted for putting this laser beam in successive laser pulse form, so that each laser pulse has an individual length which is greater than or equal to twice the Rayleigh length divided by the propagation speed of the laser pulses in the atmosphere, and less than 20 μs. Advantageously, the individual length of each laser pulse is between 0.2 and 5 times the coherence time of the atmosphere which is effective in the focusing zone. Such a LIDAR system provides values for a spectral CNR ratio which are better than those of systems from the state-of-the-art, at equivalent spatial resolution.

A sensing system is disclosed for performing distance measurements. The sensing system may include an emitter configured to emit electromagnetic radiation modulated at a known frequency. The sensing system may further include a detector configured to sample incident electromagnetic radiation at the known frequency, convert the sampled electromagnetic radiation into charge carriers, and collect the charge carriers in a storage component to produce an electronic signal. The sensing system may include a processor configured to determine a correction by applying a non-linear polynomial function to the electronic signal.

A modulated wave time of flight (mwToF) sensor combines modern digital signal processing techniques with CW quadrature sampling methods to produce a sensor that is better at rejecting environmental noise such as ambient light as well as electronic noise that comes from sources such as signal amplification.

A modulated wave time of flight (mwToF) sensor combines modern digital signal processing techniques with CW quadrature sampling methods to produce a sensor that is better at rejecting environmental noise such as ambient light as well as electronic noise that comes from sources such as signal amplification.