Systems and methods for a Time of Flight (ToF) camera system configured to be operable in a proximity mode. In the proximity mode, the proximity of an object may be estimated by relatively delaying or offsetting the charge accumulation timing of multiple different columns of pixels of the ToF imaging sensor. The relative charge accumulated in those pixel columns is dependent on the proximity of the object and the relative time delays in charge accumulation of each column. Therefore, by reading out the charge accumulated in multiple different pixel columns and knowing the relative accumulation delay of those pixel columns, the proximity of an object may be determined. This enables the operation of the ToF camera system to be switched between relatively high power, full ToF depth imaging, and relatively low power proximity mode of operation, thereby rendering a single system as being capable of performing two different functions.

A method and system for real-time motion artifact handling and noise removal for time-of-flight (ToF) sensor images. The method includes: calculating values of a cross correlation function c(τ) at a plurality of temporally spaced positions or phases from sent (s(t)) and received (r(t)) signals, thereby deriving a plurality of respective cross correlation values [c(τ.sub.0), c(τ.sub.1), c(τ.sub.2), c(τ.sub.3)]; deriving, from the plurality of cross correlation values [c(τ.sub.0), c(τ.sub.1), c(τ.sub.2), c(τ.sub.3)], a depth map D having values representing, for each pixel, distance to a portion of an object upon which the sent signals (s(t)) are incident; deriving, from the plurality of cross correlation values [c(τ.sub.0), c(τ.sub.1), c(τ.sub.2), c(τ.sub.3)], a guidance image (I; I′); and generating an output image D′ based on the depth map D and the guidance image (I; I′), the output image D′ comprising an edge-preserving and smoothed version of depth map D, the edge-preserving being from guidance image (I; I′).

A time-of-flight depth calculation method includes: obtaining a phase image, and obtaining, based on the phase image, a differential ratio of charge signals corresponding to reflected signals acquired by an image sensor at different times; in response to that the differential ratio of the charge signals is greater than or equal to a threshold, obtaining a first phase based on a phase conversion model and the differential ratio of the charge signals; and calculating a depth value of a target region based on the first phase.

The present invention is directed to LiDAR systems and methods. In specific embodiments, the received signal is transformed into a histogram, facilitating the identification and filtering of one or more peaks to enhance accuracy. Various other embodiments are also provided, offering diverse solutions for optimizing LiDAR performance in different applications.

A sensor apparatus for photon sensing comprises a plurality of pixel devices, each pixel device comprising: a plurality of photon detectors arranged to produce photon detection signals in response to photon detection events; a processing resource configured to process photon detection signals to produce photon detection event signals, wherein each photon detection event signal comprises time data representative of a photon detection time at which a respective photon detection event occurred; a pixel memory; a further processing resource configured to process the photon detection event signals to obtain detection data representative of photon detection events over a detection period; a communication resource for transmitting the detection data from the pixel device, wherein the processing of the photon detection event signals is such that storing and/or transmission of the detection data uses less storage capacity and/or communication capacity than would be used by storage and/or transmission of the photon detection event signals directly.

A photo-detecting apparatus includes an image sensor and a 3D image generator. The image sensor having a plurality of 3D photodetectors is configured to output a raw data. The 3D image generator having a storage medium for storing a calibration data is configured to output a 3D image according to the raw data and the calibration data. The calibration data includes at least one of an IQ-mismatch calibration data, a non-linearity calibration data, a temperature calibration data and an offset calibration data.

A method for time-of-flight sensing of a scene is provided. For at least one pixel position, the method includes performing at least one time-of-flight measurement using a first modulation frequency to obtain at least one first measurement value for the pixel position. Further, the method includes for the at least one pixel position performing at least one time-of-flight measurement using a second modulation frequency to obtain at least one second measurement value for the pixel position. The method additionally includes determining an estimate of a distance value of the pixel position based on the at least one first measurement value and the at least one second measurement value using a mapping function.

The disclosed systems, and methods are directed to determining distance to an in-use object from a LiDAR system, the systems and methods comprising: acquiring a series of discrete digital values representative of an optical return pulse, accessing, a pre-populated library stored in a memory for retrieving a resolution parameter, the accessing including: determining, similarity parameters between (i) the series of discrete values and (ii) respective ones of the list of template pulse profiles, a given similarity parameter being determined between (i) the series of discrete values and (i) a respective template pulse profile from the list of template pulse profiles; retrieving, from the library, at least the respective resolution parameter of the template pulse profile having a highest similarity parameter; and using, the respective resolution parameter for determining the distance of the in-use object from the LiDAR system.

In some implementations, a light detection and ranging (LIDAR) system includes a transmitter configured to transmit an optical signal that is output from a laser and modulated based on a modulating signal, a receiver configured to receive a returned optical signal in response to transmitting the optical signal, and a processor. The processor is configured to produce a first optical signal based on the returned optical signal and a first version of the modulating signal, produce a second optical signal based on the returned optical signal and a second version of the modulating signal, generate a digital signal based on the first optical signal and the second optical signal, determine a Doppler frequency shift of the returned optical signal based, at least in part, on the digital signal, and provide data indicative of the Doppler frequency shift to a vehicle.

A time delay of arrival (TDOA) between a time that a light pulse was emitted to a time that a pulse reflected off an object was received at a light sensor may be determined for saturated signals by using an edge of the saturated signal, rather than a peak of the signal, for the TDOA calculation. The edge of the saturated signal may be accurately estimated by fitting a first polynomial curve to data points of the saturated signal, defining an intermediate magnitude threshold based on the polynomial curve, fitting a second polynomial curve to data points near an intersection of the first polynomial curve and the intermediate threshold, and identifying an intersection of the second polynomial curve and the intermediate threshold as the rising edge of the saturated signal.