Dynamic biasing of photodetectors in lidar applications

Abstract

A system that includes one or more photodetector circuits. The system also includes a global biasing circuit configured to generate a first biasing voltage and coupled to each photodetector circuit of the one or more photodetector circuits such that a respective bias voltage corresponding to each photodetector circuit is based on the first biasing voltage. In addition, the system includes one or more local biasing circuits that each correspond to a respective photodetector circuit. Each local biasing circuit is configured to generate a respective second biasing voltage and is coupled to its respective photodetector circuit such that the respective bias voltage of its respective photodetector circuit is also based on the respective second biasing voltage.

Description

[0001] DYNAMIC BIASING OF PHOTODETECTORS IN LIDAR APPLICATIONS

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims priority to U.S. Provisional Patent Application Serial No. 63 / 541,273, filed September 28, 2023, entitled “DYNAMIC BIASING PHOTODETECTORS IN LIDAR APPLICATION.” The contents of this application are hereby incorporated by reference in their entireties for all purposes.

[0004] FIELD OF THE TECHNOLOGY

[0005] This disclosure relates generally to dynamically biased photodetectors in LiDAR systems.

[0006] BACKGROUND

[0007] Light detection and ranging (LiDAR) systems use light pulses to create an image or point cloud of the external environment. A LiDAR system may be a scanning or non-scanning system. Some typical scanning LiDAR systems include a light source, a light transmitter, a light steering system, and a light detector. The light source generates a light beam that is directed by the light steering system in particular directions when being transmitted from the LiDAR system. When a transmitted light beam is scattered or reflected by an object, a portion of the scattered or reflected light returns to the LiDAR system to form a return light pulse. The light detector detects the return light pulse. Using the difference between the time that the return light pulse is detected and the time that a corresponding light pulse in the light beam is transmitted, the LiDAR system can determine the distance to the object based on the speed of light. This technique of determining the distance is referred to as the time-of-flight (ToF) technique. The light steering system can direct light beams along different paths to allow the LiDAR system to scan the surrounding environment and produce images or point clouds. A typical non-scanning LiDAR system illuminate an entire field-of-view (FOV) rather than scanning through the FOV. An example of the non-scanning LiDAR system is a flash LiDAR, which can also use the ToF technique to measure the distance to an object. LiDAR systems can also use techniques other than time-of-flight and scanning to measure the surrounding environment.

[0008] A properly designed LiDAR system may need to cover a large dynamic range, up to several 10s of dBs. For example, photodetectors may be required to possess a high-gain value for the weak signal from a far-field target while also detecting bright signals while avoiding saturating or losing sensitivity. Typical photodetectors may include an APD (avalanche photodiode) based structure, a PMT (photomultiplier tube) based structure, a SiPM (Silicon photomultiplier) based structure, a SPAD (single-photon avalanche diode) based structure, and / or quantum wires. SUMMARY

[0009] A system that includes one or more photodetector circuits. The system also includes a global biasing circuit configured to generate a first biasing voltage and coupled to each photodetector circuit of the one or more photodetector circuits such that a respective bias voltage corresponding to each photodetector circuit is based on the first biasing voltage. In addition, the system includes one or more local biasing circuits that each correspond to a respective photodetector circuit. Each local biasing circuit is configured to generate a respective second biasing voltage and is coupled to its respective photodetector circuit such that the respective bias voltage of its respective photodetector circuit is also based on the respective second biasing voltage.

[0010] BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The present application can be best understood by reference to the embodiments described below taken in conjunction with the accompanying drawing figures, in which like parts may be referred to by like numerals.

[0012] FIG. 1 illustrates one or more example LiDAR systems disposed or included in a motor vehicle.

[0013] FIG. 2 is a block diagram illustrating interactions between an example LiDAR system and multiple other systems including a vehicle perception and planning system.

[0014] FIG. 3 is a block diagram illustrating an example LiDAR system.

[0015] FIG. 4 is a block diagram illustrating an example fiber-based laser source.

[0016] FIGs. 5A-5C illustrate an example LiDAR system using pulse signals to measure distances to objects disposed in a field-of-view (FOV).

[0017] FIG. 6 is a block diagram illustrating an example apparatus used to implement systems, apparatus, and methods, according to one or more embodiments.

[0018] FIG. 7 is an example block diagram illustrating an example photodetector system, according to one or more embodiments.

[0019] FIG. 8 is a circuit diagram illustrating an example photodetector system, according to one or more embodiments.

[0020] FIG. 9 is a flow diagram of a method for biasing a photodetector system, according to one or more embodiments.

[0021] DETAILED DESCRIPTION

[0022] To provide a more thorough understanding of various embodiments of the present invention, the following description sets forth numerous specific details, such as specific configurations, parameters, examples, and the like. It should be recognized, however, that such description is not intended as a limitation on the scope of the present invention but is intended to provide a better description of the exemplary embodiments.

[0023] Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise: The phrase “in one embodiment” as used herein does not necessarily refer to the same embodiment, though it may. Thus, as described below, various embodiments of the disclosure may be readily combined, without departing from the scope or spirit of the invention.

[0024] As used herein, the term “or” is an inclusive “or” operator and is equivalent to the term “and / or,” unless the context clearly dictates otherwise.

[0025] The term “based on” is not exclusive and allows for being based on additional factors not described unless the context clearly dictates otherwise.

[0026] As used herein, and unless the context dictates otherwise, the term “coupled to” is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms “coupled to” and “coupled with” are used synonymously. Within the context of a networked environment where two or more components or devices are able to exchange data, the terms “coupled to” and “coupled with” are also used to mean “communicatively coupled with”, possibly via one or more intermediary devices. The components or devices can be optical, mechanical, and / or electrical devices.

[0027] Although the following description uses terms “first,” “second,” etc. to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another. For example, a first sensor could be termed a second sensor and, similarly, a second sensor could be termed a first sensor, without departing from the scope of the various described examples. The first sensor and the second sensor can both be sensors and, in some cases, can be separate and different sensors.

[0028] In addition, throughout the specification, the meaning of “a”, “an”, and “the” includes plural references, and the meaning of “in” includes “in” and “on”.

[0029] Although some of the various embodiments presented herein constitute a single combination of inventive elements, it should be appreciated that the inventive subject matter is considered to include all possible combinations of the disclosed elements. As such, if one embodiment comprises elements A, B, and C, and another embodiment comprises elements B and D, then the inventive subject matter is also considered to include other remaining combinations of A, B, C, or D, even if not explicitly discussed herein. Further, as used herein, a recitation of “and / or” with respect to two or more elements should be interpreted to mean only one element, or a combination of elements. For example, “element A, element B, and / or element C” may include only element A, only element B, only element C, element A and element B, element A and element C, element B and element C, or elements A, B, and C. Further, the transitional term “comprising” means to have as parts or members, or to be those parts or members. As used herein, the transitional term “comprising” is inclusive or open-ended and does not exclude additional, unrecited elements or method steps.

[0030] As used in the description herein and throughout the claims that follow, when a system, engine, server, device, module, or other computing element is described as being configured to perform or execute functions on data in a memory, the meaning of “configured to” or “programmed to” is defined as one or more processors or cores of the computing element being programmed by a set of software instructions stored in the memory of the computing element to execute the set of functions on target data or data objects stored in the memory. It should be noted that any language directed to a computer should be read to include any suitable combination of computing devices or network platforms, including servers, interfaces, systems, databases, agents, peers, engines, controllers, modules, or other types of computing devices operating individually or collectively. One should appreciate the computing devices comprise a processor configured to execute software instructions stored on a tangible, non- transitory computer readable storage medium (e.g.. hard drive, FPGA, PLA, solid state drive, RAM, flash, ROM, or any other volatile or non-volatile storage devices). The software instructions configure or program the computing device to provide the roles, responsibilities, or other functionality as discussed below with respect to the disclosed apparatus. Further, the disclosed technologies can be embodied as a computer program product that includes a non-transitory computer readable medium storing the software instructions that causes a processor to execute the disclosed steps associated with implementations of computer-based algorithms, processes, methods, or other instructions. In some embodiments, the various servers, systems, databases, or interfaces exchange data using standardized protocols or algorithms, possibly based on HTTP, HTTPS, AES, public-private key exchanges, web service APIs, known financial transaction protocols, or other electronic information exchanging methods. Data exchanges among devices can be conducted over a packet-switched network, the Internet, LAN, WAN, VPN, or other type of packet switched network; a circuit switched network; cell switched network; or other type of network.

[0031] A properly designed LiDAR device or system may need to cover a large dynamic range. For instance, the dynamic range of a well-designed LiDAR system may be up to several 10s of dBs. For example, photodetector circuits of a LiDAR system may be required to be able to detect weak return signals from a far-field target while also detecting strong signals while avoiding saturating or losing sensitivity.

[0032] In these and other embodiments, photodetector circuits may include light detector structures (also referred to as “photodetectors”, “optical detectors” “light detectors” or “detectors”) that may be configured to detect the LiDAR return signals. The photodetectors may include any suitable device and / or structure that may be configured to detect light and generate an electrical signal based on such detected light. For example, a photodetector may include an APD (avalanche photodiode) based structure, a PMT (photomultiplier tube) based structure, a SiPM (Silicon photomultiplier) based structure, a SPAD (single-photon avalanche diode) based structure, and / or quantum wires. The gains of these devices are highly associated with the bias voltage applied across the respective devices. As such, dynamically controlling the bias voltage to achieve improved system performance may be desirable.

[0033] Further, individual photodetectors may have different properties (e.g., due to detector type, individual discrepancies from fabrication, etc.) such that in order to achieve similar or same gain profiles across individual detectors, different biases may be applied to the different detectors. For LiDAR systems employing multiple channels of detectors, using dynamic control of the bias to accommodate the discrepancies from individual devices may also be important to achieving a targeted system performance. Thus, there is a continual need for improved biasing circuits for photodetectors.

[0034] According to one or more embodiments of the present disclosure, a technique for biasing may include generating one global biasing voltage (also referred to as a “global voltage”) that may be used for the biasing of multiple photodetectors. As discussed in detail in the present disclosure, the global voltage may be used to provide a reference biasing voltage with respect to each individual photodetector for which the global voltage may be used. In these and other embodiments, a global voltage supply configured to supply the global voltage may be adjusted based on ambient temperature such that the reference biasing voltage for multiple photodetectors may be adjusted depending on the ambient temperature.

[0035] Additionally or alternatively, as discussed in further detail, local biasing voltages (also referred to as a “local voltage”) may be used to bias individual photodetectors. For example, the global voltage and the respective local voltages may be applied to the individual photodetectors such that the bias voltage across the individual photodetectors is based on a difference between the global voltage and the local voltages respectively corresponding to the individual photodetectors. In these and other embodiments, the individual local voltages may be controlled and regulated specifically with respect to their corresponding photodetectors. Accordingly, by adjusting the local voltages, the respective bias voltages across the individual photodetectors may be adjusted and controlled individually.

[0036] For example, the local biasing voltages may be provided by individual voltage sources. Further, in some embodiments, such local biasing voltage sources may be individually adjusted based on one or more characteristics of the corresponding detector, which may allow for individual adjustments to each detector to obtain similar or same gain profiles for the detectors despite individual differences in the detectors. Further, in some instances, the temperatures of the individual photodetectors may vary, which may change their individual characteristics. The individual local biasing voltage sources may also be adjusted based on the individual temperatures such that the corresponding photodetector gain profiles may be maintained during different temperature fluctuations.

[0037] In these and other embodiments, the local biasing voltage may be a relatively lower voltage than the global biasing voltage. As such, individual biasing voltage regulation may happen at the low voltage side. Such an implementation may simplify the overall circuit design and / or provide BOM (bill of materials) cost reduction.

[0038] FIG. 1 illustrates one or more example LiDAR systems 110 and 120A-120I disposed or included in a motor vehicle 100. Vehicle 100 can be a car, a sport utility vehicle (SUV), a truck, a train, a wagon, a bicycle, a motorcycle, a tricycle, a bus, a mobility scooter, a tram, a ship, a boat, an underwater vehicle, an airplane, a helicopter, an unmanned aviation vehicle (UAV), a spacecraft, etc. Motor vehicle 100 can be a vehicle having any automated level. For example, motor vehicle 100 can be a partially automated vehicle, a highly automated vehicle, a fully automated vehicle, or a driverless vehicle. A partially automated vehicle can perform some driving functions without a human driver’s intervention. For example, a partially automated vehicle can perform blind-spot monitoring, lane keeping and / or lane changing operations, automated emergency braking, smart cruising and / or traffic following, or the like. Certain operations of a partially automated vehicle may be limited to specific applications or driving scenarios (e.g., limited to only freeway driving). A highly automated vehicle can generally perform all operations of a partially automated vehicle but with less limitations. A highly automated vehicle can also detect its own limits in operating the vehicle and ask the driver to take over the control of the vehicle when necessary. A fully automated vehicle can perform all vehicle operations without a driver’s intervention but can also detect its own limits and ask the driver to take over when necessary. A driverless vehicle can operate on its own without any driver intervention.

[0039] In typical configurations, motor vehicle 100 comprises one or more LiDAR systems 110 and 1 0A-120I. Each of LiDAR systems 110 and 120A-120I can be a scanning-based LiDAR system and / or a non-scanning LiDAR system (e.g.. a flash LiDAR). A scanning-based LiDAR system scans one or more light beams in one or more directions (e.g.. horizontal and vertical directions) to detect objects in a field-of-view (FOV). A non-scanning based LiDAR system transmits laser light to illuminate an FOV without scanning. For example, a flash LiDAR is a type of non-scanning based LiDAR system. A flash LiDAR can transmit laser light to simultaneously illuminate an FOV using a single light pulse or light shot.

[0040] A LiDAR system is a frequently-used sensor of a vehicle that is at least partially automated. In one embodiment, as shown in FIG. 1, motor vehicle 100 may include a single LiDAR system 110 (e.g., without LiDAR systems 120A-120I) disposed at the highest position of the vehicle (e.g., at the vehicle roof). Disposing LiDAR system 110 at the vehicle roof facilitates a 360-degree scanning around vehicle 100. In some other embodiments, motor vehicle 100 can include multiple LiDAR systems, including two or more of systems 110 and / or 120A-120I. As shown in FIG. 1, in one embodiment, multiple LiDAR systems 110 and / or 120A-120I are attached to vehicle 100 at different locations of the vehicle. For example, LiDAR system 120A is attached to vehicle 100 at the front right corner; LiDAR system 120B is attached to vehicle 100 at the front center position; LiDAR system 120C is attached to vehicle 100 at the front left corner; LiDAR system 120D is attached to vehicle 100 at the right-side rear view mirror; LiDAR system 120E is attached to vehicle 100 at the left-side rear view mirror; LiDAR system 120F is attached to vehicle 100 at the back center position; LiDAR system 120G is attached to vehicle 100 at the back right comer; LiDAR system 120H is attached to vehicle 100 at the back left corner; and / or LiDAR system 1201 is attached to vehicle 100 at the center towards the backend (e.g., back end of the vehicle roof). It is understood that one or more LiDAR systems can be distributed and attached to a vehicle in any desired manner and FIG. 1 only illustrates one embodiment. As another example, LiDAR systems 120D and 120E may be attached to the B-pillars of vehicle 100 instead of the rear-view mirrors. As another example, LiDAR system 120B may be attached to the windshield of vehicle 100 instead of the front bumper.

[0041] In some embodiments, LiDAR systems 110 and 120A-120I are independent LiDAR systems having their own respective laser sources, control electonics, transmitters, receivers, and / or steering mechanisms. In other embodiments, some of LiDAR systems 110 and 120A-120I can share one or more components, thereby forming a distributed sensor system. In one example, optical fibers are used to deliver laser light from a centralized laser source to all LiDAR systems. For instance, system 110 (or another system that is centrally positioned or positioned anywhere inside the vehicle 100) includes a light source, a transmitter, and a light detector, but has no steering mechanisms. System 110 may distribute transmission light to each of systems 120A-120I. The transmission light may be distributed via optical fibers. Optical connectors can be used to couple the optical fibers to each of system 110 and 120A-120I. In some examples, one or more of systems 120A-120T include steering mechanisms but no light sources, transmitters, or light detectors. A steering mechanism may include one or more moveable mirrors such as one or more polygon mirrors, one or more single plane mirrors, one or more multi-plane mirrors, or the like. Embodiments of the light source, transmitter, steering mechanism, and light detector are described in more detail below. Via the steering mechanisms, one or more of systems 120A-120I scan light into one or more respective FOVs and receive corresponding return light. The return light is formed by scattering or reflecting the transmission light by one or more objects in the FOVs. Systems 120A-120I may also include collection lens and / or other optics to focus and / or direct the return light into optical fibers, which deliver the received return light to system 110. System 110 includes one or more light detectors for detecting the received return light. In some examples, system 110 is disposed inside a vehicle such that it is in a temperature-controlled environment, while one or more systems 120A-120I may be at least partially exposed to the external environment.

[0042] FIG. 2 is a block diagram 200 illustrating interactions between vehicle onboard LiDAR system(s) 210 and multiple other systems including a vehicle perception and planning system 220. LiDAR system(s) 210 can be mounted on or integrated to a vehicle. LiDAR system(s) 210 include sensor(s) that scan laser light to the surrounding environment to measure the distance, angle, and / or velocity of objects. Based on the scattered light that returned to LiDAR system(s) 210, it can generate sensor data (e.g.. image data or 3D point cloud data) representing the perceived external environment.

[0043] LiDAR system(s) 210 can include one or more of short-range LiDAR sensors, medium-range LiDAR sensors, and long-range LiDAR sensors. A short-range LiDAR sensor measures objects located up to about 20-50 meters from the LiDAR sensor. Short-range LiDAR sensors can be used for, e.g., monitoring nearby moving objects (e.g., pedestrians crossing street in a school zone), parking assistance applications, or the like. A medium-range LiDAR sensor measures objects located up to about 70-200 meters from the LiDAR sensor. Medium-range LiDAR sensors can be used for, e.g., monitoring road intersections, assistance for merging onto or leaving a freeway, or the like. A long- range LiDAR sensor measures objects located up to about 200 meters and beyond. Long-range LiDAR sensors are typically used when a vehicle is travelling at a high speed (e.g., on a freeway), such that the vehicle’s control systems may only have a few seconds (e.g., 6-8 seconds) to respond to any situations detected by the LiDAR sensor. As shown in FIG. 2, in one embodiment, the LiDAR sensor data can be provided to vehicle perception and planning system 220 via a communication path 213 for further processing and controlling the vehicle operations. Communication path 213 can be any wired or wireless communication links that can transfer data.

[0044] With reference still to FIG. 2, in some embodiments, other vehicle onboard sensor(s) 230 are configured to provide additional sensor data separately or together with LiDAR system(s) 210. Other vehicle onboard sensors 230 may include, for example, one or more camera(s) 232, one or more radar(s) 234, one or more ultrasonic sensor(s) 236, and / or other sensor(s) 238. Camera(s) 232 can take images and / or videos of the external environment of a vehicle. Camera(s) 232 can take, for example, high-definition (HD) videos having millions of pixels in each frame. A camera includes image sensors that facilitate producing monochrome or color images and videos. Color information may be important in interpreting data for some situations (e.g., interpreting images of traffic lights). Color information may not be available from other sensors such as LiDAR or radar sensors. Camera(s) 232 can include one or more of narrowfocus cameras, wider-focus cameras, side-facing cameras, infrared cameras, fisheye cameras, or the like. The image and / or video data generated by camera(s) 232 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations. Communication path 233 can be any wired or wireless communication links that can transfer data. Camera(s) 232 can be mounted on, or integrated to, a vehicle at any location (e.g., rear-view mirrors, pillars, front grille, and / or back bumpers, etc.).

[0045] Other vehicle onboard sensos(s) 230 can also include radar sensor(s) 234. Radar sensor(s) 234 use radio waves to determine the range, angle, and velocity of objects. Radar sensor(s) 234 produce electromagnetic waves in the radio or microwave spectrum. The electromagnetic waves reflect off an object and some of the reflected waves return to the radar sensor, thereby providing information about the object’s position and velocity. Radar sensor(s) 234 can include one or more of short-range radar(s), medium-range radar(s), and long-range radart s). A short-range radar measures objects located at about 0.1-30 meters from the radar. A short-range radar is useful in detecting objects located near the vehicle, such as other vehicles, buildings, walls, pedestrians, bicyclists, etc. A short-range radar can be used to detect a blind spot, assist in lane changing, provide rear-end collision warning, assist in parking, provide emergency braking, or the like. A medium-range radar measures objects located at about 30-80 meters from the radar. A long-range radar measures objects located at about 80-200 meters. Medium- and / or long-range radars can be useful in. for example, traffic following, adaptive cruise control, and / or highway automatic braking. Sensor data generated by radar sensor(s) 234 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations. Radar sensor(s) 234 can be mounted on, or integrated to, a vehicle at any location (e.g., rear-view mirrors, pillars, front grille, and / or back bumpers, etc.).

[0046] Other vehicle onboard sensor(s) 230 can also include ultrasonic sensor(s) 236. Ultrasonic sensor(s) 236 use acoustic waves or pulses to measure objects located external to a vehicle. The acoustic waves generated by ultrasonic sensor(s) 236 are transmitted to the surrounding environment. At least some of the transmitted waves are reflected off an object and return to the ultrasonic sensor(s) 236. Based on the return signals, a distance of the object can be calculated. Ultrasonic sensor(s) 236 can be useful in, for example, checking blind spots, identifying parking spaces, providing lane changing assistance into traffic, or the like. Sensor data generated by ultrasonic sensor(s) 236 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations. Ultrasonic sensor(s) 236 can be mounted on, or integrated to, a vehicle at any location (e.g., rearview mirrors, pillars, front grille, and / or back bumpers, etc.).

[0047] In some embodiments, one or more other sensor(s) 238 may be attached in a vehicle and may also generate sensor data. Other sensor(s) 238 may include, for example, global positioning systems (GPS), inertial measurement units (IMU), or the like. Sensor data generated by other sensor(s) 238 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations. It is understood that communication path 233 may include one or more communication links to transfer data between the various sensor(s) 230 and vehicle perception and planning system 220.

[0048] In some embodiments, as shown in FIG. 2, sensor data from other vehicle onboard sensor(s) 230 can be provided to vehicle onboard LiDAR system(s) 210 via communication path 231. LiDAR system(s) 210 may process the sensor data from other vehicle onboard sensor(s) 230. For example, sensor data from camera(s) 232, radar sensor(s) 234, ultrasonic sensor(s) 236, and / or other sensor(s) 238 may be correlated or fused with sensor data LiDAR system(s) 210, thereby at least partially offloading the sensor fusion process performed by vehicle perception and planning system 220. It is understood that other configurations may also be implemented for transmitting and processing sensor data from the various sensors (e.g., data can be transmitted to a cloud or edge computing service provider for processing and then the processing results can be transmitted back to the vehicle perception and planning system 220 and / or LiDAR system 210).

[0049] With reference still to FIG. 2, in some embodiments, sensors onboard other vehicle(s) 250 are used to provide additional sensor data separately or together with LiDAR system(s) 210. For example, two or more nearby vehicles may have their own respective LiDAR sensor(s). camera(s). radar sensor(s), ultrasonic sensor(s). etc. Nearby vehicles can communicate and share sensor data with one another. Communications between vehicles are also referred to as V2V (vehicle to vehicle) communications. For example, as shown in FIG. 2, sensor data generated by other vehicle(s) 250 can be communicated to vehicle perception and planning system 220 and / or vehicle onboard LiDAR system(s) 210, via communication path 253 and / or communication path 251, respectively. Communication paths 253 and 251 can be any wired or wireless communication links that can transfer data.

[0050] Sharing sensor data facilitates a better perception of the environment external to the vehicles. For instance, a first vehicle may not sense a pedestrian that is behind a second vehicle but is approaching the first vehicle. The second vehicle may share the sensor data related to this pedestrian with the first vehicle such that the first vehicle can have additional reaction time to avoid collision with the pedestrian. In some embodiments, similar to data generated by sensor(s) 230, data generated by sensors onboard other vehicle(s) 250 may be correlated or fused with sensor data generated by LiDAR system(s) 210 (or with other LiDAR systems located in other vehicles), thereby at least partially offloading the sensor fusion process performed by vehicle perception and planning system 220.

[0051] In some embodiments, intelligent infrastructure system(s) 240 are used to provide sensor data separately or together with LiDAR system(s) 210. Certain infrastructures may be configured to communicate with a vehicle to convey information and vice versa. Communications between a vehicle and infrastructures are generally referred to as V2I (vehicle to infrastructure) communications. For example, intelligent infrastructure system(s) 240 may include an intelligent traffic light that can convey its status to an approaching vehicle in a message such as “changing to yellow in 5 seconds.” Intelligent infrastructure system(s) 240 may also include its own LiDAR system mounted near an intersection such that it can convey traffic monitoring information to a vehicle. For example, a left-turning vehicle at an intersection may not have sufficient sensing capabilities because some of its own sensors may be blocked by traffic in the opposite direction. In such a situation, sensors of intelligent infrastructure system(s) 240 can provide useful data to the leftturning vehicle. Such data may include, for example, traffic conditions, information of objects in the direction the vehicle is turning to, traffic light status and predictions, or the like. These sensor data generated by intelligent infrastructure system(s) 240 can be provided to vehicle perception and planning system 220 and / or vehicle onboard LiDAR system(s) 210, via communication paths 243 and / or 241, respectively. Communication paths 243 and / or 241 can include any wired or wireless communication links that can transfer data. For example, sensor data from intelligent infrastructure system(s) 240 may be transmitted to LiDAR system(s) 210 and correlated or fused with sensor data generated by LiDAR system(s) 210, thereby at least partially offloading the sensor fusion process performed by vehicle perception and planning system 220. V2V and V2I communications described above are examples of vehicle-to-X (V2X) communications, where the “X” represents any other devices, systems, sensors, infrastructure, or the like that can share data with a vehicle.

[0052] With reference still to FIG. 2, via various communication paths, vehicle perception and planning system 220 receives sensor data from one or more of LiDAR system(s) 210, other vehicle onboard sensor(s) 230, other vehicle(s) 250, and / or intelligent infrastructure system(s) 240. In some embodiments, different types of sensor data are correlated and / or integrated by a sensor fusion sub-system 222. For example, sensor fusion sub-system 222 can generate a 360- degree model using multiple images or videos captured by multiple cameras disposed at different positions of the vehicle. Sensor fusion sub-system 222 obtains sensor data from different types of sensors and uses the combined data to perceive the environment more accurately. For example, a vehicle onboard camera 232 may not capture a clear image because it is facing the sun or a light source (e.g., another vehicle’s headlight during nighttime) directly. A LiDAR system 210 may not be affected as much and therefore sensor fusion sub-system 222 can combine sensor data provided by both camera 232 and LiDAR system 210, and use the sensor data provided by LiDAR system 210 to compensate the unclear image captured by camera 232. As another example, in a rainy or foggy weather, a radar sensor 234 may work better than a camera 232 or a LiDAR system 210. Accordingly, sensor fusion sub-system 222 may use sensor data provided by the radar sensor 234 to compensate the sensor data provided by camera 232 or LiDAR system 210.

[0053] In other examples, sensor data generated by other vehicle onboard sensor(s) 230 may have a lower resolution (e.g.. radar sensor data) and thus may need to be correlated and confirmed by LiDAR system(s) 210, which usually has a higher resolution. For example, a sewage cover (also referred to as a manhole cover) may be detected by radar sensor 234 as an object towards which a vehicle is approaching. Due to the low-resolution nature of radar sensor 234, vehicle perception and planning system 220 may not be able to determine whether the object is an obstacle that the vehicle needs to avoid. High-resolution sensor data generated by LiDAR system(s) 210 thus can be used to correlated and confirm that the object is a sewage cover and causes no harm to the vehicle.

[0054] Vehicle perception and planning system 220 further comprises an object classifier 223. Using raw sensor data and / or correlated / fused data provided by sensor fusion sub-system 222, object classifier 223 can use any computer vision techniques to detect and classify the objects and estimate the positions of the objects. In some embodiments, object classifier 223 can use machine-learning based techniques to detect and classify objects. Examples of the machinelearning based techniques include utilizing algorithms such as region-based convolutional neural networks (R-CNN), Fast R-CNN, Faster R-CNN, histogram of oriented gradients (HOG), region-based fully convolutional network (R- FCN), single shot detector (SSD), spatial pyramid pooling (SPP-net), and / or You Only Look Once (Yolo).

[0055] Vehicle perception and planning system 220 further comprises a road detection sub-system 224. Road detection sub-system 224 localizes the road and identifies objects and / or markings on the road. For example, based on raw or fused sensor data provided by radar sensor(s) 234, camera(s) 232, and / or LiDAR system(s) 210, road detection sub-system 224 can build a 3D model of the road based on machine-learning techniques (e.g., pattern recognition algorithms for identifying lanes). Using the 3D model of the road, road detection sub-system 224 can identify objects (e.g., obstacles or debris on the road) and / or markings on the road (e.g., lane lines, turning marks, crosswalk marks, or the like).

[0056] Vehicle perception and planning system 220 further comprises a localization and vehicle posture sub-system 225. Based on raw or fused sensor data, localization and vehicle posture sub-system 225 can determine position of the vehicle and the vehicle’s posture. For example, using sensor data from LiDAR system(s) 210, camera(s) 232, and / or GPS data, localization and vehicle posture sub-system 225 can determine an accurate position of the vehicle on the road and the vehicle’s six degrees of freedom (e.g., whether the vehicle is moving forward or backward, up or down, and left or right). In some embodiments, high-definition (HD) maps are used for vehicle localization. HD maps can provide highly detailed, three-dimensional, computerized maps that pinpoint a vehicle’s location. For instance, using the HD maps, localization and vehicle posture sub-system 225 can determine precisely the vehicle’s current position (e.g.. which lane of the road the vehicle is currently in, how close it is to a curb or a sidewalk) and predict vehicle’s future positions.

[0057] Vehicle perception and planning system 220 further comprises obstacle predictor 226. Objects identified by object classifier 223 can be stationary (e.g., a light pole, a road sign) or dynamic (e.g.. a moving pedestrian, bicycle, another car). For moving objects, predicting their moving path or future positions can be important to avoid collision. Obstacle predictor 226 can predict an obstacle trajectory and / or warn the driver or the vehicle planning sub-system 228 about a potential collision. For example, if there is a high likelihood that the obstacle’s trajectory intersects with the vehicle’s current moving path, obstacle predictor 226 can generate such a warning. Obstacle predictor 226 can use a variety of techniques for making such a prediction. Such techniques include, for example, constant velocity or acceleration models, constant turn rate and velocity / acceleration models, Kalman Filter and Extended Kalman Filter based models, recurrent neural network (RNN) based models, long short-term memory (LSTM) neural network based models, encoder-decoder RNN models, or the like.

[0058] With reference still to FIG. 2, in some embodiments, vehicle perception and planning system 220 further comprises vehicle planning sub-system 228. Vehicle planning sub-system 228 can include one or more planners such as a route planner, a driving behaviors planner, and a motion planner. The route planner can plan the route of a vehicle based on the vehicle’s current location data, target location data, traffic information, etc. The driving behavior planner adjusts the timing and planned movement based on how other objects might move, using the obstacle prediction results provided by obstacle predictor 226. The motion planner determines the specific operations the vehicle needs to follow. The planning results are then communicated to vehicle control system 280 via vehicle interface 270. The communication can be performed through communication paths 227 and 271, which include any wired or wireless communication links that can transfer data.

[0059] Vehicle control system 280 controls the vehicle’s steering mechanism, throttle, brake, etc., to operate the vehicle according to the planned route and movement. In some examples, vehicle perception and planning system 220 may further comprise a user interface 260, which provides a user (e.g., a driver) access to vehicle control system 280 to, for example, override or take over control of the vehicle when necessary. User interface 260 may also be separate from vehicle perception and planning system 220. User interface 260 can communicate with vehicle perception and planning system 220, for example, to obtain and display raw or fused sensor data, identified objects, vehicle’s location / posture, etc. These displayed data can help a user to better operate the vehicle. User interface 260 can communicate with vehicle perception and planning system 220 and / or vehicle control system 280 via communication paths 221 and 261 respectively, which include any wired or wireless communication links that can transfer data. It is understood that the various systems, sensors, communication links, and interfaces in FIG. 2 can be configured in any desired manner and not limited to the configuration shown in FIG. 2.

[0060] FIG. 3 is a block diagram illustrating an example LiDAR system 300. LiDAR system 300 can be used to implement LiDAR systems 110, 120A-120I, and / or 210 shown in FIGs. 1 and 2. In one embodiment, LiDAR system 300 comprises a light source 310, a transmitter 320, an optical receiver and light detector 330, a steering system 340, and a control circuitry 350. These components are coupled together using communications paths 312, 314, 322. 332. 342. 352. and 362. These communications paths include communication links (wired or wireless, bidirectional or unidirectional) among the various LiDAR system components, but need not be physical components themselves. While the communications paths can be implemented by one or more electrical wires, buses, or optical fibers, the communication paths can also be wireless channels or free-space optical paths so that no physical communication medium is present. For example, in one embodiment of LiDAR system 300, communication path 314 between light source 310 and transmitter 320 may be implemented using one or more optical fibers. Communication paths 332 and 352 may represent optical paths implemented using free space optical components and / or optical fibers. And communication paths 312, 322, 342, and 362 may be implemented using one or more electrical wires that carry electrical signals. The communications paths can also include one or more of the above types of communication mediums (e.g., they can include an optical fiber and a free-space optical component, or include one or more optical fibers and one or more electrical wires).

[0061] In some embodiments, LiDAR system 300 can be a coherent LiDAR system. One example is a frequency- modulated continuous-wave (FMCW) LiDAR. Coherent LiDARs detect objects by mixing return light from the objects with light from the coherent laser transmitter. Thus, as shown in FIG. 3, if LiDAR system 300 is a coherent LiDAR, it may include a route 372 providing a portion of transmission light from transmitter 320 to optical receiver and light detector 330. Route 372 may include one or more optics (e.g., optical fibers, lens, mirrors, etc.) for providing the light from transmitter 320 to optical receiver and light detector 330. The transmission light provided by transmitter 320 may be modulated light and can be split into two portions. One portion is transmitted to the FOV, while the second portion is sent to the optical receiver and light detector of the LiDAR system. The second portion is also referred to as the light that is kept local (LO) to the LiDAR system. The transmission light is scattered or reflected by various objects in the FOV and at least a portion of it forms return light. The return light is subsequently detected and interferometrically recombined with the second portion of the transmission light that was kept local. Coherent LiDAR provides a means of optically sensing an object’s range as well as its relative velocity along the line-of-sight (LOS).

[0062] LiDAR system 300 can also include other components not depicted in FIG. 3, such as power buses, power supplies, LED indicators, switches, etc. Additionally, other communication connections among components may be present, such as a direct connection between light source 310 and optical receiver and light detector 330 to provide a reference signal so that the time from when a light pulse is transmitted until a return light pulse is detected can be accurately measured.

[0063] Light source 310 outputs laser light for illuminating objects in a field of view (FOV). The laser light can be infrared light having a wavelength in the range of 700nm to 1mm. Light source 310 can be, for example, a semiconductor-based laser (e.g., a diode laser) and / or a fiber-based laser. A semiconductor-based laser can be, for example, an edge emitting laser (EEL), a vertical cavity surface emitting laser (VCSEL), an external-cavity diode laser, a vertical-external-cavity surface-emitting laser, a distributed feedback (DFB) laser, a distributed Bragg reflector (DBR) laser, an interband cascade laser, a quantum cascade laser, a quantum well laser, a double heterostructure laser, or the like. A fiber-based laser is a laser in which the active gain medium is an optical fiber doped with rare-earth elements such as erbium, ytterbium, neodymium, dysprosium, praseodymium, thulium and / or holmium. In some embodiments, a fiber laser is based on double-clad fibers, in which the gain medium forms the core of the fiber surrounded by two layers of cladding. The double-clad fiber allows the core to be pumped with a high-power beam, thereby enabling the laser source to be a high power fiber laser source.

[0064] In some embodiments, light source 310 comprises a master oscillator (also referred to as a seed laser) and power amplifier (MOPA). The power amplifier amplifies the output power of the seed laser. The power amplifier can be a fiber amplifier, a bulk amplifier, or a semiconductor optical amplifier. The seed laser can be a diode laser (e.g., a Fabry-Perot cavity laser, a distributed feedback laser), a solid-state bulk laser, or a tunable external-cavity diode laser. In some embodiments, light source 310 can be an optically pumped microchip laser. Microchip lasers are alignment-free monolithic solid-state lasers where the laser crystal is directly contacted with the end mirrors of the laser resonator. A microchip laser is typically pumped with a laser diode (directly or using a fiber) to obtain the desired output power. A microchip laser can be based on neodymium-doped yttrium aluminum garnet (Y3A15O12) laser crystals (i.e., Nd:YAG), or neodymium-doped vanadate (i.e., ND:YVO4) laser crystals. In some examples, light source 310 may have multiple amplification stages to achieve a high power gain such that the laser output can have high power, thereby enabling the LiDAR system to have a long scanning range. In some examples, the power amplifier of light source 310 can be controlled such that the power gain can be varied to achieve any desired laser output power.

[0065] FIG. 4 is a block diagram illustrating an example fiber-based laser source 400 having a seed laser and one or more pumps (e.g., laser diodes) for pumping desired output power. Fiber-based laser source 400 is an example of light source 310 depicted in FIG. 3. In some embodiments, fiber-based laser source 400 comprises a seed laser 402 to generate initial light pulses of one or more wavelengths (e.g., infrared wavelengths such as 1550 nm), which are provided to a wavelength-division multiplexor (WDM) 404 via an optical fiber 403. Fiber-based laser source 400 further comprises a pump 406 for providing laser power (e.g., of a different wavelength, such as 980 nm) to WDM 404 via an optical fiber 405. WDM 404 multiplexes the light pulses provided by seed laser 402 and the laser power provided by pump 406 onto a single optical fiber 407. The output of WDM 404 can then be provided to one or more pre-amplifier(s) 408 via optical fiber 407. Pre-amplifier(s) 408 can be optical amplifier(s) that amplify optical signals (e.g., with about 10-30 dB gain). In some embodiments, pre-amplifier(s) 408 are low noise amplifiers. Pre-amplifier(s) 408 output to an optical combiner 410 via an optical fiber 409. Combiner 410 combines the output laser light of pre-amplifier(s) 408 with the laser power provided by pump 412 via an optical fiber 411. Combiner 410 can combine optical signals having the same wavelength or different wavelengths. One example of a combiner is a WDM. Combiner 410 provides combined optical signals to a booster amplifier 414, which produces output light pulses via optical fiber 415. The booster amplifier 414 provides further amplification of the optical signals (e.g., another 20-40dB). The output light pulses can then be transmitted to transmitter 320 and / or steering mechanism 340 (shown in FIG. 3). It is understood that FIG. 4 illustrates one example configuration of fiber-based laser source 400. Laser source 400 can have many other configurations using different combinations of one or more components shown in FIG. 4 and / or other components not shown in FIG. 4 (e.g., other components such as power supplies, lens(es), filters, splitters, combiners, etc.).

[0066] In some variations, fiber-based laser source 400 can be controlled (e.g., by control circuitry 350) to produce pulses of different amplitudes based on the fiber gain profile of the fiber used in fiber-based laser source 400. Communication path 312 couples fiber-based laser source 400 to control circuitry 350 (shown in FIG. 3) so that components of fiber-based laser source 400 can be controlled by or otherwise communicate with control circuitry 350. Alternatively, fiber-based laser source 400 may include its own dedicated controller. Instead of control circuitry 350 communicating directly with components of fiber-based laser source 400, a dedicated controller of fiber-based laser source 400 communicates with control circuitry 350 and controls and / or communicates with the components of fiberbased laser source 400. Fiber-based laser source 400 can also include other components not shown, such as one or more power connectors, power supplies, and / or power lines.

[0067] Referencing FIG. 3, typical operating wavelengths of light source 310 comprise, for example, about 850 nm, about 905 nm, about 940 nm, about 1064 nm, and about 1550 nm. For laser safety, the upper limit of maximum usable laser power is set by the U.S. FDA (U.S. Food and Drug Administration) regulations. The optical power limit at 1550 nm wavelength is much higher than those of the other aforementioned wavelengths. Further, at 1550 nm, the optical power loss in a fiber is low. There characteristics of the 1550 nm wavelength make it more beneficial for long-range LiDAR applications. The amount of optical power output from light source 310 can be characterized by its peak power, average power, pulse energy, and / or the pulse energy density. The peak power is the ratio of pulse energy to the width of the pulse (e.g., full width at half maximum or FWHM). Thus, a smaller pulse width can provide a larger peak power for a fixed amount of pulse energy. A pulse width can be in the range of nanosecond or picosecond. The average power is the product of the energy of the pulse and the pulse repetition rate (PRR). As described in more detail below, the PRR represents the frequency of the pulsed laser light. In general, the smaller the time interval between the pulses, the higher the PRR. The PRR typically corresponds to the maximum range that a LiDAR system can measure. Light source 310 can be configured to produce pulses at high PRR to meet the desired number of data points in a point cloud generated by the LiDAR system. Light source 310 can also be configured to produce pulses at medium or low PRR to meet the desired maximum detection distance. Wall plug efficiency (WPE) is another factor to evaluate the total power consumption, which may be a useful indicator in evaluating the laser efficiency. For example, as shown in FIG. 1, multiple LiDAR systems may be attached to a vehicle, which may be an electrical-powered vehicle or a vehicle otherwise having limited fuel or battery power supply. Therefore, high WPE and intelligent ways to use laser power are often among the important considerations when selecting and configuring light source 310 and / or designing laser delivery systems for vehicle-mounted LiDAR applications.

[0068] It is understood that the above descriptions provide non-limiting examples of a light source 310. Light source 310 can be configured to include many other types of light sources (e.g., laser diodes, short-cavity fiber lasers, solid- state lasers, and / or tunable external cavity diode lasers) that are configured to generate one or more light signals at various wavelengths. In some examples, light source 310 comprises amplifiers (e.g., pre-amplifiers and / or booster amplifiers), which can be a doped optical fiber amplifier, a solid-state bulk amplifier, and / or a semiconductor optical amplifier. The amplifiers are configured to receive and amplify light signals with desired gains.

[0069] With reference back to FIG. 3, LiDAR system 300 further comprises a transmitter 320. Light source 310 provides laser light (e.g., in the form of a laser beam) to transmitter 320. The laser light provided by light source 310 can be amplified laser light with a predetermined or controlled wavelength, pulse repetition rate, and / or power level. Transmitter 320 receives the laser light from light source 310 and transmits the laser light to steering mechanism 340 with low divergence. In some embodiments, transmitter 320 can include, for example, optical components (e.g.. lens, fibers, mirrors, etc.) for transmitting one or more laser beams to a field-of-view (FOV) directly or via steering mechanism 340. While FIG. 3 illustrates transmitter 320 and steering mechanism 340 as separate components, they may be combined or integrated as one system in some embodiments. Steering mechanism 340 is described in more detail below.

[0070] Laser beams provided by light source 310 may diverge as they travel to transmitter 320. Therefore, transmitter 320 often comprises a collimating lens configured to collect the diverging laser beams and produce more parallel optical beams with reduced or minimum divergence. The collimated optical beams can then be further directed through various optics such as mirrors and lens. A collimating lens may be, for example, a single plano-convex lens or a lens group. The collimating lens can be configured to achieve any desired properties such as the beam diameter, divergence, numerical aperture, focal length, or the like. A beam propagation ratio or beam quality factor (also referred to as the M2 factor) is used for measurement of laser beam quality. In many LiDAR applications, it is important to have good laser beam quality in the generated transmitting laser beam. The M2 factor represents a degree of variation of a beam from an ideal Gaussian beam. Thus, the M2 factor reflects how well a collimated laser beam can be focused on a small spot, or how well a divergent laser beam can be collimated. Therefore, light source 310 and / or transmitter 320 can be configured to meet, for example, a scan resolution requirement while maintaining the desired M2 factor.

[0071] One or more of the light beams provided by transmitter 320 are scanned by steering mechanism 340 to a FOV. Steering mechanism 340 scans light beams in multiple dimensions (e.g., in both the horizontal and vertical dimension) to facilitate LiDAR system 300 to map the environment by generating a 3D point cloud. A horizontal dimension can be a dimension that is parallel to the horizon or a surface associated with the LiDAR system or a vehicle (e.g., a road surface). A vertical dimension is perpendicular to the horizontal dimension (i.e., the vertical dimension forms a 90- degree angle with the horizontal dimension). Steering mechanism 340 will be described in more detail below. The laser light scanned to an FOV may be scattered or reflected by an object in the FOV. At least a portion of the scattered or reflected light forms return light that returns to LiDAR system 300. FIG. 3 further illustrates an optical receiver and light detector 330 configured to receive the return light. Optical receiver and light detector 330 comprises an optical receiver that is configured to collect the return light from the FOV. The optical receiver can include optics (e.g., lens, fibers, mirrors, etc.) for receiving, redirecting, focusing, amplifying, and / or filtering return light from the FOV. For example, the optical receiver often includes a collection lens (e.g., a single plano-convex lens or a lens group) to collect and / or focus the collected return light onto a light detector.

[0072] A light detector detects the return light focused by the optical receiver and generates current and / or voltage signals proportional to the incident intensity of the return light. Based on such current and / or voltage signals, the depth information of the object in the FOV can be derived. One example method for deriving such depth information is based on the direct TOF (time of flight), which is described in more detail below. A light detector may be characterized by its detection sensitivity, quantum efficiency, detector bandwidth, linearity, signal to noise ratio (SNR), overload resistance, interference immunity, etc. Based on the applications, the light detector can be configured or customized to have any desired characteristics. For example, optical receiver and light detector 330 can be configured such that the light detector has a large dynamic range while having a good linearity. The light detector linearity indicates the detector’s capability of maintaining linear relationship between input optical signal power and the detector’s output. A detector having good linearity can maintain a linear relationship over a large dynamic input optical signal range. To achieve desired detector characteristics, configurations or customizations can be made to the light detector’s structure and / or the detector’s material system. Various detector structures can be used for a light detector. For example, a light detector structure can be a PIN based structure, which has a undoped intrinsic semiconductor region (i.e.. an “i” region) between a p-type semiconductor and an n-type semiconductor region. Other light detector structures comprise, for example, an APD (avalanche photodiode) based structure, a PMT (photomultiplier tube) based structure, a SiPM (Silicon photomultiplier) based structure, a SPAD (single-photon avalanche diode) based structure, and / or quantum wires. For material systems used in a light detector, Si, InGaAs, and / or Si / Ge based materials can be used. It is understood that many other detector structures and / or material systems can be used in optical receiver and light detector 330.

[0073] A light detector (e.g., an APD based detector) may have an internal gain such that the input signal is amplified when generating an output signal. However, noise may also be amplified due to the light detector’s internal gain. Common types of noise include signal shot noise, dark current shot noise, thermal noise, and amplifier noise. In some embodiments, optical receiver and light detector 330 may include a pre-amplifier that is a low noise amplifier (LNA). In some embodiments, the pre-amplifier may also include a transimpedance amplifier (TIA), which converts a current signal to a voltage signal. For a linear detector system, input equivalent noise or noise equivalent power (NEP) measures how sensitive the light detector is to weak signals. Therefore, they can be used as indicators of the overall system performance. For example, the NEP of a light detector specifies the power of the weakest signal that can be detected and therefore it in turn specifies the maximum range of a LiDAR system. It is understood that various light detector optimization techniques can be used to meet the requirement of LiDAR system 300. Such optimization techniques may include selecting different detector structures, materials, and / or implementing signal processing techniques (e.g., filtering, noise reduction, amplification, or the like). For example, in addition to, or instead of, using direct detection of return signals (e.g., by using ToF), coherent detection can also be used for a light detector. Coherent detection allows for detecting amplitude and phase information of the received light by interfering the received light with a local oscillator. Coherent detection can improve detection sensitivity and noise immunity.

[0074] FIG. 3 further illustrates that LiDAR system 300 comprises steering mechanism 340. As described above, steering mechanism 340 directs light beams from transmitter 320 to scan an FOV in multiple dimensions. A steering mechanism is referred to as a raster mechanism, a scanning mechanism, or simply a light scanner. Scanning light beams in multiple directions (e.g., in both the horizontal and vertical directions) facilitates a LiDAR system to map the environment by generating an image or a 3D point cloud. A steering mechanism can be based on mechanical scanning and / or solid-state scanning. Mechanical scanning uses rotating mirrors to steer the laser beam or physically rotate the LiDAR transmitter and receiver (collectively referred to as transceiver) to scan the laser beam. Solid-state scanning directs the laser beam to various positions through the FOV without mechanically moving any macroscopic components such as the transceiver. Solid-state scanning mechanisms include, for example, optical phased arrays based steering and flash LiDAR based steering. In some embodiments, because solid-state scanning mechanisms do not physically move macroscopic components, the steering performed by a solid-state scanning mechanism may be referred to as effective steering. A LiDAR system using solid-state scanning may also be referred to as a non-mechanical scanning or simply non-scanning LiDAR system (a flash LiDAR system is an example non-scanning LiDAR system). Steering mechanism 340 can be used with a transceiver (e.g., transmitter 320 and optical receiver and light detector 330) to scan the FOV for generating an image or a 3D point cloud. As an example, to implement steering mechanism 340, a two-dimensional mechanical scanner can be used with a single-point or several single-point transceivers. A single-point transceiver transmits a single light beam or a small number of light beams (e.g.. 2-8 beams) to the steering mechanism. A two-dimensional mechanical steering mechanism comprises, for example, polygon mirror(s), oscillating mirror(s), rotating prism(s). rotating tilt mirror surface(s), single-plane or multi-plane mirror(s), or a combination thereof. In some embodiments, steering mechanism 340 may include non-mechanical steering mechanism(s) such as solid-state steering mechanism(s). For example, steering mechanism 340 can be based on tuning wavelength of the laser light combined with refraction effect, and / or based on reconfigurable grating / phase array. In some embodiments, steering mechanism 340 can use a single scanning device to achieve two-dimensional scanning or multiple scanning devices combined to realize two-dimensional scanning.

[0075] As another example, to implement steering mechanism 340, a one-dimensional mechanical scanner can be used with an array or a large number of single-point transceivers. Specifically, the transceiver array can be mounted on a rotating platform to achieve 360-degree horizontal field of view. Alternatively, a static transceiver array can be combined with the one-dimensional mechanical scanner. A one-dimensional mechanical scanner comprises polygon mirror(s), oscillating miiTor(s), rotating prism(s), rotating tilt mirror surface(s), or a combination thereof, for obtaining a forward-looking horizontal field of view. Steering mechanisms using mechanical scanners can provide robustness and reliability in high volume production for automotive applications.

[0076] As another example, to implement steering mechanism 340, a two-dimensional transceiver can be used to generate a scan image or a 3D point cloud directly. In some embodiments, a stitching or micro shift method can be used to improve the resolution of the scan image or the field of view being scanned. For example, using a two-dimensional transceiver, signals generated at one direction (e.g., the horizontal direction) and signals generated at the other direction (e.g., the vertical direction) may be integrated, interleaved, and / or matched to generate a higher or full resolution image or 3D point cloud representing the scanned FOV.

[0077] Some implementations of steering mechanism 340 comprise one or more optical redirection elements (e.g., mirrors or lenses) that steer return light signals (e.g., by rotating, vibrating, or directing) along a receive path to direct the return light signals to optical receiver and light detector 330. The optical redirection elements that direct light signals along the transmitting and receiving paths may be the same components (e.g., shared), separate components (e.g., dedicated), and / or a combination of shared and separate components. This means that in some cases the transmitting and receiving paths are different although they may partially overlap (or in some cases, substantially overlap or completely overlap).

[0078] With reference still to FIG. 3, LiDAR system 300 further comprises control circuitry 350. Control circuitry 350 can be configured and / or programmed to control various parts of the LiDAR system 300 and / or to perform signal processing. In a typical system, control circuitry 350 can be configured and / or programmed to perform one or more control operations including, for example, controlling light source 310 to obtain the desired laser pulse timing, the pulse repetition rate, and power: controlling steering mechanism 340 (e.g.. controlling the speed, direction, and / or other parameters) to scan the FOV and maintain pixel registration and / or alignment: controlling optical receiver and light detector 330 (e.g.. controlling the sensitivity, noise reduction, filtering, and / or other parameters) such that it is an optimal state: and monitoring overall system health / status for functional safety (e.g., monitoring the laser output power and / or the steering mechanism operating status for safety).

[0079] Control circuitry 350 can also be configured and / or programmed to perform signal processing to the raw data generated by optical receiver and light detector 330 to derive distance and reflectance information, and perform data packaging and communication to vehicle perception and planning system 220 (shown in HG. 2). For example, control circuitry 350 determines the time it takes from transmitting a light pulse until a corresponding return light pulse is received; determines when a return light pulse is not received for a transmitted light pulse: determines the direction (e.g.. horizontal and / or vertical information) for a transmitted / return light pulse; determines the estimated range in a particular direction; derives the reflectivity of an object in the FOV, and / or determines any other type of data relevant to LiDAR system 300.

[0080] LiDAR system 300 can be disposed in a vehicle, which may operate in many different environments including hot or cold weather, rough road conditions that may cause intense vibration, high or low humidities, dusty areas, etc. Therefore, in some embodiments, optical and / or electronic components of LiDAR system 300 (e.g., optics in transmitter 320, optical receiver and light detector 330, and steering mechanism 340) are disposed and / or configured in such a manner to maintain long term mechanical and optical stability. For example, components in LiDAR system 300 may be secured and sealed such that they can operate under all conditions a vehicle may encounter. As an example, an antimoisture coating and / or hermetic sealing may be applied to optical components of transmitter 320, optical receiver and light detector 330, and steering mechanism 340 (and other components that are susceptible to moisture). As another example, housing(s), enclosure(s), fairing(s), and / or window can be used in LiDAR system 300 for providing desired characteristics such as hardness, ingress protection (IP) rating, self-cleaning capability, resistance to chemical and resistance to impact, or the like. In addition, efficient and economical methodologies for assembling LiDAR system 300 may be used to meet the LiDAR operating requirements while keeping the cost low.

[0081] It is understood by a person of ordinary skill in the art that FIG. 3 and the above descriptions are for illustrative purposes only, and a LiDAR system can include other functional units, blocks, or segments, and can include variations or combinations of these above functional units, blocks, or segments. For example, LiDAR system 300 can also include other components not depicted in FIG. 3, such as power buses, power supplies, LED indicators, switches, etc. Additionally, other connections among components may be present, such as a direct connection between light source 310 and optical receiver and light detector 330 so that light detector 330 can accurately measure the time from when light source 310 transmits a light pulse until light detector 330 detects a return light pulse.

[0082] These components shown in FIG. 3 are coupled together using communications paths 312, 314, 322, 332, 342, 352, and 362. These communications paths represent communication (bidirectional or unidirectional) among the various LiDAR system components but need not be physical components themselves. While the communications paths can be implemented by one or more electrical wires, buses, or optical fibers, the communication paths can also be wireless channels or open-air optical paths so that no physical communication medium is present. For example, in one example LiDAR system, communication path 314 includes one or more optical fibers: communication path 352 represents an optical path; and communication paths 312. 322. 342, and 362 are all electrical wires that carry electrical signals. The communication paths can also include more than one of the above types of communication mediums (e.g., they can include an optical fiber and an optical path, or one or more optical fibers and one or more electrical wires).

[0083] As described above, some LiDAR systems use the time-of-flight (ToF) of light signals (e.g., light pulses) to determine the distance to objects in a light path. For example, with reference to FIG. 5A, an example LiDAR system 500 includes a laser light source (e.g.. a fiber laser), a steering mechanism (e.g., a system of one or more moving mirrors), and a light detector (e.g., a photodetector with one or more optics). LiDAR system 500 can be implemented using, for example, LiDAR system 300 described above. LiDAR system 500 transmits a light pulse 502 along light path 504 as determined by the steering mechanism of LiDAR system 500. In the depicted example, light pulse 502, which is generated by the laser light source, is a short pulse of laser light. Further, the signal steering mechanism of the LiDAR system 500 is a pulsed-signal steering mechanism. However, it should be appreciated that LiDAR systems can operate by generating, transmitting, and detecting light signals that are not pulsed and derive ranges to an object in the surrounding environment using techniques other than time-of-flight. For example, some LiDAR systems use frequency modulated continuous waves (i.e., “FMCW”). It should be further appreciated that any of the techniques described herein with respect to time-of-flight based systems that use pulsed signals also may be applicable to LiDAR systems that do not use one or both of these techniques.

[0084] Referring back to FIG. 5A (e.g., illustrating a time-of-flight LiDAR system that uses light pulses), when light pulse 502 reaches object 506, light pulse 502 scatters or reflects to form a return light pulse 508. Return light pulse 508 may return to system 500 along light path 510. The time from when transmitted light pulse 502 leaves LiDAR system 500 to when return light pulse 508 arrives back at LiDAR system 500 can be measured (e.g., by a processor or other electronics, such as control circuitry 350, within the LiDAR system). This time-of-flight combined with the knowledge of the speed of light can be used to determine the range / distance from LiDAR system 500 to the portion of object 506 where light pulse 502 scattered or reflected.

[0085] By directing many light pulses, as depicted in FIG. 5B, LiDAR system 500 scans the external environment (e.g., by directing light pulses 502, 522, 526, 530 along light paths 504, 524, 528, 532, respectively). As depicted in FIG. 5C, LiDAR system 500 receives return light pulses 508, 542, 548 (which correspond to transmitted light pulses 502, 522, 530, respectively). Return light pulses 508, 542, and 548 are formed by scattering or reflecting the transmitted light pulses by one of objects 506 and 514. Return light pulses 508, 542, and 548 may return to LiDAR system 500 along light paths 510, 544, and 546, respectively. Based on the direction of the transmitted light pulses (as determined by LiDAR system 500) as well as the calculated range from LiDAR system 500 to the portion of objects that scatter or reflect the light pulses (e.g., the portions of objects 506 and 514), the external environment within the detectable range (e.g., the field of view between path 504 and 532, inclusively) can be precisely mapped or plotted (e.g., by generating a 3D point cloud or images).

[0086] If a corresponding light pulse is not received for a particular transmitted light pulse, then LiDAR system 500 may determine that there are no objects within a detectable range of LiDAR system 500 (e.g., an object is beyond the maximum scanning distance of LiDAR system 500). For example, in FIG. 5B, light pulse 526 may not have a corresponding return light pulse (as illustrated in FIG. 5C) because light pulse 526 may not produce a scattering event along its transmission path 528 within the predetermined detection range. LiDAR system 500, or an external system in communication with LiDAR system 500 (e.g.. a cloud system or service), can interpret the lack of return light pulse as no object being disposed along light path 528 within the detectable range of LiDAR system 500.

[0087] In FIG. 5B, light pulses 502, 522, 526, and 530 can be transmitted in any order, serially, in parallel, or based on other timings with respect to each other. Additionally, while FIG. 5B depicts transmitted light pulses as being directed in one dimension or one plane (e.g., the plane of the paper). LiDAR system 500 can also direct transmitted light pulses along other dimension(s) or plane(s). For example. LiDAR system 500 can also direct transmitted light pulses in a dimension or plane that is perpendicular to the dimension or plane shown in FIG. 5B, thereby forming a 2-dimensional transmission of the light pulses. This 2-dimensional transmission of the light pulses can be point-by-point, line-by-line, all at once, or in some other manner. That is, LiDAR system 500 can be configured to perform a point scan, a line scan, a one-shot without scanning, or a combination thereof. A point cloud or image from a 1 -dimensional transmission of light pulses (e.g., a single horizontal line) can generate 2-dimensional data (e.g., (1) data from the horizontal transmission direction and (2) the range or distance to objects). Similarly, a point cloud or image from a 2-dimensional transmission of light pulses can generate 3-dimensional data (e.g., (1) data from the horizontal transmission direction, (2) data from the vertical transmission direction, and (3) the range or distance to objects). In general, a LiDAR system performing an n-dimensional transmission of light pulses generates (n+1) dimensional data. This is because the LiDAR system can measure the depth of an object or the range / distance to the object, which provides the extra dimension of data. Therefore, a 2D scanning by a LiDAR system can generate a 3D point cloud for mapping the external environment of the LiDAR system.

[0088] The density of a point cloud refers to the number of measurements (data points) per area performed by the LiDAR system. A point cloud density relates to the LiDAR scanning resolution. Typically, a larger point cloud density, and therefore a higher resolution, is desired at least for the region of interest (ROI). The density of points in a point cloud or image generated by a LiDAR system is equal to the number of pulses divided by the field of view. In some embodiments, the field of view can be fixed. Therefore, to increase the density of points generated by one set of transmission-receiving optics (or transceiver optics), the LiDAR system may need to generate a pulse more frequently. In other words, a light source in the LiDAR system may have a higher pulse repetition rate (PRR). On the other hand, by generating and transmitting pulses more frequently, the farthest distance that the LiDAR system can detect may be limited. For example, if a return signal from a distant object is received after the system transmits the next pulse, the return signals may be detected in a different order than the order in which the corresponding signals are transmitted, thereby causing ambiguity if the system cannot correctly correlate the return signals with the transmitted signals.

[0089] To illustrate, consider an example LiDAR system that can transmit laser pulses with a pulse repetition rate between 500 kHz and 1 MHz. Based on the time it takes for a pulse to return to the LiDAR system and to avoid mix-up of return pulses from consecutive pulses in a typical LiDAR design, the farthest distance the LiDAR system can detect may be 300 meters and 150 meters for 500 kHz and 1 MHz, respectively. The density of points of a LiDAR system with 500 kHz repetition rate is half of that with 1 MHz. Thus, this example demonstrates that, if the system cannot correctly correlate return signals that arrive out of order, increasing the repetition rate from 500 kHz to 1 MHz (and thus improving the density of points of the system) may reduce the detection range of the system. Various techniques are used to mitigate the tradeoff between higher PRR and limited detection range. For example, multiple wavelengths can be used for detecting objects in different ranges. Optical and / or signal processing techniques (e.g., pulse encoding techniques) are also used to correlate between transmitted and return light signals.

[0090] Various systems, apparatus, and methods described herein may be implemented using digital circuitry, or using one or more computers using well-known computer processors, memory units, storage devices, computer software, and other components. Typically, a computer includes a processor for executing instructions and one or more memories for storing instructions and data. A computer may also include, or be coupled to. one or more mass storage devices, such as one or more magnetic disks, internal hard disks and removable disks, magneto-optical disks, optical disks, etc.

[0091] Various systems, apparatus, and methods described herein may be implemented using computers operating in a client-server relationship. Typically, in such a system, the client computers are located remotely from the server computers and interact via a network. The client-server relationship may be defined and controlled by computer programs running on the respective client and server computers. Examples of client computers can include desktop computers, workstations, portable computers, cellular smartphones, tablets, or other types of computing devices.

[0092] Various systems, apparatus, and methods described herein may be implemented using a computer program product tangibly embodied in an information carrier, e.g., in a non-transitory machine-readable storage device, for execution by a programmable processor; and the method processes and steps described herein, including one or more of the steps of at least some of the FIGS. 1-9, may be implemented using one or more computer programs that are executable by such a processor. A computer program is a set of computer program instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0093] A high-level block diagram of an example apparatus that may be used to implement systems, apparatus and methods described herein is illustrated in FIG. 6. Apparatus 600 comprises a processor 610 operatively coupled to a persistent storage device 620 and a main memory device 630. Processor 610 controls the overall operation of apparatus 600 by executing computer program instructions that define such operations. The computer program instructions may be stored in persistent storage device 620, or other computer-readable medium, and loaded into main memory device 630 when execution of the computer program instructions is desired. For example, processor 610 may be used to implement one or more components and systems described herein, such as control circuitry 350 (shown in FIG. 3), vehicle perception and planning system 220 (shown in FIG. 2), and vehicle control system 280 (shown in FIG. 2). Thus, the method steps of at least some of FIGS. 1 -9 can be defined by the computer program instructions stored in main memory device 630 and / or persistent storage device 620 and controlled by processor 610 executing the computer program instructions. For example, the computer program instructions can be implemented as computer executable code programmed by one skilled in the art to perform an algorithm defined by the method steps discussed herein in connection with at least some of FIGS. 1-9. Accordingly, by executing the computer program instructions, the processor 610 executes an algorithm defined by the method steps of these aforementioned figures. Apparatus 600 also includes one or more network interfaces 680 for communicating with other devices via a network. Apparatus 600 may also include one or more input / output devices 690 that enable user interaction with apparatus 600 (e.g., display, keyboard, mouse, speakers, buttons, etc.).

[0094] Processor 610 may include both general and special purpose microprocessors and may be the sole processor or one of multiple processors of apparatus 600. Processor 610 may comprise one or more central processing units (CPUs), and one or more graphics processing units (GPUs), which, for example, may work separately from and / or multi-task with one or more CPUs to accelerate processing, e.g., for various image processing applications described herein. Processor 610, persistent storage device 620, and / or main memory device 630 may include, be supplemented by, or incorporated in, one or more application-specific integrated circuits (ASICs) and / or one or more field programmable gate arrays (FPGAs).

[0095] Persistent storage device 620 and main memory device 630 each comprise a tangible non-transitory computer readable storage medium. Persistent storage device 620, and main memory device 630, may each include high-speed random access memory, such as dynamic random access memory (DRAM), static random access memory (SRAM), double data rate synchronous dynamic random access memory (DDR RAM), or other random access solid state memory devices, and may include non-volatile memory, such as one or more magnetic disk storage devices such as internal hard disks and removable disks, magneto-optical disk storage devices, optical disk storage devices, flash memory devices, semiconductor memory devices, such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), digital versatile disc readonly memory (DVD-ROM) disks, or other non-volatile solid state storage devices.

[0096] Input / output devices 690 may include peripherals, such as a printer, scanner, display screen, etc. For example, input / output devices 690 may include a display device such as a cathode ray tube (CRT), plasma or liquid crystal display (LCD) monitor for displaying information to a user, a keyboard, and a pointing device such as a mouse or a trackball by which the user can provide input to apparatus 600.

[0097] Any or all of the functions of the systems and apparatuses discussed herein may be performed by processor 610, and / or incorporated in, an apparatus or a system such as LiDAR system 300. Further, LiDAR system 300 and / or apparatus 600 may utilize one or more neural networks or other deep-learning techniques performed by processor 610 or other systems or apparatuses discussed herein.

[0098] One skilled in the art will recognize that an implementation of an actual computer or computer system may have other structures and may contain other components as well, and that FIG. 6 is a high-level representation of some of the components of such a computer for illustrative purposes.

[0099] FIG. 7 illustrates an example block diagram of a photodetector system 700 (“system 700”) configured to perform individual biasing of one or more photodetectors, according to one or more embodiments of the present disclosure. In some embodiments, the system 700 may be implemented in a LiDAR system, such as LiDAR systems HO and 120A-120I of FIG. 1, the LiDAR system 210 of FIG. 2, the LiDAR system 300 of FIG. 3, and / or any other appropriate LiDAR system.

[0100] The system 700 may be described as including various “circuits” with notations and identifiers that indicate at least some functionality that may be performed by such circuits. However, the functionality identifiers to not mean that the corresponding circuitry is only configured to perform such functions. For example, reference to a “biasing circuit” does not necessarily mean that the only function performed by the circuitry that helps accomplish the described biasing is biasing. Further, reference to a “circuit” may generally include one or more components that may be configured to perform one or more functions. Such a notation does not necessarily mean that the resulting “circuit” is a whole standalone piece in all situations. As such, use of the term “circuit” may also be synonymous with the term “circuitry.”

[0101] In the illustrated example of FIG. 7, the system 700 includes a first photodetector circuit 702a and a first local biasing circuit 706a corresponding to a first photodetector 704a. Further, the system 700 as illustrated includes a second photodetector circuit 702b and a second local biasing circuit 706b corresponding to a second photodetector 704b. However, such illustrations are for illustrative purposes and are not meant to be limiting. For example, the system 700 may include a different number of photodetectors and corresponding circuits (more or fewer) without departing from the scope of the present disclosure. Further, in the present disclosure, the first photodetector circuit 702a and the second photodetector circuit 702b may be generally referred to as “the photodetector circuits 702.”

[0102] In general, the photodetector circuits 702 may be used for detecting the light signals reflected off objects within the corresponding LiDAR system's field of view. As indicated above, LiDAR systems operate by emitting laser pulses toward a target and then measuring the time it takes for the reflected light to return to the sensor. The photodetector circuits 702 may be configured to convert these reflected light pulses into electrical signals, which are then processed to determine the distance, shape, and size of the target.

[0103] The sensitivity, speed, and dynamic range of the photodetector circuits 702 are parameters that influence the accuracy and range of the LiDAR system. For example, the photodetector circuity 702 may be designed to detect specific wavelengths of light, often in the near-infrared spectrum, where most LiDAR lasers operate. By efficiently capturing and converting these light signals, the photodetector circuity 702 may help enable the LiDAR system to create detailed 3D maps of the environment.

[0104] In some embodiments, the photodetectors 704 may be configured to detect the light signals and convert the detected light signals to electrical signals. For example, the light detector 330 of FIG. 3 may be an example of one or more of the photodetectors 704 in some embodiments. Further, one or more characteristics of the photodetectors 704 may affect one or more performance metrics of the corresponding photodetector circuits 702. For example, certain physical characteristics of the photodetectors 704 such as size, doping concentrations, temperature, etc. of the photodetectors 704 may affect sensitivity, dynamic range, etc. of the photodetector circuits 702. Additionally or alternatively, the photodetectors 704 may have individual differences such that their corresponding photodetector circuits 702 may not have the same performance metrics.

[0105] For example, in some embodiments, the first photodetector 704a may be a different photodetector structure type than the second photodetector 704b, which may result in the first photodetector 704a and the second photodetector 704b having different physical structures and characteristics. The differences may result in the first photodetector 704a and the second photodetector 704b (and their corresponding photodetector circuits 702) having different performance characteristics (e.g., different dynamic ranges).

[0106] Additionally or alternatively, the first photodetector 704a and the second photodetector 704b may have the same photodetector structure type. However, one or more actual physical characteristics of the two may not be exactly the same (e.g., due to fabrication imperfections, etc.) such that the first photodetector 704a and the second photodetector 704b (and their corresponding photodetector circuits 702) may have different individual performance characteristics even though they may be of the same type.

[0107] In these and other embodiments, the individual temperatures of the first photodetector 704a and the second photodetector 704b at different points in time may vary with respect to each other — e.g., due to physical placement and / or different components and / or circuits that may be proximate the first photodetector 704a as compared to the second photodetector 704b. The temperature differences may also result in the first photodetector 704a and the second photodetector 704b (and their corresponding photodetector circuits 702) having one or more different performance characteristics.

[0108] The performance characteristics (e.g.. dynamic range) of the individual photodetector circuits 702 may also be affected by the bias voltage that may be applied at the corresponding photodetectors 704. As discussed further in the present disclosure, the system 700 may be configured to individually adjust the bias voltages of the respective photodetectors 704 such that the performance characteristics of the respective photodetectors 704 and their corresponding photodetector circuits 702 may be individually adjusted. In these and other embodiments, the individual bias voltage adjustments may be such that the performance characteristics of different photodetectors 704 and their corresponding photodetector circuits 702 may be relatively the same even though the individual photodetectors 704 may differ.

[0109] The system 700 may include a global biasing circuit 708 in some embodiments. The global biasing circuit 708 may be configured to generate a first biasing voltage, which may also be referred to as a “global biasing voltage.” For example, in some embodiments, the global biasing circuit 708 may include a global voltage source configured to generate the global biasing voltage. In the present disclosure, use of the term “global” with respect to the global biasing circuit 708 and its corresponding components and voltages is meant to generally convey that the global biasing circuit 708 and its corresponding global biasing voltage may be used for biasing multiple photodetector circuitries (even if it is actually only used for biasing a single photodetector circuit). As such, use of the term “global” does not necessarily mean that the global biasing circuit is used “globally” with respect to all other circuits to which the system 700 may correspond.

[0110] In addition, although the terms “biasing” is used with respect to the global biasing circuit 708 and the global biasing voltage, such voltage may be used for other purposes as well. For example, the global biasing voltage may be used as a supply voltage in addition to contributing to biasing.

[0111] The global biasing circuit 708 may be coupled to the first photodetector circuit 702a and the second photodetector circuit 702b. The coupling may be such that a first bias voltage corresponding to the first photodetector circuit 702a (e.g., a first bias voltage across the first photodetector 704a) and a second bias voltage corresponding to the second photodetector circuit 702b (e.g., a second bias voltage across the second photodetector 704b) may be based on the global biasing voltage generated by the global biasing circuit 708.

[0112] For example, the photodetectors 704 may each respectively include a first node and a second node and the respective voltage across their corresponding first node and second node may be the bias voltage of the individual photodetector 704. For instance, one or more of the photodetectors 704 may include photodiodes in some embodiments. In these and other embodiments, the first node may be a cathode of a corresponding photodiode and the second node may be an anode of the corresponding photodiode. Additionally or alternatively, the global biasing circuit 708 may be coupled to the first photodetector circuit 702a and the second photodetector circuit 702b such that a first-node voltage at the first nodes of the photodetectors 704 may be based on the global biasing voltage. An example of such coupling is described with respect to FIG. 8.

[0113] In some embodiments, the global biasing circuit 708 may be configured such that the global biasing voltage is adjustable. For example, the global voltage source may be adjustable. The adjustable nature of the global biasing voltage may be such that the first bias voltage of the first photodetector circuit 702a and the second bias voltage of the second photodetector circuit 702b may both be adjusted by adjusting the global biasing voltage.

[0114] However, such an adjustment may not allow for individual adjustments of the first bias voltage and the second bias voltage. Therefore, the adjustment of the global biasing voltage may be a coarse adjustment of the individual bias voltages. In some embodiments, such coarse adjustment may be based on an ambient temperature near one or more of the photodetector circuits 702. The adjustable nature of the global biasing voltage may also therefore allow for at least dynamic coarse adjustments of the bias voltages of the photodetector circuits 702.

[0115] Further, as indicated in the present disclosure, the global biasing voltage may also operate as a supply voltage. For instance, in some embodiments, the global biasing circuit 708 may operate as a relatively high voltage supply such that the global biasing voltage may be a relatively high supply voltage as well. For example, in some embodiments, the global biasing voltage may have a voltage of 20-80V for InGaAs based photodetectors and 20-1000V for Si based photodetectors. As such, in some embodiments, the global biasing circuit 708 may also be coupled to the photodetector circuits 702 such that the global biasing voltage may operate as a power supply to each of the photodetector circuits 702.

[0116] As indicated above, the system 700 may include one or more local biasing circuits 706 that each correspond to a respective photodetector circuit 702. In general, each local biasing circuit 706 may be configured to generate a respective second biasing voltage and may be coupled to its respective photodetector circuit 702 such that the respective bias voltage of its respective photodetector circuit 702 is also based on the second biasing voltage. The individual second biasing voltages may also be referred to as “local biasing voltages.” In these and other embodiments, the local biasing voltages may be generated using local voltage supplies of the local biasing circuits 706.

[0117] For example, the first local biasing circuit 706a may correspond to the first photodetector circuit 702a and may include a first local voltage supply configured to generate a first local biasing voltage. In these and other embodiments, the first local biasing circuit 706a may be coupled to the first photodetector circuit 702a such that the first bias voltage of the first photodetector circuit 702a is based on the first local biasing voltage in addition to being based on the global biasing voltage generated by the global biasing circuit 708.

[0118] Similarly, the second local biasing circuit 706b may correspond to the second photodetector circuit 702b and may include a second local voltage supply configured to generate a second local biasing voltage. In these and other embodiments, the second local biasing circuit 706b may be coupled to the second photodetector circuit 702b such that the second bias voltage of the second photodetector circuit 702b is based on the second local biasing voltage in addition to being based on the global biasing voltage generated by the global biasing circuit 708.

[0119] In some embodiments, the coupling of the local biasing circuits 706 with their respective photodetector circuits 702 may be such that a second-node voltage at the respective second node of the corresponding photodetector circuit 702 may be based on the corresponding local biasing voltage. For example, in some embodiments, the first local biasing circuit 706a may be coupled to the first photodetector circuit 702a such that a second node voltage at the second node of the first photodetector 704a may be based on the first local biasing voltage. Similarly, the second local biasing circuit 706b may be coupled to the second photodetector circuit 702b such that a second node voltage at the second node of the second photodetector 704b may be based on the second local biasing voltage. Examples of such coupling are given in further detail with respect to FIG. 8, which provides some example implementations and corresponding details of the local biasing circuits 706.

[0120] As indicated above, the voltages across the respective first and second nodes of the photodetectors 704 may correspond to the bias voltages. As such, the first bias voltage across the first and second nodes of the first photodetector 704a may be based on the first local biasing voltage. Similarly, the second bias voltage across the first and second nodes of the second photodetector 704b may be based on the second local biasing voltage.

[0121] In some embodiments, the local biasing circuits 706 may each be configured such that their respective local biasing voltages are independently and individually adjustable. For example, in some embodiments, the first local voltage source of the first local biasing circuit 706a may be adjustable such that the first local biasing voltage may be adjustable. Further, the second local voltage source of the second local biasing circuit 706b may also be adjustable independently of any adjustment to the first local voltage source such that the first and second local biasing voltages may be adjustable individually and independent from each other. The independent adjustable nature of the local biasing voltages may accordingly be such that the first bias voltage of the first photodetector circuit 702a and the second bias voltage of the second photodetector circuit 702b may be individually adjusted. In addition, the individual and independent adjustable nature of the local biasing voltage sources may allow for dynamic adjustments to the bias voltages of the photodetector circuits 702 as conditions may change that may affect the performance characteristics of the photodetector circuits 702.

[0122] In these and other embodiments, the local biasing voltages may be adjusted based on one or more individual characteristics of its corresponding photodetectors 704. For example, the first local biasing voltage may be adjusted based on one more individual characteristics of the first photodetector 704a. Similarly, the second local biasing voltage may be adjusted based on one more individual characteristics of the second photodetector 704b. The individual characteristics may include one or more of a voltage characteristic, a current characteristic, or a temperature of the corresponding photodetector 704.

[0123] In these and other embodiments, the adjustment of the individual local biasing voltages may be performed such that the performance characteristics of the corresponding photodetector circuits 702 (e.g., of the corresponding photodetectors 704 of the photodetector circuits 702) may match (e.g., be the same or similar). For example, it may be desired that the first photodetector 704a and the second photodetector 704b have the same or similar activation characteristics (e.g., produce a same or similar amount of voltage or current in response to receiving a same amount of light at a same wavelength). However, due to differences in one or more of temperature, physical characteristics, type, etc., the first photodetector 704a and the second photodetector 704b may need different bias voltages to produce the same or similar performance characteristics (e.g., voltage output, current output, etc.). As such, the first local biasing voltage and / or the second local biasing voltage may be adjusted such that the first bias voltage and the second bias voltage may each result in the first photodetector 704a and the second photodetector 704b having similar or the same performance characteristics. The identification of the target performance characteristics and the amount and / or direction of adjustment of the first bias voltage and / or the second bias voltage to have the first photodetector 704a and the second photodetector 704b have matching performance characteristics may be accomplished using any suitable technique.

[0124] In some embodiments, the local biasing voltages may be relatively low voltage as compared to the global voltage. In some embodiments, the local biasing voltages may be relatively low voltage as compared to the global voltage. For example, the local biasing voltages may be around 1.2 V - 12V. Accordingly, the adjustment of the local biasing voltages may be controlled using less power than that which may be used to adjust the global voltage. Further, the use of the relatively small voltage local voltage sources may allow for a simplified use of materials, which may help reduce costs.

[0125] Although the local biasing circuits 706 are described as being apart and separate from the photodetector circuits 702 and are described as “biasing circuits”, such a description is not meant to be limiting. For example, the local biasing circuits 706 may also be configured to perform one or more photodetection type of operations. For instance, in some embodiments, and as discussed in further detail with respect to FIG. 8, one or more of the biasing circuits 706 may include amplifier circuitry (also referred to herein as “amplifiers”) configured to apply a gain to electrical signals generated by the photodetectors 704. Therefore, in some aspects, the local biasing circuits 706 may also be considered as being part of their corresponding photodetector circuits 702.

[0126] In some embodiments, the first photodetector circuit 702a may include a first current limiting circuit 710a. Additionally or alternatively, the second photodetector circuit 702b may include a second current limiting circuit 710b. The first current limiting circuit 710a and the second current limiting circuit 710b may be generally, collectively, and / or individually referred to as “current limiting circuits 710.” In these and other embodiments, the current limiting circuits 710 may be coupled between the global biasing circuit 708 and the respective first nodes of the photodetectors 704. Further examples of the coupling are given with respect to FIG. 8.

[0127] The current limiting circuits 710 may generally be configured to limit the current that passes through the respective photodetectors 704. For example, the first current limiting circuit 710a may be configured to limit first current that passes through the first photodetector 704a and the second current limiting circuit 710b may be configured to limit second current that passes through the second photodetector 704b.

[0128] In these and other embodiments, the current limiting may be based on a degree of activation of the corresponding photodetector 704. The limiting may be such that greater current limiting is performed in response to higher activation of the corresponding photodetector. Such current limiting may help increase the dynamic range of the corresponding photodetector 704 by allowing for increased sensitivity to low light signals while also increasing the amount of light that may result in saturation of the corresponding photodetector 704.

[0129] For example, in some embodiments, the current limiting circuits 710 may respectively include variable resistors that increase their respective resistance as an amount of current provided thereto increases. As such, in instances of relatively low activation by a corresponding photodetector 704 (e.g., due to a relatively small amount of light being detected) in which the amount of current that may be allowed to pass through the corresponding photodetector 704 by the photodetector itself is relatively small, the amount of resistance provided by the corresponding current limiting circuit 710 may be relatively small. Accordingly, in such instances the amount of current limiting that may be provided by the corresponding current limiting circuit 710 may be relatively small.

[0130] By contrast, in instances of relatively high activation by the corresponding photodetector 704 (e.g.. due to a relatively large amount of light being detected) in which the amount of current that may be allowed to pass through the corresponding photodetector 704 by the photodetector itself is relatively high, the amount of resistance provided by the corresponding current limiting circuit 710 may be relatively high. Therefore, in such instances the amount of current limiting that may be provided by the corresponding current limiting circuit 710 may be relatively high.

[0131] In these and other embodiments, the first photodetector circuit 702a may include a first reset circuit 712a. Additionally or alternatively, the second photodetector circuit 702b may include a second reset circuit 712b. The first reset circuit 712a and the second reset circuit 712b may be generally, collectively, and / or individually referred to as “reset circuits 712.” In these and other embodiments, the reset circuits 712 may be coupled to the respective second nodes of the photodetectors 704. Further examples of the coupling are given with respect to FIG. 8.

[0132] The reset circuits 712 may generally be configured to reset the respective photodetectors 704 after activation of the respective photodetectors 704. The resetting of the respective photodetectors 704 may help allow for a higher frequency response by the corresponding photodetector circuit 702 and / or the local biasing circuit 706 with respect to light that may be detected by the corresponding photodetector 704.

[0133] For example, the photodetectors 704 may activate in response to detecting first light corresponding to a first LiDAR pulse. Further, in order to differentiate between the detected first light and detected second light that corresponds to a second LiDAR pulse subsequent to the first LiDAR pulse, the photodetectors 704 may need to be reset to a state (e.g., current state and / or bias state) relatively close to that at which they were prior to detection of the first light. The reset circuits 712 may be configured to help more quickly restore their corresponding photodetectors 704 to an inactivated state following activation. Such resetting may accordingly allow for less time between LiDAR pulses such that the LiDAR pulses may be emitted at a higher frequency.

[0134] In some embodiments, one or more of the reset circuits 712 may include a respective current quenching circuit. In these and other embodiments, the current quenching circuits may be coupled between the respective second nodes of their corresponding photodetectors 704 and ground. The current quenching circuits may include any suitable component, device, circuitry, etc. that may be configured to quench the current in a corresponding photodetector circuit 702 (and / or local biasing circuit 706) that may be generated by activation of a corresponding photodetector 704.

[0135] For example, the first photodetector 704a may activate in response to receiving the first light of the first LiDAR pulse. The activation may be such that first current begins passing through the first photodetector circuit 702a. A first quenching circuit of the first reset circuit 712a may cause the activated current to quickly pass from the second node of the first photodetector 702a to ground and accordingly be quenched. The quenching may accordingly allow for the first current to be removed quickly such that a first current state of the first photodetector 704a may be reset to its inactivated state more quickly, which may allow for the first photodetector 704a to be ready to detect another pulse of light more quickly than if the first current quenching circuit were not present. The second reset circuit 712b may similarly include a second current quenching circuit. FIG. 8 illustrates a more detailed implementation of example current quenching circuits. In these and other embodiments, one or more of the reset circuits 712 may include a respective charging circuit. In these and other embodiments, the charging circuits may be coupled between the respective second nodes of their corresponding photodetectors 704 and the global biasing circuit 708. The charging circuits may include any suitable component, device, circuitry, etc. that may be configured to bring the bias voltage of a corresponding photodetector 704 back up after activation of the corresponding photodetector 704.

[0136] For example, the first photodetector 704a may activate in response to receiving the first light of the first LiDAR pulse. The activation may be such that the voltage across the first and second nodes of the first photodetector 704a (e.g., the bias voltage) drops. A first -charging circuit of the first reset circuit 712a may cause the voltage at the second node of the first photodetector to quickly pull back up (e.g., to the second-node voltage caused by the first local biasing voltage) to reset the first bias voltage of the first photodetector 704a. The charging may accordingly allow for the first bias voltage to be reset to its inactivated state more quickly, which may allow for the first photodetector 704a to be ready to detect another pulse of light more quickly than if the first charging circuit were not present. The second reset circuit 712b may similarly include a second charging circuit. FIG. 8 illustrates a more detailed implementation of example charging circuits.

[0137] The system 700 of FIG. 7 accordingly may be configured to provide for individual adjustments of bias voltages of individual photodetector circuits in a manner that allows for lower power consumption. Further, the configuration described herein may also allow for relatively high frequency emission of LiDAR pulses, which may allow for higher resolution imaging results.

[0138] Modifications, additions, or omissions may be made to the system 700 without departing from the scope of the present disclosure. For example, the number of photodetector circuits 702, corresponding local biasing circuits, etc., may vary. Further, as indicated, the types of operations of the individual circuits and such are not limited to those described. In addition, various potential implementations may be present.

[0139] FIG. 8 is a circuit diagram illustrating an example photodetector system 800 (“system 800”), according to one or more embodiments. For example, the system 800 may be an example implementation of the system 700 of FIG. 7.

[0140] In some embodiments, the system 800 may include a first photodetector circuit 802a and a second photodetector circuit 802b (generally referred to as “photodetector circuits 802). The photodetector circuits 802 may be examples of the photodetector circuits 702 of FIG. 7 in some embodiments.

[0141] The first photodetector circuit 802a may include a first photodetector 702a and the second photodetector circuit 802b may include a second photodetector 702b in some embodiments. In the illustrated example, the photodetectors 704 may each include photodiode structures respectively having a cathode and an anode. For example, the first photodetector 702a may include a first cathode 824a and a first anode 826a. Similarly, the second photodetector 702b may include a second cathode 824b and a second anode 826b. The cathodes 824 may be examples of the first nodes discussed with respect to FIG. 7 and the anodes 826 may be examples of the second nodes discussed with respect to FIG. 7.

[0142] Further, the voltages across the respective cathodes 824 and anodes 836 may correspond to respective bias voltages of the corresponding photodetectors 804 and their associated photodetector circuits 802. For example, a first cathode voltage may be present at the first cathode 824a of the first photodetector 804a. Further, a first anode voltage may be present at the first anode 826a of the first photodetector 804a. A difference between the first cathode voltage and the first anode voltage may be a first bias voltage corresponding to the first photodetector 804a. Similarly, a second cathode voltage may be present at the second cathode 824b of the second photodetector 804b. Further, a second anode voltage may be present at the second anode 826b of the second photodetector 804b. A difference between the second cathode voltage and the second anode voltage may be a second bias voltage corresponding to the second photodetector 804b. The first cathode voltage and the second cathode voltage may be examples of the first-node voltages discussed with respect to FIG. 7. Additionally or alternatively, the first anode voltage and the second anode voltage may be examples of the second-node voltages discussed with respect to FIG. 7.

[0143] The system 800 may include a voltage source 808 configured to generate a first source voltage in some embodiments. The voltage source 808 may be an example of the global biasing circuit 708 of FIG. 7.

[0144] As illustrated in FIG. 8, the voltage source 808 may be coupled to each of the cathodes 824 such that the first source voltage may affect the respective cathode voltages at the cathodes 824. For example, in some embodiments, the voltage source 808 may be directly coupled to the cathodes 824. such that the cathode voltages may be the same as or relatively the same as the first source voltage. Additionally or alternatively, such as illustrated in FIG. 8, respective current limiting circuits 810 — which may be similar or analogous to the current limiting circuits 710 of FIG. 7 — may be coupled between the first voltage source 808 and the cathodes 824. For example, a first current limiting circuit 810a may be coupled between the first voltage source 808 and the first cathode 824a. Similarly, a second current limiting circuit 810b may be coupled between the first voltage source 808 and the second cathode 824b. In instances in which the photodetectors 804 are not activated, current flowing through the photodetectors 804 may be relatively small or negligible. In such instances, the cathode voltages may also be the same as or relatively the same as the first source voltage.

[0145] Given that the respective bias voltages corresponding to the photodetectors 804 are based on the respective cathode voltages, the bias voltages may accordingly be based on the first source voltage. As such, the first source voltage may operate as a global biasing voltage such as described with respect to FIG. 7. In these and other embodiments, the first source voltage may operate as a supply voltage such as described with respect to FIG. 7.

[0146] In these and other embodiments, the first voltage source 808 may be adjustable such that the first source voltage may be adjusted. Additionally or alternatively, the first voltage source 808 may be adjusted to perform a coarse adjustment of biasing with respect to the first photodetector circuit 802a and the second photodetector circuit 802b, similar to as described with respect to FIG. 7.

[0147] As illustrated in FIG. 8, in some embodiments, the first photodetector circuit 802a may include a first local biasing circuit 806a and the second photodetector circuit may include a second local biasing circuit 806b. The local biasing circuits 806 may be examples of the local biasing circuits 706 of FIG. 7.

[0148] In some embodiments, the local biasing circuits 806 may be coupled to the respective anodes 826 of the photodetectors 804. Further, the local biasing circuits 806 may be configured to affect the corresponding anode voltages such that the local biasing circuits 806 may affect the respective bias voltages of the photodetectors 804 and their corresponding photodetector circuits 802. For example, the first local biasing circuit 806a may include a first amplifier 818a having a first first-amplifier input 830a and a second first-amplifier input 832a. Similarly, the second local biasing circuit 806b may include a second amplifier 818b having a first second-amplifier input 830b and a second second-amplifier input 832b. Further, the amplifiers 818 may be respectively configured such that they attempt to maintain the same voltage at their respective inputs. For example, the first amplifier 818a may operate to maintain the same voltage at the first first-amplifier input 830a and at the second first-amplifier input 832a. Similarly, the second amplifier 818b may operate to maintain the same voltage at the first second-amplifier input 830b and at the second second-amplifier input 832b.

[0149] The average voltages at the inputs of amplifiers configured as such are often referred to as “common-mode voltages.” For example, reference to a first common-mode voltage of the first amplifier 818a may refer to an average voltage that is present at both the first first-amplifier input 830a and the second first-amplifier input 832a. Similarly, reference to a second common-mode voltage of the second amplifier 818b may refer to an average voltage that is present at both the first second-amplifier input 830b and the second second-amplifier input 832b

[0150] In some embodiments, the first local biasing circuit 806a may include a first local voltage source 820a and the second local biasing circuit 806b may include a second local voltage source 820b. The local voltage sources 820 may be configured to respectively generate local source voltages that may affect the respective bias voltages of the corresponding photodetector circuits 802 and their associated photodetectors 804.

[0151] For example, the first local voltage source 820a may be coupled between the second first-amplifier input 832a and ground. Similarly, the second local voltage source 820b may be coupled between the second second-amplifier input 832b and ground. In the illustrated example, a first local voltage generated by the first local voltage source 820a may accordingly be applied to the second first-amplifier input 832a. Further, a second local voltage generated by the second local voltage source 820b may accordingly be applied to the second second-amplifier input 832b.

[0152] Further, due to the characteristics of the amplifiers 818, the voltages at the first inputs 830 of the amplifiers 818 may also correspond to the local source voltages. For example, the voltage at the first first-amplifier input 830a may be the same as or substantially the same as the first local voltage and the voltage at the first second-amplifier input 830b may be the same as or substantially the same as the second local voltage. The common-mode voltages of the amplifiers 818 may accordingly be based on (e.g., correspond to and / or be the same as or substantially the same as) the local voltages. For example, the first common-mode voltage of the first amplifier 818a may be based on the first local voltage and the second common-mode voltage of the second amplifier 818b may be based on the second local voltage.

[0153] In addition, the anodes 826 of the photodetectors 804 may be respectively coupled to the amplifiers 818 such that the bias voltages of the corresponding photodetectors 804 are affected by the amplifier common-mode voltages. For example, the first anode 826a may be coupled to the first first-amplifier input 830a. As such, the first anode voltage at the first anode 826a (and accordingly the first bias voltage of the first photodetector 804a) may be based on (e.g., the same as or substantially the same as) the voltage at the first first-amplifier input 830a. As indicated above, the voltage at the first first-amplifier input 830a may correspond to the first common-mode voltage and may be based on (e.g., the same as or substantially the same as) on the first source voltage generated by the first local voltage source 820a due to the coupling of the first local voltage source 820a with the second first-amplifier input 832a. The first local source voltage may accordingly operate as a first local biasing voltage that affects the first bias voltage. Similarly, the second anode 826b may be coupled to the first second-amplifier input 830b such that the second local source voltage generated by the second local voltage source 820b may operate as a second local biasing voltage that affects the second bias voltage of the second photodetector 804b.

[0154] In these and other embodiments, the first local voltage source 820a and the second local voltage source 820b may be individually adjustable such that their corresponding local source voltages may be individually adjusted. As such, the first bias voltage of the first photodetector 804a may be individually adjusted by adjusting the first local voltage source 820a and its corresponding first source voltage. Similarly, the second bias voltage of the second photodetector 804b may be individually adjusted by adjusting the second local voltage source 820b and its corresponding second source voltage. The individual adjustments of the local source voltages for adjustment of the bias voltages may be based on a number of characteristics, such as described with respect to FIG. 7.

[0155] As also illustrated in FIG. 8, the local biasing circuits 806 may also be configured to perform operations in addition to biasing. For example, the local biasing circuits 806 as illustrated may be configured to operate as transimpedance amplifier circuits that convert the current that may pass through the photodetectors 804 in response to activation of the photodetectors 804 into an output voltage. In these and other embodiments, in the illustrated examples, the amplifier circuits may be configured as positive feedback amplifiers.

[0156] For instance, the first amplifier 818a may be an operational amplifier (“op-amp”), the first first-amplifier input 830a may be a positive input terminal of the first amplifier 818a, and the second first-amplifier input 832a may be a negative input terminal of the first amplifier 818a. Further, the first local biasing circuit 806a may include a first feedback resistor 822a coupled between the first first-amplifier input 830a and a first output 828a of the first amplifier 818a.

[0157] Additionally or alternatively, the second amplifier 818b may similarly be an op-amp, the first second -amplifier input 830b may be a positive input terminal of the second amplifier 818b, and the second second-amplifier input 832b may be a negative input terminal of the second amplifier 818b. Further, the second local biasing circuit 806b may include a second feedback resistor 822b coupled between the first second-amplifier input 830b and a second output 828b of the second amplifier 818b.

[0158] In these and other embodiments, one or more of the photodetector circuits 802 may include a corresponding reset circuit 812. For example, the first photodetector circuit 802a may include a first reset circuit 812a and the second photodetector circuit 802b may include a second reset circuit 812b. The reset circuits 812 may be examples of the reset circuits 712 of FIG. 7 and may be configured to reset the photodetectors 804.

[0159] For example, in some embodiments, the first reset circuit 812a may include a first charging circuit 814a coupled between the first anode 826a and the voltage source 808. Additionally or alternatively, the second reset circuit 812b may include a second charging circuit 814b coupled between the second anode 826b and the voltage source 808. The first charging circuit 814a and the second charging circuit 814b may be configured to restore the first and second bias voltages, respectively, such as described with respect to the respective charging circuits of the reset circuits 712 of FIG. 7.

[0160] In these and other embodiments, the first reset circuit 812a may include a first current quenching circuit 816a coupled between the first anode 826a and ground. Additionally or alternatively, the second reset circuit 812b may include a second current quenching circuit 816b coupled between the second anode 826b and ground. The first current quenching circuit 816a and the second current quenching circuit 816b may be configured to quench current passing through the first photodetector 804a and the second photodetector 804b, respectively, such as described with respect to the respective current quenching circuits of the reset circuits 712 of FIG. 7.

[0161] Modifications, additions, or omissions may be made to the system 800 without departing from the scope of the present disclosure. For example, the number of photodetector circuits 802, corresponding local biasing circuits, etc., may vary. Further, as indicated, the types of operations of the individual circuits and such are not limited to those described. In addition, various potential implementations may be present. For example, the exact types of photodetector structures used may vary for different implementations or across the same implementations. Further, specific amplifier circuit configurations may vary.

[0162] In addition, in some embodiments and as indicated above, the system 700 and / or the system 800 may be implemented in any appropriate LiDAR system, such as those described in the present disclosure. In these and other embodiments, the LiDAR system may include the systems 700 or 800 may be included in a vehicle.

[0163] FIG. 9 is a flow diagram of a method 900 for biasing a photodetector system, according to one or more embodiments. One or more operations of the method 900 may be performed by any suitable system or device. For example, one or more operations of the method 900 may be performed by one or more elements of the photodetector system 700 and / or 800 of FIGS. 7 and 8.

[0164] The method 900 may include a block 902. At block 902, a global biasing voltage may be provided to each photodetector circuit of one or more photodetector circuits. The providing of the global biasing voltage may be applied such that a respective bias voltage corresponding to each photodetector circuit is based on the global biasing voltage. In some embodiments, the applying of the global biasing voltage may be accomplished in any manner described above with respect to FIG. 7 and / or FIG. 8.

[0165] The method 900 may also include a block 904. At block 904, a respective local biasing voltage may be applied to each respective photodetector circuit. The biasing voltage may be such that the respective bias voltage of the respective photodetector circuit is also based on the respective local biasing voltage. In some embodiments, the applying of the local biasing voltages may be accomplished in any manner described above with respect to FIG. 7 and / or FIG. 8.

[0166] Modifications, additions, or omissions may be made to the method 900 without departing from the scope of the present disclosure. For example, although illustrated as discrete blocks, various blocks of the method 900 may be divided into additional blocks, combined into fewer blocks, or eliminated, depending on the particular implementations. Further, any of one or more of the operations described with respect to any of the systems described in the present disclosure may be included in the method 900 in some embodiments. For example, the method 900 may include operations corresponding to those described in the present disclosure with respect to the current limiting circuits 710 of FIG. 7 and 810 of FIG. 8 and / or the reset circuits 712 and 812 of FIG. 8.

[0167] The foregoing specification is to be understood as being in every respect illustrative and exemplary, but not restrictive, and the scope of the invention disclosed herein is not to be determined from the specification, but rather from the claims as interpreted according to the full breadth permitted by the patent laws. It is to be understood that the embodiments shown and described herein are only illustrative of the principles of the present invention and that various modifications may be implemented by those skilled in the art without departing from the scope and spirit of the invention. Those skilled in the art could implement various other feature combinations without departing from the scope and spirit of the invention.

[0168] The subject technology of the present disclosure is illustrated, for example, according to various aspects described below. Various examples of aspects of the present disclosure are described as numbered examples (1, 2. 3. etc.) for convenience. These are provided as examples and do not limit the present disclosure. The aspects of the various implementations described herein may be omitted, substituted for aspects of other implementations, or combined with aspects of other implementations unless context dictates otherwise. For example, one or more aspects of example 1 below may be omitted, substituted for one or more aspects of another example (e.g., example 2) or examples, or combined with aspects of another example The following is a non-limiting summary of some example implementations presented herein.

[0169] Example 1. A system comprising: one or more photodetector circuits; a global biasing circuit configured to generate a first biasing voltage and coupled to each photodetector circuit of the one or more photodetector circuits such that a respective bias voltage corresponding to each photodetector circuit is based on the first biasing voltage; and one or more local biasing circuits that each correspond to a respective photodetector circuit, each local biasing circuit being configured to generate a respective second biasing voltage and being coupled to its respective photodetector circuit such that the respective bias voltage of its respective photodetector circuit is also based on the second biasing voltage.

[0170] Example 2. The system of claim 1, wherein: the global biasing circuit includes a global voltage source configured to generate the first biasing voltage; and each local biasing circuit includes a respective local voltage source configured to generate its respective second biasing voltage.

[0171] Example 3. The system of any of Example 1 or Example 2, wherein: each photodetector circuit includes a respective photodetector having a respective first node and a respective second node; the global biasing circuit is coupled to each photodetector circuit such that a first-node voltage at its respective first node is based on the first biasing voltage; each local biasing circuit is coupled to its corresponding photodetector circuit such that a second-node voltage at its respective second node is based on the second biasing voltage; and the respective bias voltage of each photodetector circuit is the voltage across the respective first node and the respective second node of its respective photodetector. Example 4. The system of Example 3. wherein the respective first node is a cathode of its respective photodetector and the second node is an anode of its respective photodetector.

[0172] Example 5. The system of any of Example 3 or Example 4, wherein each local biasing circuit includes a respective amplifier coupled to the respective second node of the respective photodetector of its corresponding photodetector circuit such that the respective second-node voltage at the respective second node is based on a respective common-mode voltage of the respective amplifier.

[0173] Example 6. The system of Example 5. wherein the respective second node is coupled to a respective first input of its corresponding amplifier.

[0174] Example 7. The system of any of Example 5 or Example 6, wherein the respective local voltage source of each local biasing circuit is coupled between ground and a respective second input of the respective amplifier of its respective local biasing circuit.

[0175] Example 8. The system of any of Examples 5-7, wherein each local biasing circuit includes a respective resistor coupled between the respective first input and a respective output of its corresponding amplifier.

[0176] Example 9. The system of any of Examples 3-8, wherein at least one respective photodetector circuit of the one or more photodetector circuits includes a respective current limiting circuit coupled between the global biasing circuit and the respective first node of its corresponding photodetector.

[0177] Example 10. The system of any of Examples 3-9, wherein at least one respective photodetector circuit of the one or more photodetector circuits includes a respective reset circuit coupled to the respective second node of its corresponding photodetector and configured to reset the corresponding photodetector after activation of the corresponding photodetector.

[0178] Example 11. The system of Example 10, wherein the respective reset circuit includes a fast-charging circuit coupled between the global biasing circuit and the respective second node of its corresponding photodetector.

[0179] Example 12. The system of any of Example 10 or Example 11, wherein the respective reset circuit includes a current quenching circuit coupled between ground and the respective second node of its corresponding photodetector.

[0180] Example 13. The system of any of Examples 1-12, wherein the first biasing voltage is adjustable such that the respective bias voltage of each photodetector circuit is adjustable via adjustment of the first biasing voltage. Example 14. The system of Example 13, wherein the first biasing voltage is adjusted based on an ambient temperature near at least one of the one or more photodetector circuits.

[0181] Example 15. The system of any of Examples 1-14, wherein the respective second biasing voltage of each respective local biasing circuit is adjustable such that the respective bias voltage of its corresponding photodetector circuit is individually adjustable via adjustment of its corresponding second biasing voltage.

[0182] Example 16. The system of Example 15, wherein the respective second biasing voltage is adjusted based on one or more characteristics of the corresponding photodetector.

[0183] Example 17. The system of Example 16, wherein the one or more characteristics of the corresponding photodetector include one or more of: a voltage characteristic; a current characteristic; or a temperature.

[0184] Example 18. The system of any of Examples 15-17, wherein: the one or more photodetector circuits includes a plurality of photodetector circuits; and at least one respective second biasing voltage is adjusted such that one or more performance characteristics of two or more of the photodetector circuits match.

[0185] Example 19. A system, comprising: a photodetector; a first voltage source configured to generate a first biasing voltage and coupled to the photodetector such that a first-node voltage at a first node of the photodetector is based on the first biasing voltage; an amplifier coupled to the photodetector such that a second-node voltage at a second node of the photodetector is based on a common-mode voltage of the amplifier, a bias voltage across the photodetector being based on the first-node voltage and the second-node voltage; and a second voltage source configured to generate a second biasing voltage and coupled to the amplifier such that the common-mode voltage is based on the second biasing voltage.

[0186] Example 20. The system of Example 19, wherein the first node of the photodetector is a cathode and the second node of the photodetector is an anode.

[0187] Example 21. The system of any of Example 19 or claim 20, wherein: the second node of the photodetector is coupled to a first input of the amplifier: and the second voltage source is coupled between a second input of the amplifier and a ground. Example 22. The system of any of Examples 19-21, further comprising a resistor coupled between the first input of the amplifier and an output of the amplifier.

[0188] Example 23. The system of any of Examples 19-22, further comprising a current limiting circuit coupled between the first voltage source and the first node of the photodetector.

[0189] Example 24. The system of any of Examples 19-23, further comprising a reset circuit coupled to the second node of the photodetector and configured to reset the photodetector after activation of the photodetector.

[0190] Example 25. The system of Example 24, wherein the reset circuit includes a fast-charging circuit coupled between the first voltage source and the second node of the photodetector.

[0191] Example 26. The system of any of Example 24 or Example 25, wherein the reset circuit includes a current quenching circuit coupled between ground and the second node of the photodetector.

[0192] Example 27. The system of any of Examples 19-26, further comprising: an additional photodetector coupled to the first voltage source such that an additional first-node voltage at an additional first node of the additional photodetector is based on the first- biasing voltage; an additional amplifier coupled to the additional photodetector such that an additional second-node voltage at an additional second node of the additional photodetector is based on an additional common-mode voltage of the additional amplifier, an additional bias voltage across the additional photodetector being based on the additional first- node voltage and the additional second-node voltage; and a third voltage source configured to generate a third-biasing voltage and coupled to the additional amplifier such that the additional common-mode voltage is based on the third-biasing voltage.

[0193] Example 28. The system of any of Examples 19-27, wherein the bias voltage across the photodetector is adjusted by adjusting the second biasing voltage.

[0194] Example 29. The system of any of Examples 19-28, wherein the second biasing voltage is adjusted based on one or more characteristics of the photodetector.

[0195] Example 30. The system of Example 29, wherein the one or more characteristics of the photodetector include one or more of: a voltage characteristic; a current characteristic; or a temperature. Example 31. A LiDAR system comprising the system of any of Examples 1-30.

[0196] Example 32. A vehicle comprising a LiDAR system comprising the system of any of Examples 1-30.

[0197] Example 33. A method comprising: providing a global biasing voltage to each photodetector circuit of a plurality of photodetector circuits such that a respective bias voltage corresponding to each photodetector circuit is based on the global biasing voltage; and providing a respective local biasing voltage to each respective photodetector circuit of the plurality of photodetector circuits such that the respective bias voltage of the respective photodetector circuit is also based on the respective local biasing voltage.

[0198] Example 34. The method of Example 33, wherein the global biasing voltage is provided via a global biasing circuit configured to generate the global biasing voltage and coupled to each photodetector circuit of the plurality of photodetector circuits such that the respective bias voltage corresponding to each photodetector circuit is based on the first biasing voltage.

[0199] Example 35. The method of Example 33, wherein the respective local biasing is provided via a respective local biasing circuit corresponding to each respective photodetector circuit, the respective local biasing circuit being configured to generate the respective local biasing voltage and coupled to its corresponding photodetector circuit such that the respective bias voltage of its corresponding photodetector circuit is also based on the respective local biasing voltage.

[0200] Example 36. The method of any of Examples 33-35, wherein the method is implemented using the system of any of claims 1-30.

Claims

CLAIMSWhat is claimed is:

1. A system comprising: one or more photodetector circuits; a global biasing circuit configured to generate a first biasing voltage and coupled to each photodetector circuit of the one or more photodetector circuits such that a respective bias voltage corresponding to each photodetector circuit is based on the first biasing voltage; and one or more local biasing circuits that each correspond to a respective photodetector circuit, each local biasing circuit being configured to generate a respective second biasing voltage and being coupled to its respective photodetector circuit such that the respective bias voltage of its respective photodetector circuit is also based on the respective second biasing voltage.

2. The system of claim 1, wherein: the global biasing circuit includes a global voltage source configured to generate the first biasing voltage; and each local biasing circuit includes a respective local voltage source configured to generate its respective second biasing voltage.

3. The system of any of claim 1 or claim 2, wherein: each photodetector circuit includes a respective photodetector having a respective first node and a respective second node; the global biasing circuit is coupled to each photodetector circuit such that a first-node voltage at its respective first node is based on the first biasing voltage; each local biasing circuit is coupled to its corresponding photodetector circuit such that a second-node voltage at its respective second node is based on the second biasing voltage; and the respective bias voltage of each photodetector circuit is the voltage across the respective first node and the respective second node of its respective photodetector.

4. The system of claim 3, wherein the respective first node is a cathode of its respective photodetector and the second node is an anode of its respective photodetector.

5. The system of any of claim 3 or claim 4, wherein each local biasing circuit includes a respective amplifier coupled to the respective second node of the respective photodetector of its corresponding photodetector circuit such that the respective second-node voltage at the respective second node is based on a respective commonmode voltage of the respective amplifier.

6. The system of claim 5, wherein the respective second node is coupled to a respective first input of its corresponding amplifier.

7. The system of any of claim 5 or claim 6, wherein the respective local voltage source of each local biasing circuit is coupled between ground and a respective second input of the respective amplifier of its respective local biasing circuit.

8. The system of any of claims 5-7. wherein each local biasing circuit includes a respective resistor coupled between the respective first input and a respective output of its corresponding amplifier.

9. The system of any of claims 3-8, wherein at least one respective photodetector circuit of the one or more photodetector circuits includes a respective current limiting circuit coupled between the global biasing circuit and the respective first node of its corresponding photodetector.

10. The system of any of claims 3-9, wherein at least one respective photodetector circuit of the one or more photodetector circuits includes a respective reset circuit coupled to the respective second node of its corresponding photodetector and configured to reset the corresponding photodetector after activation of the corresponding photodetector.

11. The system of claim 10, wherein the respective reset circuit includes a fast-charging circuit coupled between the global biasing circuit and the respective second node of its corresponding photodetector.

12. The system of any of claim 10 or claim 11, wherein the respective reset circuit includes a current quenching circuit coupled between ground and the respective second node of its corresponding photodetector.

13. The system of any of claims 1-12, wherein the first biasing voltage is adjustable such that the respective bias voltage of each photodetector circuit is adjustable via adjustment of the first biasing voltage.

14. The system of claim 13, wherein the first biasing voltage is adjusted based on an ambient temperature near at least one of the one or more photodetector circuits.

15. The system of any of claims 1 -14, wherein the respective second biasing voltage of each respective local biasing circuit is adjustable such that the respective bias voltage of its corresponding photodetector circuit is individually adjustable via adjustment of its corresponding second biasing voltage.

16. The system of claim 15, wherein the respective second biasing voltage is adjusted based on one or more characteristics of the corresponding photodetector.

17. The system of claim 16. wherein the one or more characteristics of the corresponding photodetector include one or more of: a voltage characteristic; a current characteristic; or a temperature.

18. The system of any of claims 15-17, wherein: the one or more photodetector circuits includes a plurality of photodetector circuits: and at least one respective second biasing voltage is adjusted such that one or more performance characteristics of two or more of the photodetector circuits match.

19. A system, comprising: a photodetector; a first voltage source configured to generate a first biasing voltage and coupled to the photodetector such that a first-node voltage at a first node of the photodetector is based on the first biasing voltage; an amplifier coupled to the photodetector such that a second-node voltage at a second node of the photodetector is based on a common-mode voltage of the amplifier, a bias voltage across the photodetector being based on the first-node voltage and the second-node voltage; and a second voltage source configured to generate a second biasing voltage and coupled to the amplifier such that the common-mode voltage is based on the respective second biasing voltage.

20. The system of claim 19, wherein the first node of the photodetector is a cathode and the second node of the photodetector is an anode.

21. The system of any of claim 19 or claim 20, wherein: the second node of the photodetector is coupled to a first input of the amplifier; and the second voltage source is coupled between a second input of the amplifier and a ground.

22. The system of any of claims 19-21, further comprising a resistor coupled between the first input of the amplifier and an output of the amplifier.

23. The system of any of claims 19-22, further comprising a current limiting circuit coupled between the first voltage source and the first node of the photodetector.

24. The system of any of claims 19-23, further comprising a reset circuit coupled to the second node of the photodetector and configured to reset the photodetector after activation of the photodetector.

25. The system of claim 24. wherein the reset circuit includes a fast-charging circuit coupled between the first voltage source and the second node of the photodetector.

26. The system of any of claim 24 or claim 25, wherein the reset circuit includes a current quenching circuit coupled between ground and the second node of the photodetector.

27. The system of any of claims 19-26, further comprising: an additional photodetector coupled to the first voltage source such that an additional first-node voltage at an additional first node of the additional photodetector is based on the first- biasing voltage; an additional amplifier coupled to the additional photodetector such that an additional second-node voltage at an additional second node of the additional photodetector is based on an additional common-mode voltage of the additional amplifier, an additional bias voltage across the additional photodetector being based on the additional first- node voltage and the additional second-node voltage; and a third voltage source configured to generate a third-biasing voltage and coupled to the additional amplifier such that the additional common-mode voltage is based on the third-biasing voltage.

28. The system of any of claims 19-27, wherein the bias voltage across the photodetector is adjusted by adjusting the second biasing voltage.

29. The system of any of claims 19-28, wherein the second biasing voltage is adjusted based on one or more characteristics of the photodetector.

30. The system of claim 29, wherein the one or more characteristics of the photodetector include one or more of: a voltage characteristic; a current characteristic; or a temperature.

31. A LiDAR system comprising the system of any of claims 1-30.

32. A vehicle comprising a LiDAR system comprising the system of any of claims 1 -30.

33. A method comprising: providing a global biasing voltage to each photodetector circuit of a plurality of photodetector circuits such that a respective bias voltage corresponding to each photodetector circuit is based on the global biasing voltage; andproviding a respective local biasing voltage to each respective photodetector circuit of the plurality of photodetector circuits such that the respective bias voltage of the respective photodetector circuit is also based on the respective local biasing voltage.

34. The method of claim 33, wherein the global biasing voltage is provided via a global biasing circuit configured to generate the global biasing voltage and coupled to each photodetector circuit of the plurality of photodetector circuits such that the respective bias voltage corresponding to each photodetector circuit is based on the first biasing voltage.

35. The method of claim 33, wherein the respective local biasing is provided via a respective local biasing circuit corresponding to each respective photodetector circuit, the respective local biasing circuit being configured to generate the respective local biasing voltage and coupled to its corresponding photodetector circuit such that the respective bias voltage of its corresponding photodetector circuit is also based on the respective local biasing voltage.

36. The method of any of claims 33-35, wherein the method is implemented using the system of any of claims 1-30.

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