Patent Description:
Optical detection of range using lasers, often referenced by a mnemonic, LIDAR, for light detection and ranging, also sometimes called laser RADAR, is used for a variety of applications, from altimetry, to imaging, to collision avoidance. LIDAR provides finer scale range resolution with smaller beam sizes than conventional microwave ranging systems, such as radio-wave detection and ranging (RADAR). Optical detection of range can be accomplished with several different techniques, including direct ranging based on round trip travel time of an optical pulse to an object, and chirped detection based on a frequency difference between a transmitted chirped optical signal and a returned signal scattered from an object, and phaseencoded detection based on a sequence of single frequency phase changes that are distinguishable from natural signals. An example for such a Lidar system is disclosed in <CIT>.

Aspects of the present disclosure relate generally to light detection and ranging (LIDAR) in the field of optics, and more particularly to systems and methods for pulsed-wave LIDAR to support the operation of a vehicle.

One implementation disclosed here is directed to a LIDAR system. The LIDAR system includes the technical features set out in clam <NUM>. Additional technical details are set out in the dependent claims.

In some implementations, the amplifier includes an erbium doped fiber amplifier (EDFA) or a semiconductor optical amplifier (SOA). The amplifier includes the SOA, and wherein the SOA modulates the optical signal using index modulation.

In another aspect, the present disclosure is directed to an autonomous vehicle control system including the claimed Lidar system.

In another aspect, the present disclosure is directed to an autonomous vehicle including the claimed Lidar system.

Implementations are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings in which like reference numerals refer to similar elements and in which:.

A LIDAR system includes a transmit (Tx) path and a receive (Rx) path. The transmit (Tx) path includes a laser source for providing a light signal (sometimes referred to as, "beam") that is derived from (or associated with) a local oscillator (LO) signal, one or more modulators for modulating a phase and/or a frequency of the light signal using Continuous Wave (CW) modulation or quasi-CW modulation, and an amplifier for amplifying the modulated signal before sending the signal to optics (e.g., an oscillatory scanner, a unidirectional scanner, a Risley prism, a circulator optic, and/or a beam collimator, etc.).

The optics are configured to steer the amplified signal that it receives from the Tx path into an environment within a given field of view toward an object, receive a returned signal reflected back from the object, and provide the returned signal to the receive (Rx) path.

The Rx path may include a mixer (e.g., <NUM>/<NUM>) for mixing the LO signal with the returned signal to generate a down-converted signal, and a transimpedance (TIA) amplifier for amplifying the down-converted signal. The Rx path provides the down-converted signal (now amplified) to one or more processors for determining a distance to the object and/or measuring the velocity of the object.

Operating an autonomous vehicle poses significant challenges for the conventional LIDAR system. First, the LIDAR system should be able to detect objects (e.g., street signs, people, cars, trucks, etc.) at short distances (e.g., less than <NUM> meters) and long distances (e.g., <NUM> meters and beyond). Detecting objects at long distances, however, is not an easy feat for the conventional LIDAR system. Namely, the amplifiers of the conventional LIDAR system do not have enough power to amplify the transmitted light signal enough for it to reach a long-distance object. Second, the beam scanning techniques used by conventional LIDAR systems often produce long measurement times, which in turn, require for the LIDAR system to meet a tighter and difficult speckle processing requirements.

Accordingly, the present disclosure is directed to systems and methods for pulsed-wave LIDAR to support the operation of a vehicle.

In general, as described in the below passages, an implementation of a pulsed-wave LIDAR system may be achieved by varying a gain configuration on an EDFA across a plurality of gain configurations of the EDFA. For example, the LIDAR system may include a laser source configured to provide an optical signal; an erbium doped fiber amplifier (EDFA) that has a plurality of gain configurations, where the EDFA is configured to receive the optical signal, and amplify the optical signal based on a gain configuration of the plurality of gain configurations; and one or more processors (e.g., autonomous vehicle control system <NUM>, computing system <NUM>, etc.) that are configured to adjust the gain configuration of the EDFA across at least a subset of the plurality of gain configurations to cause the EDFA to generate an amplified signal corresponding to a pulse envelope signal.

Another example of a pulsed-wave LIDAR system may be achieved by toggling an optical switch. For example, the pulsed-wave LIDAR system may include a laser source configured to provide an optical signal; an optical switch having a first terminal, a second terminal, and a switch mode, where the optical switch is configured to receive the optical signal at the first terminal; and either allow a transmission of the optical signal from the first terminal to the second terminal if the switch mode is configured in a first mode, or block the transmission of the optical signal to the second terminal if the switch mode is configured in a second mode; and one or more processors configured to toggle the optical switch mode between the first mode and the second mode to cause the optical switch to generate a pulse envelope signal.

An implementation of a pulsed-wave LIDAR system is achieved by detecting a relative phase difference between two optical signals. For example, the pulse-wave LIDAR system includes a laser source configured to provide an optical signal; a pulse envelope generator (e.g., Mach-Zehnder modulator) configured to generate a pulse envelope signal based on a relative phase difference between a first optical signal associated with the optical signal and a second optical signal associated with the optical signal; and an EDFA configured to amplify the pulse envelope signal and send the pulse envelope signal into free space via one or more optical elements.

Another implementation of a pulsed-wave LIDAR system may be achieved by modulating a light signal using an electrical field. For example, the pulse-wave LIDAR system may include a laser source configured to provide an optical signal; a pulse envelope generator (e.g., electro-absorption modulator (EAM)) configured to generate a pulse envelope signal by modulating the light signal using an electric field; and an EDFA configured to amplify the pulse envelope signal and send the amplified pulse envelope signal into free space via one or more optical elements.

Another implementation of a pulsed-wave LIDAR system may be achieved by varying a gain configuration on a semiconductor optical amplifier (SOA) across a plurality of gain configurations of the SOA. For example, the pulse-wave LIDAR system may include a laser source configured to provide an optical signal; an SOA having a plurality of gain configurations, where the SOA is configured to receive the optical signal, and amplify the optical signal based on a gain configuration of the plurality of gain configurations; and one or more processors configured to adjust the gain configuration of the SOA across at least a subset of the plurality of gain configurations to cause the SOA to generate an amplified signal corresponding to a pulse envelope signal.

The pulsed-wave LIDAR systems in the aforementioned implementations are able to achieve object recognition at a wide range of distances (e.g., short and long) that are required for autonomous vehicle applications, and without having to produce more amplifier power than that capable by the amplifiers in the conventional LIDAR system. Furthermore, the pulsed-wave LIDAR system relaxes the speckle processing requirements.

In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the present disclosure.

<FIG> is a block diagram illustrating an example of a system environment for autonomous vehicles according to some implementations.

Referring to <FIG>, an example autonomous vehicle <NUM> within which the various techniques disclosed herein may be implemented. The vehicle <NUM>, for example, may include a powertrain <NUM> including a prime mover <NUM> powered by an energy source <NUM> and capable of providing power to a drivetrain <NUM>, as well as a control system <NUM> including a direction control <NUM>, a powertrain control <NUM>, and a brake control <NUM>. The vehicle <NUM> may be implemented as any number of different types of vehicles, including vehicles capable of transporting people and/or cargo, and capable of traveling in various environments, and it will be appreciated that the aforementioned components <NUM> - <NUM> can vary widely based upon the type of vehicle within which these components are utilized.

For simplicity, the implementations discussed hereinafter will focus on a wheeled land vehicle such as a car, van, truck, bus, etc. In such implementations, the prime mover <NUM> may include one or more electric motors and/or an internal combustion engine (among others). The energy source may include, for example, a fuel system (e.g., providing gasoline, diesel, hydrogen, etc.), a battery system, solar panels or other renewable energy source, and/or a fuel cell system. The drivetrain <NUM> can include wheels and/or tires along with a transmission and/or any other mechanical drive components to convert the output of the prime mover <NUM> into vehicular motion, as well as one or more brakes configured to controllably stop or slow the vehicle <NUM> and direction or steering components suitable for controlling the trajectory of the vehicle <NUM> (e.g., a rack and pinion steering linkage enabling one or more wheels of the vehicle <NUM> to pivot about a generally vertical axis to vary an angle of the rotational planes of the wheels relative to the longitudinal axis of the vehicle). In some implementations, combinations of powertrains and energy sources may be used (e.g., in the case of electric/gas hybrid vehicles), and in some instances multiple electric motors (e.g., dedicated to individual wheels or axles) may be used as a prime mover.

The direction control <NUM> may include one or more actuators and/or sensors for controlling and receiving feedback from the direction or steering components to enable the vehicle <NUM> to follow a desired trajectory. The powertrain control <NUM> may be configured to control the output of the powertrain <NUM>, e.g., to control the output power of the prime mover <NUM>, to control a gear of a transmission in the drivetrain <NUM>, etc., thereby controlling a speed and/or direction of the vehicle <NUM>. The brake control <NUM> may be configured to control one or more brakes that slow or stop vehicle <NUM>, e.g., disk or drum brakes coupled to the wheels of the vehicle.

Other vehicle types, including but not limited to off-road vehicles, all-terrain or tracked vehicles, construction equipment etc., will necessarily utilize different powertrains, drivetrains, energy sources, direction controls, powertrain controls and brake controls. Moreover, in some implementations, some of the components can be combined, e.g., where directional control of a vehicle is primarily handled by varying an output of one or more prime movers. Therefore, implementations disclosed herein are not limited to the particular application of the herein-described techniques in an autonomous wheeled land vehicle.

Various levels of autonomous control over the vehicle <NUM> can be implemented in a vehicle control system <NUM>, which may include one or more processors <NUM> and one or more memories <NUM>, with each processor <NUM> configured to execute program code instructions <NUM> stored in a memory <NUM>. The processors(s) can include, for example, graphics processing unit(s) ("GPU(s)")) and/or central processing unit(s) ("CPU(s)").

Sensors <NUM> may include various sensors suitable for collecting information from a vehicle's surrounding environment for use in controlling the operation of the vehicle. For example, sensors <NUM> can include radar sensor <NUM>, LIDAR (Light Detection and Ranging) sensor <NUM>, a 3D positioning sensors <NUM>, e.g., any of an accelerometer, a gyroscope, a magnetometer, or a satellite navigation system such as GPS (Global Positioning System), GLONASS (Globalnaya Navigazionnaya Sputnikovaya Sistema, or Global Navigation Satellite System), BeiDou Navigation Satellite System (BDS), Galileo, Compass, etc. The 3D positioning sensors <NUM> can be used to determine the location of the vehicle on the Earth using satellite signals. The sensors <NUM> can include a camera <NUM> and/or an IMU (inertial measurement unit) <NUM>. The camera <NUM> can be a monographic or stereographic camera and can record still and/or video images. The IMU <NUM> can include multiple gyroscopes and accelerometers capable of detecting linear and rotational motion of the vehicle in three directions. One or more encoders (not illustrated), such as wheel encoders may be used to monitor the rotation of one or more wheels of vehicle <NUM>. Each sensor <NUM> can output sensor data at various data rates, which may be different than the data rates of other sensors <NUM>.

The outputs of sensors <NUM> may be provided to a set of control subsystems <NUM>, including, a localization subsystem <NUM>, a planning subsystem <NUM>, a perception subsystem <NUM>, and a control subsystem <NUM>. The localization subsystem <NUM> can perform functions such as precisely determining the location and orientation (also sometimes referred to as "pose") of the vehicle <NUM> within its surrounding environment, and generally within some frame of reference. The location of an autonomous vehicle can be compared with the location of an additional vehicle in the same environment as part of generating labeled autonomous vehicle data. The perception subsystem <NUM> can perform functions such as detecting, tracking, determining, and/or identifying objects within the environment surrounding vehicle <NUM>. A machine learning model in accordance with some implementations can be utilized in tracking objects. The planning subsystem <NUM> can perform functions such as planning a trajectory for vehicle <NUM> over some timeframe given a desired destination as well as the static and moving objects within the environment. A machine learning model in accordance with some implementations can be utilized in planning a vehicle trajectory. The control subsystem <NUM> can perform functions such as generating suitable control signals for controlling the various controls in the vehicle control system <NUM> in order to implement the planned trajectory of the vehicle <NUM>. A machine learning model can be utilized to generate one or more signals to control an autonomous vehicle to implement the planned trajectory.

It will be appreciated that the collection of components illustrated in <FIG> for the vehicle control system <NUM> is merely exemplary in nature. Individual sensors may be omitted in some implementations. Additionally or alternatively, in some implementations, multiple sensors of types illustrated in <FIG> may be used for redundancy and/or to cover different regions around a vehicle, and other types of sensors may be used. Likewise, different types and/or combinations of control subsystems may be used in other implementations. Further, while subsystems <NUM> - <NUM> are illustrated as being separate from processor <NUM> and memory <NUM>, it will be appreciated that in some implementations, some or all of the functionality of a subsystem <NUM> - <NUM> may be implemented with program code instructions <NUM> resident in one or more memories <NUM> and executed by one or more processors <NUM>, and that these subsystems <NUM> - <NUM> may in some instances be implemented using the same processor(s) and/or memory. Subsystems may be implemented at least in part using various dedicated circuit logic, various processors, various field programmable gate arrays ("FPGA"), various application-specific integrated circuits ("ASIC"), various real time controllers, and the like, as noted above, multiple subsystems may utilize circuitry, processors, sensors, and/or other components. Further, the various components in the vehicle control system <NUM> may be networked in various manners.

In some implementations, the vehicle <NUM> may also include a secondary vehicle control system (not illustrated), which may be used as a redundant or backup control system for the vehicle <NUM>. In some implementations, the secondary vehicle control system may be capable of fully operating the autonomous vehicle <NUM> in the event of an adverse event in the vehicle control system <NUM>, while in other implementations, the secondary vehicle control system may only have limited functionality, e.g., to perform a controlled stop of the vehicle <NUM> in response to an adverse event detected in the primary vehicle control system <NUM>. In still other implementations, the secondary vehicle control system may be omitted.

In general, an innumerable number of different architectures, including various combinations of software, hardware, circuit logic, sensors, networks, etc. may be used to implement the various components illustrated in <FIG>. Each processor may be implemented, for example, as a microprocessor and each memory may represent the random access memory ("RAM") devices comprising a main storage, as well as any supplemental levels of memory, e.g., cache memories, non-volatile or backup memories (e.g., programmable or flash memories), read- only memories, etc. In addition, each memory may be considered to include memory storage physically located elsewhere in the vehicle <NUM>, e.g., any cache memory in a processor, as well as any storage capacity used as a virtual memory, e.g., as stored on a mass storage device or another computer controller. One or more processors illustrated in <FIG>, or entirely separate processors, may be used to implement additional functionality in the vehicle <NUM> outside of the purposes of autonomous control, e.g., to control entertainment systems, to operate doors, lights, convenience features, etc..

In addition, for additional storage, the vehicle <NUM> may include one or more mass storage devices, e.g., a removable disk drive, a hard disk drive, a direct access storage device ("DASD"), an optical drive (e.g., a CD drive, a DVD drive, etc.), a solid state storage drive ("SSD"), network attached storage, a storage area network, and/or a tape drive, among others.

Furthermore, the vehicle <NUM> may include a user interface <NUM> to enable vehicle <NUM> to receive a number of inputs from and generate outputs for a user or operator, e.g., one or more displays, touchscreens, voice and/or gesture interfaces, buttons and other tactile controls, etc. Otherwise, user input may be received via another computer or electronic device, e.g., via an app on a mobile device or via a web interface.

Moreover, the vehicle <NUM> may include one or more network interfaces, e.g., network interface <NUM>, suitable for communicating with one or more networks <NUM> (e.g., a Local Area Network ("LAN"), a wide area network ("WAN"), a wireless network, and/or the Internet, among others) to permit the communication of information with other computers and electronic device, including, for example, a central service, such as a cloud service, from which the vehicle <NUM> receives environmental and other data for use in autonomous control thereof. Data collected by the one or more sensors <NUM> can be uploaded to a computing system <NUM> via the network <NUM> for additional processing. In some implementations, a time stamp can be added to each instance of vehicle data prior to uploading.

Each processor illustrated in <FIG>, as well as various additional controllers and subsystems disclosed herein, generally operates under the control of an operating system and executes or otherwise relies upon various computer software applications, components, programs, objects, modules, data structures, etc., as will be described in greater detail below. Moreover, various applications, components, programs, objects, modules, etc. may also execute on one or more processors in another computer coupled to vehicle <NUM> via network <NUM>, e.g., in a distributed, cloud-based, or client-server computing environment, whereby the processing required to implement the functions of a computer program may be allocated to multiple computers and/or services over a network.

In general, the routines executed to implement the various implementations described herein, whether implemented as part of an operating system or a specific application, component, program, object, module or sequence of instructions, or even a subset thereof, will be referred to herein as "program code". Program code can include one or more instructions that are resident at various times in various memory and storage devices, and that, when read and executed by one or more processors, perform the steps necessary to execute steps or elements embodying the various aspects of the present disclosure. Moreover, while implementations have and hereinafter will be described in the context of fully functioning computers and systems, it will be appreciated that the various implementations described herein are capable of being distributed as a program product in a variety of forms, and that implementations can be implemented regardless of the particular type of computer readable media used to actually carry out the distribution.

Examples of computer readable media include tangible, non-transitory media such as volatile and non-volatile memory devices, floppy and other removable disks, solid state drives, hard disk drives, magnetic tape, and optical disks (e.g., CD-ROMs, DVDs, etc.) among others.

In addition, various program code described hereinafter may be identified based upon the application within which it is implemented in a specific implementation. However, it should be appreciated that any particular program nomenclature that follows is used merely for convenience, and thus the present disclosure should not be limited to use solely in any specific application identified and/or implied by such nomenclature. Furthermore, given the typically endless number of manners in which computer programs may be organized into routines, procedures, methods, modules, objects, and the like, as well as the various manners in which program functionality may be allocated among various software layers that are resident within a typical computer (e.g., operating systems, libraries, API's, applications, applets, etc.), it should be appreciated that the present disclosure is not limited to the specific organization and allocation of program functionality described herein.

The environment illustrated in <FIG> is not intended to limit implementations disclosed herein. Indeed, other alternative hardware and/or software environments may be used without departing from the scope of implementations disclosed herein.

A truck can include a LIDAR system (e.g., vehicle control system <NUM> in <FIG>, LIDAR system 301A in <FIG>, LIDAR system 301B in <FIG>, LIDAR system 401A in <FIG>, LIDAR system 401B in <FIG>, LIDAR system <NUM> in <FIG>, LIDAR system <NUM> in <FIG>, LIDAR system <NUM> in <FIG>, LIDAR system <NUM> in <FIG>, etc.). In some implementations, the LIDAR system can use frequency modulation to encode an optical signal and scatter the encoded optical signal into free-space using optics. By detecting the frequency differences between the encoded optical signal and a returned signal reflected back from an object, the frequency modulated (FM) LIDAR system can determine the location of the object and/or precisely measure the velocity of the object using the Doppler effect. In some implementations, an FM LIDAR system may use a continuous wave (referred to as, "FMCW LIDAR") or a quasi-continuous wave (referred to as, "FMQW LIDAR"). In some implementations, the LIDAR system can use phase modulation (PM) to encode an optical signal and scatters the encoded optical signal into free-space using optics.

An FM or phase-modulated (PM) LIDAR system may provide substantial advantages over conventional LIDAR systems with respect to automotive and/or commercial trucking applications. To begin, in some instances, an object (e.g., a pedestrian wearing dark clothing) may have a low reflectivity, in that it only reflects back to the sensors (e.g., sensors <NUM> in <FIG>) of the FM or PM LIDAR system a low amount (e.g., <NUM>% or less) of the light that hit the object. In other instances, an object (e.g., a shiny road sign) may have a high reflectivity (e.g., above <NUM>%), in that it reflects back to the sensors of the FM LIDAR system a high amount of the light that hit the object.

Regardless of the object's reflectivity, an FM LIDAR system may be able to detect (e.g., classify, recognize, discover, etc.) the object at greater distances (e.g., 2x) than a conventional LIDAR system. For example, an FM LIDAR system may detect a low reflectivity object beyond <NUM> meters, and a high reflectivity object beyond <NUM> meters.

To achieve such improvements in detection capability, the FM LIDAR system may use sensors (e.g., sensors <NUM> in <FIG>). In some implementations, these sensors can be single photon sensitive, meaning that they can detect the smallest amount of light possible. While an FM LIDAR system may, in some applications, use infrared wavelengths (e.g., <NUM>, <NUM>, etc.), it is not limited to the infrared wavelength range (e.g., near infrared: <NUM> - <NUM>; middle infrared: <NUM> - <NUM>; and far infrared: <NUM> - <NUM>,<NUM>,<NUM>). By operating the FM or PM LIDAR system in infrared wavelengths, the FM or PM LIDAR system can broadcast stronger light pulses or light beams while meeting eye safety standards. Conventional LIDAR systems are often not single photon sensitive and/or only operate in near infrared wavelengths, requiring them to limit their light output (and distance detection capability) for eye safety reasons.

Thus, by detecting an object at greater distances, an FM LIDAR system may have more time to react to unexpected obstacles. Indeed, even a few milliseconds of extra time could improve safety and comfort, especially with heavy vehicles (e.g., commercial trucking vehicles) that are driving at highway speeds.

Another advantage of an FM LIDAR system is that it provides accurate velocity for each data point instantaneously. In some implementations, a velocity measurement is accomplished using the Doppler effect which shifts frequency of the light received from the object based at least one of the velocity in the radial direction (e.g., the direction vector between the object detected and the sensor) or the frequency of the laser signal. For example, for velocities encountered in on-road situations where the velocity is less than <NUM> meters per second (m/s), this shift at a wavelength of <NUM> nanometers (nm) amounts to the frequency shift that is less than <NUM> megahertz (MHz). This frequency shift is small such that it is difficult to detect directly in the optical domain. However, by using coherent detection in FMCW, PMCW, or FMQW LIDAR systems, the signal can be converted to the RF domain such that the frequency shift can be calculated using various signal processing techniques. This enables the autonomous vehicle control system to process incoming data faster.

Instantaneous velocity calculation also makes it easier for the FM LIDAR system to determine distant or sparse data points as objects and/or track how those objects are moving over time. For example, an FM LIDAR sensor (e.g., sensors <NUM> in <FIG>) may only receive a few returns (e.g., hits) on an object that is <NUM> away, but if those return give a velocity value of interest (e.g., moving towards the vehicle at ><NUM> mph), then the FM LIDAR system and/or the autonomous vehicle control system may determine respective weights to probabilities associated with the objects.

Faster identification and/or tracking of the FM LIDAR system gives an autonomous vehicle control system more time to maneuver a vehicle. A better understanding of how fast objects are moving also allows the autonomous vehicle control system to plan a better reaction.

Another advantage of an FM LIDAR system is that it has less static compared to conventional LIDAR systems. That is, the conventional LIDAR systems that are designed to be more light-sensitive typically perform poorly in bright sunlight. These systems also tend to suffer from crosstalk (e.g., when sensors get confused by each other's light pulses or light beams) and from self-interference (e.g., when a sensor gets confused by its own previous light pulse or light beam). To overcome these disadvantages, vehicles using the conventional LIDAR systems often need extra hardware, complex software, and/or more computational power to manage this "noise.

In contrast, FM LIDAR systems do not suffer from these types of issues because each sensor is specially designed to respond only to its own light characteristics (e.g., light beams, light waves, light pulses). If the returning light does not match the timing, frequency, and/or wavelength of what was originally transmitted, then the FM sensor can filter (e.g., remove, ignore, etc.) out that data point. As such, FM LIDAR systems produce (e.g., generates, derives, etc.) more accurate data with less hardware or software requirements, enabling safer and smoother driving.

Lastly, an FM LIDAR system is easier to scale than conventional LIDAR systems. As more self-driving vehicles (e.g., cars, commercial trucks, etc.) show up on the road, those powered by an FM LIDAR system likely will not have to contend with interference issues from sensor crosstalk. Furthermore, an FM LIDAR system uses less optical peak power than conventional LIDAR sensors. As such, some or all of the optical components for an FM LIDAR can be produced on a single chip, which produces its own benefits, as discussed herein.

<FIG> is a block diagram illustrating an example of a system environment for autonomous commercial trucking vehicles, according to some implementations. The environment 100B includes a commercial truck 102B for hauling cargo 106B. In some implementations, the commercial truck 102B may include vehicles configured to long-haul freight transport, regional freight transport, intermodal freight transport (i.e., in which a road-based vehicle is used as one of multiple modes of transportation to move freight), and/or any other road-based freight transport applications. In some implementations, the commercial truck 102B may be a flatbed truck, a refrigerated truck (e.g., a reefer truck), a vented van (e.g., dry van), a moving truck, etc. In some implementations, the cargo 106B may be goods and/or produce. In some implementations, the commercial truck 102B may include a trailer to carry the cargo 106B, such as a flatbed trailer, a lowboy trailer, a step deck trailer, an extendable flatbed trailer, a sidekit trailer, etc..

The environment 100B includes an object 110B (shown in <FIG> as another vehicle) that is within a distance range that is equal to or less than <NUM> meters from the truck.

The commercial truck 102B may include a LIDAR system 104B (e.g., an FM LIDAR system, vehicle control system <NUM> in <FIG>, LIDAR system <NUM> in <FIG>, etc.) for determining a distance to the object 110B and/or measuring the velocity of the object 110B. Although <FIG> shows that one LIDAR system 104B is mounted on the front of the commercial truck 102B, the number of LIDAR system and the mounting area of the LIDAR system on the commercial truck are not limited to a particular number or a particular area. The commercial truck 102B may include any number of LIDAR systems 104B (or components thereof, such as sensors, modulators, coherent signal generators, etc.) that are mounted onto any area (e.g., front, back, side, top, bottom, underneath, and/or bottom) of the commercial truck 102B to facilitate the detection of an object in any free-space relative to the commercial truck 102B.

As shown, the LIDAR system 104B in environment 100B may be configured to detect an object (e.g., another vehicle, a bicycle, a tree, street signs, potholes, etc.) at short distances (e.g., <NUM> meters or less) from the commercial truck 102B.

<FIG> is a block diagram illustrating an example of a system environment for autonomous commercial trucking vehicles, according to some implementations. The environment 100C includes the same components (e.g., commercial truck 102B, cargo 106B, LIDAR system 104B, etc.) that are included in environment 100B.

The environment 100C includes an object 110C (shown in <FIG> as another vehicle) that is within a distance range that is (i) more than <NUM> meters and (ii) equal to or less than <NUM> meters from the commercial truck 102B. As shown, the LIDAR system 104B in environment 100C may be configured to detect an object (e.g., another vehicle, a bicycle, a tree, street signs, potholes, etc.) at a distance (e.g., <NUM> meters) from the commercial truck 102B.

<FIG> is a block diagram illustrating an example of a system environment for autonomous commercial trucking vehicles, according to some implementations. The environment 100D includes the same components (e.g., commercial truck 102B, cargo 106B, LIDAR system 104B, etc.) that are included in environment 100B.

The environment 100D includes an object 110D (shown in <FIG> as another vehicle) that is within a distance range that is more than <NUM> meters from the commercial truck 102B. As shown, the LIDAR system 104B in environment 100D may be configured to detect an object (e.g., another vehicle, a bicycle, a tree, street signs, potholes, etc.) at a distance (e.g., <NUM> meters) from the commercial truck 102B.

In commercial trucking applications, it is important to effectively detect objects at all ranges due to the increased weight and, accordingly, longer stopping distance required for such vehicles. FM LIDAR systems (e.g., FMCW and/or FMQW systems) or PM LIDAR systems are well-suited for commercial trucking applications due to the advantages described above. As a result, commercial trucks equipped with such systems may have an enhanced ability to safely move both people and goods across short or long distances, improving the safety of not only the commercial truck but of the surrounding vehicles as well. In various implementations, such FM or PM LIDAR systems can be used in semi-autonomous applications, in which the commercial truck has a driver and some functions of the commercial truck are autonomously operated using the FM or PM LIDAR system, or fully autonomous applications, in which the commercial truck is operated entirely by the FM or LIDAR system, alone or in combination with other vehicle systems.

In a LIDAR system that uses CW modulation (sometimes referred to as, "CW operation"), the modulator modulates the laser light continuously. For example, if a modulation cycle is <NUM> microseconds, an input signal is modulated throughout the whole <NUM> microseconds.

In a LIDAR system that uses quasi-CW modulation (sometimes referred to as, "quasi-CW operation"), the modulator modulates the laser light to have both an active portion and an inactive portion. For example, for a <NUM> microsecond cycle, the modulator modulates the laser light only for <NUM> microseconds (sometimes referred to as, "the active portion"), but does not modulate the laser light for <NUM> microseconds (sometimes referred to as, "the inactive portion"). Since the light signal does not have to be in the on-state (e.g., enabled, powered, transmitting, etc.) all the time, the LIDAR system may be able to reduce power consumption for the portion of time (e.g., <NUM> microseconds) where the modulator does not have to provide a continuous signal. Furthermore, if the energy in the off-state (e.g., disabled, powered-down, etc.) can be expended during the actual measurement time, then there may be a boost to signal-to-noise ratio (SNR) and/or a reduction in signal processing requirements to coherently integrate all the energy in the longer time scale.

In a LIDAR system that uses pulsed-wave modulation (sometimes referred to as, "pulsed-wave operation"), the modulator modulates the laser light to have both an active portion and an inactive portion. One or more gates then seed the laser input to an optical amplifier via an optical switch, thereby taking advantage of the optical gain buildup that results in an instantaneous output power increase of <NUM> / (optical duty cycle) and a reduction (e.g., by the duty cycle) in the processing requirements, all while maintaining a constant signal power.

<FIG> is a time-based graph depicting the differences (e.g., differences in amplitude, period, average power, duty cycle, etc.) between the waveforms produced by one or more LIDAR systems that use CW operation, quasi-CW operation, and/or pulsed-wave operation. The time-based graph <NUM> includes waveform 202a, waveform 202b, and waveform 202c. A LIDAR system (e.g., LIDAR <NUM> in <FIG>) that uses CW operation may construct a waveform 202a (e.g., a continuous wave) having an amplitude of 'h' based on a plurality of Codes (e.g., Code <NUM>, Code <NUM>, Code <NUM>, and Code <NUM>). A LIDAR system (e.g., LIDAR <NUM> in <FIG>) that uses quasi-CW operation may construct a waveform 202b (e.g., a quasi-CW) having a duty cycle equal (or substantially equal) to <NUM>% and an amplitude that this equal to (or substantially equal to) twice (e.g., <NUM>) the amplitude of waveform 202a based on a plurality of Codes (e.g., Code <NUM> and Code <NUM>). A LIDAR system (e.g., LIDAR <NUM> in <FIG>) that uses pulsed-wave operation may construct a waveform 202c (e.g., a pulsed-wave) having a duty cycle that is equal (or substantially equal) to <NUM>/<NUM> the duty cycle of waveform 202a and an amplitude that this equal (or substantially equal) to 12x (e.g., <NUM>) the amplitude of waveform 202a based on a plurality of Codes (e.g., Code <NUM> and Code <NUM>).

<FIG> is a block diagram illustrating an example environment of a LIDAR system in pulsed-wave operation using an EDFA for operating an autonomous vehicle. The environment 300A includes a LIDAR system 301A that includes a transmit (Tx) path and a receive (Rx) path. The Tx path may include one or more Tx input/output ports (not shown in <FIG>) and the Rx path may include one or more Rx input/output ports (not shown in <FIG>).

The environment 300A includes one or more optics <NUM> (e.g., an oscillatory scanner, a unidirectional scanner, a Risley prism, a circulator optic, and/or a beam collimator, etc.) that are coupled to the LIDAR system 301A. The one or more optics <NUM> may be coupled to the Tx path via the one or more Tx input/output ports. The one or more optics <NUM> may be coupled to the Rx path via the one or more Rx input/output ports.

The environment 300A includes a vehicle control system <NUM> (e.g., vehicle control system <NUM> in <FIG>) that is coupled to the LIDAR system <NUM>. The vehicle control system <NUM> may be coupled to the Rx path via the one or more Rx input/output ports.

The Tx path includes a laser source <NUM>, an electro-optic modulator (EOM) 304A, and an erbium doped fiber amplifier (EDFA) <NUM>. The Rx path includes a mixer <NUM>, a detector <NUM>, and a transimpedance (TIA) <NUM>. Although <FIG> shows only a select number of components and only one input/output channel; the environment 300A may include any number of components and/or input/output channels (in any combination) that are interconnected in any arrangement to facilitate combining multiple functions of a LIDAR system, to support the operation of a vehicle.

The laser source <NUM> is configured to generate a light signal that is derived from (or associated with) a local oscillator (LO) signal. The light signal may have an operating wavelength that is equal to or substantially equal to <NUM> nanometers. In some implementations, the light signal may have an operating wavelength that is between <NUM> nanometers and <NUM> nanometers.

The laser source <NUM> is configured to provide the light signal to the EOM 304A, which is configured to modulate a phase and/or a frequency of the light signal based on a code signal (e.g., "<NUM>") to generate a modulated light signal. The EOM 304A is configured to send the modulated light signal to the EDFA <NUM>. The EDFA <NUM> is associated with a plurality of gain configurations, each that determine the level at which the EDFA <NUM> should amplify (e.g., boost) an input signal. The EDFA <NUM> may be configured in a constant current mode.

One or more processors (e.g., autonomous vehicle control system <NUM>, computing system <NUM>, etc.) are configured to vary (e.g., change, adjust, modify, etc.) a gain configuration of the EDFA <NUM> to cause the EDFA <NUM> to generate a pulsed envelope signal by amplifying the modulated light signal. The one or more processors may vary the gain configuration of the EDFA <NUM> across one or more gain configurations (e.g., a subset, all) of the plurality of gain configurations in a random, periodic (e.g., at any point between <NUM> milliseconds to <NUM> milliseconds, etc.), or continuous manner. The EDFA <NUM> is configured to send the pulsed envelope signal to the optics <NUM>.

The optics <NUM> are configured to steer the amplified light signal that it receives from the Tx path into free space within a given field of view toward an object <NUM>, receive a returned signal reflected back from the object <NUM> via a receiver (not shown in <FIG>), and provide the returned signal to the mixer <NUM> of the Rx path.

The laser source <NUM> may be configured to provide an unmodulated LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path. The EOM <NUM>, in some implementations, may be configured to provide a modulated LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path.

The mixer <NUM> is configured to mix (e.g., combine, multiply, etc.) the LO signal (modulated or unmodulated) with the returned signal to generate a down-converted signal and send the down-converted signal to the detector <NUM>. In some arrangements, the mixer <NUM> is configured to send the LO signal (modulated or unmodulated) to the detector <NUM>.

The detector <NUM> is configured to generate an electrical signal based on the down-converted signal and send the electrical signal to the TIA <NUM>. In some arrangements, the detector <NUM> is configured to generate an electrical signal based on the down-converted signal and the modulated light signal.

The TIA <NUM> is configured to amplify the electrical signal and send the amplified electrical signal to the vehicle control system <NUM>.

The vehicle control system <NUM> is configured to determine a distance to the object <NUM> and/or measures the velocity of the object <NUM> based on the one or more electrical signals that it receives from the TIA.

<FIG> is a block diagram illustrating an example environment of a LIDAR system in pulsed-wave operation using an EDFA and directly modulating a laser source for operating an autonomous vehicle. Other than the removal of the electro-optic modulator (EOM) 304A, the environment 300B in <FIG> includes the same components (and at least their same functionality) as the environment 300A in <FIG>.

The laser source <NUM> is configured to generate a light signal that is derived from (or associated with) an LO signal. The laser source <NUM> is also configured to modulate a phase and/or a frequency of the light signal based on a code signal (e.g., "<NUM>") to generate a modulated light signal. The laser source <NUM> is configured to send the modulated light signal to the EDFA <NUM>. The laser source <NUM>, in some arrangements, may be configured to provide an unmodulated or modulated LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path.

One or more processors (e.g., autonomous vehicle control system <NUM>, computing system <NUM>, etc.) are configured to vary (e.g., change, adjust, modify, etc.) a gain configuration of the EDFA <NUM> to cause the EDFA <NUM> to generate a pulsed envelope signal by amplifying the modulated light signal. The one or more processors, in some arrangements may vary the gain configuration of the EDFA <NUM> across one or more gain configurations (e.g., a subset, all) of the plurality of gain configurations in a random, periodic (e.g., at any point between <NUM> milliseconds to <NUM> milliseconds, etc.), or continuous manner. The EDFA <NUM> is configured to send the pulsed envelope signal to the optics <NUM>.

As discussed herein with respect to <FIG>, the optics <NUM> are configured to steer the light signal that it receives from the Tx path into free space within a given field of view toward an object <NUM>, receive a returned signal reflected back from the object <NUM> via a receiver, and provide the returned signal to the Rx path. The Rx path generates one or more electrical signals from the returned signal and delivers the one or more electrical signals to the vehicle control system <NUM>, which is configured to determine a distance to the object <NUM> and/or measures the velocity of the object <NUM> based on the one or more electrical signals that it receives from the Rx path.

An EDFA (e.g., EDFA <NUM> in <FIG> and/or <FIG>), in some implementations, may have a constant pumping rate of the gain, which in the absence of light on the input may cause the gain to increase over time, building up potential energy for optical energy release when an optical pulse is input to the EDFA. This energy storage mechanism of the EDFA makes it simple to concentrate the output optical energy into a pulse and achieve relatively similar average power (e.g., averaged over many pulse cycles) to if the input and output of the EDFA were continuous or quasi-continuous.

<FIG> illustrates an example waveform of the optical intensity before an EDFA, where the EDFA has a constant pumping rate of gain. <FIG> illustrates an example waveform of the optical intensity after an EDFA, where the EDFA has a constant pumping rate of gain, according to some implementations. However, in some arrangements, the power in the pulse in both instances (e.g., before and after) would be increased by the inverse of the duty cycle.

<FIG> is a block diagram illustrating an example environment of a LIDAR system in pulsed-wave operation using an optical switch for operating an autonomous vehicle. The environment 400A includes a LIDAR system 401A that includes a transmit (Tx) path and a receive (Rx) path. The Tx path may include one or more Tx input/output ports (not shown in <FIG>) and the Rx path may include one or more Rx input/output ports (not shown in <FIG>).

The environment 400A includes one or more optics <NUM> that are coupled to the LIDAR system 401A. In some implementations, the one or more optics <NUM> may be coupled to the Tx path via the one or more Tx input/output ports. In some arrangements, the one or more optics <NUM> may be coupled to the Rx path via the one or more Rx input/output ports.

The environment 400A includes a vehicle control system <NUM> (e.g., vehicle control system <NUM> in <FIG>) that is coupled to the LIDAR system <NUM>. In some arrangements, the vehicle control system <NUM> may be coupled to the Rx path via the one or more Rx input/output ports.

The Tx path includes a laser source <NUM>, an electro-optic modulator (EOM) 404A, an optical switch <NUM>, and an erbium doped fiber amplifier (EDFA) <NUM>. The Rx path includes a mixer <NUM>, a detector <NUM>, and a transimpedance (TIA) <NUM>. Although <FIG> shows only a select number of components and only one input/output channel; the environment 400A may include any number of components and/or input/output channels (in any combination) that are interconnected in any arrangement to facilitate combining multiple functions of a LIDAR system, to support the operation of a vehicle.

The laser source <NUM> is configured to generate a light signal that is derived from (or associated with) an LO signal. The laser source <NUM> is configured to provide the light signal to the EOM 404A. The laser source <NUM>, in some arrangements, may be configured to provide an unmodulated LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path.

The EOM 404A is configured to modulate a phase and/or a frequency of the light signal based on a code signal (e.g., "<NUM>") to generate a modulated light signal. The EOM 404A is configured to send the modulated light signal to the optical switch <NUM>. The EOM 404A, in some implementations, may be configured to modulate an LO signal (not shown in <FIG>) and provide the modulated LO signal to the mixer <NUM> of the Rx path.

One or more processors (e.g., autonomous vehicle control system <NUM>, computing system <NUM>, etc.) are configured to toggle (e.g., activate, deactivate, enable, disable, move, flip, adjust, configure, etc.) the optical switch <NUM> between an enabled state (e.g., allowing a light signal to pass between an input and an output of the switch) and disabled state (e.g., preventing a light signal from passing between an input and an output of the switch) to cause the optical switch <NUM> to generate a pulsed envelope signal based on the modulated light signal. The one or more processors, in some arrangements, may toggle the optical switch <NUM> in a random, periodic (e.g., at any point between <NUM> microseconds to <NUM> microseconds, etc.) or continuous manner. The optical switch <NUM> is configured to send the pulsed envelope signal to the EDFA <NUM>.

The EDFA <NUM> is configured to generate an amplified pulsed envelope signal by amplifying the pulsed envelope signal and send the amplified pulsed envelope signal to the optics <NUM>.

The waveform at node <NUM> (i.e., output of laser <NUM>) that corresponds to the optical signal may be represented by the following equation: <MAT>.

The waveform at node <NUM> (i.e., output of EOM <NUM>) that corresponds to the modulated optical signal may be represented by the following equation: <MAT> ;where Ø(t)=π(code).

The waveform at node <NUM> (i.e., output of switch <NUM>) that corresponds to the pulse envelope signal may be represented by the following equation: <MAT> ; where ψ = {<NUM>,t = <NUM>: T <NUM>,t = T: PRP}.

<FIG> is a block diagram illustrating an example environment of a LIDAR system in pulsed-wave operation using an optical switch for operating an autonomous vehicle. Other than the removal of the electro-optic modulator (EOM) 404A, the environment 400B in <FIG> includes the same components (and at least their same functionality) as the environment 400A in <FIG>.

The laser source <NUM> is configured to generate a light signal that is derived from (or associated with) an LO signal. The laser source <NUM> is also configured to modulate a phase and/or a frequency of the light signal based on a code signal (e.g., "<NUM>") to generate a modulated light signal. The laser source <NUM> is configured to send the modulated light signal to the optical switch <NUM>. The laser source <NUM>, in some arrangements, may be configured to provide an unmodulated or modulated LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path.

<FIG> is a flow chart that illustrates an example method for pulsed-wave LIDAR to support the operation of a vehicle. Although steps are depicted in <FIG> as integral steps in a particular order for purposes of illustration, in other implementations, one or more steps, or portions thereof, are performed in a different order, or overlapping in time, in series or in parallel, or are omitted, or one or more additional steps are added, or the method is changed in some combination of ways. Some or all operations of method 400C may be performed by one or more of the components (e.g., LIDAR system <NUM>, optics <NUM>, autonomous vehicle control system <NUM>) depicted in environment 400A in <FIG>. Some or all operations of method 400C may be performed by one or more of the components (e.g., LIDAR system <NUM>, optics <NUM>, autonomous vehicle control system <NUM>) depicted in environment 400B in <FIG>.

The method 400C includes the operation 402C of modulating an optical signal to generate a modulated optical signal. In some implementations, the method 400C includes the operation 404C of selecting a plurality of pulses from the modulated optical signal to generate a pulsed envelope signal. The method 400C includes the operation 406C of transmitting the pulsed envelope signal via one or more optical elements. The method 400C includes the operation 408C of receiving a reflected signal responsive to transmitting the pulsed envelope signal. The method 400C includes the operation 410C of determining a range to an object based on an electrical signal associated with the reflected signal.

<FIG> is a block diagram illustrating an example environment of a LIDAR system in pulsed-wave operation using a Mach-Zehnder modulator for operating an autonomous vehicle, according to some implementations of the invention. The environment 500A includes a LIDAR system <NUM> that includes a transmit (Tx) path and a receive (Rx) path. The Tx path may include one or more Tx input/output ports (not shown in <FIG>) and the Rx path may include one or more Rx input/output ports (not shown in <FIG>).

The environment 500A includes one or more optics <NUM> that are coupled to the LIDAR system <NUM>. In some implementations, the one or more optics <NUM> may be coupled to the Tx path via the one or more Tx input/output ports. In some implementations, the one or more optics <NUM> may be coupled to the Rx path via the one or more Rx input/output ports.

The environment 500A includes a vehicle control system <NUM> (e.g., vehicle control system <NUM> in <FIG>) that is coupled to the LIDAR system <NUM>. In some implementations, the vehicle control system <NUM> may be coupled to the Rx path via the one or more Rx input/output ports.

The Tx path includes a laser source <NUM>, a Mach-Zehnder modulator <NUM>, and an erbium doped fiber amplifier (EDFA) <NUM>. The Rx path includes a mixer <NUM>, a detector <NUM>, and a transimpedance (TIA) <NUM>. Although <FIG> shows only a select number of components and only one input/output channel, the environment 500A may include any number of components and/or input/output channels (in any combination) that are interconnected in any arrangement to facilitate combining multiple functions of a LIDAR system, to support the operation of a vehicle.

The laser source <NUM> is configured to generate a light signal that is derived from (or associated with) an LO signal. The laser source <NUM> is configured to provide the light signal to the Mach-Zehnder modulator <NUM>. The laser source <NUM>, in some implementations, may be configured to provide an LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path.

The Mach-Zehnder modulator <NUM> is configured to convert the relative phase shift variations between two paths derived by splitting the light signal from the laser source <NUM> and modulating the two paths with electro-optic modulation. The Mach-Zehnder modulator <NUM> is configured to generate a pulse envelope signal based on the relative phase variations. In some implementations, the Mach-Zehnder modulator <NUM> modulates a phase and/or a frequency of the pulse envelope signal based on a code signal (e.g., "<NUM>") to generate a modulated pulse envelope signal. The Mach-Zehnder modulator <NUM> is configured to send the pulse envelope signal (unmodulated or modulated) to the EDFA <NUM>. The Mach-Zehnder modulator <NUM> may, in some implementations, modulate an LO signal and provide the modulated LO signal to the mixer <NUM> of the Rx path. The Mach-Zehnder modulator <NUM> may, in some implementations, be used with pulse shaping to correct for output amplitude decay on a signal.

Referring back to <FIG>, one or more processors (e.g., autonomous vehicle control system <NUM>, computing system <NUM>, etc.) are configured to toggle (e.g., activate, deactivate, enable, disable, move, flip, adjust, configure, etc.) the output of the MZ modulator 505between an enabled state (e.g., allowing a light signal to pass between an input and an output) and disabled state (e.g., preventing a light signal from passing between an input and an output) such that the MZ modulator 505can generate a pulsed envelope signal in addition to the modulated light signal. The one or more processors, in some implementations, may toggle the output of the MZ modulator <NUM> in a random, periodic (e.g., at any point between <NUM> microseconds to <NUM> microseconds, etc.), or continuous manner. The the MZ modulator <NUM> is configured to send the modulated pulsed envelope signal to the EDFA <NUM>.

In some implementations, the waveform at node <NUM> (i.e., output of laser <NUM>) that corresponds to the optical signal may be represented by the following equation: <MAT>.

In some implementations, the waveform at node <NUM> (i.e., output of MZ modulator <NUM>) that corresponds to the modulated and pulsed optical signal may be represented by the following equation: <MAT> ; where ψ = {<NUM>,t = <NUM>:T <NUM>, t = T: PRP }.

<FIG> is a block diagram illustrating an example environment of a LIDAR system in pulsed-wave operation using an electro-absorption modulator (EAM) for operating an autonomous vehicle, according to some implementations. The environment <NUM> includes a LIDAR system <NUM> that includes a transmit (Tx) path and a receive (Rx) path. The Tx path may include one or more Tx input/output ports (not shown in <FIG>) and the Rx path may include one or more Rx input/output ports (not shown in <FIG>).

The environment <NUM> includes one or more optics <NUM> that are coupled to the LIDAR system <NUM>. In some implementations, the one or more optics <NUM> may be coupled to the Tx path via the one or more Tx input/output ports. In some implementations, the one or more optics <NUM> may be coupled to the Rx path via the one or more Rx input/output ports.

The environment <NUM> includes a vehicle control system <NUM> (e.g., vehicle control system <NUM> in <FIG>) that is coupled to the LIDAR system <NUM>. In some implementations, the vehicle control system <NUM> may be coupled to the Rx path via the one or more Rx input/output ports.

The Tx path includes a laser source <NUM>, an EAM <NUM>, and an erbium doped fiber amplifier (EDFA) <NUM>. The Rx path includes a mixer <NUM>, a detector <NUM>, and a transimpedance (TIA) <NUM>. Although <FIG> shows only a select number of components and only one input/output channel; the environment <NUM> may include any number of components and/or input/output channels (in any combination) that are interconnected in any arrangement to facilitate combining multiple functions of a LIDAR system, to support the operation of a vehicle.

The laser source <NUM> is configured to generate a light signal that is derived from (or associated with) an LO signal. The laser source <NUM> is configured to provide the light signal to the EAM <NUM>. The laser source <NUM>, in some implementations, may be configured to provide an LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path.

The EAM <NUM> is configured to modulate the amplitude (e.g., intensity) of the light signal via an electric voltage according to a code signal (e.g., "<NUM>"). That is, the EAM <NUM> is constructed from a semiconductor material that has an absorption coefficient. When one or more processors (e.g., autonomous vehicle control system <NUM>, computing system <NUM>, etc.) apply an external electric field to the EAM <NUM>, the absorption coefficient changes resulting in a change in the bandgap energy, which in turn, causes the EAM <NUM> to modulate the amplitude of the incoming light signal. By modulating the amplitude of the light signal, the EAM <NUM> is able to generate a pulse envelope signal. The EAM <NUM> is configured to send the pulse envelope signal to the EDFA <NUM>. The EAM <NUM> may, in some implementations, modulate an LO signal and provide the modulated LO signal to the mixer <NUM> of the Rx path.

The EDFA <NUM> amplifies the pulse envelope signal to generate an amplified pulse envelope signal and sends the amplified pulsed envelope signal to the optics <NUM>.

<FIG> is a block diagram illustrating an example environment of a LIDAR system in pulsed-wave operation using a semiconductor optical amplifier (SOA) for operating an autonomous vehicle, according to some implementations. The environment <NUM> includes a LIDAR system <NUM> that includes a transmit (Tx) path and a receive (Rx) path. The Tx path may include one or more Tx input/output ports (not shown in <FIG>) and the Rx path may include one or more Rx input/output ports (not shown in <FIG>).

The Tx path includes a laser source <NUM>, a modulator <NUM>, a semiconductor optical amplifier (SOA) <NUM>. The Rx path includes a mixer <NUM>, a detector <NUM>, and a transimpedance (TIA) <NUM>. Although <FIG> shows only a select number of components and only one input/output channel; the environment <NUM> may include any number of components and/or input/output channels (in any combination) that are interconnected in any arrangement to facilitate combining multiple functions of a LIDAR system, to support the operation of a vehicle.

The laser source <NUM> is configured to generate a light signal that is derived from (or associated with) an LO signal. The laser source <NUM> is configured to provide the light signal to the modulator <NUM>. The laser source <NUM>, in some implementations, may be configured to provide an LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path.

The modulator is configured to modulate a phase and/or a frequency and/or intensity of the light signal based on a code signal (e.g., "<NUM>") to generate a modulated light signal. The modulator <NUM>, in some implementations, may be an EOM (e.g., EOM <NUM> in <FIG>), an EAM (e.g., EAM <NUM> in <FIG>), or a Mach-Zehnder modulator (e.g., Mach-Zehnder modulator <NUM> in <FIG>). The modulator <NUM> is configured to send the modulated light signal to the SOA <NUM>. The modulator <NUM> may, in some implementations, modulate an LO signal and provide the modulated LO signal to the mixer <NUM> of the Rx path.

The SOA <NUM> may be associated with a plurality of gain configurations, each that determine the level at which the SOA <NUM> should amplify (e.g., boost) an input signal.

One or more processors (e.g., autonomous vehicle control system <NUM>, computing system <NUM>, etc.) are configured to vary (e.g., change, adjust, modify, etc.) a gain configuration of the SOA <NUM> to cause the SOA <NUM> to generate a pulsed envelope signal by amplifying the modulated light signal. The one or more processors, in some implementations, may vary the gain configuration of the SOA <NUM> across one or more gain configurations (e.g., a subset, all) of the plurality of gain configurations in a random, periodic (e.g., at any point between <NUM> microseconds to <NUM> microseconds, etc.), or continuous manner. The SOA <NUM> is configured to send the pulsed envelope signal to the optics <NUM>.

<FIG> is a block diagram illustrating an example environment of a LIDAR system in pulsed-wave operation using a semiconductor optical amplifier (SOA) and index modulation for operating an autonomous vehicle, according to some implementations. Other than the removal of the modulator <NUM>, the environment 800B in <FIG> includes the same components (and at least their same functionality) as the environment <NUM> in <FIG>.

The laser source <NUM> is configured to generate a light signal that is derived from (or associated with) an LO signal. The laser source <NUM> is configured to send the modulated light signal to the SOA <NUM>. The laser source <NUM>, in some implementations, may be configured to provide an LO signal (not shown in <FIG>) to the mixer <NUM> of the Rx path.

The SOA <NUM> is associated with a plurality of gain configurations, each that determine the level at which the SOA <NUM> should amplify (e.g., boost) an input signal.

One or more processors (e.g., autonomous vehicle control system <NUM>, computing system <NUM>, etc.) are configured to vary (e.g., change, adjust, modify, etc.) a gain configuration of the SOA <NUM> to cause the SOA <NUM> to generate a pulsed envelope signal by amplifying the modulated light signal. The one or more processors, in some implementations, may vary the gain configuration of the SOA <NUM> across one or more gain configurations (e.g., a subset, all) of the plurality of gain configurations in a random, periodic (e.g., at any point between <NUM> microseconds to <NUM> microseconds, etc.), or continuous manner.

The SOA <NUM> is configured to modulate the light signal and/or the pulse envelope signal using index modulation and based on a code signal (e.g., "<NUM>"). The SOA <NUM> is configured to send the pulsed envelope signal to the optics <NUM>. The SOA <NUM> may, in some implementations, modulate an LO signal and provide the modulated LO signal to the mixer <NUM> of the Rx path.

Thus, the claims are not intended to be limited to the aspects shown herein, but is to be accorded the full scope consistent with the language claims, wherein reference to an element in the singular is not intended to mean "one and only one" unless specifically so stated, but rather "one or more. All structural and functional equivalents to the elements of the various aspects described throughout the previous description that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. No claim element is to be construed as a means plus function unless the element is expressly recited using the phrase "means for.

It is understood that the specific order or hierarchy of blocks in the processes disclosed is an example of illustrative approaches. Based upon design preferences, it is understood that the specific order or hierarchy of blocks in the processes may be rearranged while remaining within the scope of the previous description.

The previous description of the disclosed implementations is provided to enable any person skilled in the art to make or use the disclosed subject matter. Various modifications to these implementations will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other implementations without departing from the spirit or scope of the previous description. Thus, the previous description is not intended to be limited to the implementations shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The various examples illustrated and described are provided merely as examples to illustrate various features of the claims. However, features shown and described with respect to any given example are not necessarily limited to the associated example and may be used or combined with other examples that are shown and described. Further, the claims are not intended to be limited by any one example.

The foregoing method descriptions and the process flow diagrams are provided merely as illustrative examples and are not intended to require or imply that the blocks of various examples must be performed in the order presented. As will be appreciated by one of skill in the art the order of blocks in the foregoing examples may be performed in any order. Words such as "thereafter," "then," "next," etc. are not intended to limit the order of the blocks; these words are simply used to guide the reader through the description of the methods.

The various illustrative logical blocks, modules, circuits, and algorithm blocks described in connection with the examples disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and blocks have been described above generally in terms of their functionality.

The hardware used to implement the various illustrative logics, logical blocks, modules, and circuits described in connection with the examples disclosed herein may be implemented or performed with a general purpose processor, a DSP, an ASIC, an FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. Alternatively, some blocks or methods may be performed by circuitry that is specific to a given function.

In some exemplary examples, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a non-transitory computer-readable storage medium or non-transitory processor-readable storage medium. The blocks of a method or algorithm disclosed herein may be embodied in a processor-executable software module which may reside on a non-transitory computer-readable or processor-readable storage medium. Non-transitory computer-readable or processor-readable storage media may be any storage media that may be accessed by a computer or a processor. By way of example but not limitation, such non-transitory computer-readable or processor-readable storage media may include RAM, ROM, EEPROM, FLASH memory, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that may be used to store desired program code in the form of instructions or data structures and that may be accessed by a computer. Combinations of the above are also included within the scope of non-transitory computer-readable and processor-readable media. Additionally, the operations of a method or algorithm may reside as one or any combination or set of codes and/or instructions on a non-transitory processor-readable storage medium and/or computer-readable storage medium, which may be incorporated into a computer program product.

The preceding description of the disclosed examples is provided to enable any person skilled in the art to make or use the present disclosure.

Notwithstanding that the numerical ranges and parameters setting forth the broad scope are approximations, the numerical values set forth in specific non-limiting examples are reported as precisely as possible. Any numerical value, however, inherently contains certain errors necessarily resulting from the standard deviation found in their respective testing measurements at the time of this writing. Furthermore, unless otherwise clear from the context, a numerical value presented herein has an implied precision given by the least significant digit. Thus a value <NUM> implies a value from <NUM> to <NUM>. The term "about" is used to indicate a broader range centered on the given value, and unless otherwise clear from the context implies a broader range around the least significant digit, such as "about <NUM>" implies a range from <NUM> to <NUM>. If the least significant digit is unclear, then the term "about" implies a factor of two, e.g., "about X" implies a value in the range from <NUM>. 5X to 2X, for example, about <NUM> implies a value in a range from <NUM> to <NUM>. Moreover, all ranges disclosed herein are to be understood to encompass any and all sub-ranges subsumed therein. For example, a range of "less than <NUM>" for a positive only parameter can include any and all sub-ranges between (and including) the minimum value of zero and the maximum value of <NUM>, that is, any and all sub-ranges having a minimum value of equal to or greater than zero and a maximum value of equal to or less than <NUM> (e.g., <NUM> to <NUM>).

Claim 1:
A light detection and ranging, LIDAR, system (<NUM>) comprising:
a laser source (<NUM>) configured to provide an optical signal at a first signal power;
a pulse envelope generator (<NUM>) configured to generate a pulse envelope signal by splitting the optical signal into a first optical signal and a second optical signal and based on a relative phase difference between the first optical signal and the second optical signal;
an amplifier (<NUM>) having a plurality of gain configurations, wherein the amplifier is configured to receive the pulse envelope signal and amplify the pulse envelope signal based on a gain configuration of the plurality of gain configurations; and one or more processors (<NUM>) configured to:
adjust the gain configuration of the amplifier across two or more of the plurality of gain configurations to cause the amplifier to generate the pulse envelope signal at a second signal power, wherein the second signal power is greater than the first signal power by at least an amount corresponding to an inverse of a duty cycle of the optical signal.