Patent Description:
The techniques of this disclosure enable FMCW lidar systems to operate as fast-scanning lidar systems. A fast-scanning FMCW lidar system operates with a quicker overall frame rate without adding additional light emitting diodes (e.g., lasers) or performing complex modulations of slopes. The frequency pattern of chirps, including slopes and shapes, are consistent for each pixel within each frame, but they are different from one frame to the next. During an initial frame, each pixel within a field-of-view is scanned with a standard chirp pattern (e.g., two or more slopes and a longer chirp period), then during a subsequent frame, each pixel is scanned with a different chirp pattern, with fewer chirps or a shorter duration. The longer standard chirp pattern utilizes two or more slopes so that both range and Doppler information can be determined. Assuming a constant object velocity between the two consecutive frames, during the subsequent frame, the second chirp pattern can use fewer chirps and/or different slopes in combination with reusing part of the information obtained from the initial frame, which enables both range and range-rate (velocity) information to be determined for the subsequent frame. Therefore, the scan-time of two consecutive frames of a fast-scanning lidar system is less than the amount of time it takes to scan two consecutive frames of a traditional lidar system that repeats the same chirp pattern from one frame to the next. The shorter scan-time increases the scanning speed, which leads to improved frame rate while maintaining the capability of both distance and velocity sensing.

In some aspects, a method is described including scanning, by a FMCW lidar system of an automobile, during an initial frame of two consecutive frames and for each pixel within a field-of-view, an initial pattern of two or more chirps, determining, by the lidar system, based on the scanning of the initial pattern of the two or more chirps, a beat frequency associated with the initial frame, identifying, based on the beat frequency associated with the initial frame, object range and range-rate information associated with the initial frame. The method further includes scanning, by the lidar system, during a subsequent frame of the two consecutive frames and for each pixel within the field-of-view, a different pattern of one or more chirps, determining, by the lidar system, based on the scanning of the different pattern of the one or more chirps, a beat frequency associated with the initial frame, identifying, based on the beat frequency associated with the subsequent frame, object range and range rate information associated with the subsequent frame. The method further includes determining, based on the object range and range rate information associated with each of the initial and subsequent frames, distance and velocity for objects present in the field-of-view, and outputting, by the lidar system, the distance and velocity of the objects present in the field-of-view.

In other aspects, a lidar system is described including at least one processor or processing unit is configured to perform the above method. In additional aspects, a computer-readable storage medium is described including instructions for configuring the lidar system to perform the method above. Still, in other aspects, a system is described including means for performing the above method.

This summary is provided to introduce simplified concepts for fast-scanning FMCW lidar systems, which is further described below in the Detailed Description and Drawings. For ease of description, the disclosure focuses on automotive lidar systems; however, the techniques are not limited to automobiles but apply to lidars of other types of vehicles and systems. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended for use in determining the scope of the claimed subject matter.

The details of one or more aspects of fast-scanning FMCW lidar systems are described in this document with reference to the following drawings. The same numbers are used throughout the drawings to reference like features and components:.

The details of one or more aspects of fast-scanning FMCW lidar systems are described below. Automotive lidar systems are becoming one of the vital sensing technologies some vehicle-based subsystems rely on for acquiring critical information about an environment surrounding a vehicle. A lidar system has a field-of-view which represents a volume of space that the lidar system is looking for objects. The field-of-view is composed of a large number of pixels (roughly one million pixels). A frame represents the time it takes to complete a scan of each pixel within the field-of-view (e.g., collect information for all of the pixels). By scanning each pixel in a sequence of frames, range and range-rate (e.g., distance and velocity) of objects can be inferred. To scan each pixel, the FMCW lidar system emits a frequency-modulated laser signal with multiple chirps that alternate between positive and negative frequency-modulated slopes. Typically, the FMCW lidar system includes a delay time in each chirp to avoid chirp ambiguity. This delay varies (e.g., one to ten microseconds) based on the desired detection range. By mixing a local laser signal with signals returned from the objects, the lidar system determines the respective beat frequencies associated with the chirps. When reflected chirped signals returns to the FMCW lidar system, the reflected signals mixe with an outgoing chirped beam in a photodiode to produce a beat frequency. The beat frequencies from different chirps are decomposed into object distance or "range" and object velocity or "range-rate" for each pixel during each frame. The process repeats for each frame.

Traditionally, this process causes lidar systems to have slow scanning speeds and therefore slow frame rates, making them less suited for high-throughput applications. To combat this, some complex FMCW lidar systems included multiple lasers or lasers that perform advanced modulations to improve scanning speed. Dual-chirps in different frequency ranges or different chirping-sidebands may be implemented to reduce the scanning time at each pixel and increase the frame rate by reducing the time spent scanning each pixel. These systems require multiple lasers, a more complex readout, or other additional hardware that increases volume, weight, and cost, making them less suited for automotive applications.

The techniques of this disclosure enable existing lidar systems to operate as fast-scanning FMCW lidar systems. The system alternates chirp patterns frame-by-frame as a way to increase scanning speed and as a way to obtain a higher confidence on multiple object identification without adding additional lasers or other hardware. Each consecutive pair of frames includes an initial frame with a standard or long chirp pattern including at least two chirps with different slopes preceding a subsequent frame, which has different chirp pattern than the standard or long chirp pattern from the initial frame. The chirp pattern applied to each pixel is consistent within each frame but different from one frame to the next. The combined duration of two consecutive frames from the fast-scanning FMCW lidar system is less than the combined duration of two consecutive frames of a traditional FMCW lidar system which uses the same chirp pattern from one frame to the next. The shorter duration increases scanning speed and average frame rate of the fast-scanning lidar system.

The different chirp patterns also enable the fast-scanning FMCW lidar system to distinguish multiple objects on same pixel, but with less scanning time and/or fewer chirps. The average frame rate and therefore scanning speed is substantially improved over existing lidar systems while maintaining the capability of both distance and velocity sensing. This frame-based chirp-pattern-variation, enables more pixels to be scanned in less time and also enables multiple object identification. With the fast-scanning FMCW lidar system, another system of a vehicle (e.g., a collision avoidance system) is able to obtain lidar data more quickly so as to have a better picture of the vehicle's surroundings.

<FIG> illustrates an example environment <NUM> in which a fast-scanning FMCW lidar system <NUM> can be implemented. In the depicted environment <NUM>, the fast-scanning FMCW lidar system <NUM> (referred to simply as "lidar system <NUM>") is mounted to, or integrated within, a vehicle <NUM>. The lidar system <NUM> is capable of detecting one or more objects <NUM> that are within proximity to the vehicle <NUM>. Although illustrated as a car, the vehicle <NUM> can represent other types of motorized vehicles (e.g., a motorcycle, a bus, a tractor, a semi-trailer truck, or construction equipment), types of non-motorized vehicles (e.g., a bicycle), types of railed vehicles (e.g., a train or a trolley car), watercraft (e.g., a boat or a ship), aircraft (e.g., an airplane or a helicopter), or spacecraft (e.g., satellite). In some cases, the vehicle <NUM> can tow or include a trailer or other attachments. In general, the lidar system <NUM> can be mounted to any type of moving platform, including moving machinery or robotic equipment.

In the depicted implementation, the lidar system <NUM> is mounted on the roof of the vehicle <NUM> and provides a field-of-view <NUM> illuminating an object <NUM>. The field-of-view <NUM> is divided into pixels. The lidar system <NUM> can project the field-of-view <NUM> from any exterior surface of the vehicle <NUM>. For example, the lidar system <NUM> is integrated in a bumper, side mirror, or any other interior or exterior location where object distance and velocity requires detection. In some cases, the vehicle <NUM> includes multiple lidar systems <NUM>, such as a first lidar system <NUM> and a second lidar system <NUM> that together provide a larger field-of-view. In general, locations of the one or more lidar systems <NUM> can be designed to provide a particular field-of-view <NUM> that encompasses a region of interest in which the object <NUM> may be present. Example field-of-views <NUM> include a <NUM>-degree field-of-view, one or more <NUM>-degree fields of view, one or more <NUM>-degree fields of view, and so forth, which can overlap or be combined into a field-of-view of a particular sized.

The object <NUM> is composed of one or more materials that reflect lidar signals. Depending on the application, the object <NUM> can represent a target of interest or clutter. In some cases, the object <NUM> is a moving object <NUM>, such as another vehicle <NUM>-<NUM>, a semi-trailer truck <NUM>-<NUM>, a human <NUM>-<NUM>, an animal <NUM>-<NUM>, a bicycle <NUM>-<NUM>, or a motorcycle <NUM>-<NUM>. In other cases, the object <NUM> represents a stationary object <NUM>, such as traffic cone <NUM>-<NUM>, a concrete barrier <NUM>-<NUM>, a guard rail <NUM>-<NUM>, a fence <NUM>-<NUM>, a tree <NUM>-<NUM>, or a parked vehicle <NUM>-<NUM>. The stationary object <NUM> may even comprise a road barrier, which can be continuous or discontinuous along a portion of the road. The lidar system <NUM> and the vehicle <NUM> are further described with respect to <FIG>.

In general, the lidar system <NUM> is different than a traditional FMCW lidar system because, unlike a traditional FMCW lidar system that uses the same triangular chirp pattern frame after frame, the lidar system <NUM> uses different chirp patterns between consecutive frames. The lidar system <NUM> is configured to scan a pattern of multiple chirps for each pixel in an initial frame of two consecutive frames before scanning a pattern of fewer chirps and/or different chirp slopes for each pixel in a subsequent frame of the two consecutive frames. The initial frame may be longer in duration than the subsequent frame because the subsequent frame can require less chirps per pixel. From the chirp pattern scanned for each pixel in the initial frame, the lidar system <NUM> identifies an object range and an object range-rate. The lidar system <NUM> reuses the Doppler-frequency determined in the initial frame for determining, from less chirps per pixel, an object range and range-rate associated with the subsequent frame. The lidar system <NUM> determines beat frequencies associated with each of the two frames as the basis for the object range and range rate information for each frame. The lidar system <NUM> outputs distance and velocity information determined from the object range and range rate information. In this way, the lidar system <NUM> can scan more frames in less time than a traditional lidar system that repeats the same chirp pattern frame after frame.

<FIG> illustrates the lidar system <NUM> as part of the vehicle <NUM>. The vehicle <NUM> also includes vehicle-based subsystems <NUM> that rely on data from the lidar system <NUM>, such as a driver-assistance system <NUM> and/or an autonomous-driving system <NUM>. Generally, the vehicle-based subsystems <NUM> use lidar data provided by the lidar system <NUM> to perform a function. For example, the driver-assistance system <NUM> provides blind-spot monitoring and generates an alert that indicates a potential collision with an object <NUM> that is detected by the lidar system <NUM>. In this case, the lidar data from the lidar system <NUM> indicates when it is safe or unsafe to change lanes.

As another example, the driver-assistance system <NUM> suppresses alerts responsive to the lidar system <NUM>, indicating that the object <NUM> represents a stationary object <NUM>, such as a road barrier. In this way, the driver-assistance system <NUM> can avoid annoying the driver with alerts while the vehicle <NUM> is driving next to the road barrier. This can also be beneficial in situations in which reflections from the road barrier generate false detections that appear to be moving objects. By suppressing the alerts, these false detections will not cause the driver-assistance system <NUM> to alert the driver.

The autonomous-driving system <NUM> may move the vehicle <NUM> to a particular location while avoiding collisions with other objects <NUM> detected by the lidar system <NUM>. The lidar data provided by the lidar system <NUM> can provide information about distance and velocity of the other objects <NUM> to enable the autonomous-driving system <NUM> to perform emergency braking, perform a lane change, or adjust the vehicle <NUM>'s speed.

The lidar system <NUM> includes a communication interface <NUM> to transmit the lidar data to the vehicle-based subsystems <NUM> or to another component of the vehicle <NUM> over a communication bus of the vehicle <NUM>, for example, when the individual components shown in the lidar system <NUM> are integrated within the vehicle <NUM>. In general, the lidar data provided by the communication interface <NUM> is in a format usable by the vehicle-based subsystems <NUM>. In some implementations, the communication interface <NUM> may provide information to the lidar system <NUM>, such as the speed of the vehicle <NUM> or whether a turning blinker is on or off. The lidar system <NUM> can use this information to appropriately configure itself. For example, the lidar system <NUM> can determine an absolute speed of the object <NUM> by compensating for the speed of the vehicle <NUM>. Alternatively, the lidar system <NUM> can dynamically adjust the field-of-view <NUM> based on whether a right-turning blinker or a left-turning blinker is on.

The lidar system <NUM> also includes a set of beam steering components <NUM>, a transmitter <NUM>, and a receiver <NUM>. The beam steering components <NUM> may include mechanical and/or electromechanical components to shape or steer lidar signals and for detecting lidar reflections in response to the same. Using the beam steering components <NUM>, the lidar system <NUM> can form beams of lidar signals that are steered and shaped through various beamforming techniques.

The lidar system <NUM> may be a mechanical lidar. In which case, the beam steering components <NUM> include high-grade optics and a rotating assembly to create a wide (e.g., three-hundred sixty degree) field-of-view Alternatively, the lidar system <NUM> may be a solid-state lidar, such as a micro electrical mechanical system (MEMS) based lidar, a flash based lidar, or an optical phase array lidar. When configured as a solid-state lidar, the beam steering components <NUM> do not include the rotating mechanical and may therefore be less expensive than a mechanical lidar. A solid-state lidar has a reduced field-of-view. The lidar system <NUM> may include multiple solid-state lidar modules, with each module positioned at a different location on the vehicle <NUM>. For example, the lidar system <NUM> may be on the front, rear, and/or sides of a vehicle and when fused together to create a single point cloud, the lidar system has a field-of-view that is similar to that of a mechanical lidar system.

The transmitter <NUM> includes circuitry and logic for emitting lidar signals via the beam steering components <NUM>. The receiver <NUM> includes components necessary to identify reflections detected by the beam steering components, from the lidar signals.

The lidar system <NUM> also includes one or more processors <NUM> and computer-readable storage media (CRM) <NUM>. The CRM <NUM> includes a raw-data processing module <NUM> and a lidar control module <NUM>. The raw-data processing module <NUM> and the lidar control module <NUM> can be implemented using hardware, software, firmware, or a combination thereof. In this example, the processor <NUM> executes instructions for implementing the raw-data processing module <NUM> and the lidar control module <NUM>. Together, the raw-data processing module <NUM> and the lidar control module <NUM> enable the processor <NUM> to process responses from the receiving beam steering components <NUM> in order to detect the object <NUM> and generate the lidar data for the vehicle-based subsystems <NUM>.

The raw-data processing module <NUM> transforms raw data provided by the transmitter <NUM> and receiver <NUM> into lidar data that is usable by the lidar control module <NUM>. The lidar control module <NUM> analyzes the lidar data to map one or more detections.

The lidar control module <NUM> produces the lidar data for the vehicle-based subsystems <NUM>. Example types of lidar data include a Boolean value that indicates whether or not the object <NUM> is present within a particular region of interest, a number that represents a characteristic of the object <NUM> (e.g., range, range-rate, distance, velocity), or a value that indicates the type of object <NUM> detected (e.g., a moving object <NUM> or a stationary object <NUM>). The lidar control module <NUM> configures the transmitter <NUM> and receiver <NUM> to emit lidar signals and detect reflections via the beam steering components <NUM>. The lidar control module <NUM> outputs information associated with the lidar reflections detected from lidar signals that reach targets, such as the object <NUM>.

<FIG> through <FIG> illustrate an example operation of the lidar system <NUM>. For reference, refer to <FIG> which shows the pixels <NUM>-<NUM>, <NUM>-<NUM>, <NUM>-<NUM>. , <NUM>-XY, <NUM>-3Y, <NUM>-2Y, <NUM>-1Y, and all other pixels scanned during a frame <NUM>. The pixels <NUM> are shown arranged in X pixels wide by Y pixels high grid and are scanned individually in the order shown by arrows, one row (or column) at a time.

Back to <FIG>, in environment <NUM>, the object <NUM> is located at a particular slant range and angle from the lidar system <NUM>. To detect the object <NUM>, the lidar system <NUM> transmits a lidar transmit signal <NUM>. At least a portion of the lidar transmit signal <NUM> is reflected by the object <NUM>. This reflected portion represents a lidar receive signal <NUM>. The lidar system <NUM> receives the lidar receive signal <NUM> and processes the lidar receive signal <NUM> to extract lidar data for the vehicle-based subsystems <NUM>. As depicted, an amplitude of the lidar receive signal <NUM> is smaller than an amplitude of the lidar transmit signal <NUM> due to losses incurred during propagation and reflection.

Collectively referred to as "chirps <NUM>", the lidar system <NUM> transmits the chirps <NUM>-<NUM>-<NUM>, <NUM>-<NUM>-<NUM>, <NUM>-<NUM>-<NUM>, and <NUM>-<NUM>-<NUM> in a continuous sequence during an initial frame <NUM>. The chirps <NUM> represent a scan of individual pixels <NUM> (not shown) within the field-of-view <NUM>. A frame <NUM> represents the time it takes to scan all the individual pixels <NUM> within the field-of-view <NUM>.

Each of the chirp <NUM> can be emitted using a laser signal with which the frequency increases (up-chirp), decreases (down-chirp), or remains constant (flat-chirp) over time. In the depicted example, the lidar system <NUM> employs a triangle-slope cycle, which alternates the frequency of each chirp between linearly increasing and linearly decreasing over time. In general, transmission characteristics of the chirps <NUM> (e.g., bandwidth, center frequency, duration, and transmit power) can be tailored to achieve a particular detection range, range resolution, or Doppler resolution for detecting the object <NUM>.

At the lidar system <NUM>, the lidar receive signal <NUM> represents a delayed version of the lidar transmit signal <NUM>. The amount of delay is proportional to the range (e.g., distance) from the lidar system <NUM> to the object <NUM>. In particular, this delay represents a summation of a time it takes for the lidar transmit signal <NUM> to propagate from the lidar system <NUM> to the object <NUM> and a time it takes for the lidar receive signal <NUM> to propagate from the object <NUM> to the lidar system <NUM>. If the object <NUM> and/or the lidar system <NUM> is moving, the lidar receive signal <NUM> is shifted in frequency relative to the lidar transmit signal <NUM> due to the Doppler effect. In other words, characteristics of the lidar receive signal <NUM> are dependent upon motion of the object <NUM> and/or motion of the vehicle <NUM>. Similar to the lidar transmit signal <NUM>, the lidar receive signal <NUM> is composed of one or more of the chirps <NUM>. The transmission of the lidar transmit signal <NUM> and the reception of the lidar receive signal <NUM> is further described with respect to <FIG>.

<FIG> illustrates chart <NUM> which shows the lidar transmit signal <NUM> and the lidar receive signal <NUM> in more detail. Referring to chart <NUM>, the vertical axis represents frequency while the horizontal axis represents time. The chart spans a single frame <NUM> made up of multiple pixels including pixels <NUM>-<NUM>, <NUM>-<NUM>, and so forth.

During the frame <NUM>, the lidar system <NUM> scans the lidar receive signal <NUM> obtaining range and range-rate information from chirps <NUM>-<NUM>-<NUM> and <NUM>-<NUM>-<NUM> for the pixel <NUM>-<NUM>. Then, the lidar system <NUM> scans the lidar receive signal <NUM> obtaining range and range-rate information from chirps <NUM>-<NUM>-<NUM> and <NUM>-<NUM>-<NUM> for the pixel <NUM>-<NUM>, e.g., for quasi-simultaneous range-Doppler sensing. By mixing the laser (local or "LO") signal with the lidar receive signal <NUM>, the lidar system <NUM> generates two beat frequencies, an upchirp beat frequency (fbu) and a downchirp beat frequency (fbd), which can then be decomposed into velocity and distance information, as presented in the following equations. For the following equations, assume R is range (distance) to an object, v is velocity (range-rate) of the object, c is the speed of light, fc is the carrier frequency (the lidar transmit signal <NUM>), T is chirp time, and B is bandwidth. Accordingly:.

For each chirp, and to avoid the chirp ambiguity, a delay time Td is required before integrating the lidar receive signal <NUM> during each chirp to determine the upchirp or downchirp beat frequency. This delay time Td is dependent on the maximum range of the lidar system <NUM>, and thus in the range of one to ten microseconds, typically limits the scanning speed. Following the delay time Td, the lidar receive signal <NUM> is integrated during Ti. The process repeats for each pixel in the frame. For example, during chirp <NUM>-<NUM>-<NUM>, the lidar system <NUM> delays for a delay time Td1 before integrating the receive signal <NUM> during Ti1. During the subsequent chirp, chirp <NUM>-<NUM>-<NUM>, the lidar system <NUM> delays for a delay time Td2 before integrating <NUM> the receive signal during Ti2. By repeating a triangular chirp pattern including frame after frame, as is done with a traditional lidar system to capture both velocity and distance information, the delay time Td limits the scanning speed at each pixel and the overall frame rate.

As will be made clear below, the lidar system <NUM> overcomes the traditional lidar system's limitations on scanning speed and, therefore, frame rate by applying fast-scanning techniques. The lidar system <NUM> alternates between using two different chirp patterns (e.g., one with two chirps and the other with one chirp) in consecutive frames in such a way as to distinguish the Doppler frequency for both frames, while reducing the scanning time for each pixel. The frame rate is substantially improved because the chirp pattern in the latter of two consecutive frames has a shorter duration than the chirp pattern in the initial of the two consecutive frames, unlike traditional lidar systems where the chirp pattern is the same frame after frame.

<FIG> illustrates an example transmitter <NUM>-<NUM> and an example receiver <NUM>-<NUM> of the fast-scanning FMCW lidar system <NUM>. The transmitter <NUM>-<NUM> shown in <FIG> is an example of the transmitter <NUM> from <FIG>. Likewise, the receiver <NUM>-<NUM> is an example of the receiver <NUM> from <FIG>. In the depicted configurations, the transmitter <NUM>-<NUM> and the receiver <NUM>-<NUM> are each coupled between the beam steering components <NUM> and the processor <NUM>.

The transmitter <NUM>-<NUM> includes an emitter <NUM>, such as a laser, among other transmit elements, and the receiver <NUM>-<NUM> includes a photo-detector <NUM>, such as a Ge photodiode, among other receiver elements.

The processor <NUM> executes the lidar control module <NUM>, which inputs a control signal <NUM> to the transmitter <NUM>-<NUM>. In response to the control signal <NUM>, the transmitter <NUM>-<NUM> outputs the transmit signal <NUM> using emitter <NUM> according to the frequency-modulation specified in the control signal <NUM>. The photo-detector <NUM> detects the receive signal <NUM> which is output as a beat signal <NUM> to the raw-data processing module <NUM>.

<FIG> illustrates an example scheme implemented by the processor <NUM> of the lidar system <NUM> for performing lidar functions. In the depicted configuration, the processor <NUM> implements the raw-data processing module <NUM>, and the lidar control module <NUM> outputs lidar data <NUM> for vehicle-based subsystems <NUM>. The processor <NUM> is connected to the receive channel <NUM>.

During reception, the raw-data processing module <NUM> accepts the beat signal <NUM>. The beat signal <NUM> represents raw or unprocessed complex lidar data. The raw-data processing module <NUM> performs one or more operations to generate a lidar data based on the beat signals <NUM>. As an example, the raw-data processing module <NUM> can perform one or more Fourier transform operations, such as a Fast Fourier Transform (FFT) operation. Over time, the raw-data processing module <NUM> generates lidar data for multiple frames <NUM> of the lidar receive signal <NUM>.

The raw-data processing module <NUM> outputs amplitude and/or phase information (e.g., in-phase and quadrature components). The lidar control module <NUM> analyzes information to generate lidar data <NUM> for the vehicle-based subsystems <NUM>. As an example, the lidar data <NUM> indicates whether or not an object <NUM> is in a blind spot of the vehicle <NUM>.

<FIG> illustrates example chirp patterns of a traditional lidar system juxtaposed to example chirp patterns of a fast scanning lidar system which relies on different chirping patterns in consecutive frames. As illustrated in the <FIG>, the chirp patterns <NUM>-<NUM> through <NUM>-<NUM> (collectively "chirp patterns <NUM>") are consistent for each pixel within a frame for any of the waveforms <NUM>-<NUM> through <NUM>-<NUM>. However, the waveforms <NUM>-<NUM> and <NUM>-<NUM> alternate frame-by-frame between the chirp patterns <NUM>-<NUM> and <NUM>-<NUM> or <NUM>-<NUM> and <NUM>-<NUM>, respectively. The velocity and distance information can be extracted from detecting and comparing the beat signals across two consecutive frames, in serial. The long chirp pattern of frame n utilizes two or more slopes so that both range and Doppler information can be determined. The object range-rate or velocity v is assumed to be constant in between these two consecutive frames n and n+<NUM>. The Doppler frequency at frame n can therefore be reused for measurements in frame n+<NUM>. Equations <NUM> to <NUM>, therefore, provides velocity v, and range Rn+<NUM> at the frame n+<NUM>.

For example, a traditional lidar system may output waveform <NUM>-<NUM> including chirp pattern <NUM>-<NUM>, which is a dual chirp, triangular waveform at each pixel, from one frame to the next. The traditional lidar system scans each pixel in frame n using the chirp pattern <NUM>-<NUM> between times t0 and t3, and then after a short delay between frames, the traditional lidar system scans each pixel in frame n+<NUM> using the same chirp pattern <NUM>-<NUM> between times t<NUM> and t7. Having two different slopes enables the frequency shift caused by an object's range (distance) to be separated from the frequency shift caused by the object's range rate (velocity).

In contrast to a traditional lidar system, the lidar system <NUM> changes chirp patterns from one frame to the next as shown by waveforms <NUM>-<NUM> and <NUM>-<NUM>. The lidar system <NUM> outputs the chirp pattern <NUM>-<NUM> for each pixel in frame n, just like the traditional lidar system does in waveform <NUM>-<NUM>. However, in the subsequent frame n+<NUM> of waveform <NUM>-<NUM>, the lidar system <NUM> outputs a different chirp pattern <NUM>-<NUM> to scan each pixel. At each pixel, the chirp pattern <NUM>-<NUM> includes the chirp having different slopes from the chirp pattern <NUM>-<NUM>. Frame n+<NUM> in waveform <NUM>-<NUM> is of shorter duration than frame n+<NUM> of waveform <NUM>-<NUM> because the chirp pattern <NUM>-<NUM> has half the quantity of chirps as the chirp pattern <NUM>-<NUM>.

As already explained, having two different slopes enables the frequency shift caused by an object's range to be separated from the frequency shift caused by the object's range rate. With a single-slope shorter chirp pattern, like the chirp pattern <NUM>-<NUM>, this information cannot be separated. Accordingly, the lidar system <NUM> relies on the Doppler information determined during the previous frame from the chirp pattern <NUM>-<NUM>.

As another example, the lidar system <NUM> outputs waveform <NUM>-<NUM> including the chirp pattern <NUM>-<NUM> for each pixel in frame n and outputs the chirp pattern <NUM>-<NUM> for the subsequent frame n+<NUM>. At each pixel, the chirp pattern <NUM>-<NUM> includes an up chirp followed by a constant chirp, whereas the chirp pattern <NUM>-<NUM> includes the up chirp but omits the constant chirp from the chirp pattern <NUM>-<NUM>. Frame n+<NUM> in waveform <NUM>-<NUM> is of shorter duration because the chirp pattern <NUM>-<NUM> has half the quantity of chirps as the chirp pattern <NUM>-<NUM>.

The change of chirp pattern frame-by-frame can be performed by the lidar control module <NUM>, which does not require additional hardware and therefore does not increase cost or complexity. Lidar frame rate or scanning speed is however increased. Costs can be reduced by limiting the quantity of channels.

Many other kinds of waveforms are possible. For example, a first chirp pattern and a second chirp pattern can be interspersed across a single frame. For example, frame n includes a first chirp pattern for pixel <NUM>-<NUM> and second chirp pattern for pixel <NUM>-<NUM>. A subsequent frame n+<NUM> includes a second chirp pattern for pixel <NUM>-<NUM> and a first chirp pattern for Pixel <NUM>-<NUM>.

<FIG> illustrates an example process <NUM> performed by the processor <NUM> of a fast scanning FMCW lidar system <NUM>. The process <NUM> may be performed including additional or fewer operations than what is shown or in a different order.

At <NUM>, the processor <NUM> causes the lidar system <NUM> to, during an initial frame, scan an initial pattern of two or more chirps for each pixel within a field-of-view of a lidar system of an automobile. For example, the lidar system <NUM> may output waveform <NUM>-<NUM> including the chirp pattern <NUM>-<NUM> at each pixel in the initial frame.

At <NUM>, the processor <NUM> determines a beat frequency associated with the initial frame based on the scanning of the initial pattern of two or more chirps. At <NUM>, the processor <NUM> identifies object range and range-rate information associated with the initial frame based on the beat frequency associated with the initial frame.

At <NUM>, the processor <NUM> causes the lidar system <NUM> to, during a subsequent frame, scan a different pattern of one or more chirps for each pixel with the field-of-view. For example, the lidar system <NUM> may output waveform <NUM>-<NUM> including the chirp pattern <NUM>-<NUM> at each pixel in the subsequent frame.

At <NUM>, the processor <NUM> determines a beat frequency associated with the subsequent frame based on the scanning of the different pattern. At <NUM>, the processor <NUM> identifies object range and range-rate information associated with the subsequent frame based on the beat frequency associated with the initial and the subsequent frames.

At <NUM>, the processor <NUM> determines distance and velocity information for at least one object present in the field-of-view based on the beat frequency associated with the initial frame and the beat frequency associated with the subsequent frame. For example, the raw-data processing module <NUM> transforms the information contained in the beat signals <NUM> into object range and range-rate information for one or more objects in each pixel in the field-of-view <NUM>.

The following are additional examples of fast-scanning FMCW lidar systems and applicable techniques.

Scanning by a lidar system of an automobile, during an initial frame of two consecutive frames and for each pixel within a field-of-view, an initial pattern of two or more chirps; determining, by the lidar system, based on the scanning of the initial pattern of the two or more chirps, a beat frequency associated with the initial frame; identifying, based on the beat frequency associated with the initial frame, the object range and range-rate information associated with the initial frame; scanning, by the lidar system, during a subsequent frame of the two consecutive frames and for each pixel within the field-of-view, a different pattern of one or more chirps; determining, by the lidar system, based on the scanning of the different pattern of the one or more chirps, a beat frequency associated with the subsequent frame; identifying, based on the beat frequency associated with each of the initial frame and the subsequent frame, object range and range-rate information associated with the subsequent frame; determining, based on the object range and range rate information associated with each of the initial and subsequent frames, distance and velocity for at least one object present in the field-of-view; and outputting, by the lidar system, the distance and velocity of the at least one object present in the field-of-view.

Preferably identifying the object information associated with the subsequent frame further comprises applying a Doppler frequency determined for the initial frame as the Doppler frequency for the subsequent frame.

The initial pattern of two or more chirps may comprise a pair of chirps, and the subsequent pattern of one or more chirps comprises a single chirp.

The pair of chirps in the initial frame may comprise a first chirp and a second chirp and the single chirp in the subsequent frame may comprise a third chirp different or similar with the first chirp or the second chirp.

A frequency of the first chirp increases over time and a frequency of the second chirp decreases or remains constant.

A duration of the initial frame exceeds a duration of the subsequent frame.

The distance and velocity for the objects present in the field-of-view can include distance and velocity information for a single object present a single pixel in the field-of-view.

The distance and velocity for the objects present in the field-of-view can include distance and velocity information for multiple objects present a single pixel in the field-of-view.

Outputting the distance and velocity information of the at least one obj ect present in the field-of-view may comprise outputting the distance and velocity information of the object present in the field-of-view to another system of the automobile.

According to another example, a lidar system comprises: a transmitter; a receiver; and at least one processing unit configured to: direct the transmitter and receiver to scan, during an initial frame of two consecutive frames and for each pixel within a field-of-view, an initial pattern of two or more chirps; determine, based on the scanning of the initial pattern of the two or more chirps, the beat frequency associated with the initial frame; identify, based on the beat frequency with the initial frame, object range and range-rate information associated with the initial frame, a; direct the transmitter and receiver to scan, during a subsequent frame of the two consecutive frames and for each pixel within the field-of-view, a different pattern of one or more chirps; determine, based on the scanning of the different pattern of the one or more chirps, the beat frequency associated with the subsequent frame; identify, based on the beat frequency associated with the initial frame and the subsequent frame, , object range and range-rate information associated with the subsequent frame; determine, based on the beat frequencies associated with the initial and subsequent frames, distance and velocity for at least one object present in the field-of-view; and output the distance and velocity of the at least one object present in the field-of-view.

Claim 1:
A method comprising:
scanning, by an FMCW lidar system (<NUM>) of an automobile (<NUM>), during an initial frame of two consecutive frames and for each pixel within a field-of-view (<NUM>), wherein the field-of-view is divided into pixels, an initial chirp pattern of two or more chirps;
determining, by the lidar system (<NUM>), based on the scanning of the initial chirp pattern of the two or more chirps, a beat frequency associated with the initial frame;
identifying, based on the beat frequency associated with the initial frame, object range and range rate information associated with the initial frame;
scanning, by the lidar system (<NUM>), during a subsequent frame of the two consecutive frames and for each pixel within the field-of-view, a different chirp pattern of one or more chirps, a duration of the initial frame exceeding a duration of the subsequent frame;
determining, by the lidar system (<NUM>), based on the scanning of the different chirp pattern of the one or more chirps, a beat frequency associated with the subsequent frame;
identifying, based on the beat frequency associated with each of the initial frame and the subsequent frame, object range and range rate information associated with the subsequent frame;
determining, based on the object range and range rate information associated with each of the initial and subsequent frames, distance and velocity for at least one object (<NUM>) present in the field-of-view (<NUM>); and
outputting, by the lidar system (<NUM>), the distance and velocity of the at least one object (<NUM>) present in the field-of-view (<NUM>).