BACKGROUND

Autonomous vehicles (AVs) are vehicles that are able to travel over roadways without a human driver. An exemplary AV includes several types of sensor systems, including but not limited to a camera-based system, a global positioning systems (GPS), a radar system, a lidar system, etc. These sensor systems output sensor signals that are indicative of parameters of an environment in which the AV is traveling. The exemplary AV further includes a computing system that is configured to control operation of mechanical systems of the AV based upon the sensor signals output by the sensor systems. Exemplary mechanical systems include, but are not limited to, a propulsion system (e.g., an electric motor, a combustion engine, a hybrid propulsion system, etc.), a braking system, and a steering system.

Reference is now made more specifically to operation of the lidar sensor system in the AV. Conventionally, the lidar sensor system is employed in several use cases, including object detection and avoidance, localization, and detection of ground truth. These different use cases operate in different range regimes and also require different range resolution. For example, with respect to an object (such as a vehicle or pedestrian) that is between 100 m and 200 m away from the AV, it may be sufficient to detect the object at a resolution of 5 cm to identify and track the object over time. Contrarily, to localize the AV in a geographic region at a desired accuracy (by comparing lidar outputs with a predefined map), it may be necessary to detect objects in a scene that are at a distance of between 35 m and 45 m from the autonomous vehicle at a resolution of 1 cm. Accordingly, and generally, it is desirable to compute distances to objects that are closer to the AV at a more granular resolution than is necessary when computing distances to objects that are further from the AV.

Accordingly, a conventional AV can include multiple sensor systems (one sensor system for each range). Therefore, in a specific example, the AV may include a first sensor system that is configured to compute distances to objects in a first range (e.g., 0-50 m) at a first resolution, and may include a second sensor system that is configured to compute distances to objects in a second range (e.g., 50-200 m) at a second resolution that is more coarse than the first resolution. This adds complexity and expense to the AV.

An exemplary type of lidar system that can be included in an AV is a frequency-modulated continuous wave (FMCW) lidar system. An FMCW lidar system exhibits several advantages over a direct time-of-flight (TOF) lidar system. For instance, the FMCW lidar system employs a coherent detection method, and therefore the FMCW lidar system is generally immune to interference, while performance of the TOF lidar system may be negatively impacted due to interference. Additionally, for the same output power per photon budget, the FMCW lidar system is able to achieve higher signal-to-noise compared to the TOF lidar system. In the conventional FMCW lidar system, however, once electronics and maximum detectable distance are set, resolution is independent of distance of an object from the lidar system. Put differently, resolution at which distance can be computed by the FMCW lidar system is the same across the entire sensing range of the FMCW lidar system. Hence, if it is desirable to both use FMCW lidar systems and have different range resolutions, multiple FMCW lidar systems having overlapping fields of view must be employed (e.g., one FMCW lidar system for short-range sensing and one FMCW lidar system for long-range sensing).

SUMMARY

The following is a brief summary of subject matter that is described in greater detail herein. This summary is not intended to be limiting as to the scope of the claims.

Described herein is a lidar system that is particularly well-suited for use in an autonomous vehicle (AV) (although other applications are contemplated). The lidar system described herein is configured to compute a distance between the lidar system and an object with a resolution that is dependent upon the distance between the object and the lidar system. For example, when the object is between 0 and 90 m from the lidar system, the lidar system can be configured to compute the distance with a first resolution (e.g., a resolution of 1 cm), while when the object is between 90 m and 200 m from the lidar system, the lidar system is configured to compute the distance with a second resolution (e.g., 5 cm) that is different from the first resolution. The ability to compute distances within different ranges with different resolutions is enabled through use of a piecewise linear modulation scheme, such that a lidar signal generated and emitted by the lidar system includes a frequency modulation (chirp) that has an up-chirp and a down-chirp (monotonically increasing or decreasing in frequency, respectively), and further wherein at least the up-chirp includes multiple linear segments that have different slopes. In a nonlimiting example, the up-chirp can include a first segment and a second segment that immediately succeeds the first portion, wherein the first segment has a first slope and the second segment has a second slope, and further wherein the first slope is greater than the second slope (i.e., the rate of change of frequency in the first segment of the up-chirp is greater than the rate of change of frequency in the second segment of the up-chirp).

As will be described in greater detail herein, the lidar system splits the lidar signal into two signals: a local oscillator (LO) that is kept local to the system, and an emitted signal that is transmitted into the world and may reflect from an object in the field of view of the lidar system, resulting in a return reflection. At the lidar system, the return reflection constructively interferes with the LO, and a sensor outputs an analog sensor signal that is indicative of such interference. An analog-to-digital converter (ADC) converts the analog signal to a digital signal (at a sampling rate of the ADC), and processing circuitry of the lidar system performs a Fast Fourier Transform (FFT) over a portion of the digital signal that corresponds to a period of the chirp, thereby forming a frequency signal that identifies one or more beat signals when the object is within the maximum range of the lidar system. A beat signal is indicative of an instantaneous difference between the frequency of the LO and the frequency of the return reflection.

Due to the piecewise linear nature of the up-chirp, two beat frequencies are represented in the frequency signal when the object is within a first range, while one beat frequency is represented in the frequency signal when the object is within a second range (which is non-overlapping with the first range). Once the range is detected, the processing circuitry of the lidar system performs different processing depending upon the detected range, such that lidar system computes the distance to the object with a first resolution when the object is within the first range and computes the distance to the object with a second resolution when the object is within the second range. Hence, in an example, when the processing circuitry determines that an object is between 0 and 90 m from the lidar system, the processing circuitry computes the distance with a first resolution; contrarily, when the processing circuitry determines that the object is between 90 and 200 m from the lidar sensor system, the processing circuitry computes the distance to the object at a second resolution that is less granular than the first resolution.

The above summary presents a simplified summary in order to provide a basic understanding of some aspects of the systems and/or methods discussed herein. This summary is not an extensive overview of the systems and/or methods discussed herein. It is not intended to identify key/critical elements or to delineate the scope of such systems and/or methods. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.

