Lidar sensing arrangement

Abstract

To provide a new system and method for light detecting and ranging (LIDAR).SOLUTION: A LIDAR system includes a light source configured to project a beam at various wavelengths toward a wavelength dispersive element. The wavelength dispersive element is configured to receive the beam and send at least a portion of the beam into a field of view (FOV) at an angle depending on a frequency. The system also includes a detector that is positioned to receive portions of the beam reflected from an object within the FOV, and a processor configured to control the light source and determine the velocity of the object.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Patent Application No. 16 / 810,269, filed March 5, 2020, which is incorporated by reference in its entirety.

[0002] This application relates generally to the field of sensing, and more particularly to Light Detection and Ranging (LIDAR) sensing devices. [Background technology]

[0003] A LIDAR system uses light to detect the distance between a light source and a target. A beam (e.g., a laser) is sent out towards the target. A LIDAR system typically determines the time it takes for the light to reach the target, be deflected off the target, and return to the detector. Based on this time and the speed of light, the distance to the target is determined. Detecting targets and determining their movement are functions that must be performed reliably, continuously, and in a timely manner in order for a machine (i.e., an autonomous vehicle) to operate safely. Summary of the Invention

[0004] The technology provides systems and methods for LIDAR that can capture, track, and determine the velocity of objects within a field of view (FOV). In one implementation, the LIDAR system includes a light source configured to generate a beam having discrete frequencies at various times, a wavelength dispersive element arranged to receive at least a portion of the beam and configured to sweep the beam over a range of angles in the field of view (FOV), where each discrete frequency of the beam corresponds to a different angle in the FOV, a detector arranged to receive portions of the beam reflected from an object within the FOV, and a processor communicatively coupled to the detector. The processor is configured to cause the light source to generate a beam that sweeps from a first frequency at a first time to a second frequency over a ramp up time period and sweeps from the second frequency back to the first frequency over a ramp down time period, and determine the velocity of the object based on the beam.

[0005] In some embodiments, to determine the velocity of the object, the processor is further configured to identify a first portion of the object signal corresponding to an object detected during the ramp-up period and to identify a second portion of the object signal corresponding to an object detected during the ramp-down period. In some embodiments, to determine the velocity of the object, the processor is further configured to calculate a first beat frequency for the first portion of the object signal and a second beat frequency for the second portion of the object signal. In some embodiments, the first beat frequency is calculated using the first portion of the object signal and the first portion of the generated beam corresponding to the first object signal, and the second beat frequency is calculated using the second portion of the object signal and the second portion of the generated beam corresponding to the second object signal. In some embodiments, the processor is further configured to determine a distance from the LIDAR system to the object using the first beat frequency and the second beat frequency. In some embodiments, the system further includes an interferometer and a beam splitting device disposed between the light source and the wavelength dispersive element, the beam splitting device configured to receive a beam generated by the light source and split the beam into an object beam that is sent toward the wavelength dispersive element and a reference beam that is sent toward the interferometer, the interferometer configured to detect a frequency of the reference beam.

[0006] In some embodiments, the ramp-up and ramp-down periods correspond to a first frame, and the processor is further configured to sweep the beam from the first frequency to the second frequency at a second time point over a second ramp-up period and sweep the beam from the second frequency back to the first frequency over a second ramp-down period, where the second time point, the second ramp-up period, and the second ramp-down period correspond to the second frame. In some embodiments, the processor is further configured to determine a first range and a first angle of the object relative to the LIDAR system during the first frame, determine a second range and a second angle of the object relative to the LIDAR system during the second frame, and determine a velocity vector of the object relative to the LIDAR system using the first range, the second range, the first angle, and the second angle. In some embodiments, to determine a second distance of the object, the processor is further configured to predict a second distance of the object relative to the LIDAR system using the first distance and velocity of the object, generate a filter based on the predicted second distance, and filter the received light signal from the object in the second frame using the filter. In some embodiments, the processor is further configured to determine a velocity vector of the object relative to an environment external to the LIDAR system using a velocity vector of the object relative to the LIDAR system and a velocity vector of the LIDAR system relative to an environment external to the LIDAR system.

[0007] In another implementation, a system includes a light source configured to generate a beam having discrete frequencies at different times, a wavelength dispersive element positioned to receive at least a portion of the beam and configured to sweep the beam over a range of angles in a field of view (FOV), where each discrete frequency of the beam corresponds to a different angle in the FOV, a detector positioned to receive portions of the beam reflected from an object within the FOV, and a processor communicatively coupled to the detector, The processor is configured to cause the light source to generate a beam that sweeps from a first frequency at a first time to a second frequency over a period of time and to determine a velocity of the object based on portions of the beam received by the detector.

[0008] In some embodiments, to determine the velocity, the processor is further configured to determine a phase of a first portion of the object signal based on each portion of the beam received by the detector, and to determine a phase of a second portion of the object signal. In some embodiments, the phase of the first portion is determined by performing a Fast Fourier Transform (FFT) on the first portion of the object signal, and the phase of the second portion is determined by performing an FFT on the second portion of the object signal. In some embodiments, the processor is further configured to determine a distance of the object from the system, the distance being determined based on an amplitude of an FFT of the first portion of the object signal and an amplitude of an FFT of the second portion of the object signal. In some embodiments, to determine the velocity, the processor is further configured to determine a time difference between the first and second portions, estimate a wavelength of the beam, and determine the velocity using the phase of the first portion, the phase of the second portion, the time difference, and the wavelength.

[0009] In some embodiments, the time period corresponds to a first frame, and the processor is further configured to cause the beam to sweep continuously from the first frequency at a second time to the second frequency over a second time period, the second time period corresponding to the second frame. In some embodiments, to determine the velocity, the processor is further configured to determine a phase of a first object signal corresponding to the object in the first frame, determine a phase of a second object signal corresponding to the object in the second frame, and determine the velocity using the phase of the first portion, the phase of the second portion, and a wavelength corresponding to the first object signal.

[0010] In another implementation, a method includes controlling a light source via a processor to project a beam that is continuously swept from a first frequency to a last frequency starting at a first time point over a first period of time, the light source being configured to project the beam into an FOV at an angle that is frequency dependent, the beam being projected towards a wavelength dispersive element further configured to direct each portion of the beam that is reflected from an object within the FOV towards a detector, the detector being configured to generate an object signal, and determining, via the processor, a velocity of the object based on the object signal.

[0011] In some embodiments, the velocity of the object is determined using the phase of the first portion of the object signal and the phase of the second portion of the object signal. In some embodiments, the method further includes controlling the light source via the processor to continuously sweep the beam from the last frequency back to the first frequency over a second time period after the first time period, and determining the velocity of the object is based on the object signal corresponding to the object detected during the first time period and the object signal corresponding to the object detected during the second time period. In some embodiments, the method further includes controlling the light source via the processor to project a beam that continuously sweeps from the first frequency to the last frequency at a second time point during the second time period, the second time point being after the first time period, and determining the velocity of the object is based on the object signal corresponding to the object detected during the first time period and the object signal corresponding to the object detected during the second time period.

[0012] The foregoing summary is illustrative only and is not in any way limiting. In addition to the illustrative aspects and features described above, further aspects and features will become apparent by reference to the following drawings and detailed description.

[0013] These and other features of the present disclosure will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings, in which: The present disclosure will be described with additional specificity and detail, with the understanding that such drawings are merely illustrative of certain implementations in accordance with the present disclosure and are therefore not to be considered limiting of its scope, and in which: [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is a block diagram illustrating a LIDAR system in accordance with an exemplary embodiment. [Diagram 2] 1 is a graph illustrating a signal profile from a LIDAR system in accordance with an example embodiment. [Diagram 3] FIG. 1 is a block diagram illustrating a LIDAR system in accordance with an exemplary embodiment. [Figure 4] 1 is a graph illustrating a signal profile from a LIDAR system in accordance with an example embodiment. [Diagram 5] 1 is a graph illustrating a signal profile including multiple frames from a LIDAR system in accordance with an exemplary embodiment. [Figure 6] FIG. 1 is a block diagram illustrating a LIDAR system in accordance with an exemplary embodiment. [Figure 7a] 1 is a graph illustrating a signal profile from a LIDAR system with an interferometer in accordance with an example embodiment. [Figure 7b] 1 is a graph illustrating a signal profile for multiple frames from a LIDAR system with an interferometer in accordance with an exemplary embodiment. [Figure 8a] FIG. 7b illustrates a beat signal profile of a beat signal corresponding to the signal profile of FIG. 7a in accordance with an exemplary embodiment. [Figure 8b] FIG. 7B illustrates a beat signal profile of a beat signal corresponding to the signal profile of FIG. 7B in accordance with an exemplary embodiment. [Figure 9] FIG. 1 illustrates a LIDAR system in motion in accordance with an exemplary embodiment. [Figure 10] FIG. 1 illustrates a field of view (FOV) of a LIDAR system in accordance with an exemplary embodiment. [Figure 11] 1 is an illustration of filtering an object signal in accordance with an illustrative embodiment; [Figure 12] FIG. 1 illustrates an FOV of a LIDAR system in accordance with an exemplary embodiment. [Figure 13] FIG. 1 illustrates a LIDAR system in motion in accordance with an exemplary embodiment. [Figure 14] 1 is a flow diagram illustrating a method for calculating the velocity of an object within the FOV of a LIDAR system in accordance with an illustrative embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the various drawings, like symbols typically identify like components unless otherwise noted. The exemplary implementations described in the detailed description, drawings, and claims are not intended to be limiting. Other implementations may be utilized, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that the aspects of the present disclosure, as generally described herein and illustrated in the figures, can be arranged, substituted, combined, and designed in a wide variety of different configurations, all of which are expressly contemplated and made a part of this disclosure.

[0016] Described herein are systems and methods for LIDAR sensing. As described in more detail below, disclosed herein is a LIDAR sensing system that includes a light source controlled to project beams at various wavelengths (e.g., infrared beams, beams, collimated beams, etc.). The beams are sent toward a wavelength dispersive element. The beams are projected from one or more wavelength dispersive elements at angles corresponding to the wavelengths of the beams. As a result of varying the wavelengths of the beams, the LIDAR sensing system generates a vertical scan (e.g., a two-dimensional scan) of a field of view (FOV) of an external environment. A beam steering device may be used to enable the LIDAR sensing system to generate multiple vertical scans along a horizontal axis (or vice versa) to generate a three-dimensional scan of the field of view (FOV) of the LIDAR sensing system. In some embodiments, the three-dimensional scan of the FOV is achieved with only static elements (e.g., the first and second elements of the wavelength dispersive element are both static elements). The received portions of the beams from this scan may then be processed to calculate the velocity of objects within the FOV. One or more scans of the FOV may be repeated multiple times (e.g., to generate multiple frames) to enable the LIDAR system to track an object over time, calculate the object's absolute velocity vector, or otherwise monitor the object's range, velocity, and location relative to the LIDAR system. The ability of the LIDAR system to measure the velocity of an object within a short time frame allows the LIDAR system to predict the object's future location relative to the LIDAR system, thereby enabling the LIDAR system to be used in applications (e.g., autonomous vehicles) that require enhanced monitoring and tracking of objects within the LIDAR system's FOV. Thus, the LIDAR system can determine the velocity of an object within the FOV in a very short time, taking into account the Doppler effect or phase change in each signal, thereby reducing the likelihood that the LIDAR system will mistake a first object detected during a first measurement for a second object detected during a second measurement.As a result, LIDAR systems can be implemented in applications where objects must be tracked with precision (e.g., autonomous vehicles).

[0017] 1, a block diagram of a LIDAR sensing system 100 is shown. The LIDAR sensing system 100 is shown as including a LIDAR system 101 and a field of view (FOV) 190 of the LIDAR system 101. In some embodiments, an object 190 may be present within the FOV 190. In some embodiments, one or more objects 191 may be present within the FOV 190, each having a unique range and velocity relative to the LIDAR system 101.

[0018] The LIDAR system 101 comprises a light source 102. In some implementations, the light source 102 outputs a beam. In some embodiments, the beam (e.g., a laser beam) has a selectable discrete frequency. Additionally, the light source 102 is configured to tune the wavelength λ (e.g., and therefore the frequency) of the beam. That is, in some embodiments, the light source 102 may be a tunable laser, where the wavelength λ of the laser is tuned or selected. The light source 102 may be configured to tune the wavelength λ of the beam over a range. In some examples, the range of wavelength λ may be between 1.25 μm and 1.35 μm. As described in more detail below, the light source 102 may be swept over a range of wavelengths λ. In some embodiments, the light source 102 may be swept continuously over a range of wavelengths from a first wavelength (and therefore a first frequency) to a last wavelength (and therefore a last frequency). The light source 102 may be swept continuously from the first wavelength to the last wavelength in a linear or non-linear pattern. In some embodiments, light source 102 may include one or more tunable lasers cascaded together such that light source 102 has an even broader range of wavelengths λ.

[0019] 1, the LIDAR system 101 is also shown to include a wavelength dispersive element 104, a detector 109, and a computing system 114. The wavelength dispersive element 104 is configured to transmit light from the light source 102 through the FOV 190 and return scattered or reflected portions of the received light to the detector 109. That is, the light source 102 is configured to project components of a beam onto the wavelength dispersive element 104. The wavelength dispersive element 104 receives the beam and transmits portions of the beam toward the FOV 190. The portions of the beam reflect off an object 191 in the FOV 190, and at least a portion of the reflected beam is received back by the wavelength dispersive element 104. The wavelength dispersive element 104 receives a portion of the reflected beam and transmits a portion of the reflected beam toward the detector 109. The detector 109 receives the portions of the reflected beam and generates an electrical signal indicative of the portions of the reflected light received and thus indicative of the object. This electrical signal may be transmitted to a processor 114 of a computing system 112 that can process the electrical signal (eg, an object signal) to determine the range and velocity of an object 191 within the FOV 190.

[0020] In some embodiments, the wavelength dispersive element 104 may comprise a first element 140 configured to direct or control at least a portion of the beam from the light source 102 along an angle of the first axis 191 of the FOV 190. In some embodiments, the first element 140 directs the beam portions along various angles relative to the first axis 191 of the FOV 190 based on the wavelength of each of the beam portions. In some embodiments, the first element 140 may comprise one or more diffraction gratings, prisms, crystals, or other dispersive optical elements. In some embodiments, the one or more diffraction gratings may be configured to receive the beam portions from the light source 102 at a constant angle of incidence and reflect the beam portions towards the FOV 190 at a diffraction angle that depends on the wavelength λ of the beam portions. The beam portions directed towards the environment may then be reflected from objects 191 within the FOV 190, and the reflected portions of the beam may be received at the diffraction grating and directed towards the detector 109. In this manner, in some embodiments, the first element 140 may be configured to disperse the light beam along a first axis of the FOV 190 based on a characteristic (e.g., wavelength) of the light beam.

[0021] In some embodiments, the wavelength dispersion element 104 may also include a second element 141. In some embodiments, the second element 141 is configured to transmit at least a portion of the beam from the light source 102 along a second axis (e.g., a horizontal axis) of the FOV 190. In some embodiments, the second element 141 may include a beam steering device (e.g., a rotating mirror, or an actuator of the first element). In some embodiments, the beam steering device 102 may be configured to control, rotate, or adjust the first element (e.g., a diffraction grating) such that the first element 140 can be used to generate multiple scans (e.g., each scan along the first axis) along the second axis to generate a three-dimensional scan of the FOV 190. In some embodiments, the second element 140 may comprise a 1×N splitter that splits the beam from the light source 102 into N portions and directs each of the N portions toward a respective dispersive element (e.g., the first element 140) at each output of the 1×N splitter. That is, each of the dispersive elements may generate a scan by directing a respective portion of the beam along a first axis, and the second element 141 (e.g., a 1×N splitter) allows each dispersive element's scan to be spread throughout the second axis. In this manner, in one implementation, a three-dimensional scan of the environment external to the LIDAR system 101 may be performed using only static elements in the LIDAR system.

[0022] The detector 109 is configured and disposed within the system to receive portions of light reflected from objects within the FOV 190. In some embodiments, the detector 109 may be communicatively coupled to the computing system 112 (e.g., the processor 114). In some embodiments, the detector 109 comprises an infrared sensor, a camera, an infrared camera, or any other light detection device capable of sensing the frequency of light received. The detector 109 is disposed to transmit light received at the wavelength dispersive element 104 (e.g., light reflected from the object 190) toward the detector 109. For example, in some embodiments, the LIDAR system 101 may comprise a beam splitting device 157 disposed between the light source 102 and the wavelength dispersive element 104 such that a beam from the light source 102 traverses the beam splitting device 157 and is transmitted toward the wavelength dispersive element 104. In some embodiments, the beam splitting device 157 may comprise a half mirror, a one-way mirror, a half silver mirror, or other optical element configured to direct light from the light source 102 towards the wavelength dispersive element 104 and direct light from the wavelength dispersive element 104 towards the detector 109. The beam splitting device 157 may also be positioned such that light reflected from the object 190 (and light directed by the wavelength dispersive element 104) is reflected, diffracted, or otherwise directed by the beam splitting device 157 towards the detector 109. In some embodiments, other optical or other components may be used in addition to or in place of the beam splitting device 157. The detector 109 is configured to generate an object signal indicative of each portion of the beam detected by the detector 109. In some embodiments, the object signal is in the form of an electrical signal and is transmitted to the computing system 112 for processing.

[0023] The computing system 112 comprises a processor 114 and a memory 116. The processor 114 may include any component or group of components configured to execute, implement, and / or perform any of the processes or functions described herein, or any form of instructions to execute or enable such processes to be performed. In one or more configurations, the processor 114 may be the main processor of the LIDAR sensing system 100. Examples of suitable processors include microprocessors, microcontrollers, DSP processors, and other circuits capable of executing software. Further examples of suitable processors include, but are not limited to, central processing units (CPUs), array processors, vector processors, digital signal processors (DSPs), field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), application specific integrated circuits (ASICs), programmable logic circuits, and controllers. The processor 114 may comprise at least one hardware circuit (e.g., an integrated circuit) configured to execute instructions contained in a program code. In configurations where multiple processors are present, such processors may operate independently of one another, or one or more processors may operate in combination with one another.

[0024] The memory 116 may be configured to store one or more types of data. The storage of the memory 116 may include volatile and / or non-volatile memory. Examples of suitable memory 116 include RAM (random access memory), flash memory, ROM (read only memory), PROM (programmable read only memory), EPROM (erasable programmable read only memory), EEPROM (electrically erasable programmable read only memory), registers, magnetic disks, optical disks, hard drives, or any other suitable storage medium, or any combination thereof. In some embodiments, the memory 116 includes a persistent computer-readable storage medium communicatively coupled to the processor 114. The computer-readable storage medium may encode or otherwise store instructions that, when executed by the processor, enable the processor to perform any of the operations, steps, or methods described herein. The memory 116 may be a component of the processor 114, or the memory 116 may be operably connected to the processor 114 for use by the processor 114. In some configurations, the memory 116 may be located remotely and accessible by the processor 114 via a suitable communications device or the like.

[0025] The processor 114 is communicatively coupled to the light source 102 and may be configured to read and execute instructions from a light source controller 118 stored or programmed on the memory 118. The light source controller 118 may be or include computer readable instructions for controlling one or more features of the light source 102. As shown, the light source controller 118 may be stored in the memory 116. In other implementations, the light source controller 118 may be stored remotely and accessible by various components of the LIDAR sensing system 100. The processor 114 may control the light source 102 according to instructions from the light source controller 118.

[0026] The light source controller 118 may include instructions to generate a pattern of the beam projected from the light source 102. For example, in some implementations, the beam may be projected from the light source 102 in a pattern having a frequency (e.g., pulsed, sawtooth, etc.). The light source controller 118 may include instructions to generate, for example, a sawtooth signal corresponding to the frequency pattern of the beam projected from the light source 102. In some embodiments, the light source controller 118 may include instructions to cause the light source 102 to generate a beam that sweeps from a first frequency at a first time to a second frequency over a ramp-up period and sweeps from the second frequency back to the first frequency over a ramp-down period. In some embodiments, the light source controller 118 may include instructions to cause the light source to generate one or more frames. In some embodiments, the multiple frames are periodic with a set period between each frame. The frequency pattern of the frames may be used to determine the range and velocity of the object 190, as described in more detail below.

[0027] In some embodiments, one or more components of LIDAR system 101 may be omitted. In some embodiments, various other components of LIDAR system 101 may be included. It should be understood that FIG. 1 is an example of an implementation of LIDAR system 101 and is not limiting.

[0028] For example, in some embodiments, the LIDAR system 101 may include an interferometer. The interferometer may be or may include a component configured to receive a beam from the light source 102 and split the beam into one or more component beams. For example, the interferometer 110 may split the beam into an object beam and a reference beam. The object beam may be projected toward the wavelength dispersive element 104, and the reference beam may be projected toward a reference mirror. The interferometer may generate an interference pattern based on the difference between light reflected from a surface of an object in the external environment and light reflected from the reference mirror. The LIDAR sensing system 100 (e.g., the processor 114) may determine the distance to the object based on the interference pattern.

[0029] Referring to Figure 2, an example of a corresponding signal profile 200 of an object 190 is shown. For demonstration purposes, consider Figure 2 with reference to various components of Figure 1. The signal profile 200 includes a y-axis that indicates frequency and an x-axis that indicates time. In some embodiments, the signal profile 200 is a first "frame" of measurements from the LIDAR system 100. This first frame includes a complete sweep of the LIDAR system along a first axis of the FOV 190.

[0030] The signal profile 200 includes a reference signal 201, a stationary object signal 202, and a moving object signal 203. The reference signal 201 is generated from the light source 102 and represents the frequency of a beam projected from the light source over time 102. In some embodiments, the light source controller 118 generates a reference signal pattern (e.g., a sawtooth pattern) and the processor 114 communicates with the light source 102 to enable the light source 102 to emit a beam having a reference signal characteristic over time (e.g., from a first frequency to a last frequency and back to the first frequency). In some embodiments, the reference signal 201 is estimated to have the characteristics of the pattern stored in the light source controller 118. In some embodiments, the reference signal 201 may be measured by an interferometer, a detector 109, a second detector, or with another device.

[0031] In some embodiments, the wavelength dispersive element 104 directs the beam at an angle that depends on the wavelength of the beam (e.g., the inverse of the frequency of the beam). For example, the wavelength dispersive element 104 may direct the beam such that when the beam is at a first wavelength λ1, the beam is directed toward the center of a first section A1 of the FOV 190, when the beam is at a second wavelength λ2, the beam is directed toward the center of a second section A2 of the FOV 190, and when the beam is at a third wavelength λ3, the beam is directed toward the center of a third section A3 of the FOV 190. In some embodiments, the angle at which the wavelength dispersive element 104 directs the beam toward the FOV 190 may vary linearly with the frequency of the beam.

[0032] The light source 102 starts sweeping at a first frequency f0 at a first time t0. The light source 102 sweeps for a first period Δt m The beam is then modulated at the highest frequency f max Continuously sweep up to the highest frequency f max and the first frequency f1 may be referred to as a change in frequency Δf in this example. The time between the first time t0 and the second time t1 may be referred to as a "ramp-up" time in this example. The light source 102 then linearly sweeps the beam back to the first frequency f1 for another period of time to a third time t2. The time between the second time t1 and the third time t2 may be referred to as a ramp-down time in this example. The time between the first time t0 and the third time t2 may be referred to as a frame. A frame is one cycle of the sweep from the light source 102. In some embodiments, a frame may include only a ramp-up period or a ramp-down period.

[0033] In this example, the equation for the ramp-up time of the reference signal 201 can be given by equation (1) for the ramp-up time and equation (2) for the ramp-down time.

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[0034]

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[0035] In one example, when the object is stationary relative to the LIDAR system 101, the detected frequency from the object 191 is indicated by a stationary object signal 202. This stationary object signal may include a first signal 220 representing the frequency and time when light reflected from the object 191 is received during a ramp-up period and the object 191 is stationary relative to the LIDAR system 101. The stationary object signal 202 may also include a second signal 221 representing the frequency and time when light reflected from the object 191 is received during a ramp-down period and the object 191 is stationary relative to the LIDAR system 101.

[0036] In another example, when the object 191 is stationary relative to the LIDAR system 101, the detected frequency from the object 191 is indicated by a moving object signal 203. The moving object signal 203 includes a first signal 230 representing the frequency and time at which light reflected from the object 191 is received during a ramp-up period as the object 191 moves away from the LIDAR system 101. The moving object signal 203 may include a second signal 231 representing the frequency and time at which light reflected from the object 191 is received during a ramp-down period as the object 191 moves away from the LIDAR system 101.

[0037] The stationary object signal 202 and the moving object signal 203 are shifted by a time constant τ with respect to the reference signal 201. The time constant τ is the time it takes for the beam to reach the object and reflect back to the LIDAR system 101. Thus, in some embodiments, the time constant τ is equal to twice the range R of the object divided by the speed of light c.

[0038] The detected frequency from object 191 may be used in conjunction with (or in comparison with) equation (3) when the beam is impinging on (and reflecting from) object 191 during the ramp-up period, and may be used in conjunction with equation (4) when the beam is impinging on (and reflecting from) object 191 during the ramp-down period.

[0039]

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[0040]

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[0041] That is, the processor 114 may use equations (3) and (4) with the detected object signal to estimate or determine the velocity and / or position of the object 191. It should be understood that when the beam is not impinging on the object 191 (e.g., because the frequency and resulting angle of the beam do not correspond to the position of the object 191), there should be no detected light or resulting signal (e.g., a moving object signal or a stationary object signal). However, there may be noise in the signal. The processor 114 may then use equations (3) and (4) with the detected object signal to estimate or determine the velocity and / or position of the object 191.

[0042] In some embodiments, the computing system 112 may calculate a first beat frequency f corresponding to a first signal (e.g., signal 220 or 230) during the ramp-up period. beat1 , and a second beat frequency f corresponding to a second signal (e.g., signal 221 or 231) of the detection signal during the ramp-down period beat2In some embodiments, the beat frequency may be calculated for a non-moving object by subtracting the reference signal from the detected signal. In some embodiments, the beat frequency may be used to determine the distance of the object 190 using a known value of the time shift between the reference signal and the detected signal.

[0043] The processor 114 may use the characteristics of the signal profile 200 and the Doppler effect to calculate the velocity of the object 191. The Doppler effect is shown in FIG. 2 as a difference 280 (e.g., Doppler shift 280) between the stationary object signal 202 and the moving object signal 203. The Doppler shift may be given by equation (5):

[0044]

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[0045] Therefore, the Doppler shift 280 is proportional to the velocity v of the object 181. Taking the Doppler shift 280 into account, the first beat frequency f beat1 (e.g., the beat frequency corresponding to the ramp-up time) may be calculated using equation (6), and the second beat frequency f beat2 (eg, the beat frequency corresponding to the ramp-down time) may be calculated using equation (7).

[0046]

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[0047]

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[0048] In equations (6) and (7), t3 corresponds to a first signal (e.g., signal 220 or 230) detected during the ramp-up time, and t5 corresponds to a second signal (e.g., signal 221 or 231) detected during the ramp-down time. The range of object 191 may be determined using equation (8), and the velocity of object 191 may be determined using equation (9).

[0049]

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[0050]

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[0051] In equations (8) and (9), f c is the center frequency at which the object is measured. For example, the center frequency of the object 191 in FIG. 1 may be given or estimated as the speed of light divided by the second wavelength λ2. Thus, by using a reference signal 201 that rises from a first frequency to a highest frequency and back to the first frequency, the processor 114 can determine both the range and the velocity of the object (e.g., by taking into account the Doppler effect). It should be understood that FIG. 2 is by way of example, and that numerous objects within the FOV of the LIDAR system 101 may be measured, determined, or calculated in a similar manner. That is, the range and velocity of objects in the environment may be measured continuously across a sweep of frequencies in either two dimensions (via a sweep on the first axis) or three dimensions (via a sweep along the first axis and a sweep through numerous portions, or a sweep along the second axis).

[0052] FIG. 3 illustrates a system 300 similar to the LIDAR sensing system 100 of FIG. 1. FIG. 3 includes a LIDAR system 101, a field of view 190, and an object 301. To demonstrate how the phase shift in adjacent sections of the LIDAR system 101 measurements is used to measure the velocity of the object 301, FIG. 4 is referenced in conjunction with FIG. 3. FIG. 4 includes a signal profile 400 of the LIDAR system 101 measurements in the system 300. The signal profile 400 includes a reference signal 401 and an object signal 402. The object signal 402 is detected by the detector 109 at every frequency at which the beam from the light source 102 is transmitted toward the FOV 190 and reflected from the object 301. As with the signal profile 200 of FIG. 2, the object signal 402 is shifted graphically by an amount of time equal to τ (e.g., the time it takes for the beam to reflect from the object 301 back to the LIDAR system 101).

[0053] The signal profile 400 shows a first period 420 during which the frequency of the beam scans, sweeps across, or corresponds to a first portion A0 of the FOV 190, a second period 421 during which the frequency of the beam scans, sweeps across, or corresponds to a second portion A1 of the FOV 190, and a third period 422 during which the frequency of the beam scans, sweeps across, or corresponds to a second portion A2 of the FOV 190. Each portion of the object signal 402 corresponding to the first period 420, the second period 421, and the third period 422 may be decomposed into discrete signals and processed to determine the velocity of the object 301. For example, if the velocity of the object 301 is sufficiently low (e.g., less than 1 m / sec) that the first frequency to the highest frequency (f1 to f2) is not too high, the object signal 402 may be processed to determine the velocity of the object 301. max In embodiments where the distance to the object 301 does not change significantly during the sweep time of ( ), the phase shift of adjacent portions of the object signal 402 corresponding to the first period 420, the second period 421, and the third period 422 may be used to determine the velocity of the object 301.

[0054] As shown in equation (10), the phase φ of the reflected object beam (e.g., the beam corresponding to the object signal 402) is proportional to the phase φ of the reference beam (e.g., the object beam of this beam). r It is associated with.

number

[0055] In equation (10), R is the distance of the object 290 from the LIDAR system, and λ is the estimated central wavelength of the relevant portion of the object signal 403. The change in phase with time can be expressed using equation (11). (11) dφ / dt=4π / λ*dR / dt=4π / λ*v

[0056] Thus, the change in phase Δφ over a period T can be used to calculate the velocity. Thus, the velocity can be calculated from detecting the phase difference between adjacent portions of the object signal 402 corresponding to the first period 420, the second period 421, and the third period 422. Specifically, the period T may be set by the processor or may be known by the processor. For example, the period between the first wavelength λ1 and the second wavelength λ2 (e.g., the first period 420, i.e., the first portion A0 of the FOV) may be used as the period T. The velocity of the object 301 can be calculated using equation (12).

[0057]

number

[0058] In equation (12), φ i is the initial phase of the object signal 402 in the first period of the period 420, 421, or 422, and φ i+1 is the phase of the object signal 402 in adjacent periods. However, adjacent periods may differ in that λ is i and both are approximately equal to λ i+1 Approximately equal to (for example, λ i+1The phase shifts should be used to calculate the maximum velocity V for a particular LIDAR system 101 according to equation (13). max The velocity of object 301 up to can be accurately calculated.

[0059]

number

[0060] In some embodiments, the phase shift between adjacent portions of the object signal 402 may be calculated by performing a Fast Fourier Transform (FFT) on the adjacent portions of the object signal 402. The magnitude of the FFT may be used to calculate the distance (i.e., or range) of the object 301 from the LIDAR system 101. The phase shift between each adjacent portion of the object signal 402 may be calculated by using the FFT of each signal at the range of the object 301 and subtracting a first phase at the range of a first signal of the object signal 402 from a second phase at the range of a second (e.g., or adjacent) object signal 402. In some embodiments, the phase shift calculation may be performed multiple times using multiple adjacent portions of the object signal 402 and then the multiple calculated phase shifts may be averaged together to reduce any potential for error in the velocity calculation.

[0061] In some embodiments, the velocity of the object 301 may be measured without using adjacent portions of the object signal 402. This can be advantageous in situations where the object 301 may be small or far away from the LIDAR system 101, such that the object signal 402 does not have sufficient (or possibly any) adjacent portions that can be used to calculate the phase shift. For example, Figure 5 illustrates one way of measuring or calculating the velocity of the object 301 without using adjacent portions of the object signal.

[0062] 5 illustrates multiple frames of a signal profile 500 that may be used to calculate a phase shift. The signal profile 500 includes a first frame 501, a second frame 502, and an Nth frame 503. The first frame 501 includes a first reference signal 510 and a first object signal 511. The second frame 502 includes a second reference signal 520 and a second object signal 521. The Nth frame includes an Nth reference signal 530 and an Nth object signal 531. That is, in some embodiments, more than one frame may be used to calculate the phase shift between the object signals 511, 521, and 531 in adjacent frames. In some embodiments, when the object 301 is moving very slowly (e.g., slower than the wavelength divided by four times the period T), the phase shift may be calculated between adjacent frames that are two or more frames apart from each other. The LIDAR system 101 may assume that each of the object signals 511, 521, 531 corresponds to the same object 301 due to where the object signals are received relative to the reference signals 510, 520, and 530 in each frame. For example, the object signals 511, 521, and 531 all correspond to the same (or similar) frequency of the reference signals 510, 520, and 530 in each frame. In some embodiments, the frames 501, 502, and 503 are of consistent duration T f adjacent to other frames.

[0063] For example, in some embodiments, the velocity of the object 301 may be calculated using equation (14) between the first frame 501 (i.e., the first frame i) and the period T f It may be calculated between

number

[0064] As mentioned above, the measurable velocity resolution of the object 301 is v resmay be limited in situations where the phase shift between adjacent frames is very small (e.g., the velocity of the object 301 is very low). In some such embodiments, the processor 114 may select the object signal 511, 521, or 531 from a frame that is further away to accurately measure, calculate, or estimate the velocity of the object. For example, the resolution of the measurable velocity between adjacent frames v res is the minimum measurable phase shift Δφ of the LIDAR system 101 min The measurable velocity resolution v res may be calculated using equation (15).

[0065]

number

[0066] Thus, in some embodiments, each frame selected by the processor 114 to calculate velocity is augmented to provide a measurable velocity resolution v res For example, the resolution of the measurable velocity v res may be improved by selecting frames that are N frames apart. In this way, the velocity of an object that is moving very slowly relative to the LIDAR system 101 can still be accurately measured or calculated. The resolution of measurable velocity v between object signals 511, 521, and 531 that are N frames apart is res may be calculated using equation (16).

[0067]

number

[0068] However, it should be appreciated that in order to uniquely determine velocity without error due to dominant shifts, the maximum velocity that can be measured across N frames should be limited to situations where the phase shift Δφ between N frames is greater than negative piπ, but also less than piπ. That is, the maximum velocity that can be uniquely measured across N frames can be calculated using equation (17).

[0069]

number

[0070] FIG. 6 illustrates a LIDAR system 600 according to an exemplary embodiment. As described in FIG. 1, in some embodiments, the LIDAR system 101 may include an interferometer. The LIDAR system 600 includes various similar components as the LIDAR system 101 and the interferometer 603. That is, the LIDAR system 600 includes a light source 102, a wavelength dispersive element 104, and a detector 109. In some embodiments, the interferometer 603 may be a reference interferometer implemented as a Mach-Zehnder interferometer. In some embodiments, the light source 102 projects a beam 602 toward a beam splitter 603, which splits the beam 602 into a reference beam 604 and an object beam 605. The reference beam 604 is sent toward the input of the interferometer 608. Interferometer 608 then diffracts, reflects, or otherwise directs the reference beam 604 over a known distance, where it is received by a second detector 609. In some embodiments, second detector 609 and detector 109 may be the same detector, which may be configured to receive both the reference beam 604 and the reflected portion of the object beam 605 from the FOV.

[0071] In some embodiments, the object beam 605 is directed towards the beam splitter 603 where it is refracted or passes through it and passes through the half mirror 611. The object beam 605 strikes the wavelength dispersive element 104 and is directed towards the FOV. The object beam 605 may strike an object in the FOV and be reflected or scattered back towards the wavelength dispersive element 104. The wavelength dispersive element 104 may then direct a reflected portion of the object beam 605 towards the detector 109. In some embodiments, the reflected portion of the object beam 605 strikes the half mirror 611 and is reflected, refracted or otherwise directed towards the detector 109.

[0072] In some embodiments, the interferometer 603 enables the LIDAR system 600 to generate an interference signal between the reflected portion of the object beam 605 and the reference beam 604 to calculate a beat signal. In some embodiments, the interferometer is used to monitor the frequency sweep and identify intervals in the ramp-up and ramp-down portions of the frame (e.g., the period during which the beam is sent toward a first portion of the FOV A0). In some embodiments, the interferometer 603 enables the processor 614 to use the calculated interference signal between the reflected portion of the object beam 605 and the reference beam 604 and the known distance traveled by the reference beam 604 to calculate the distance (e.g., i.e., range) of the object within the FOV.

[0073] FIG. 7a illustrates a signal profile 700 across a ramp-up and ramp-down period (e.g., a frame) of a LIDAR system according to an exemplary embodiment. FIG. 7a illustrates a signal profile 750 across multiple ramp-up periods (e.g., multiple frames) of a LIDAR system according to an exemplary embodiment. FIG. 8a illustrates a beat signal profile 800 of a beat signal from an interferometer that corresponds to the signal profile 700. FIG. 8b illustrates a beat signal profile 850 of a beat signal from an interferometer that corresponds to the signal profile 750 across multiple frames. To demonstrate, refer to FIG. 6 while considering FIGS. 7 and 8. The signal profile 700 includes a reference signal 701. In some embodiments, the reference signal 701 is intentionally or unintentionally nonlinear due to constraints of the light source 102. The nonlinearity of the reference signal 701 may distort the time at which the object beam 605 is sent toward a particular portion of the FOV (e.g., A0, A1, or A2, etc.). As a result, the calculation of the object signal position and the object signal size may also be distorted. The LIDAR system 600 (e.g., processor 114) may use the beat signal profile 800 as a reference to correct for distortions while calculating the range and velocity of one or more objects in the FOV. For example, the beat signal profile 800 includes a beat signal 801 that indicates the time that the object beam is swept through each portion of the FOV (e.g., A0, A1, and A2). In some embodiments, the beat signal 801 may indicate the time and angular position of the object beam by creating a cosine graph where each cycle of the cosine is associated with a portion of the FOV. Thus, the beat signal 801 from the interferometer 603 may be used to identify the interval during which the object beam 605 is projected toward or swept across a particular portion of the FOV, even in the presence of nonlinearities in the reference signal. Additionally, the beat signal 801 may also be used to identify the time when the ramp-up and ramp-down regions of a frame occur, even if they are not identical.That is, the beat signal 801 may be used by the processor 114 to compensate for nonlinearities in the frequency sweep to ensure that accurate position, distance, and velocity are measured for each object in the FOV. In some embodiments, the LIDAR system 600 may calculate and compensate for nonlinearities in the reference signal 701 by detecting the reference signal 701 (e.g., via an interferometer), recording when the reference beam 701 is at a particular frequency, and cross-referencing the received object signal based on this recording. Although described between Figures 7a-8a, it should be understood that the signal profile 750 in Figure 7b, and the corresponding beat profile in Figure 8b, may be used to calculate and compensate for nonlinearities in the reference signal in each frame.

[0074] FIG. 9 illustrates a moving LIDAR system 900 in accordance with an example embodiment. The moving LIDAR system 900 is moving at a velocity v L In some embodiments, the LIDAR system 101 (or 600) is on a vehicle (e.g., an automobile or autonomous vehicle) and therefore has a velocity of v L The LIDAR system 101 uses the connected sensors to measure the velocity v L For example, the LIDAR system 101 may include a geographic location system (GPS) coupled to the processor 114 to indicate the velocity of the LIDAR system 101 to the processor 114. In some embodiments, the processor 114 may determine the velocity v L The LIDAR system 101 may be connected to another sensor (e.g., a speedometer) that indicates the velocity v . The LIDAR system 101 may determine an angle θ from an axis 980 normal to the LIDAR system 101 at which the object is located based on the frequency at which the object signal is received. The LIDAR system 101 may then use the determined, received, or accessed velocity v L , the absolute velocity v of object 901 along the angle θ aFor example, as described above, the LIDAR system 101 may detect the object 901 and calculate the distance (e.g., i.e., range) of the object 901 and the velocity v of the object 901 relative to the LIDAR system 101. The LIDAR system 101 (e.g., the processor 114) may use this measured, determined, or calculated information to calculate the absolute velocity v of the object 901. a For example, the LIDAR system 101 may determine the absolute velocity of the object 901 using equation (18). (18) v a =v0+v L *cos(θ)

[0075] FIG. 10 illustrates a field of view (FOV) 1000 of a LIDAR system (e.g., 102 or 600) according to an example embodiment. In some embodiments, the FOV 1000 may be the FOV 190 described above. The FOV 1000 includes an object 1001 detected during a first frame from the LIDAR system 101. The object 1001 may be measured or calculated by the LIDAR system 101 to be at a first angle θ1 with respect to an axis 1050 normal to the LIDAR system 101, a first distance R1 (i.e., or range) from the LIDAR system 101, and to have a first velocity v1 along the first angle θ1 with respect to the axis 1050 normal to the LIDAR system 101. The LIDAR system 101 may use the calculated or measured characteristics to predict the position of the object 1001 in the next frame (or subsequent frames). The LIDAR system may predict the position of the object 1001 to improve the signal-to-noise ratio of the signal in the next frame (or subsequent frames) and also enable better object tracking over time. That is, the LIDAR system 101 detects and calculates a first velocity v1 of the object 1001, which only indicates the velocity of the object 1001 at a first angle θ1. Thus, by tracking the object 1001 over multiple frames, the absolute velocity can be determined by also determining a second velocity component perpendicular to the first velocity v1. However, if the object 1001 is moving very rapidly, the LIDAR system 101 may need to predict the position of the object 1001 in the second frame (or subsequent frames) to ensure that the object 1001 is measured in the second frame (as opposed to, for example, a second object).

[0076] That is, the FOV 1000 also includes a predicted area 1020 of the object 1001 in the next frame (i.e., the second frame) based on the calculated or measured first velocity v1, first angle θ1, and first distance R1 of the object 1001 in the first frame. The LIDAR system 101 determines the predicted area 1020 of the object 1001 in the next frame (i.e., the second frame) based on the calculated or measured first velocity v1, first angle θ1, and first distance R1 of the object 1001 in the first frame. fThe LIDAR system 101 may calculate a predicted change within range ΔR between the first and second frames by multiplying the first velocity v1 by the first velocity v1. The LIDAR system 101 may determine a second expected range R2 of the object 1001 at a distance that is the predicted change in range ΔR plus R1. An object detected at the second range R2 in the second frame may then be considered as the object 1001.

[0077] FIG. 11 illustrates a diagram 1100 of filtering an FFT signal of an object signal according to an exemplary embodiment. The diagram 1100 includes a first FFT signal 1101, a second FFT signal 1102, and a filter FFT function 1103. The first FFT signal 1101 is an FFT of the object 1001 in a first frame (e.g., a first position as shown in FIG. 10). The distance of the object is determined to be a first distance R1. The processor 114 may calculate a second predicted range R2 in a subsequent frame (i.e., a second frame) (e.g., using a first velocity measured in the first frame) and generate a filter FFT function 1103. The filter FFT function 1103 includes a filter signal 1130 having a peak 1131 corresponding to the second range R2. In some embodiments, the FFT function 1103 may be a Gaussian filter or a square filter having a peak corresponding to the second range R2. The second FFT signal 1102 corresponds to an FFT of the object signal captured during the second frame. The second FFT signal 1102 includes a second peak 1120, but also includes noise 1121. The second FFT signal 1102 may then be multiplied by a filter FFT function 1103 to generate a noise-reduced FFT signal 1104. The FFT signal 1104 (and / or the corresponding function) may then be used by the processor 114 to perform one or more operations described herein. It should be understood that FIGS. 10 and 11 are by way of example only. That is, in some embodiments, other methods or steps may be used to predict the range of the object in the second frame, depending on the particular implementation. For example, the LIDAR system 101 may monitor the position of the object (e.g., object 1001) over time, determine any components of the velocity of each object, and use the components to generate the filter function in the subsequent frame. In some embodiments, the acceleration of the LIDAR system 101 is also compensated for when determining the filter function. In some embodiments, the first and second frames are N frames apart. In some embodiments, other types of transforms may be implemented instead of or in addition to a Fast Fourier Transform (FFT).

[0078] 12 illustrates a field of view (FOV) 1200 of a LIDAR system (e.g., 102 or 600) according to an example embodiment. The FOV 1200 illustrates a measured position of an object 1001 within the FOV 1001. That is, the FOV 1200 illustrates a first range R1 and a first angle θ1 of the object 1001 in a previous frame (i.e., the first frame), and a second range R2 and a second angle θ2 of the object 1001 measured or detected in a second frame. The processor 114 may use the measured object information in the first and second frames to calculate a velocity vector v(t) of the object 1001. In some embodiments, this velocity vector v(t) may be determined by subtracting a position vector r2(R2, θ2) corresponding to the position of the object 1001 in the second frame from a first position vector r1(R1, θ1) corresponding to the position of the object 1001 in the first frame, and dividing the result by the time between the second and first frames. In some embodiments, this velocity vector v(t) may be determined in other manners, such as by transforming the position vector into a different coordinate system (e.g., a Cartesian coordinate system) before calculating the velocity vector v(t).

[0079] It should be understood that Figures 10-12 are by way of example only. That is, in some embodiments, other methods or steps may be used to predict the range of the object in the second frame depending on the particular implementation. For example, the LIDAR system 101 may monitor the position of the object (e.g., object 1001) over time, determine every component of the velocity of each object, and use the components to generate the filter function in the subsequent frame. In some embodiments, one or more objects may be traced, predicted, and measured over multiple frames. In some embodiments, the acceleration of the LIDAR system 101 is also compensated for when determining the filter function. In some embodiments, the first and second frames are N frames apart from each other. In some embodiments, other forms of transformation may be implemented instead of or in addition to the Fast Fourier Transform (FFT).

[0080] 13 illustrates a moving LIDAR system 1300 according to an example embodiment. The moving LIDAR system 1300 is configured to move in a direction parallel to the moving LIDAR axis, with a velocity vector v L The LIDAR system 101 may include a LIDAR system (such as a LIDAR system described herein) moving at a velocity represented by (t) and an object 1301. The object 1301 may have a velocity vector v(t) relative to the LIDAR system 101 that is detected, measured, or calculated by the LIDAR system 101. The velocity vector v(t) of the LIDAR system 101 may be expressed as L (t) is added to the velocity vector v(t) of the object 1301 to obtain the absolute velocity vector v of the object 1301 relative to the external environment of the LIDAR system 101. a In some embodiments, when the LIDAR system 101 accelerates (e.g., when a vehicle carrying the LIDAR system 101 accelerates), v L The velocity vector of (t) may change, and the predicted position of the object 1301 relative to the LIDAR system in subsequent frames (e.g., over time) may be adjusted accordingly. In this manner, the LIDAR system 101 may measure, detect, and calculate one or more objects within the FOV to trace, predict, or estimate the objects' respective positions relative to the LIDAR system over time, which may enable the LIDAR system 101 to be implemented in many different applications (e.g., in autonomous vehicles) and to provide safety benefits for such applications.

[0081] FIG. 14 illustrates a flow diagram of a method 1400 for calculating a velocity of an object within the FOV of a LIDAR system according to an example embodiment. In operation 1401, a processor controls a light source to generate a beam over a sweep of frequencies over a first time period or enables the light source to generate a beam over a sweep of frequencies over a first time period. In some embodiments, the processor may cause the light source to generate a beam that continuously sweeps from a first frequency at a first time point to a second frequency at a second time point. In some embodiments, the sweep of the beam over each frequency is linear with a particular slope. In some embodiments, the sweep of the beam over each frequency is non-linear. In some embodiments, the processor further causes the light source to generate a beam that sweeps from the first frequency to the second frequency during a ramp-up period and back to the first frequency during a ramp-down period. In some embodiments, the processor uses a light source generator to determine the pattern of the sweep. In some embodiments, the processor may cause the light source to re-sweep the frequencies at a time point after the first time point. That is, the processor may enable the light source to re-sweep each frequency to generate multiple frames, in some embodiments, each of the multiple frames separated from adjacent frames by a set, known, or predetermined period of time.

[0082] In operation 1402, the LIDAR system projects a beam toward a wavelength dispersive element. In some embodiments, the beam may be projected toward one or more wavelength dispersive elements. The wavelength dispersive element may include a volume grating, a diffraction grating, or other type of diffraction grating located within or on a coupler or other device. In some embodiments, the wavelength dispersive element may include a crystal, a prism, or other wavelength dispersive device in combination with other optical elements such as mirrors or lenses.

[0083] In operation 1403, the beam is projected or sent from the wavelength dispersive element towards the FOV of the LIDAR system at an angle that depends on the frequency of the beam. That is, the beam (or a portion of the beam) may strike the wavelength dispersive element at a constant angle of incidence throughout the frequency sweep of the beam. The wavelength dispersive element reflects, sends, disperses or projects the beam into the FOV based on the frequency of the beam. That is, a first frequency may be projected into the FOV at a first angle and a last frequency may be projected into the FOV at a second angle. Sweeping the beam ensures that every angle between the first and second angles at the FOV is scanned. For a particular LIDAR system or wavelength dispersive element, the angle at which each particular frequency of the beam is projected into the FOV is known, and therefore the LIDAR system can determine the angular position of the object based on the frequency of each portion of the beam received at the detector.

[0084] In operation 1404, portions of the beam reflected from objects in the FOV are directed towards a detector. In some embodiments, the detector is positioned to receive portions of the beam reflected from objects in the FOV. In some embodiments, the wavelength dispersive element is configured to receive portions of the beam reflected from objects in the FOV and direct the reflected portions of the beam towards the detector. In some embodiments, one or more other optical elements may be used and configured to direct the reflected portions of the beam towards the detector.

[0085] In operation 1405, the detector generates an object signal based on the received reflected portion of the beam. The detector receives the reflected portion of the beam and generates an object signal. In some embodiments, the object signal is an electrical signal (e.g., analog or digital) that may be sent to a processor or detector of the LIDAR system for processing. In some embodiments, the object signal is immediately stored in memory for processing at a later time. In some embodiments, the object signal includes noise or other imperfections that require processing to identify the object and / or calculate the velocity or position of the object. In some embodiments, the object signal includes every output of the detector over a specified period of time, and each portion of the object signal may be identified as a first portion or a second portion.

[0086] In operation 1406, the LIDAR system determines the velocity of the object based on the detected light (i.e., the object signal) corresponding to the first time period. In some embodiments, the processor uses characteristics of the object signal and the reference signal to determine the velocity of the object. For example, a reference signal with a sawtooth shape (e.g., i.e., rising and then falling) allows the processor to calculate the distance and velocity of the object based on the Doppler effect. In some embodiments, the processor uses adjacent portions of the first object signal corresponding to an object sensed or detected during the ramp-up period to determine the velocity of the object. In some embodiments, the processor determines the velocity of the object by calculating the phase shift between each adjacent portion of the first object signal.

[0087] In some embodiments, the processor determines the velocity of the object by determining a phase shift between a first object signal and a second object signal corresponding to an object sensed or detected at different times (e.g., during ramp-up periods of different frames). In some embodiments, the processor determines the velocity of the object by determining a Doppler shift between the first object signal and another object signal corresponding to an object sensed during a ramp-down period. In some embodiments, the processor may determine the velocity by calculating a first beat signal in the first object signal and a second beat signal in the second object signal. The processor may further determine a range or distance of the object based on the first and second beat signals.

[0088] In some embodiments, the processor is further configured to determine a velocity vector of the object relative to the LIDAR system using the velocity and position determination from the multiple frames. In some embodiments, the processor is further configured to track or trace the object over time and across the multiple frames. In some embodiments, the processor is further configured to predict the position of the object in a subsequent frame based on the determined velocity or velocity vector. In some embodiments, the processor is further configured to generate a filter from the predicted position of the object. In some embodiments, the filter enables noise reduction in a received signal corresponding to a subsequent frame. In some embodiments, the processor is further configured to determine an absolute velocity vector of the object relative to an environment external to the LIDAR system using the known, accessed, received, or determined velocity of the LIDAR system. In some embodiments, the processor is further configured to receive acceleration information regarding the LIDAR system to adjust the prediction or trace the object in a world-centric perspective.

[0089] The foregoing description of the exemplary embodiments has been presented for purposes of illustration and description. It is not intended to be exhaustive or to be limiting to the precise form disclosed, and modifications and variations may be possible in light of the above teachings or may be acquired from practicing the disclosed embodiments.

[0090] While certain embodiments have been shown and described, it will be understood that changes and modifications may be made thereto by those skilled in the art without departing from the technology in its broader aspects as defined in the appended claims.

[0091] The embodiments illustratively described herein may be suitably implemented in the absence of any element(s) or limitation(s) not specifically disclosed herein. Thus, for example, terms such as "comprising," "including," and "containing" are to be read expansively and not limiting. Furthermore, the terms and expressions employed herein are used as terms of description and not of limitation, and in using such terms and expressions, there is no intention to exclude equivalents of the features shown and described in the figures or portions thereof, but it is recognized that various modifications are feasible within the scope of the claimed technology. Furthermore, the phrase "consisting essentially of" will be understood to include the elements specifically recited and additional elements that do not materially affect the basic and novel characteristics of the claimed technology. The phrase "consisting of" excludes any elements not specified.

[0092] It is not intended that the disclosure be limited to the specific embodiments described herein. As will be apparent to those skilled in the art, numerous modifications and variations may be made without departing from the spirit and scope of the present application. In addition to the methods and configurations recited herein, functionally equivalent methods and configurations within the scope of the present disclosure will be apparent to those skilled in the art from the foregoing description.

[0093] Such modifications and variations are intended to be within the scope of the appended claims. The present disclosure is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is to be understood that this disclosure is not limited to particular methods, reagents, compounds, compositions or biological systems, which may, of course, vary.

[0094] It should also be understood that the terminology used herein is for the purpose of illustrating specific embodiments only and is not intended to be limiting. It should also be understood by those skilled in the art that "based on" should be interpreted as "based at least on" unless expressly stated otherwise.

[0095] As will be understood by those skilled in the art, for any and all purposes, particularly with respect to presenting the written description, any range disclosed herein also encompasses any and all feasible subranges and combinations of the subranges. Any recited range can be readily recognized as fully describing and allowing the same range to be divided into at least two, three, four, five, ten, etc. As a non-limiting example, each range described herein may be readily divided into a lower third, a middle third, an upper third, etc. As will also be understood by those skilled in the art, any language such as "up to," "at least," "greater than," "less than" and the like, refers to a range that is inclusive of the recited numbers and may be subsequently divided into subranges as described above. Finally, as will be understood by those skilled in the art, a range includes each individual element.

[0096] All publications, patent applications, issued patents, and other documents mentioned in this specification are incorporated by reference into this specification to the same extent as if each individual publication, patent application, issued patent, or other document was specifically and individually indicated to be incorporated by reference in its entirety.

[0097] Definitions contained in texts incorporated by reference are excluded to the extent that they conflict with a definition in this disclosure.

[0098] Other embodiments are within the scope of the following claims.

Claims

1. a light source configured to generate a beam having discrete frequencies at various times; a wavelength dispersive element positioned to receive at least a portion of the beam and configured to sweep the beam over a range of angles in a field of view (FOV), wherein each discrete frequency of the beam corresponds to a different angle in the FOV; and a detector positioned to receive each portion of the beam reflected from an object within the FOV and configured to generate an object signal based on the received portions of the beam; a processor communicatively coupled to the detector; wherein the processor: sweeping the beam from a first frequency at a first time to a second frequency over a ramp-up period; sweeping the beam from the second frequency back to the first frequency over a ramp-down period; Determining a velocity of the object based on a characteristic of the beam.

1. A light detection and ranging (LIDAR) system configured as follows:

2. To determine the velocity of the object, the processor: identifying a first portion of the object signal corresponding to the object detected during the ramp-up period; Identifying a second portion of the object signal corresponding to the object detected during the ramp down period. The system of claim 1 further configured to:

3. To determine the velocity of the object, the processor: calculating a first beat frequency for the first portion of the object signal; Calculating a second beat frequency for the second portion of the object signal. The system of claim 2 further configured to:

4. 4. The system of claim 3, wherein the first beat frequency is calculated using the first portion of the object signal and a first portion of the generated beam corresponding to the first object signal, and the second beat frequency is calculated using the second portion of the object signal and a second portion of the generated beam corresponding to the second object signal.

5. 4. The system of claim 3, wherein the processor is further configured to use the first beat frequency and the second beat frequency to determine a distance from the LIDAR system to the object.

6. An interferometer; a beam splitting device disposed between the light source and the wavelength dispersive element, the beam splitting device configured to receive the beam generated by the light source and split the beam into an object beam that is delivered towards the wavelength dispersive element and a reference beam that is delivered towards the interferometer; Further equipped with The system of claim 1 , wherein the interferometer is configured to detect a frequency of the reference beam.

7. 2. The system of claim 1 , wherein the ramp-up period and the ramp-down period correspond to a first frame, and the processor is further configured to sweep the beam from the first frequency to the second frequency at a second time point over a second ramp-up period and to sweep the beam from the second frequency back to the first frequency over a second ramp-down period, wherein the second time point, the second ramp-up period, and the second ramp-down period correspond to a second frame.

8. The processor, determining a first distance and a first angle of the object relative to a LIDAR system during the first frame; determining a second distance and a second angle of the object relative to the LIDAR system during the second frame; determining a velocity vector of the object relative to the LIDAR system using the first distance, the second distance, the first angle, and the second angle; The system of claim 7 further configured to:

9. To determine the second distance of the object, the processor: predicting a second range of the object relative to the LIDAR system using the first range and the velocity of the object; generating a filter based on the predicted second distance; Filtering the received light signal from the object in the second frame using the filter. The system of claim 7 further configured to:

10. 8. The system of claim 7, wherein the processor is further configured to determine a velocity vector of the object relative to the environment external to the LIDAR system using the velocity vector of the object relative to the LIDAR system and a velocity vector of the LIDAR system relative to an environment external to the LIDAR system.

11. a light source configured to generate a beam having discrete frequencies at various times; a wavelength dispersive element positioned to receive at least a portion of the beam and configured to sweep the beam over a range of angles in a field of view (FOV), wherein each discrete frequency of the beam corresponds to a different angle in the FOV; and a detector positioned to receive each portion of the beam reflected from an object within the FOV and configured to generate an object signal based on the received portions of the beam; a processor communicatively coupled to the detector; wherein the processor: sweeping the beam from a first frequency at a first time to a second frequency over a period of time; A system configured to determine a velocity of the object based on the portion of the beam received by the detector.

12. To determine the rate, the processor: determining a phase of a first portion of the object signal based on the portion of the beam received by the detector; determining a phase of a second portion of the object signal The system of claim 11 further configured to:

13. 13. The system of claim 12, wherein the phase of the first portion of the object signal is determined by performing a Fast Fourier Transform (FFT) on the first portion, and the phase of the second portion of the object signal is determined by performing an FFT on the second portion of the object signal.

14. 14. The system of claim 13, wherein the processor is further configured to determine a distance of the object from the system, the distance being determined based on an amplitude of the FFT of the first portion of the object signal and an amplitude of the FFT of the second portion of the object signal.

15. To determine the rate, the processor: determining a time difference between the first portion and the second portion; Estimating the wavelength of the beam; determining the velocity using the phase of the first portion, the phase of the second portion, the time difference, and the wavelength; The system of claim 12 further configured to:

16. the time period corresponds to a first frame, and the processor is further configured to cause the beam to sweep continuously from the first frequency to the second frequency at a second time over a second time period, the second time period corresponding to a second frame, and to determine the velocity, the processor: determining a phase of a first object signal corresponding to the object in the first frame; determining a phase of a second object signal corresponding to the object in the second frame; determining the velocity using the phase of the first portion, the phase of the second portion, and a wavelength corresponding to the first object signal; The system of claim 11 further configured to:

17. 1. A method for determining a velocity of an object within a field of view (FOV) of a sensing system, comprising: controlling the light source via the processor to project a beam that is swept over a first time period from a first frequency to a last frequency beginning at a first time; projecting the beam towards a wavelength dispersive element; directing said beam into a FOV at an angle according to frequency; directing each portion of the beam that reflects off an object within the FOV towards a detector; generating an object signal based on each portion of the beam received from the object within the FOV; determining, via the processor, a velocity of the object based on the object signal; A method comprising:

18. 20. The method of claim 17, wherein the velocity of the object is determined using a phase of a first portion of the object signal and a phase of a second portion of the object signal.

19. controlling the light source via a processor to continuously sweep the beam from the last frequency back to the first frequency over a second period of time after the first period of time. Further comprising:

20. The method of claim 17, wherein determining the velocity of the object is based on an object signal corresponding to the object detected during the first time period and an object signal corresponding to the object detected during the second time period.

20. controlling the light source via the processor to project a beam that is continuously swept from the first frequency to a final frequency at a second time during a second period of time. Further comprising: the second time point being after the first time period; 20. The method of claim 18, wherein determining the velocity of the object is based on an object signal corresponding to the object detected during the first time period and an object signal corresponding to the object detected during the second time period.

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