Signal level of the captured target

Abstract

A laser source generates an optical signal. A splitter divides the optical signal into a first signal and a second signal. A first modulator modulates the first signal. A second modulator modulates the second signal. A scanner scans the first signal following the modulation by the first modulator. A coupler combines the modulated second signal with the modulated first signal following the scanning of the first signal. A detector detects attributes corresponding to the combined signal of the modulated second and modulated first signals and acquires a target based on the combined signal of the modulated second and modulated first signals.

Description

Technical Field

[0001] Cross - reference to related applications This application claims priority based on U.S. Provisional Patent Application No. 63 / 420439, filed with the United States Patent and Trademark Office on October 28, 2022, and incorporates herein by reference in its entirety.

[0002] Field of the Invention The present invention relates to a method for improving the signal level of a target captured using Lidar (Light Detection and Ranging).

Background Art

[0003] Lidar technology has a cornucopia of applications in fields such as aerospace (atmosphere and outer space), autonomous or semi - autonomous driving, and meteorology due to its high - speed, high - precision, and high - accuracy processing.

Summary of the Invention

Means for Solving the Problems

[0004] Various examples of the present invention can include a system comprising a laser source; a splitter; a first modulator; a second modulator; a scanner; a coupler; and a detector. The laser source is configured to generate an optical signal, the splitter is configured to split the optical signal into a first signal and a second signal, the first modulator is configured to modulate the first signal, the second modulator is configured to modulate the second signal, the scanner is configured to scan the first signal following modulation by the first modulator, the coupler is configured to combine the modulated second signal and the modulated first signal following the scanning of the first signal, and the detector is configured to detect an attribute corresponding to the signal obtained by combining the modulated second signal and the modulated first signal and to capture a target based on the signal obtained by combining the modulated second signal and the modulated first signal.

[0005] In some examples, the above system may further include a processor that generates a first frequency-modulated continuous wave (FMCW) signal and a second FMCW signal, respectively, for modulating the first signal and the second signal.

[0006] In some cases, the processor processes the captured target and determines and executes navigation actions based on the processed target.

[0007] In some examples, navigation actions include yielding, making sharp turns, or turning around.

[0008] In some cases, the second FMCW signal has a delay relative to the first FMCW signal, and the processor controls the magnitude of this delay.

[0009] In some cases, the processor controls the amount of delay based on the distance from the processor to the target.

[0010] In some cases, the processor controls the magnitude of the delay to increase in response to smaller distances from the processor to the target.

[0011] In some cases, the second FMCW signal includes a reference beat signal, which creates a beat (beat) with the signal reflected from the target.

[0012] In some examples, the system further comprises a first digital-to-analog converter (DAC) that controls the first modulator and a second DAC that controls the second modulator.

[0013] In some examples, the system further comprises a field-programmable gate array (FPGA) that controls the first and second DACs.

[0014] In some examples, the corresponding method performed by the above system and its elements includes: generating an optical signal; splitting the optical signal into a first signal and a second signal; modulating the first signal; modulating the second signal; scanning the first signal following modulation by a first modulator; combining the modulated second signal and the modulated first signal following scanning the first signal; detecting attributes corresponding to the combined signal of the modulated second signal and the modulated first signal; and capturing a target based on the combined signal of the modulated second signal and the modulated first signal. [Brief explanation of the drawing]

[0015] [Figure 1] This diagram shows the realization of FMCW riders. [Figure 2] This is a diagram illustrating the schematic implementation of a LiDAR system. [Figure 3] This figure shows two fixed-delay sweep signals. [Figure 4] This figure shows two fixed-delay sweep signals when the target is at close range. [Figure 5] This figure shows two fixed-delay sweep signals when the target is at a long distance. [Figure 6] This diagram illustrates a navigation scenario where navigation enhances the acquisition of one or more targets with increased signal strength. [Figure 7] This diagram illustrates a navigation scenario where navigation enhances the acquisition of one or more targets with increased signal strength. [Figure 8] This diagram illustrates a navigation scenario where navigation enhances the acquisition of one or more targets with increased signal strength. [Figure 9] This diagram illustrates a navigation scenario where navigation enhances the acquisition of one or more targets with increased signal strength. [Figure 10]A diagram showing a navigation scenario, enhancing navigation by capturing one or more targets with increased signal strength. [Figure 11] A diagram showing a navigation scenario, enhancing navigation by capturing one or more targets with increased signal strength. [Figure 12] A diagram showing a navigation scenario, enhancing navigation by capturing one or more targets with increased signal strength. [Figure 13] A diagram showing a method according to any of FIGS. 1 - 12. [Figure 14] A block diagram showing a computer system on which any of the embodiments described herein can be implemented.

Embodiments for Carrying Out the Invention

[0016] In coherent lidar detection, in a single modulator scenario, the return signal reflected from a target can only beat (produce a beat) with the modulated signal transmitted to the target, which results in a short integration time when the target is located at a long distance. Since the integration time is correlated with the level of the signal to be acquired, the detection of long - distance signals using a single modulator is disadvantageous. In particular, the overlap region within the region between two signals can represent the total signal strength. Therefore, in order to improve the signal captured during the detection of long - distance targets without compromising the signal captured during the detection of short - distance targets, a new technique implements two modulators. In this technique, the first frequency - modulated continuous - wave (FMCW) signal is directly transmitted to the lidar scanner (scanning device), while the second FMCW signal is delayed for a fixed time with respect to the return signal as a reference beat frequency signal.

[0017] Figure 1 shows an implementation of an FMCW lidar, in which, following the application of an input voltage 102, the laser source 103 is directed to two separate paths: a reference path 111 as a local oscillator and a probe path 112 toward the target 122. The laser source 103 can be a linear frequency modulated chirp laser. A photodetector 104 can detect the interference signal between the light from the probe path 112 and the light from the reference path 111, which can appear as a beat signal 108. The beat signal 108 can be a sine wave, and the frequency of the beat signal can be proportional to the distance to the target. The laser source 103 can be part of a lidar, which can be placed on a moving object such as a vehicle. For example, at least one of the lidar or the target 122 can be in motion. In some examples, the maximum relative speed between the lidar and target 122 can be approximately 300 kilometers per hour, where both the lidar and target 122 are moving in opposite directions at approximately 150 kilometers per hour. In other examples, either the lidar or target 122 can be approximately stationary, while one of them is moving at approximately 150 kilometers per hour. The relative speed can range from 150 kilometers per hour to 300 kilometers per hour.

[0018] The rider can be associated with a computer system 152, which includes one or more processors and memory. The processor can include one or more hardware processors 153. In some examples, one or more of the hardware processors 153 can be combined or integrated into a single processor, and some or all of the functions executed by one or more of the hardware processors 153 need not be spatially separated and instead can be executed by a common processor. The hardware processor 153 can further be connected to, include, or incorporate a logic circuit 163, which can include, for example, a protocol executed to perform the functions of the hardware processor 153. These functions can include any of the functions described in the foregoing drawings such as FIGS. 2 - 13. One or more hardware processors 153 can also be associated with a storage device 154, which can include a permanent storage device or cache for storing any output or intermediate output from the hardware processor 153.

[0019] Figure 2 shows a schematic implementation of a lidar system, which includes a laser source 202, a splitter 203, a digital-to-analog converter (DAC) 205, a DAC 207, a modulator 204 corresponding to DAC 205, a modulator 206 corresponding to DAC 207, a scanner 208, a coupler 209, a detector 210, and a processor 212. The processor 212 can generate a first FMCW signal for optical signal modulation and a second signal corresponding to the return optical signal, which is detected by the detector 210 after sampling. The laser source 202 can generate an optical signal, which can be split into two paths using the splitter 203, and modulated by the two FMCW signals generated by the processor 212 in modulators 204 and 206. Modulator 204 can modulate the optical signal with the first FMCW signal, while modulator 206 can modulate the optical signal with the second FMCW signal. DAC205 can control modulator 204, while DAC207 can control modulator 206. DACs 205 and 207 can be controlled by a field-programmable gate array (FPGA) 213. The optical signal modulated with the first FMCW signal can first be transmitted to scanner 208, while the optical signal modulated with the second FMCW signal can be transmitted directly to coupler 209. The optical signal modulated with the first FMCW signal can then be transmitted to scanner 208 and subsequently to coupler 209. The two signals transmitted to coupler 209 are then transmitted to detector 210 for beat detection or beat sound detection. Thus, modulator 204 is used for modulation and transmission, while modulator 206 can be used for beat detection with the received signal, thereby improving the integration time for long-distance return signals and improving the signal-to-noise ratio for long-distance signals. By implementing two modulators, the return signal beats with the second FMCW signal rather than the first FMCW signal. Even for nearby objects, a stronger signal may be sufficient to detect and recognize the target even with a short integration time. Therefore, short integration times for nearby objects tend to become less detrimental.

[0020] Figure 3 shows two fixed-delay sweep signals 304 and 306, which are generated using an FPGA (e.g., FPGA213) that controls two DACs (e.g., DAC205 and 207) as implemented in Figure 2. This delay can be a programmable digital electronic delay on the FPGA. Sweep signal 304 represents a reference signal delayed by a fixed time and / or synchronized with the return signal. Sweep signal 306 represents the signal to be transmitted. Figure 4 shows two fixed-delay sweep signals when the target is at a short distance. In Figure 4, the previous sweep signal 304 can be shifted up to shift signal 404, while the previous sweep signal 305 can be shifted up to shift signal 405. Figure 5 shows two fixed-delay sweep signals when the target is at a long distance. In Figure 5, the previous sweep signal 304 can be shifted up to shift signal 504, while the previous sweep signal 305 can be shifted up to shift signal 505. In Figure 5, the overlap time between the sweep signal 306 and the shift signal 504 can be made longer than the overlap time in Figure 4, thus increasing the integration time. In each of Figures 3-5, the two sweep signals have the same slope magnitude. For shorter distances, the beat frequency will be larger.

[0021] Figures 6-12 illustrate navigation scenarios, where navigation is enhanced by acquiring one or more targets with increased signal strength. In Figure 6, a LiDAR 602 (which may include, for example, a laser source 103) associated with and / or on the vehicle 620 can detect targets such as obstacles 621 on the road, such as potholes, bumps, or rocks, using one of the techniques described with respect to Figures 1-5. The hardware processor 153 can determine a driving action or maneuver for the vehicle 620 to pass over or avoid the obstacle 621. The driving action or maneuver for the vehicle 620 to be determined may be based on the size and location of the obstacle 621 and / or the predicted position of the vehicle 620 when it passes over the obstacle 621. In some examples, the hardware processor 153 may determine that the obstacle 621 is too large and / or too dangerous for the vehicle 620 to pass over or go over without making a sharp turn. For example, the hardware processor 153 can predict that if vehicle 620 attempts to drive directly onto obstacle 621 without making a sharp turn, one or more wheels of vehicle 620 may strike obstacle 621, causing previously stationary obstacle 621 to roll into an adjacent lane or to the opposite side of the road, thereby increasing the risk to other vehicles in the adjacent lane or on the opposite side of the road. The hardware processor 153 can predict changes in the trajectories of other vehicles in the adjacent lane or on the opposite side of the road as a result of obstacle 621 rolling. The hardware processor 153 can further predict changes in the trajectory of vehicle 620 itself as a result of striking obstacle 621, such as changes in vehicle 620's speed, acceleration, attitude, orientation, and / or equilibrium. If the hardware processor 153 predicts that after hitting obstacle 621, the change in the trajectory of vehicle 620 will exceed an acceptable range, or that the change in the trajectory of another vehicle will exceed an acceptable range, the hardware processor 153 can determine that vehicle 620 should make a sharp turn to avoid obstacle 621. The hardware processor 153 can adjust the trajectory of vehicle 620 to avoid obstacle 621.The hardware processor 153 can select from possible trajectories 623, 624, 625, 626, 627, and 628. Possible trajectories 623, 624, 625, 626, 627, and 628 can be based on historical data of previous trajectories under similar conditions, determined by obstacle size, traffic density, road conditions, lighting conditions, and / or weather conditions. For example, possible trajectories 623, 624, 625, 626, 627, and 628 can be determined based on the recent driving history of the vehicle 620. Possible trajectories 623, 624, 625, 626, 627, and 628 can be, for example, recent actual trajectories with the best safety metric over the past year, month, or week. The hardware processor 153 can select a trajectory 628 based on the predicted adverse effects on the trajectory 628, on the trajectory of the obstacle 621, and on other nearby vehicles that may be adversely affected by the obstacle 621. For example, the hardware processor 153 can predict that vehicle 620 will not hit the obstacle 621 while following the trajectory 628, and therefore the obstacle 621 will remain stationary without changing its trajectory. The hardware processor 153 can then navigate or operate vehicle 620 to pass the obstacle 621 along the trajectory 628. After following the trajectory 628, the hardware processor 153 can determine the actual effects on the trajectory 628, the trajectory of the obstacle 621, and the trajectories of nearby vehicles. Therefore, if the hardware processor 153 determines that vehicle 620 will actually hit obstacle 621 while following trajectory 628, the hardware processor 153 can update or adjust the predicted impact on trajectory 628, on the trajectory of obstacle 621, and on other nearby vehicles. The predicted impact can be stored in the model. Updating or adjusting the predicted impact can involve updating the model. As a result, the updated or adjusted predicted impact of the updated or adjusted model can be used in subsequent situations to show that possible trajectories will place a greater distance between vehicle 620 and obstacle 621.

[0022] In Figure 7, a hardware processor (e.g., hardware processor 153) associated with the LiDAR 702 of vehicle 740 (which may include, for example, a laser source 103) can sense other vehicles 742, 744, 746, and 748 in a given environment using any of the techniques described above in Figures 1-5. The hardware processor 153 can determine a driving action or operation for vehicle 740 based on the other vehicles 742, 744, 746, and 748, for example, while vehicle 740 is about to turn left. The determined driving action or operation for vehicle 740 may also be based on the size and position of vehicles 742, 744, 746, and 748. The hardware processor 153 can predict the trajectories 743, 745, 747, and 749 of the other vehicles 742, 744, 746, and 748, respectively, based on the determined direction of motion and velocity of those vehicles, as a result of vehicle 740 following its chosen trajectory 741, and can predict any changes in those trajectories 743, 745, 747, and 749 in the meantime. The hardware processor 153 can further predict any changes in vehicle 740's own chosen trajectory 741 resulting from its interaction with vehicles 742, 744, 746, and 748. If the hardware processor 153 predicts that a change in the trajectory of vehicle 740 itself will exceed an acceptable range, or that a change from one or more of the predicted trajectories 743, 745, 747, and 749 will exceed an acceptable range, the hardware processor 153 can update the selected trajectory 741 or select another trajectory so that the changes that fall outside the acceptable range are within an acceptable range. For example, the hardware processor 153 can predict that while vehicle 740 follows trajectory 741, vehicle 740 will maintain at least a predetermined distance from each of the predicted trajectories 743, 745, 747, and 749 without causing any of vehicles 742, 744, 746, and 748 to decelerate by more than an acceptable amount, or to deviate from each of the predicted trajectories 743, 745, 747, and 749.After following trajectory 741, the hardware processor 153 can determine the actual changes or effects on the selected trajectory 741 and on the predicted trajectories 743, 745, 747, and 749. If the hardware processor 153 determines that at least one of the actual trajectories of vehicles 742, 744, 746, and / or 748 deviated from the predicted trajectories 743, 745, 747, and 749, or that at least one of vehicles 742, 744, 746, and 748 reduced its respective speed by a greater amount than acceptable, the hardware processor 153 can update or adjust the predicted trajectories 743, 745, 747, and 749, or the predicted effects on the predicted trajectories 743, 745, 747, and 749. The predicted trajectories 743, 745, 747, and 749 can be stored in the model. Updating or adjusting the predicted trajectories 743, 745, 747, and 749, or the predicted effects on the predicted trajectories 743, 745, 747, and 749, can involve updating the model. For example, if the hardware processor 153 determines that trajectory 741 is too close to one of the predicted trajectories, such as predicted trajectory 743, and therefore vehicle 742 must make a sharp turn, the result of this interaction can be stored in the model. The model can then be updated so that the next time, the selected trajectory does not get too close to one of the predicted trajectories. As a result, using the updated or adjusted predicted effects of the updated or adjusted model, possible trajectories in subsequent interactions can be placed further away from vehicle 740 and the predicted trajectory.

[0023] In Figure 8, as vehicle 860 approaches parking lot 863, the vehicle 860's computer system (e.g., including computer system 152 and hardware processor 153) and the vehicle 860's associated LiDAR 802 (e.g., which may include laser source 103) can sense other vehicles and the surrounding environment using any of the techniques described above in Figures 1-5. In some examples, the entrance to parking lot 863 may not include a clear lane divider to separate vehicles entering parking lot 863 from vehicles leaving parking lot 863, such as vehicle 864. In such examples, the hardware processor 153 may, based on the detected vehicle 864, select a trajectory, such as trajectory 861, that vehicle 860 should follow when entering parking lot 863. For example, trajectory 861 is set to a point one-quarter of the way from the entrance on one side of the entrance (e.g., the right side) and three-quarters of the way from the entrance on the opposite side (e.g., the left side), thereby leaving sufficient spatial clearance for a vehicle 864 to exit parking lot 863 simultaneously from the opposite side. The hardware processor 153 can determine the driving behavior or operation of vehicle 860 in consideration of vehicle 864. The determined driving behavior or operation of vehicle 860 may be based on the size and position of vehicle 864. The hardware processor 153 can predict trajectory 862 and predict changes in trajectory 862 as a result of vehicle 860 following the selected trajectory 861. The hardware processor 153 can further predict changes in the vehicle 860's own selected trajectory 861 resulting from its interaction with vehicle 864. If the hardware processor 153 predicts that the change in the vehicle 860's trajectory will exceed an acceptable range, or that the change from the predicted trajectory 862 will exceed an acceptable range, the hardware processor 153 may update the selected trajectory 861 or select a different trajectory so that the change that falls outside the acceptable range falls within the acceptable range.For example, the hardware processor 153 can predict that while vehicle 860 follows trajectory 861, vehicle 864 will maintain at least a predetermined distance from the predicted trajectory 862 without decelerating by more than an acceptable amount or deviating from the predicted trajectory 862. After following trajectory 861, the hardware processor 153 can determine the actual changes or effects on trajectory 861 and the actual changes or effects of vehicle 864 on the predicted trajectory 862. If the hardware processor 153 determines that the actual trajectory of vehicle 864 deviated from the predicted trajectory 862, or that vehicle 864 reduced its speed by more than an acceptable amount, the hardware processor 153 can update or adjust the predicted trajectory 862, or update or adjust the effects on the predicted trajectory 862 that are predicted as a result of vehicle 860 following trajectory 861. The predicted trajectory 862 can be stored in the model. Updating the predicted trajectory 862 and the predicted effects on that trajectory 862 can include updating the model. For example, if the hardware processor 153 determines that trajectory 861 is too close to the predicted trajectory 862, causing vehicle 864 to actually make a sharp turn to avoid vehicle 860, the result of this interaction can be stored in the model. The model can then be updated so that the trajectory chosen by vehicle 860 is not too close to the predicted trajectory the next time. As a result, using the updated or adjusted predicted effects of the updated or adjusted model, possible trajectories in subsequent interactions can be placed further away from vehicle 860 and the predicted trajectory.

[0024] In Figure 9, as vehicle 970 enters the parking lot between vehicles 972 and 973 while maintaining at least a predetermined distance from vehicle 974, the computer system of vehicle 970 (e.g., including computer system 152 and hardware processor 153) and associated LiDAR 902 (e.g., which may include laser source 103) can sense other vehicles and the surrounding conditions, such that vehicle 974 may be currently in motion and may also be attempting to enter the same parking lot. The hardware processor 153 can sense, detect, or acquire vehicle 974 using any of the techniques described above in Figures 1-5. Based on the relative positions of vehicles 970 and 974, including vehicle 974's speed, acceleration, and attitude, and the predicted trajectory of vehicle 974, the hardware processor 153 can determine whether it will be competing with other vehicles like vehicle 974 for a common parking space. If the hardware processor 153 determines that it should attempt to acquire that parking space, it can select a trajectory 971. If vehicle 970 fails to secure a parking space, or if the distance between vehicle 970 and vehicle 974 falls below a threshold distance while both vehicle 970 and vehicle 974 are attempting to secure the same parking space, the hardware processor 153 can store the data and results of the interaction between vehicle 971 and vehicle 974 in the model, thereby enabling vehicle 970 to improve its decision-making process in similar future situations when vehicle 970 is attempting to enter a parking space.

[0025] In Figure 10, vehicle 1010 may be traveling in lane 1030 according to a selected trajectory 1012. Another vehicle 1020, which may be an AV (autonomous vehicle), may be traveling in lane 1040 to the left of vehicle 1010. The computer system of vehicle 1010 (e.g., including computer system 152 and hardware processor 153) and associated LiDAR 1002 (e.g., which may include laser source 103) can sense the other vehicle and the surrounding conditions of vehicle 1010 to determine and / or perform navigation actions. The other vehicle 1020 may signal to vehicle 1010 that it intends to pass or overtake vehicle 1010 and merge into lane 1030. Vehicle 1010 may detect and recognize, by one or more hardware processors (e.g., hardware processor 153), that the other vehicle 1020 intends to merge into lane 1030. The sensing, detection, and / or acquisition of other vehicles 1020 and their intention to merge can be carried out by any of the techniques described above in Figures 1-5. The hardware processor 153 can determine whether or not to allow other vehicles 1020 to merge into lane 1030. This decision may include predicting the trajectory 1028 of other vehicles 1020 as a result of vehicle 1010 allowing other vehicles 1220 to merge into lane 1030, and predicting changes in the selected trajectory 1012 of vehicle 1010. For example, if the predicted changes in the selected trajectory 1012 exceed an acceptable amount, the hardware processor 153 may not allow other vehicles 1020 to merge into lane 1030. For example, the predicted changes in the selected trajectory 1012 may include a predicted decrease in the speed of vehicle 1010. If vehicle 1010 allows another vehicle 1020 to merge into lane 1030, the hardware processor 153 can determine the actual change in the selected trajectory 1012 caused by the merging of the other vehicle 1020, and can determine the actual trajectory of the other vehicle 1020 while it is merging.If the actual change in the selected trajectory 1012 deviates by a threshold amount from the predicted change in the selected trajectory 1012, if the actual change in the selected trajectory 1012 exceeds an acceptable amount, or if the actual trajectory of another vehicle 1020 merging deviates from the predicted trajectory 1028, the hardware processor 153 can update or adjust the predicted trajectory 1028, or update or adjust the predicted impact on the selected trajectory 1012 as a result of the vehicle 1010 following trajectory 1012. The predicted trajectory 1028 and the predicted impact on the selected trajectory 1012 can be stored in the model. Updating or adjusting the predicted trajectory 1028 and the predicted impact on the selected trajectory 1012 may involve updating the model. For example, if the processor 153 determines that another vehicle 1020 is following its actual trajectory 1029, and therefore vehicle 1010 must decelerate more than an acceptable amount to maintain a predetermined distance from the other vehicle 1020, the result of this interaction can be stored in the model. The model can then be updated so that the next time, vehicle 1010 is less likely to allow the other vehicle to merge into lane 1030. Similarly, when vehicle 1010 transmits the model update to other vehicles in its fleet or network, the other vehicles can also adjust their own behavior, making it less likely that the other vehicles will attempt to merge in such situations.

[0026] In Figure 11, vehicle 1110 may be traveling in lane 1180 according to a selected trajectory 1112. The vehicle's computer system (e.g., including computer system 152 and hardware processor 153) and associated LiDAR 1102 (e.g., which may include laser source 103) can sense other vehicles and the environment surrounding vehicle 1110 to determine and / or perform navigation operations. Another vehicle 1120, which may be an AV, may be traveling in lane 1190 to the left of vehicle 1110. The other vehicle 1120 may suddenly attempt to merge into lane 1180 without adequately signaling to vehicle 1110 that it intends to pass or overtake vehicle 1110 and merge into lane 1180. Vehicle 1110 can detect and recognize, by its hardware processor 153, that the other vehicle 1120 intends to merge into lane 1180. The hardware processor 153 can detect, capture, or sense the other vehicle 1120 and its attempt or intention to merge by any of the techniques described above in Figures 1-5, predict the trajectory of the other vehicle 1120, and / or infer or predict any point where the other vehicle intends to merge into lane 1180. The hardware processor 153 can decide whether to allow the other vehicle 1120 to merge into lane 1180 by decelerating or accelerating to move ahead of the other vehicle 1120. This decision may include predicting the trajectory 1128 of the other vehicle 1120 and predicting changes in the selected trajectory 1112 of vehicle 1110 as a result of vehicle 1110 allowing the other vehicle 1120 to merge into lane 1180, or as a result of vehicle 1110 accelerating. For example, if allowing another vehicle 1120 to merge into lane 1180 would result in a predicted change in the selected trajectory 1112 exceeding an acceptable amount, the hardware processor 153 may decide not to allow the other vehicle 1120 to merge into lane 1180. For example, the predicted change in the selected trajectory 1112 could include a predicted decrease in the speed of vehicle 1110.If vehicle 1110 allows another vehicle 1120 to merge into lane 1180, the hardware processor 153 can determine the actual change in the selected trajectory 1112 resulting from the merging of the other vehicle 1120, and can determine the actual trajectory of the other vehicle 1120 during the merging. If the actual change in the selected trajectory 1112 deviates by a threshold amount from the predicted change in the selected trajectory 1112, if the actual change in the selected trajectory 1112 exceeds an acceptable amount, or if the actual trajectory of the other vehicle 1120 during the merging deviates from the predicted trajectory 1128, the hardware processor 153 can update or adjust the predicted trajectory 1128, or update or adjust the predicted impact on the selected trajectory 1112 as a result of vehicle 1110 following the trajectory 1112. The predicted trajectory 1128 and the predicted impact on the selected trajectory 1112 can be stored in the model. Updating or adjusting the predicted trajectory 1128 and the predicted impact on the selected trajectory 1112 can include updating the model. For example, if another vehicle 1120 follows its actual trajectory 1129, and as a result vehicle 1110 must decelerate more than an acceptable amount to maintain a predetermined distance from the other vehicle 1120, the result of this interaction can be stored in the model. The model can then be updated so that vehicle 1110 will next allow the other vehicle to merge into lane 1180, and as a result, vehicle 1110 will be less likely to instead move in front of another vehicle attempting to merge into a lane without signaling. Similarly, when vehicle 1110 transmits the model update to other vehicles in its fleet or network, the other vehicles can also adjust their own behavior, making it less likely that the other vehicles will attempt to merge in such situations.

[0027] In Figure 12, vehicle 1210 may be traveling within lane 1280. Vehicle 1210, via its hardware processor 153, can detect and recognize one or more pedestrians 1240 intending to cross the street using any of the techniques described above in Figures 1-5. The vehicle's hardware processor 153 and associated LiDAR 1202 (which may include, for example, a laser source 103) can sense other vehicles and the surrounding environment of vehicle 1210 to determine and / or perform navigation actions. Vehicle 1210 can individually and / or collectively determine or predict the direction and speed of movement of pedestrians 1240, predict the trajectory of pedestrians 1240 based on the direction or speed, and predict the delay time resulting from yielding to pedestrians 1240. After pedestrians 1240 have finished crossing the street, the hardware processor 153 can determine the actual delay time resulting from yielding to pedestrians 1240. If the actual delay time deviates significantly from the predicted delay time by a threshold amount, the hardware processor 153 can take this deviation (magnitude of the deviation) into account, update the predicted delay time, and include the updated predicted delay time in future measurements.

[0028] Figure 13 shows one of the methods described in Figures 1 to 12 above.

[0029] In step 1306, a laser source (such as a LiDAR 102) can generate an optical signal, which may include a light signal.

[0030] In step 1308, a splitter (e.g., splitter 203) can split the optical signal into a first signal and a second signal, which are then transmitted along separate paths (e.g., a first path and a second path). The first path can pass through modulator 204, and the second path can pass through modulator 206. In step 1310, modulator 204 can modulate the first signal, while modulator 206 can modulate the second signal. Modulator 204 can modulate the first signal using a first modulation signal, such as a frequency-modulated continuous wave (FMCW) signal generated by processor 212. Similarly, modulator 206 can modulate the second signal using a second modulation signal, such as an FMCW signal generated by processor 212.

[0031] In step 1312, the first signal can be scanned by the scanner 208 after being modulated by the modulator 204. Meanwhile, the second signal can be transmitted directly to the coupler 209 without passing through the scanner 208, after being modulated by the modulator 206. The second signal can be delayed by a fixed delay time relative to the return light signal as a reference beat frequency signal. In step 1314, the coupler 209 can couple the modulated second signal with the modulated and scanned first signal. The received signal and other modulated signals can be transmitted together into the coupler 209 and sent to the detector 210, where the detector 210 can detect the reference beat frequency signal.

[0032] In step 1316, the detector 210 can detect an attribute corresponding to the signal obtained by combining the modulated second signal and the modulated first signal, such as the beat frequency. In step 1318, the detector 210 can acquire a target based on the modulated second signal and the modulated first signal. In particular, this dual-modulated signal can increase the integration time, which corresponds to the time range of the overlap between the modulated second signal and the modulated first signal. This acquired target can be further processed by, for example, the processor 212. For example, the navigation operation of a vehicle (e.g., vehicle 106) can be determined based on this acquired target, and the scenario is shown in Figures 6-12.

[0033] Hardware implementation The technologies described herein are implemented by one or more dedicated computer systems. These dedicated computer systems may be hardwired (wired logic) circuits for implementing these technologies, or may include one or more application-specific integrated circuits (ASICs) or field-programmable gate arrays (FPGAs) or other circuits or digital electronic devices permanently programmed to implement these technologies, or may include one or more hardware processors programmed to implement these technologies according to program instructions in firmware, memory, other storage devices, or a combination thereof. Such dedicated computer systems may also implement the technologies by combining custom hardwired logic circuits, ASICs, or FPGAs with custom programming. These dedicated computer systems may be desktop computer systems, server computer systems, portable computer systems, handheld devices, network devices, or other devices or combinations of devices incorporating hardwired and / or programmable logic circuits for implementing the technologies.

[0034] Computer devices are generally controlled and coordinated by operating system software. The operating system, in particular, controls and schedules computer processes for execution, manages memory, provides file systems, network configuration, I / O (input / output) services, and offers user interface functions such as a graphical user interface (GUI).

[0035] Figure 14 is a block diagram showing computer system 1400, on which any of the embodiments described herein can be implemented. In some examples, computer system 1400 may include a cloud-based computer system or a remote computer system. For example, computer system 1400 may include a group of machines organized as a parallel processing infrastructure. Computer system 1400 includes a bus 1402 or other communication mechanism for transmitting information, and one or more hardware processors 1404 coupled to the bus 1402 for processing information. The hardware processors 1404 may be, for example, one or more general-purpose microprocessors.

[0036] The computer system 1400 is coupled to the bus 1402 and includes main memory such as random access memory (RAM) for storing information and instructions executed by the processor 1404, as well as a cache and / or other dynamic storage devices. The main memory 1406 can also be used to store temporary variables or other intermediate information while instructions are being executed by the processor 1404. Once these instructions are stored in a storage medium accessible to the processor 1404, the computer system 1400 becomes a dedicated machine customized to perform the actions specified in the instructions.

[0037] The computer system 1400 further includes a read-only memory (ROM) 1408 or other static storage device, which is coupled to the bus 1402 to store static information and instructions for the processor 1404. A storage device 1410, such as a magnetic disk, optical disk, USB (universal serial bus) thumb drive (flash drive), is provided and is coupled to the bus 1402 to store information and instructions.

[0038] The computer system 1400 can be coupled via bus 1402 to a display 1412, such as a cathode ray tube (CRT) or liquid crystal display (LCD) display (or touchscreen), for displaying information to the computer user. An input device 1414, including alphanumeric and other keys, is coupled to bus 1402 to transmit information and command selections to the processor 1404. Another type of user input device is a cursor control device 1416, such as a mouse, trackball, or cursor pointer keys, which transmits information and command selections to the processor 1404 and controls cursor movement on the display 1412. This input device generally has two axes, i.e., two degrees of freedom, namely a first axis (e.g., x) and a second axis (e.g., y), and the two degrees of freedom allow the device to specify a position in a plane. In some embodiments, the same pointer information and command selection as cursor control can be achieved by receiving touches on a touchscreen without a cursor.

[0039] The computer system 1400 may include a user interface module for implementing a GUI, which can be stored in a mass storage device as executable software code executed by the computer device. This module and other modules may include components such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables, as examples.

[0040] Generally, as used herein, “includes” refers to a logic circuit embedded in hardware or firmware, or, in some cases, a set of software instructions having entry and exit points, written in a programming language such as Java®, C, or C++. Software modules can be compiled and linked into an executable program and installed in the form of a dynamic-link library, or they can be written in an interpreted programming language such as BASIC, Perl, or Python. It is understood that software modules can be called from other modules or from themselves, and / or can be invoked in response to detected events or interrupts. Software modules configured for execution on a computer device can be provided on a computer-readable medium such as a compact disk, digital video disk, flash drive, magnetic disk, or any other tangible medium, or they can be provided as a digital download (originally stored in a compressed or installable format, such formats requiring installation, decompression, or decryption before execution). Such software code can be stored, partially or entirely, on the memory device of the computer device for execution by the computer device. Software instructions can be embedded in firmware such as EPROM (erasable programmable ROM). It is further understood that hardware modules can consist of connected logic units such as gates and flip-flops, and / or programmable units such as programmable gate arrays or processors. Modules or computer devices functionally described herein are preferably implemented as software modules, but can be represented in the form of hardware or firmware.In general, the modules described herein can be combined with other modules or divided into submodules, regardless of their physical organization or storage location.

[0041] The computer system 1400 can implement the techniques described herein using customized hardwired logic circuits, one or more ASICs or FPGAs, firmware and / or programmable logic circuits, the firmware and / or programmable logic circuits, in combination with the computer system, make the computer system 1400 a dedicated machine or program it to be a dedicated machine. According to one embodiment, the techniques described herein are executed by the computer system 1400 in response to the processor 1404 executing one or more sequences of one or more instructions contained in the main memory 1406. These instructions can be read into the main memory 1406 from other storage media such as the storage device 1410. The execution of the sequence of instructions contained in the main memory 1406 causes the processor 1404 to perform the processing steps described herein. In alternative embodiments, hardwired circuits can be used instead of or in combination with software instructions.

[0042] As used herein, “non-temporary media” and similar terms refer to any media that stores data and / or instructions that cause a machine to operate in a particular manner. Such non-temporary media may include non-volatile media and volatile media. Non-volatile media include, for example, optical or magnetic disks such as storage device 1410. Volatile media include dynamic memory such as main memory 1406. Common forms of non-volatile media include, for example, floppy disks, flexible disks, hard disks, semiconductor (solid-state) drives, magnetic tapes, or any other magnetic data storage media, CD-ROMs (compact disc ROMs), any other optical data storage media, any physical media having a pattern of holes, RAM, PROMs (programmable ROMs), and EPROMs, flash EPROMs, NVRAMs (non-volatile RAMs), any other memory chips or cartridges, and network versions thereof.

[0043] Non-transient media are distinct from transmission media, but can be used together with them. Transmission media are involved in transferring information between non-transient media. For example, transmission media include coaxial cables, copper wires, and optical fibers, which include the wiring that constitutes bus 1402. Transmission media can also take the form of sound waves or light waves, such as those generated during radio and infrared data communications.

[0044] Various forms of media can be involved in transporting one or more sequences of one or more instructions to the processor 1404 for execution. For example, these instructions can initially be carried on a magnetic disk or semiconductor drive of a remote computer. The remote computer can load these instructions into its dynamic memory and transmit them over a telephone line using a modem. A modem locally connected to computer system 1400 can receive the data over the telephone line and convert the data into an infrared signal using an infrared transmitter. An infrared detector can receive the data being transported in the form of an infrared signal, and appropriate circuitry can output this data onto bus 1402. Bus 1402 transports this data to main memory 1406, from which the processor 1404 can read and execute the instructions. The instructions received by main memory 1406 can be read and executed. The instructions received by main memory 1406 can optionally be stored on storage device 1410 either before or after execution by processor 1404.

[0045] The computer system 1400 also includes a communication interface 1418 coupled to bus 1402. The communication interface 1418 provides bidirectional data communication coupling to one or more network links connected to one or more local networks. For example, the communication interface 1418 may be an integrated service digital network (ISDN) card, a cable modem, a satellite modem, or a modem that provides data communication connectivity to a corresponding type of telephone line. As another example, the communication interface 1418 may be a LAN card (or a WAN component for communicating with a wide area network (WAN)) that provides data communication to a compatible local area network (LAN). A wireless link can also be implemented. In any such implementation, the communication interface 1418 transmits and receives electrical, electromagnetic, or optical signals that carry data streams (data flows) representing various types of information.

[0046] A network link generally provides data communication to other data devices through one or more networks. For example, a network link can provide connection to a host computer through a local network, or to data devices operated by an Internet Service Provider (ISP). ISPs similarly provide data communication services through the worldwide packet data communication network, now commonly referred to as the "Internet." Both local networks and the Internet use electrical, electromagnetic, or optical signals to carry digital data streams. Signals carrying digital data to and from computer system 1400, through various networks, and signals on network links and through communication interface 1418 are examples of forms of transmission media.

[0047] The computer system 1400 can send messages and receive data, including program code, through the network, network links, and communication interface 1418. In the case of the internet, a server can send code required by an application program through the internet, ISP, local network, and communication interface 1418.

[0048] The received code can be executed by the processor 1404 upon receipt, and / or stored in the memory device 1410 or other non-volatile memory device for later execution.

[0049] The processes, methods, and algorithms described in the preceding sections can be embodied in the form of code modules executed by one or more computer systems or computer processors equipped with computer hardware, and these code modules can be automated in whole or in part. These processes and algorithms can be implemented in part or in whole within application-specific circuits.

[0050] The various features and processes described above can be used independently of each other or combined in various ways. All possible combinations and subcombinations are intended to fall within the scope of the present invention. In addition, certain blocks of methods or processes can be omitted in some implementations. Furthermore, the methods and processes described herein are not limited to any particular order, and blocks and associated states can be executed in any other order as appropriate. For example, the described blocks or states can be executed in an order other than that specifically disclosed, or multiple blocks or states can be combined into a single block or state. Examples of blocks or states can be executed serially, in parallel, or in any other manner. Blocks or states can be added to or removed from the disclosed embodiments. Examples of systems and components described herein can be configured differently from those described. For example, elements can be added, removed, or rearranged compared to the disclosed embodiments.

[0051] Conditional language, in particular, such as "may," "may," "may," or "may," is generally intended to convey that a particular embodiment includes certain features, elements, and / or steps, but does not include other embodiments, unless otherwise specifically stated or understood in the context in which it is used. Therefore, such conditional language is generally not intended to implicitly mean that features, elements, and / or steps are required to some extent in one or more embodiments, or that one or more embodiments necessarily include logic for determining whether these features, elements, and / or steps are included in or performed in any particular embodiment, with or without user input or input facilitation.

[0052] Any process description, element, or block described herein and / or illustrated in any accompanying drawings should be understood to represent one or more parts of a module, segment, or code containing one or more executable instructions for implementing a particular logical function or step in the process. It will be understood by those skilled in the art that alternative implementations are included within the scope of the embodiments described herein, and that in these alternative implementations, elements or functions may be removed, and the order in which they are illustrated or described may be changed, including, depending on the function in question, almost simultaneously or in reverse order.

[0053] It should be emphasized that numerous variations and modifications can be made to the embodiments described above, and the elements of these variations and modifications should be understood as being among other acceptable examples. All such modifications and variations are intended to be within the scope of the disclosure herein. The above description details specific embodiments of the invention. However, regardless of how the above is detailed and appears in the text, the invention can be carried out in numerous ways. As also explicitly stated above, it should be noted that the use of specific technical terms when describing specific features or aspects of the invention should not be interpreted as implicitly meaning that such technical terms are redefined herein to include all specific characteristics of such features or aspects of the invention related to such technical terms. Accordingly, the scope of the invention should be interpreted by the appended claims and all their equivalents.

[0054] Wording Throughout this specification, multiple examples can realize components, operations, or structures described as single examples. While individual operations of one or more methods are illustrated and described as separate operations, one or more of these individual operations can be performed simultaneously, and nothing requires them to be performed in the order illustrated. Structures and functions presented as separate components in the examples can be realized as combined structures or components. Similarly, structures and functions presented as single components can be realized as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter of this specification.

[0055] While the outline of the subject matter has been described with reference to specific embodiments, various modifications and changes can be made to these embodiments without departing from the broader range of embodiments of the invention. Such embodiments of the subject matter may be referred to individually or collectively in this specification by the term “invention” for mere convenience, and where two or more are actually disclosed, the scope of this application is not intended to be spontaneously limited to any single disclosure or concept.

[0056] The embodiments illustrated herein are described in sufficient detail to enable those skilled in the art to implement the disclosed teachings. Other embodiments can be used and derived from these embodiments to make structural and logical substitutions and modifications without departing from the scope of the invention. Accordingly, the detailed description should not be interpreted as restrictive, and the scope of the various embodiments is defined solely by the appended claims and, together with them, the entire scope of the equivalents to which such claims are qualified.

[0057] It is understood that “logic circuits,” “systems,” “data storage devices,” and / or “databases” may include software, hardware, firmware, and / or circuits. In one example, one or more software programs containing instructions that can be made executable by a processor may perform one or more of the functions of the data storage devices, databases, or systems described herein. In other examples, circuits may perform the same or similar functions. Alternative embodiments may comprise more, fewer, or functionally equivalent systems, data storage devices, or databases, which still fall within the scope of embodiments of the present invention. For example, these various systems, data storage devices, and / or databases may be combined or divided in different ways.

[0058] In this specification, “open source” software is defined as source code that is available for distribution as source code and in compiled form, with permission to modify and derive work at will, using means of obtaining the fully publicly available and indexed source.

[0059] The data storage devices described herein can be any suitable structure (e.g., active databases, relational databases, self-referencing databases, tables, matrices, arrays, flat files, document-oriented storage systems, non-relational NoSQL (Not only Structured Query Language) systems, etc.) and can be cloud-based or otherwise.

[0060] The term "or" as used herein should be interpreted either in an inclusive or exclusive sense. Furthermore, multiple examples may be provided for resources, operations, or structures described as a single example herein. In addition, the boundaries between various resources, operations, and data storage devices are somewhat arbitrary, and specific operations are illustrated in relation to specific exemplary configurations. Other functional assignments are conceivable and may fall within the scope of various embodiments of the present invention. In general, structures and functions presented as separate resources in these example configurations can be realized as combined structures or resources. Similarly, structures and functions presented as single resources can be realized as separate resources. These and other variations, modifications, additions, and improvements fall within the scope of embodiments of the present invention as expressed by the appended claims. Accordingly, this specification and the drawings should be considered illustrative rather than restrictive.

[0061] While the present invention has been described in detail for illustrative purposes based on what is currently considered the most practical and suitable implementation, it should be understood that these details are for illustrative purposes only, and that the present invention is not limited to the disclosed implementations, but rather intended to cover modifications and equivalent configurations that fall within the spirit and scope of the appended claims. For example, it should be understood that the present invention aims to allow, to the extent possible, one or more features of any drawing or example to be combined with one or more features of any other drawing or example. Component implemented as another component can be interpreted as operating in the same or similar manner as and / or possessing the same or similar features, characteristics, and parameters as the other component.

[0062] Phrases such as "at least one of...", "at least one selected from the group of...", or "at least one selected from the group consisting of..." should be interpreted disjunctly (for example, not as "at least one of A and at least one of B").

[0063] Throughout this specification, any reference to “(one) example” or “(more) examples” means that a particular feature, structure, or characteristic described in relation to that example is included in at least one example of the present invention. Therefore, throughout this specification, the phrases “in one example” or “in some examples” appearing in various places do not necessarily all refer to the same example, but may refer to several examples. Furthermore, a particular feature, structure, or characteristic may be combined in any suitable manner in one or more different examples.

Claims

1. A laser source configured to generate an optical signal, A splitter configured to divide the optical signal into a first signal and a second signal, A first modulator configured to modulate the first signal, A second modulator configured to modulate the second signal, Following modulation by the first modulator, a scanner scans the first signal, Following the scanning of the first signal, a coupler is provided to connect the modulated second signal and the modulated first signal. A detector configured to detect attributes corresponding to a signal obtained by combining the modulated second signal and the modulated first signal, and to capture a target based on the signal obtained by combining the modulated second signal and the modulated first signal, A system equipped with [that feature].

2. The system according to claim 1, further comprising a processor which generates a first frequency-modulated continuous wave (FMCW) signal and a second FMCW signal, respectively, for modulating the first signal and the second signal.

3. The system according to claim 2, wherein the processor processes the captured target and determines and executes a navigation operation based on the processed target.

4. The system according to claim 3, wherein the navigation operation includes an action of yielding the right of way, an action of making a sudden turn, or an action of turning around.

5. The system according to claim 2, wherein the second FMCW signal has a delay relative to the first FMCW signal, and the processor controls the magnitude of the delay.

6. The system according to claim 5, wherein the processor controls the magnitude of the delay based on the distance from the processor to the target.

7. The system according to claim 5, wherein the processor controls the magnitude of the delay to increase in response to a smaller distance from the processor to the target.

8. The system according to claim 2, wherein the second FMCW signal includes a reference beat signal, the reference beat signal generates a beat with the signal reflected from the target.

9. The system according to claim 1, further comprising a first digital-to-analog converter (DAC) for controlling the first modulator and a second DAC for controlling the second modulator.

10. The system according to claim 9, further comprising a field-programmable gate array (FPGA) for controlling the first DAC and the second DAC.

11. The steps of generating an optical signal and The steps include dividing the optical signal into a first signal and a second signal, The steps include modulating the first signal and The steps include modulating the second signal and The steps include: Modulation by the first modulator followed by scanning the first signal; The steps include: following the modulation of the first signal, coupling the modulated second signal with the modulated first signal; The steps include detecting an attribute corresponding to a signal obtained by combining the modulated second signal and the modulated first signal, A step of capturing a target based on a signal obtained by combining the modulated second signal and the modulated first signal. A method that includes this.

12. The method according to claim 11, further comprising the step of generating a first frequency-modulated continuous wave (FMCW) signal and a second FMCW signal, respectively, for modulating the first signal and the second signal.

13. The steps include processing the captured target, The steps include determining and executing a navigation operation based on the processed target, and The method according to claim 12, further comprising:

14. The method according to claim 13, wherein the navigation operation includes an action of yielding the right of way, an action of making a sharp turn, or an action of turning around.

15. The method according to claim 12, further comprising the step of controlling the magnitude of the delay of the second FMCW signal with respect to the first FMCW signal.

16. The method according to claim 15, further comprising the step of controlling the magnitude of the delay based on the distance from the processor to the target.

17. The method according to claim 15, further comprising the step of controlling the magnitude of the delay to increase in response to a smaller distance from the processor to the target.

18. The method according to claim 12, wherein the second FMCW signal includes a reference beat signal, and the reference beat signal generates a beat with the signal reflected from the target.

19. The method according to claim 12, further comprising the steps of controlling the first modulator using a first digital-to-analog converter (DAC) and controlling the second modulator using a second DAC.

20. The method according to claim 19, further comprising the step of controlling the first DAC and the second DAC using a field-programmable gate array (FPGA).

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