LIDAR device

Abstract

To suppress the decline in measurement sensitivity and measurement accuracy in a LIDAR device.SOLUTION: A LIDAR device 100 includes: a transmitting unit 10 that transmits a transmission wave; a scanning unit 20 that scans the transmission wave; a receiving unit 30 that receives a reflected wave; a data converting unit 40 that converts the reflected wave into sampling data; a data holding unit 51 that holds the sampling data; frequency analyzing units 52, 53, and 54 that perform frequency analysis and acquire ranging point data; and a point cloud generating unit 55 that generates a point cloud consisting of a plurality of ranging points indicated by ranging point data acquired using results of frequency analysis targeted for a first analysis target data set, and a point cloud consisting of a plurality of ranging points indicated by ranging point data acquired using results of frequency analysis targeted for a second analysis target data set.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to LIDAR devices. [Background technology]

[0002] Conventionally, there is a technology that measures the distance to a measured object by transmitting a continuous wave that modulates over time and utilizing the phase difference between the transmitted continuous wave and the wave reflected from the measured object. The distance measuring system described in Patent Document 1 suppresses a decrease in measurement efficiency by changing the resolution according to the distance to the measured object. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2020-501130 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the distance measurement system described in Patent Document 1 may not be able to detect the object when the S / N ratio is low, such as when the object is far away or when the reflectivity of the object is low. Furthermore, if the measurement time is extended to detect the object in such a situation, the resolution decreases, which causes a problem in that the position of the object cannot be identified with high accuracy. [Means for solving the problem]

[0005] The present disclosure can be realized in the following forms.

[0006] According to one aspect of the present disclosure, there is provided a LIDAR device (100), comprising: At least one of transmitting two types of transmission waves in parallel, one being a transmission wave whose frequency is modulated to increase over time and the other being a transmission wave whose frequency is modulated to decrease over time, and transmitting a transmission wave whose frequency and amplitude are modulated over time is carried out.a transmitting unit (10), a scanning unit (20) that scans the transmitted wave within a range of a preset scanning angle, a receiving unit (30) that receives a reflected wave generated when the transmitted wave is reflected by an object, a data converting unit (40) that converts the reflected wave received within the range of the scanning angle into sampling data, a data holding unit (51) that holds the sampling data, and one or more first analysis target data sets obtained by reading the sampling data from the data holding unit for each first angle range that is equal to or less than the scanning angle, and a plurality of first analysis target data sets obtained by reading the sampling data for each second angle range that is smaller than the first angle. and a second analysis target data set, and using a result of the frequency analysis to acquire ranging point data including at least information on distances and directions of ranging points relative to the LIDAR device; and a point cloud generation unit (55) that generates a point cloud consisting of a plurality of ranging points indicated by the ranging point data acquired using a result of the frequency analysis targeting the first analysis target data set, and a point cloud consisting of a plurality of ranging points indicated by the ranging point data acquired using a result of the frequency analysis targeting the second analysis target data set. When the peak intensity of the reflected wave in the result of the frequency analysis targeting the first analysis target data set is equal to or greater than a preset threshold, the frequency analysis unit performs the frequency analysis targeting a plurality of third analysis target data sets obtained by reading out the sampling data for each range of a third angle smaller than the second angle, instead of the second analysis target data set, to acquire the range-finding point data. . With this type of LIDAR device, even objects with low S / N ratios can be detected with good sensitivity by frequency analysis of the first analysis target data set, and objects with high S / N ratios can be detected with good resolution by frequency analysis of the second analysis target data set, thereby suppressing a decrease in sensitivity and resolution in object detection.

[0007] The present disclosure may be realized in various forms, such as a vehicle equipped with a LIDAR device, an object detection method, a computer program for implementing the device and method, and a storage medium storing such a computer program. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is an explanatory diagram showing a schematic configuration of a LIDAR device according to an embodiment of the present invention. [Figure 2]FIG. 3 is an explanatory diagram showing the procedure of object detection processing according to the first embodiment. [Figure 3] FIG. 10 is an explanatory diagram showing the reading range of sampling data of each data set. [Figure 4] FIG. 10 is an explanatory diagram showing the procedure of a distance measurement point output process. [Figure 5] FIG. 10 is an explanatory diagram showing the procedure of an object detection process according to the second embodiment. [Figure 6] FIG. 10 is an explanatory diagram showing the procedure of an object detection process according to the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] A. First embodiment: A-1.Device configuration: The LIDAR device 100 of this embodiment emits laser light as a transmission wave and detects a reflected wave generated when the transmission wave is reflected by the object, thereby measuring the distance, direction, and relative speed of the object relative to the LIDAR device 100. The LIDAR device 100 of this embodiment is mounted on a vehicle and detects objects present around the vehicle, such as other vehicles, pedestrians, and buildings.

[0010] 1, the LIDAR device 100 includes a transmitter 10, a scanner 20, a receiver 30, a data converter 40, a processor 50, and a controller 60. The processor 50 includes a data holder 51, a plurality of frequency analyzers 52 to 54, and a point cloud generator 55.

[0011] The transmitter 10 generates and transmits transmission waves. In this embodiment, the transmitter 10 transmits two types of transmission waves in parallel: one whose frequency is modulated to increase over time, and the other whose frequency is modulated to decrease over time. By transmitting transmission waves in this manner, the position and velocity of a target object can be measured even if sampling data is extracted in any sampling interval. Furthermore, by driving the scanner 20, the scanner 20 can continuously transmit transmission waves within a predetermined scanning angle range.

[0012] The receiving unit 30 receives a reflected wave generated when the transmitted wave is reflected by an object present in the transmission direction of the transmitted wave. The data converting unit 40 acquires sampling data at a preset sampling frequency from a frequency difference signal between the reflected wave and the transmitted wave (hereinafter also referred to as a "beat signal"). The sampling frequency is set to be at least twice the maximum frequency that the beat signal can have, which is determined in advance by experiment or the like. The sampled data is stored in the data storage unit 51.

[0013] In a ranging point output process described later, the frequency analysis units 52 to 54 acquire ranging point data by using a frequency spectrum obtained by performing frequency analysis on the sampling data read from the data storage unit 51. In this embodiment, the frequency analysis unit 52 performs a fast Fourier transform (hereinafter also referred to as "FFT"). In this embodiment, the ranging point data includes at least information on the distance, direction, and relative speed of an object relative to the LIDAR device 100.

[0014] The point cloud generation unit 55 generates a point cloud by mapping multiple ranging points indicated by ranging point data obtained in ranging point output processing, which will be described later. The ranging points represent points at which the transmitted wave is reflected within the range of the scanning angle described above.

[0015] The control unit 60 is configured as a logic circuit centered on a microcomputer. More specifically, the control unit 60 includes a CPU that performs calculations according to a preset control program, a ROM that stores in advance control programs and control data necessary for the CPU to perform various calculation processes, a RAM that temporarily reads and writes various data necessary for the CPU to perform various calculation processes, and ports for inputting and outputting various signals. The control unit 60 controls the LIDAR device 100 in an object detection process, which will be described later.

[0016] A-2. Object detection processing: The LIDAR device 100 of this embodiment detects other vehicles, pedestrians, buildings, etc. that exist around the vehicle by executing the object detection process shown in Fig. 2. In step S100 of Fig. 2, the transmitter 10 transmits a transmission wave within a preset scanning angle range. The LIDAR device 100 repeatedly executes this step while the vehicle is traveling.

[0017] In parallel with step S100, when the receiving unit 30 receives reflected waves within a preset angle range within the scanning angle range, the data converting unit 40 converts the received reflected waves into sampling data (step S200). In this embodiment, when the LIDAR device 100 receives reflected waves within an angle range of 0.6°, it converts the received reflected waves into sampling data. The converted sampling data is stored in the data storing unit 51.

[0018] The LIDAR device 100 executes, in parallel, a ranging point output process (step S300) for dataset DS1, a ranging point output process (step S400) for dataset DS2, and a ranging point output process (step S500) for dataset DS3. Dataset DS1 is a dataset obtained by reading out sampling data for each preset first angle range. Dataset DS1 corresponds to the "first dataset to be analyzed" in this disclosure. Datasets DS2 and DS3 refer to datasets obtained by reading out sampling data for each preset second angle range that is smaller than the first angle. Datasets DS2 and DS3 correspond to the "second dataset to be analyzed" in this disclosure. In this embodiment, as shown in FIG. 3, the first angle is 0.6°, and corresponds to a dataset obtained by reading out all of the sampling data converted in step S200 of FIG. 2. In this embodiment, the second angle is 0.4°, and datasets DS2 and DS3 include data that belong to overlapping angle ranges.

[0019] In this embodiment, in ranging point output processing described later, the LIDAR device 100 performs frequency analysis on the data set DS1 in the frequency analysis unit 52, frequency analysis on the data set DS2 in the frequency analysis unit 53, and frequency analysis on the data set DS3 in the frequency analysis unit 54. The LIDAR device 100 performs similar processing in ranging point output processing on any of the data sets, and therefore, in the following explanation, the ranging point output processing on the data set DS1 shown in FIG. 4 will be described as an example.

[0020] In step S310, the LIDAR device 100 reads the data set DS1 into the frequency analysis unit 52.

[0021] In step S320, the frequency analysis unit 52 performs frequency analysis on the data set DS1 to acquire ranging point data. As described above, the frequency analysis unit 52 acquires ranging point data by using the frequency spectrum obtained by performing frequency analysis on the data set DS1. Note that the frequency analysis performed in this step is similar to the frequency analysis generally performed in FMCW ranging.

[0022] In step S330, the point cloud generation unit 55 outputs ranging points indicating ranging point data corresponding to the data set DS1. After this step is completed, the ranging point output process for the data set DS1 is completed.

[0023] 2, after completing the ranging point output process for all of the data sets DS1 to DS3, the LIDAR device 100 executes step S200 again. While the vehicle is traveling, the LIDAR device 100 repeatedly executes the processes of steps S200 to S500 each time it receives reflected waves within a preset angle range. In this way, the LIDAR device 100 repeatedly executes the above-described process, outputs multiple ranging points, and generates a point cloud, thereby identifying the position of an object present within the scanning angle range.

[0024] According to the LIDAR device 100 described above, even objects with a low S / N ratio can be detected with good sensitivity by frequency analysis of the data set DS1, and objects with a high S / N ratio can be detected with good resolution by frequency analysis of the data sets DS2 and DS3, thereby suppressing a decrease in sensitivity and resolution in object detection.

[0025] Furthermore, since data sets DS2 and DS3 contain data belonging to overlapping angular ranges, the possibility that data indicating the presence of an object in the sampling data will be split into two different data sets, resulting in an inability to properly detect the object, can be reduced.

[0026] Furthermore, since the LIDAR device 100 includes three frequency analysis units 52 to 54, the frequency analysis units can perform frequency analysis in parallel on different analysis target data sets, thereby preventing a decrease in the processing performance of the LIDAR device 100.

[0027] B. Second embodiment: The LIDAR device 100 of the second embodiment differs from the LIDAR device 100 of the first embodiment in that the readout angle is set according to the peak intensity of the reflected wave in the result of frequency analysis of the data set DS1, and sampling data is read out for each range of the readout angle.

[0028] As shown in FIG. 5, after step S200, the LIDAR device 100 executes ranging point output processing for the data set DS1 prior to ranging point output processing for the data sets DS2A and DS3A, which will be described later (step S300).

[0029] In step S340A, the LIDAR device 100 sets a read angle for reading sampled data according to the peak intensity of the reflected wave in the result of frequency analysis of the data set DS1. For example, if the peak intensity is six times a preset threshold, the LIDAR device 100 sets a third angle, which is 1 / 6 the magnitude of the first angle, as the read angle. If the peak intensity is high, the object's SNR is likely to be high. Therefore, in this case, the object's position can be identified with a smaller number of sampled data than when the object's SNR is low. For this reason, in this embodiment, the third angle, which is smaller than the second angle, is set as the read angle.

[0030] The LIDAR device 100 executes a ranging point output process (step S400A) for the data set DS2A and a ranging point output process (step S500A) for the data set DS3A in parallel. The data sets DS2A and DS3A refer to data sets obtained by reading out sampling data for each third angle range. The data sets DS2A and DS3A correspond to the "third data set to be analyzed" in this disclosure.

[0031] According to the LIDAR device 100 of the second embodiment described above, the readout angle is set according to the peak intensity of the reflected wave in the result of frequency analysis of data set DS1, and sampling data is read out for each range of the readout angle. This allows measurements to be performed at an appropriate resolution for each object's SNR, and reduces the deterioration of object detection sensitivity and resolution.

[0032] C. Third embodiment: The LIDAR device 100 of the third embodiment differs from the LIDAR device 100 of the second embodiment in that the thinning interval is set according to the peak frequency of the reflected wave in the result of frequency analysis of the data set DS1, and the sampling data is read out at such thinning intervals.

[0033] As shown in FIG. 6, after performing ranging point output processing (step S300) for data set DS1, the LIDAR device 100 sets a thinning interval for reading sampled data according to the peak frequency of reflected waves in the results of frequency analysis for data set DS1 (step S340B). For example, if the peak frequency is equal to or less than ¼ of the sampling frequency, the LIDAR device 100 sets the thinning interval to “1.” If the thinning interval is set to “1,” the frequency analysis units 53 and 54 read sampled data every other point in the subsequent ranging point output processing. Even in this case, the effective sampling frequency is at least twice the peak frequency. This prevents aliasing, in which the frequency of the signal to be measured is detected as a value different from the actual value when the sampling frequency is equal to or less than twice the frequency of the signal to be measured.

[0034] The LIDAR device 100 executes a ranging point output process (step S400B) for the data set DS2B and a ranging point output process (step S500B) for the data set DS3B in parallel. The data sets DS2B and DS3B refer to data sets obtained by reading out sampled data for each of the second angle ranges at thinning intervals. The data sets DS2B and DS3B correspond to the "second thinned data set to be analyzed" in this disclosure.

[0035] According to the LIDAR device 100 of the third embodiment described above, a thinning interval is set according to the peak frequency of the reflected wave in the result of frequency analysis of data set DS1, and sampled data is read at this thinning interval. This makes it possible to perform frequency analysis with a small amount of data, and suppresses a decrease in the processing performance of the LIDAR device 100.

[0036] D. Other Embodiments: (D1) In the above embodiment, the transmitter 10 transmits two types of transmission waves in parallel: one whose frequency is modulated to increase over time, and the other whose frequency is modulated to decrease over time. However, the present disclosure is not limited to this. The transmitter 10 may transmit a transmission wave modulated using a modulation method that is not limited to the above modulation method and that allows the sampling interval to be set arbitrarily. For example, the transmitter 10 may transmit a transmission wave whose frequency and amplitude are modulated over time.

[0037] (D2) In the above embodiment, the LIDAR device 100 reads out a data set corresponding to the entire sampling data as the first data set to be analyzed, but the present disclosure is not limited to this. The LIDAR device 100 may set the first angle to an angle smaller than the angle at which the reflected wave is received in step S200, and may read out the sampling data for each range of the first angle to obtain a plurality of data sets to be analyzed.

[0038] (D3) In the above embodiment, the LIDAR device 100 executes the ranging point output process each time it receives reflected waves within a preset angle range, but the present disclosure is not limited to this. The LIDAR device 100 may execute the ranging point output process after receiving reflected waves within the entire scanning angle range.

[0039] (D4) In the above embodiment, the data sets DS2 and DS3 include data belonging to overlapping angular ranges, but the present disclosure is not limited to this. The data sets DS2 and DS3 do not have to include data belonging to overlapping angular ranges. According to this embodiment, the number of data items to be subjected to frequency analysis for each data set is reduced, thereby suppressing a decrease in the processing performance of the LIDAR device 100.

[0040] (D5) In the above embodiment, the LIDAR device 100 includes three frequency analysis units 52 to 54, but the present disclosure is not limited to this. The LIDAR device 100 may include only one frequency analysis unit. According to this embodiment, frequency analysis of multiple data sets is performed sequentially rather than in parallel, which can prevent the frequency analysis in the object detection process from becoming too complicated.

[0041] (D6) In the above embodiment, the LIDAR device 100 performs ranging point output processing on the data sets DS1, DS2, and DS3, but the present disclosure is not limited to this. The LIDAR device 100 may also perform ranging point output processing on multiple data sets obtained by reading sampling data for each angle range that is smaller than the first angle and different from the second angle. This configuration increases the likelihood that frequency analysis can be performed with an appropriate number of sampling data points for the object's SNR, thereby preventing a decrease in object detection sensitivity and resolution.

[0042] (D7) In the second embodiment, the LIDAR device 100 sets one read angle according to the peak intensity of the reflected wave in the results of frequency analysis of the data set DS1. However, the present disclosure is not limited to this. If the results of frequency analysis of the data set DS1 contain multiple peaks of the reflected wave, the LIDAR device 100 may set multiple read angles according to the intensity of each peak. For example, if there is a peak whose peak intensity is six times the threshold and a peak whose peak intensity is twice the threshold, the LIDAR device 100 may set two read angles: one that is 1 / 6 the magnitude of the first angle and one that is 1 / 2 the magnitude of the first angle. Furthermore, the LIDAR device 100 may execute ranging point output processing for multiple data sets obtained by reading sampling data for each of the set angle ranges. This embodiment can suppress degradation of object detection sensitivity and resolution when measuring multiple objects.

[0043] (D8) In the second embodiment, the LIDAR device 100 performs the ranging point output process using the data sets DS2A and DS3A instead of the data sets DS2 and DS3, but the present disclosure is not limited to this. The LIDAR device 100 may perform the ranging point output process using the data sets DS2A and DS3A in addition to the data sets DS2 and DS3.

[0044] (D9) In the third embodiment, the LIDAR device 100 performs the ranging point output process using the data sets DS2B and DS3B instead of the data sets DS2 and DS3, but the present disclosure is not limited to this. The LIDAR device 100 may perform the ranging point output process using the data sets DS2B and DS3B in addition to the data sets DS2 and DS3.

[0045] The present disclosure is not limited to the above-described embodiments and can be realized in various configurations without departing from the spirit thereof. For example, the technical features in each embodiment corresponding to the technical features in the form described in the Summary of the Invention section can be appropriately replaced or combined to solve some or all of the above-described problems or achieve some or all of the above-described effects. Furthermore, if a technical feature is not described as essential in this specification, it can be appropriately deleted.

[0046] The controller and the methods described herein may be implemented by a special-purpose computer configured with a processor and memory programmed to perform one or more functions embodied in a computer program. Alternatively, the controller and the methods described herein may be implemented by a special-purpose computer configured with a processor configured with one or more dedicated hardware logic circuits. Alternatively, the controller and the methods described herein may be implemented by one or more special-purpose computers configured with a processor and memory programmed to perform one or more functions in combination with a processor configured with one or more hardware logic circuits. Furthermore, the computer program may be stored as instructions executed by a computer on a computer-readable non-transitory storage medium. [Explanation of symbols]

[0047] 10...transmitting unit, 20...scanning unit, 30...receiving unit, 40...data conversion unit, 51...data holding unit, 52, 53, 54...frequency analysis unit, 55...point cloud generation unit, 100...LIDAR device

Claims

1. A LIDAR device (100), comprising: a transmitting unit (10) that performs at least one of transmitting two types of transmission waves in parallel, one being a transmission wave whose frequency is modulated to increase over time and the other being a transmission wave whose frequency is modulated to decrease over time, and transmitting a transmission wave whose frequency and amplitude are modulated over time; a scanning unit (20) that scans the transmission wave within a range of a preset scanning angle; a receiving unit (30) for receiving a reflected wave generated when the transmitted wave is reflected by an object; a data conversion unit (40) that converts the reflected waves received within the range of the scanning angle into sampling data; a data storage unit (51) for storing the sampling data; a frequency analysis unit (52, 53, 54) that performs frequency analysis on one or more first analysis target data sets obtained by reading the sampling data from the data storage unit for each first angle range that is equal to or less than the scanning angle, and on multiple second analysis target data sets obtained by reading the sampling data for each second angle range that is smaller than the first angle, and that uses the results of the frequency analysis to acquire ranging point data that includes at least information on the distance and direction of ranging points relative to the LIDAR device; a point cloud generation unit (55) that generates a point cloud consisting of a plurality of ranging points indicated by the ranging point data acquired using the result of the frequency analysis targeted at the first analysis target data set, and a point cloud consisting of a plurality of ranging points indicated by the ranging point data acquired using the result of the frequency analysis targeted at the second analysis target data set; Equipped with When the peak intensity of the reflected wave in the result of the frequency analysis targeting the first analysis target data set is equal to or greater than a preset threshold, the frequency analysis unit performs the frequency analysis targeting a plurality of third analysis target data sets obtained by reading out the sampling data for each range of a third angle smaller than the second angle, instead of the second analysis target data set, to acquire the ranging point data. LIDAR device.

2. 2. The LIDAR device of claim 1, the plurality of second analysis target data sets include at least two second analysis target data sets obtained by reading out the sampling data for two ranges of the second angle that partially overlap each other, LIDAR device.

3. 3. The LIDAR device according to claim 1 or 2, A plurality of the frequency analysis units are provided, the plurality of frequency analysis units perform the frequency analysis in parallel on the second analysis target data sets that are different from each other among the plurality of second analysis target data sets. LIDAR device.

4. 2. The LIDAR device of claim 1, the plurality of third analysis target data sets include at least two third analysis target data sets obtained by reading out the sampling data for each of two ranges of the third angle that partially overlap each other, LIDAR device.

5. The LIDAR device according to claim 1 or claim 4, A plurality of the frequency analysis units are provided, the plurality of frequency analysis units perform the frequency analysis in parallel on the third analysis target data sets that are different from each other among the plurality of third analysis target data sets. LIDAR device.

6. 2. The LIDAR device of claim 1, the frequency analysis unit sets a thinning interval in accordance with a peak frequency of the reflected wave in a result of the frequency analysis of the first analysis target data set; performing the frequency analysis on a plurality of second analysis target thinned data sets obtained by reading the sampling data for each of the second angle ranges at the thinning intervals instead of the second analysis target data set, and acquiring the range measurement point data; LIDAR device.

7. 7. The LIDAR device according to claim 6, the plurality of second analysis target thinned data sets include at least two second analysis target thinned data sets obtained by reading out the sampling data for each of two ranges of the second angle that partially overlap each other, LIDAR device.

8. 8. The LIDAR device according to claim 6 or claim 7, A plurality of the frequency analysis units are provided, the plurality of frequency analysis units perform the frequency analysis in parallel on different second analysis target thinned data sets among the plurality of second analysis target thinned data sets, respectively. LIDAR device.

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