Information processing device, radar device, and information processing method

Abstract

In order to achieve this purpose, an information processing device according to the present technology comprises: a control unit that causes a transmission wave, which is an electromagnetic wave, to be transmitted from a transmission antenna toward an environment surrounding a mobile body; a processing unit that generates point cloud data on the basis of a reflected wave reflected by an object which exists in the environment surrounding the mobile body and which has been received by a reception antenna; a determination unit that determines a traveling scene on the basis of the generated point cloud data; and a map generation unit that generates, on the basis of a result of the determination by the determination unit, a map having regions with different object detection accuracies.

Description

Information processing device, radar device, and information processing method 【0001】 This technology relates to an information processing device, a radar device, and an information processing method for detecting objects present in the surrounding environment of a vehicle. 【0002】 Conventional technologies have been known for detecting objects that obstruct the movement of a moving vehicle around it. For example, Patent Document 1 discloses an in-vehicle sensor system comprising a first sensor for detecting the conditions around the vehicle and a second sensor having a higher angular resolution than the first sensor, characterized in that the system comprises an acquisition means for acquiring detection results from the first sensor and a range determination means for determining an observation range that the second sensor should observe within the area around the vehicle based on the detection results. 【0003】 Japanese Patent Publication No. 2021-168065 【0004】 However, Patent Document 1 had the problem of being costly because it required multiple types of sensors. 【0005】 In light of the above circumstances, the objective of this technology is to provide an information processing device, a radar device, and an information processing method that can perform robust and highly accurate object detection while reducing costs. 【0006】 To achieve the above objective, an information processing device according to one embodiment of this technology comprises a control unit, a processing unit, a determination unit, and a map generation unit. The control unit causes a transmitting antenna to transmit electromagnetic waves toward the surrounding environment of the moving object. The processing unit generates point cloud data based on reflected waves reflected by objects present in the surrounding environment of the moving object, which are received by the receiving antenna. The determination unit determines the driving scene based on the generated point cloud data. The map generation unit generates a map having regions with different accuracy levels for detecting the objects, based on the determination result of the determination unit. 【0007】The map generation unit may further include a detection unit that detects the object based on the point cloud data, and the map generation unit may detect the object in a region of interest which is a predetermined range of the object with a first accuracy based on the detection result of the detection unit, and detect the object in a region other than the region of interest with a second accuracy lower than the first accuracy. 【0008】 The map generation unit may generate the map by calculating an index that indicates the likelihood of whether the object exists in a region where the detection rate of the object is highly accurate. 【0009】 The map generation unit may also generate an occupied grid map that divides the surrounding environment into a grid for regions where the detection rate of the object is highly accurate, and describes the probability of the object occupying each grid cell. 【0010】 The map generation unit described above may generate areas with low accuracy in detecting the object by integrating the point cloud data. 【0011】 The system further comprises a calculation unit that calculates the speed of the moving object based on the transmitted wave and the reflected wave, and the map generation unit may generate the map based on the calculation results of the calculation unit. 【0012】 The calculation unit described above may calculate the velocity of the moving object using the RANSAC (Random Sample Consensus) method. 【0013】To achieve the above object, a radar device according to one embodiment of the present technology includes a radar and an information processing device. The radar has a transmission antenna that transmits a transmission wave, which is an electromagnetic wave, toward the surrounding environment of the moving body, and a reception antenna that receives a reflected wave reflected by an object existing in the surrounding environment of the moving body. The information processing device includes a control unit, a processing unit, a determination unit, and a map generation unit. The control unit causes the transmission antenna to transmit a transmission wave, which is an electromagnetic wave, toward the surrounding environment of the moving body. The processing unit generates point cloud data based on the reflected wave reflected by an object existing in the surrounding environment of the moving body and received by the reception antenna. The determination unit determines a driving scene based on the generated point cloud data. The map generation unit generates a map having regions with different accuracies of the detection rate of the object based on the determination result of the determination unit. 【0014】 To achieve the above object, an information processing method according to one embodiment of the present technology includes causing a transmission antenna to transmit a transmission wave, which is an electromagnetic wave, toward the surrounding environment of a moving body, generating point cloud data based on a reflected wave reflected by an object existing in the surrounding environment of the moving body and received by a reception antenna, determining a driving scene based on the generated point cloud data, and generating a map showing the probability of existence of the object and having regions with different accuracies of the detection rate of the object based on the determined driving scene. 【0015】It is a graph showing the waveform of the FMCW chirp. It is a graph showing the frequency of the FMCW chirp. It is a graph showing the waveforms of a plurality of consecutive chirps. It is a graph showing the frequencies of a plurality of consecutive chirps. It is a schematic diagram of a radar using the FMCW method. It is a schematic diagram of the radar apparatus according to the present embodiment. It is a graph of the transmission signal of the first chirp group that the radar control unit of the information processing apparatus included in the radar apparatus causes the signal generation unit to generate. It is a diagram showing the map generated by the map generation unit. It is a diagram showing the occupancy grid map. It is a diagram showing a second region with low accuracy of object detection rate, where (A) shows the movement of the moving body and (B) shows the object detection method. It is a graph of the transmission signal of the second chirp group that the radar control unit causes the signal generation unit to generate. It is a graph of the transmission signal of the third chirp group that the radar control unit causes the signal generation unit to generate. It is a graph of the transmission signal of the fourth chirp group that the radar control unit causes the signal generation unit to generate. It is a schematic diagram of the first transmission pattern of the transmission signal generated by the radar control unit. It is a schematic diagram of the second transmission pattern of the transmission signal generated by the radar control unit. It is a block diagram showing an example of the schematic configuration of the vehicle control system. It is an explanatory diagram showing an example of the installation positions of the vehicle exterior information detection unit and the imaging unit. 【0016】 Hereinafter, embodiments of the present invention will be described with reference to the drawings. 【0017】 [Regarding FMCW] The FMCW (Frequency Modulated Continuous Wave) used by the radar apparatus according to the present embodiment will be described. FIG. 1 is a graph showing the waveform of the FMCW chirp, and FIG. 2 is a graph showing the frequency of the FMCW chirp. As shown in these figures, the chirp has a waveform in which the frequency monotonically increases with time. Hereinafter, the time from the start time of the chirp to the start time of the next chirp is defined as the chirp time TC. 【0018】Figure 2 also shows the minimum frequency fL, maximum frequency fH, and bandwidth W of the chirp. The bandwidth W is the frequency difference between the minimum frequency fL and the maximum frequency fH. In millimeter-wave radar, for example, a chirp with a minimum frequency fL of 77 GHz, a maximum frequency fH of 81 GHz, and a bandwidth W of 4 GHz is used. The slope of this chirp is "W / TC". 【0019】 Figure 3 is a graph showing the waveforms of multiple consecutive chirps, and Figure 4 is a graph showing the frequencies of multiple consecutive chirps. As shown in these figures, the N consecutive chirps are referred to as "Chirp 1," "Chirp 2," "Chirp 3," ... "Chirp N" in order. The multiple chirps from Chirp 1 to Chirp N are referred to as a "frame." The number of chirps N contained in one frame is not particularly limited. Also, the chirps contained in one frame have the same shape, i.e., the same chirp time TC and bandwidth W. If the time between the start time and end time of one frame is the frame time Tf, then the frame time Tf is "NTc." 【0020】 Figure 5 is a block diagram showing the configuration of the FMCW radar 110. As shown in the figure, the radar 110 includes a transmitting antenna 111, a receiving antenna 112, a signal generation unit 113, and a signal mixing unit 114. 【0021】 The transmitting antenna 111 transmits radar waves towards the surrounding environment of the moving object based on the transmission signal supplied from the signal generation unit 113. Hereinafter, the radar waves transmitted from the transmitting antenna 111 will be referred to as the "transmitted waves." The transmitted waves are FMCW (Frequency Continuous Modulation) as shown in Figure 3. 【0022】 The receiving antenna 112 receives radar waves reflected by objects in the surrounding environment of the moving object and generates a received signal. Hereinafter, the radar waves received by the receiving antenna 112 will be referred to as "received waves (reflected waves)". As described above, the received waves are transmitted waves sent from the transmitting antenna 111 that have been reflected by some object. The receiving antenna 112 outputs the generated received signal to the signal mixing unit 114. 【0023】The signal generation unit 113 generates a transmission signal. The transmission signal generated by the signal generation unit 113 is a wave with continuous chirps as shown in Figure 3, i.e., an FMCW signal. The signal generation unit 113 outputs the generated transmission signal to the transmitting antenna 111, and the transmission signal is transmitted from the transmitting antenna 111 as a transmission wave. When the transmission wave is reflected by an object, it is received as a received wave by the receiving antenna 112, and a received signal is generated by the receiving antenna 112. 【0024】 The signal mixing unit 114 is a mixer that mixes the transmitted signal and the received signal to generate an intermediate frequency (IF) signal. Since the received signal has a time delay (distance component) and a Doppler shift (relative velocity component) relative to the transmitted signal, the frequency of the intermediate frequency signal indicates the distance to the object, and the phase change of the frequency signal between chirps indicates the relative velocity to the object. The signal mixing unit 114 outputs the generated intermediate frequency signal to the information processing device 120. 【0025】 [Configuration of the Radar System] The radar system according to this embodiment will now be described. Figure 6 is a schematic diagram of the radar system 100 according to this embodiment. As shown in the figure, the radar system 100 includes a radar 110 and an information processing device 120. 【0026】 Radar 110 is an FMCW millimeter-wave radar and has the configuration described above (see Figure 5). Each radar 110 may be equipped with multiple transmitting antennas 111 and multiple receiving antennas 112, forming a MIMO (Multi-Input Multi-Output) radar. Alternatively, each radar 110 may be equipped with one transmitting antenna 111 and one receiving antenna 112, and not form a MIMO radar. 【0027】 The number of radars 110 in the radar system 100 is not particularly limited; it may be one or multiple. The radar system 100 can be mounted on a mobile device such as an automobile or a drone. In this case, the entire radar system 100 may be mounted on the mobile device, or only the radars 110 may be mounted on the mobile device. 【0028】[Configuration of the Information Processing Device] The information processing device 120 controls the radar 110 and performs data processing. As shown in Figure 6, the information processing device 120 includes a radar control unit (control unit) 121, a radar data acquisition unit (acquisition unit) 122, a radar data processing unit (processing unit) 123, an object detection unit (detection unit) 124, a speed calculation unit (calculation unit) 125, a situation determination unit (determination unit) 126, a map generation unit 127, and a storage unit 128. These are functional configurations realized through the cooperation of hardware and software. 【0029】 The radar control unit 121 and the radar data acquisition unit 122 are connected to the radar 110 provided by the radar device 100. The radar data acquisition unit 122 acquires the intermediate frequency signal generated by the signal mixing unit 114 described above. The information processing device 120 may be mounted on a mobile device together with the radar 110, or it may be installed separately from the mobile device and connected to the radar 110 directly or via a communication network. 【0030】 The radar control unit 121 specifies the conditions for the transmission signal to the signal generation unit 113, causing the signal generation unit 113 to generate the transmission signal. Figure 7 is a schematic diagram of the transmission signal that the radar control unit 121 causes the signal generation unit 113 to generate. The radar control unit 121 causes the signal generation unit 113 to generate the first chirp group G1 shown in Figure 7 as the transmission signal. 【0031】 As shown in Figure 7, the first chirp group G1 has multiple first chirps C1. As shown in the same figure, the N first chirps C1 in the first chirp group G1 are sequentially named "first chirp C11", "first chirp C12", "first chirp C13", ... "first chirp C1N". The number N of first chirps C1 included in the first chirp group G1 is not particularly limited and can be 2 or more. 【0032】The radar data processing unit 123 processes the intermediate frequency signals acquired by the radar data acquisition unit 122. As described above, the frequency of the intermediate frequency signal indicates the distance to an object, so the radar data processing unit 123 can calculate the distance to each object by performing a Fourier transform on the intermediate frequency signal for each chirp to convert it into the frequency domain. This distance Fourier transform can be performed using the Fast Fourier Transform (FFT), and is called the distance FFT or 1D-FFT. 【0033】 Furthermore, since the phase change of the intermediate frequency signal between chirps indicates the relative velocity with respect to the object, the radar data processing unit 123 can calculate the relative velocity between the receiving antenna 112 and each object by performing a Fourier transform on the intermediate frequency signal, which has been Fourier transformed in the distance direction, for each frame. This Fourier transform in the velocity direction can also be performed by FFT, and is called velocity FFT or 2D-FFT. 【0034】 Furthermore, if the radar 110 is equipped with multiple receiving antennas 112, the phase difference of the intermediate frequency signals between each receiving antenna 112 indicates the angle between each receiving antenna 112 and the object. Therefore, by performing a Fourier transform on all of the intermediate frequency signals obtained by performing a Fourier transform in the velocity direction at each receiving antenna 112, the angle of each object relative to the receiving antenna 112 can be detected. 【0035】 The radar data processing unit 123 performs the above processing on the intermediate frequency signal and generates detection data from the intermediate frequency signal. The detection data is the data of the three-dimensional coordinates of the detection points detected based on the intermediate frequency signal, and this detection data will be referred to as "point cloud data" below. 【0036】 The object detection unit 124 detects objects (or their types) present in the surrounding environment of a moving object based on point cloud data generated by the radar data processing unit 123. Here, an object refers to a three-dimensional object, and includes, for example, people, cars, guardrails, and other stationary objects. Furthermore, detecting an object means detecting (identifying) an object based on its attributes and characteristics (such as reflectance and shape). 【0037】The speed calculation unit 125 calculates the speed of the moving object based on the point cloud data generated by the radar data processing unit 123. The speed calculation unit 125 also calculates the speed of the moving object itself from the relative speed between the receiving antenna 112 and each object, which is generated by the radar data processing unit 123. 【0038】 However, the objects include not only stationary objects (such as guardrails) but also moving objects (such as automobiles). Therefore, the speed calculation unit 125 calculates the speed of the moving object using a model estimation algorithm that is robust to outliers (in this embodiment, relative speed with the moving object) such as the RANSAC (Random Sample Consensus) method, since the number of reflected waves from stationary objects such as guardrails is dominant in many driving scenarios. 【0039】 The situation determination unit 126 determines the surrounding environment (surrounding conditions) of the mobile body equipped with the radar device 100. Based on the point cloud data generated by the radar data processing unit 123, the situation determination unit 126 can determine the driving scene (surrounding environment of the mobile body). 【0040】 The situation determination unit 126 determines the driving scene to be a parking lot if, for example, the speed of the moving object is below a predetermined speed (for example, 20 km / h or less) and there are multiple vehicles stopped at a 90-degree angle to the moving object. It also determines the driving scene to be an urban area if there are vehicles moving in the opposite direction to the moving object in the oncoming lane and there are no multiple vehicles stopped at a 90-degree angle to the moving object. Furthermore, it determines the driving scene to be a highway if the speed of the moving object is above a certain speed (for example, 70 km / h or more). These determination methods are just examples and are not limited to them, nor are the driving scenes limited to these examples. 【0041】Figure 8 shows the map M generated by the map generation unit 127. As shown in Figure 8, the map generation unit 127 generates a map having regions (R1, R2) with different accuracy levels for object detection based on the determination result of the situation determination unit 126. The map generation unit 127 has a first region R1 with high accuracy for object detection and a second region R2 with lower accuracy for object detection than the first region R1. In this embodiment, the map generation unit 127 generates an occupancy grid map (OGM) as a map for recognizing the surrounding environment of a moving object. In this embodiment, the first region R1 is generated by 3DOGM and the second region R2 by 2DOGM or simple summation, but of course, it is not limited to this. 【0042】 Figure 9 shows the occupied grid map OGM. Here, the occupied grid map OGM is a map that represents the area in which the mobile body C travels, using an index (likelihood in this embodiment) that indicates the likelihood of whether or not an object (obstacle) B1 exists in the surrounding environment. As shown in Figure 9, the probabilities of existence are α, β, and γ in descending order. The index that indicates the likelihood of whether or not an object exists includes the likelihood. Note that the method for calculating the likelihood is not limited and may be calculated by any method. 【0043】 The map generation unit 127 divides the absolute coordinate system into a grid using the position of the moving object C as the origin, indicates the probability of object B1 being present in each grid, and generates an occupied grid map OGM. In other words, grids on the occupied grid map OGM with a low probability of object presence are areas where movement is likely (areas without obstacles such as cars or guardrails). The grid size is determined by the driving scene, etc. In this embodiment, the occupied grid map OGM is generated only in front of the moving object C (towards the direction of travel), but of course, it is not limited to this and may also be generated behind it. 【0044】Furthermore, the accuracy of object detection can be changed by the grid size. In other words, the accuracy of object (stationary object B1) detection can be increased by reducing the grid size. On the other hand, the accuracy of object (stationary object B1) detection decreases when the grid size is increased. For example, if the driving scene is the parking lot described above, the grid size can be set to 0.1m square (high accuracy) only for short distances (e.g., 20m in front and behind), and to 0.5m square (low accuracy) for the rest of the range. 【0045】 In other words, by dividing the driving scene into areas with high object detection accuracy (first area R1) and areas with low accuracy (second area R2), and generating a map M, it is possible to perform object detection quickly while maintaining high accuracy. Furthermore, because the area is divided into areas with high and low object detection accuracy, the resources used for computational processing can be reduced, thus reducing costs. 【0046】 Furthermore, in this embodiment, since the movement of the moving object itself is estimated and object detection is performed using only radar, robust and appropriate mapping processing can be achieved without being affected by nighttime or rainy weather. 【0047】 Furthermore, in this embodiment, the influence of outliers (other moving objects) can be suppressed by calculating the travel speed of the moving object using the RANSAC method. 【0048】 Furthermore, the map generation unit 127 detects objects in a predetermined area of ​​interest, which is the region of interest, with a first level of accuracy, based on the detection results of the object detection unit 124, and detects objects in areas outside the region of interest with a second level of accuracy lower than the first level. Here, the region of interest is an area of ​​interest within the driving scene determined by the situation determination unit 126, and is required to detect objects with high accuracy. 【0049】For example, if the driving scene is a parking lot and a pedestrian is detected there, the region of interest will be the area around the pedestrian detected within that parking lot. In other words, the map generation unit 127 detects the pedestrian around the pedestrian with a grid size of 0.05m square (first precision), and detects objects elsewhere with a grid size of 0.1m square (second precision). 【0050】 This allows for rapid object detection while maintaining high accuracy in areas of interest (regions of interest) where detection needs to be performed with greater precision, depending on the driving scenario. 【0051】 Figure 10 shows a second region where the accuracy of object detection is low, where (A) shows the movement of moving object C, and (B) shows the object detection method. 【0052】 In addition to adjusting the grid size, another method for low-precision detection is to integrate the detection points K without performing likelihood calculations, as shown in Figure 10. 【0053】 In other words, as shown in Figure 10, the two detection points K1 and K2 detected by the moving object C at time T-Δt moved to K1' and K2' after Δt seconds. In this case, as shown in Figure 10(B), since there are two detection points K1' and K2 in one grid, it may be assumed that an object exists in that grid (if there is only one point (detection points K1, K2') in the grid, it may be assumed that no object exists). 【0054】 Of course, this is not the only option; a point cloud map that simply accumulates reflection points from multiple time frames may also be used (objects may also be considered to exist in the grid where detection points K1 and K2' in Figure 10(B) are located). 【0055】 In this embodiment, a map was generated for stationary objects. For moving objects such as automobiles, a tracking process is performed separately from the map to track the moving object over time. 【0056】 In this embodiment, a millimeter-wave radar was used, but of course, it is not limited to this, and LiDAR (Light Detection and Ranging) may also be used. 【0057】 [Regarding velocity expansion] As described above, by transmitting the chirp of chirp time T Ｃ (see Fig. 4) N times and observing the time change between chirps, the velocity of an object can be detected. The velocity resolution that can be detected from the point cloud data of this chirp group is defined as velocity resolution V ｒｅｓ Then, the velocity resolution V ｒｅｓ is expressed by the following (Equation 1). Here, "λ" is the wavelength of the intermediate frequency signal. V ｒｅｓ = λ / 2T ｆ = λ / 2NT Ｃ (Equation 1) 【0058】 On the other hand, the maximum velocity that can be detected from the point cloud data of this chirp group is defined as the maximum detected velocity V ｍａｘ Then, the maximum detected velocity V ｍａｘ is expressed by the following (Equation 2). V ｍａｘ = λ / 4T Ｃ (Equation 2) 【0059】 That is, there is a trade-off relationship such that when the chirp time T Ｃ is increased to raise the velocity resolution V ｒｅｓ , the maximum detected velocity V ｍａｘ decreases. Also, regarding the detection distance, there is a trade-off relationship such that when the frequency band is increased to raise the distance resolution, the maximum detection distance decreases. 【0060】 Therefore, by preparing a plurality of radar irradiation modes considering these trade-offs and selectively using them according to the application, the performance of the radar can be compensated. For example, it is preferable to arrange a radar for low-resolution and long-distance detection in front of the vehicle and radars for high-resolution and short-distance detection at the four corners of the vehicle. 【0061】 Here, regarding the maximum detected velocity V ｍａｘ , velocity expansion by the Chinese Remainder Theorem is generally performed. In this velocity expansion, the velocity of an object exceeding the detectable velocity is utilized by being detected as "(N - 1) * 2 * V ｍａｘ + V" due to the folding of the radar wave. For example, when the maximum detected velocities V ｍａｘ are different values, velocity V ｍａｘ１ and velocity Vｍａｘ２ The chirp time T is such that this occurs. Ｃ The transmission wave is sent in two modes, each with only slight variations. 【0062】 At this time, the velocity V ｍａｘ１ and speed V ｍａｘ２ If there is an object with a velocity exceeding (N), then in each mode the velocity of the object is "(N １ -1) * 2 * V ｍａｘ１ +V １ " or "(N ２ -1) * 2 * V ｍａｘ２ +V ２ It is detected as "N". １ " and "N ２ " is the number of chirps per frame in each mode. From this, by the Chinese Remainder Theorem, "N １ " and "N ２ When we find the combination of "", the maximum detection speed V ｍａｘ It is possible to derive the correct velocity of an object beyond a certain point, that is, velocity extension can be achieved. 【0063】 Existing FMCW-type in-vehicle radar systems enable object detection in real-world driving environments by switching modes based on the installation locations of multiple radars and by extending their speed, as described above. However, when switching modes of multiple radars according to their installation locations, there is a problem in that the resolution decreases or the maximum detection distance decreases in areas where the field of view does not overlap. 【0064】 In contrast, this technology, as explained below, enables both short-range, high-resolution detection and long-range, low-resolution detection using all of the radars installed. 【0065】 As described above, the radar control unit 121 specifies the conditions for the transmission signal to the signal generation unit 113 and causes the signal generation unit 113 to generate the transmission signal. Figures 7 and 11 to 13 are schematic diagrams of the transmission signals that the radar control unit 121 causes the signal generation unit 113 to generate. The radar control unit 121 causes the signal generation unit 113 to generate four types of chirp groups as transmission signals: the first chirp group G1 shown in Figure 7, the second chirp group G2 shown in Figure 11, the third chirp group G3 shown in Figure 12, and the fourth chirp group G4 shown in Figure 13. 【0066】As shown in Figure 11, the second chirp group G2 has multiple second chirps C2. As shown in the same figure, the M second chirps C2 of the second chirp group G2 are sequentially referred to as "second chirp C2 １ "Second Chirp C2 ２ "Second Chirp C2 ３ "..."C2 Chirp 2 Ｍ The number M of second chirps C2 included in the second chirp group G2 is 2 or more, and may be the same as or different from the above "N". 【0067】 Here, the second chirp group G2 is a chirp group with a different distance detection range from the first chirp group G1. For example, if the first chirp group G1 is a chirp group capable of detecting distances from 0 to 50 m, then the second chirp group G2 is a chirp group capable of detecting distances from 0 to 100 m. Specifically, the second chirp group G2 has a slope "W / T Ｃ (See Figure 2) differs from the slope of the first chirp C1. In addition, the second chirp group G2 has a bandwidth W and a minimum frequency f Ｌ , highest frequency f Ｈ These may differ from the first chirp group G1. 【0068】 As shown in Figure 12, the third chirp group G3 has multiple third chirps C3. As shown in the same figure, the N third chirps C3 of the third chirp group G3 are sequentially referred to as "third chirp C3 １ "Third Chirp C3 ２ "Third Chirp C3 ３ "..."Third Chirp C3 Ｎ The number of third chirps C3 included in the third chirp group G3 is "N", which is the same number as the number of first chirps C1 included in the first chirp group G1. 【0069】 Here, the third chirp group G3 is a chirp group with a different velocity detection range from the first chirp group G1. For example, if the first chirp group G1 is a chirp group capable of detecting velocities from 0 to 5 m / s, then the third chirp group G3 is a chirp group capable of detecting velocities from 5 to 10 m / s. Specifically, the third chirp group G3 has a chirp time T Ｃ However, this differs from the first chirp group G1. The third chirp group G3 has a chirp time TＣ Other conditions, namely the bandwidth W and the chirp slope "W / T" Ｃ ”, lowest frequency f Ｌ and the highest frequency f Ｈ These are the same as those in the first chirp group G1. 【0070】 As shown in Figure 14, the fourth chirp group G4 has multiple fourth chirps C4. As shown in the same figure, the M fourth chirps C4 of the fourth chirp group G4 are sequentially referred to as "fourth chirp C4 １ "4th Chirp C4 ２ "4th Chirp C4 ３ "..."C4 Chirp 4 Ｍ Let's assume that the number of fourth chirps C4 included in the fourth chirp group G4 is "M", which is the same number as the number of second chirps C2 included in the second chirp group G2. 【0071】 Here, the fourth chirp group G4 is a chirp group with a different velocity detection range from the second chirp group G2. For example, if the second chirp group G2 is a chirp group capable of detecting velocities from 0 to 5 m / s, then the fourth chirp group G4 is a chirp group capable of detecting velocities from 5 to 10 m / s. Specifically, the fourth chirp group G4 has a chirp time T Ｃ This differs from the second chirp group G2. The fourth chirp group G4 has a chirp time T Ｃ Other conditions, namely the bandwidth W and the chirp slope "W / T" Ｃ ”, lowest frequency f Ｌ and the highest frequency f Ｈ These are the same as those in the second chirp group G2. 【0072】 The radar control unit 121 generates a transmission signal pattern (hereinafter referred to as the transmission pattern) using the four types of chirp groups described above, and instructs the signal generation unit 113 to transmit the transmission pattern from the transmitting antenna 111. The radar control unit 121 can generate the following two types of transmission patterns. Figure 14 is a schematic diagram showing the first transmission pattern. As shown in the figure, the first transmission pattern includes four modes in order for each frame: "Mode 1", "Mode 2", "Mode 1#", and "Mode 2#". 【0073】"Mode 1" is the mode in which the first chirp group G1 is transmitted, and "Mode 2" is the mode in which the second chirp group G2 is transmitted. "Mode 1" and "Mode 2" are modes in which the detection performance differs depending on the difference in the chirp groups. For example, "Mode 1" is a mode with a narrow distance detection range but high distance resolution, and "Mode 2" is a mode with a wide distance detection range but low distance resolution. "Mode 1#" is a speed extension mode for "Mode 1" and is the mode in which the third chirp group G3 is transmitted. "Mode 2#" is a speed extension mode for "Mode 2" and is the mode in which the fourth chirp group G4 is transmitted. 【0074】 Therefore, in the first transmission pattern, the transmission signals for each chirp group are transmitted from the transmitting antenna 111 in the order of the first chirp group G1, the second chirp group G2, the third chirp group G3, and the fourth chirp group G4. From the next frame 5 onwards, the above pattern is repeated, and similarly, the transmission signals for each chirp group are transmitted from the transmitting antenna 111. 【0075】 Figure 15 is a schematic diagram showing the second transmission pattern. As shown in the figure, the second transmission pattern includes four modes in each frame: "Mode 1", "Mode 1#", "Mode 2", and "Mode 2#". Each mode is the same as the mode in the first transmission pattern. 【0076】 Therefore, in the second transmission pattern, the transmission signals for each chirp group are transmitted from the transmitting antenna 111 in the order of the first chirp group G1, the third chirp group G3, the second chirp group G2, and the fourth chirp group G4. From the next frame 5, the above pattern is repeated, and similarly, the transmission signals for each chirp group are transmitted from the transmitting antenna 111. 【0077】 As described above, the status determination unit 126 determines the status of the mobile object on which the radar device 100 is mounted. Hereinafter, the status of the mobile object determined by the status determination unit 122 will be referred to as the "mobile object status". The status determination unit 126 can determine the mobile object status based on the point cloud data output from the radar 110. 【0078】Specifically, the situation determination unit 126 can determine if the moving object is a vehicle, such as whether the vehicle is driving in a parking lot or on a highway. Similarly, the situation determination unit 122 can determine if the moving object is a drone, such as whether the drone is taking off or landing, or flying horizontally. The situation determination unit 126 can detect the speed of the moving object and the positions of surrounding obstacles from point cloud data and use this information to determine the status of the moving object. The situation determination unit 126 then supplies the determined status of the moving object to the radar control unit 121. 【0079】 When a transmission wave is transmitted from the transmitting antenna 111 according to the first transmission pattern (see Figure 13) or the second transmission pattern (see Figure 14), the received wave reflected by an object is received by the receiving antenna 112, and a received wave is generated. The radar data processing unit 123 generates point cloud data from the intermediate frequency signal of the transmitted signal and the received signal. The radar data processing unit 123 supplies the generated point cloud data to the velocity calculation processing unit 125 or stores it in a data storage unit (not shown). 【0080】 The velocity calculation unit 125 processes the point cloud data described above. The velocity calculation unit 125 calculates the velocity of the object based on the received signals of the first chirp group G1 and the third chirp group G3, and calculates the velocity of the object based on the received signals of the second chirp group G2 and the fourth chirp group G4. 【0081】 Specifically, the velocity calculation unit 125 performs velocity expansion by pairing point cloud data based on the received signal of the first chirp group G1 with point cloud data based on the received signal of the third chirp group G3. Furthermore, the velocity calculation unit 125 performs velocity expansion by pairing point cloud data based on the received signal of the second chirp group G2 with point cloud data based on the received signal of the fourth chirp group G4. Note that pairing means identifying detection points by the same object across different frames. 【0082】In the first transmission pattern (see Figure 14), the first chirp group G1 is transmitted in frame 1, and the third chirp group G3 is transmitted in frame 3. Therefore, the velocity calculation unit 125 performs point cloud data pairing between frame 3 and frame 1 and performs velocity expansion using the Chinese Remainder Theorem. As a result, the velocity calculation unit 125 can detect a velocity that exceeds the maximum detected velocity of the first chirp group G1 and the maximum detected velocity of the third chirp group G3. 【0083】 Furthermore, the second chirp group G2 is transmitted in frame 2, and the fourth chirp group G4 is transmitted in frame 4. Therefore, the speed calculation unit 125 performs pairing between frame 4 and frame 2 and performs speed expansion according to the Chinese Remainder Theorem. As a result, the radar data processing unit 124 can detect speeds that exceed the maximum detected speed of the second chirp group G2 and the maximum detected speed of the fourth chirp group G4. 【0084】 In this way, the speed calculation unit 125 performs speed expansion by always pairing each frame with the point cloud data from two frames prior. During pairing, in order to take into account changes in the surrounding environment due to time changes, the distance of each detection point from two frames prior is set to "2*T". ｆ *V ｄｏｐｐｌｅｒ Apply the correction to "V". ｄｏｐｐｌｅｒ " is Doppler shift, and "T ｆ '' represents the frame time (see Figure 4). 【0085】 As this correction demonstrates, this speed enhancement method requires a larger correction amount the larger the time difference between the pairing frame and the current frame. However, it does not account for speed changes during this time, making pairing errors more likely. Therefore, in practical use, a certain tolerance for error must be allowed in the pairing conditions. Consequently, while the first transmission pattern can maintain the frame rate, it is a speed enhancement method prone to false detections. 【0086】On the other hand, in the second transmission pattern (see Figure 15), the first chirp group G1 is transmitted in frame 1, and the third chirp group G3 is transmitted in frame 2. Therefore, the speed calculation unit 125 performs point cloud data pairing between frame 2 and frame 1 and performs speed expansion using the Chinese Remainder Theorem. As a result, the speed calculation unit 125 can detect speeds that exceed the maximum detected speed of the first chirp group G1 and the maximum detected speed of the third chirp group G3. 【0087】 Furthermore, the second chirp group G2 is transmitted in frame 3, and the fourth chirp group G4 is transmitted in frame 4. Therefore, the speed calculation unit 125 performs point cloud data pairing between frame 4 and frame 3 and performs speed expansion using the Chinese Remainder Theorem. As a result, the speed calculation unit 125 can detect speeds that exceed the maximum detected speed of the second chirp group G2 and the maximum detected speed of the fourth chirp group G4. 【0088】 This second transmission pattern has a specific mode and a mode for speed extension in succession, so the correction amount between frames is "T ｆ *V ｄｏｐｐｌｅｒ This makes pairing errors less likely. However, the "Mode 1" in the 5th frame is three frames earlier than the previous "Mode 1#", resulting in a larger correction amount. To avoid this, in practice, it is necessary to pair the "Mode 1#" in frame 6 with the "Mode 1" in frame 5. 【0089】 In this way, the speed calculation unit 125 always pairs with the point cloud data from the previous frame in each frame, but does not pair with the point cloud data from three frames prior, thereby performing speed expansion. Therefore, the second transmission pattern is a speed expansion method that suppresses false detections but reduces the frame rate. 【0090】The information processing device 120 has the configuration described above. However, the configuration of the information processing device 120 is not limited to that described above. For example, in addition to the four chirp groups described above, the radar control unit 121 can also have the signal generation unit 113 generate a fifth chirp group which has a different distance detection range from the first chirp group G1 and the second chirp group G2, and a sixth chirp group which has a different velocity detection range from the fifth chirp group. Furthermore, the radar control unit 121 may have the signal generation unit 113 generate a larger number of chirp groups. 【0091】 [Operation and Effects of the Radar System] The operation of the radar system 100 will now be described. In the radar system 100, as described above, the radar control unit 121 (see Figure 6) specifies the transmission signal to the signal generation unit 113. At this time, the radar control unit 121 acquires the status of a moving object, such as a driving scene, from the status determination unit 126, and determines the transmission order from the transmitting antennas 111 of the first chirp group G1, second chirp group G2, third chirp group G3, and fourth chirp group G4 according to the status of the moving object. 【0092】 Specifically, the radar control unit 121 selects either the first transmission pattern (see Figure 14) or the second transmission pattern (see Figure 15) depending on the moving object status, and instructs the signal generation unit 113 to transmit the transmission signals for each chirp group from the transmitting antenna 111 according to the selected pattern. 【0093】 When a received signal is output from each receiving antenna 112 and point cloud data is output from the radar data processing unit 123, the velocity calculation unit 125 determines the velocity of the object based on the point cloud data of the first chirp group G1 and the point cloud data of the third chirp group G3. Specifically, the velocity calculation unit 125 pairs the point cloud data of the first chirp group G1 and the point cloud data of the third chirp group G3 and performs velocity expansion using the Chinese Remainder Theorem. 【0094】 Furthermore, the velocity calculation unit 125 determines the velocity of the object based on the point cloud data of the second chirp group G2 and the point cloud data of the fourth chirp group G4. Specifically, the velocity calculation unit 125 pairs the point cloud data of the second chirp group G2 and the point cloud data of the fourth chirp group G4 and performs velocity expansion using the Chinese Remainder Theorem. 【0095】In this case, the pairing frame interval differs between the first transmission pattern and the second transmission pattern, allowing for detection that prioritizes frame rate in the first transmission pattern and detection accuracy in the second transmission pattern. Therefore, by switching between the first and second transmission patterns according to the moving object status, the radar control unit 121 can achieve both short-range, high-resolution detection and long-range, low-resolution detection with all radars 110. 【0096】 When the movement of a moving object changes, such as from driving on a highway to driving in a parking lot, the situation determination unit 126 supplies the new movement status to the radar control unit 121, and the radar control unit 121 switches between the first transmission pattern and the second transmission pattern according to the new movement status. This enables adaptive detection that takes the actual environment into account. The radar control unit 121 may transmit either the first transmission pattern or the second transmission pattern regardless of the movement status. The radar control unit 121 can also switch between the first transmission pattern and the second transmission pattern at regular intervals. 【0097】 <Examples of application to mobile devices> The technology disclosed herein (this technology) can be applied to various products. For example, the technology disclosed herein may be implemented as a device mounted on any type of mobile device such as automobiles, electric vehicles, hybrid electric vehicles, motorcycles, bicycles, personal mobility devices, airplanes, drones, ships, and robots. 【0098】 Figure 16 is a block diagram showing a schematic configuration example of a vehicle control system, which is an example of a mobile control system to which the technology described herein may be applied. 【0099】The vehicle control system 12000 comprises a plurality of electronic control units connected via a communication network 12001. In the example shown in Figure 15, the vehicle control system 12000 includes a drive system control unit 12010, a body system control unit 12020, an external information detection unit 12030, an internal information detection unit 12040, and an integrated control unit 12050. The functional configuration of the integrated control unit 12050 is shown in the figure, which includes a microcomputer 12051, an audio / image output unit 12052, and an in-vehicle network interface 12053. 【0100】 The drivetrain control unit 12010 controls the operation of devices related to the vehicle's drivetrain according to various programs. For example, the drivetrain control unit 12010 functions as a control device for a drivetrain generating device that generates driving force for the vehicle, such as an internal combustion engine or a drive motor; a drivetrain transmission mechanism that transmits driving force to the wheels; a steering mechanism that adjusts the steering angle of the vehicle; and a braking device that generates braking force for the vehicle. 【0101】 The body system control unit 12020 controls the operation of various devices mounted on the vehicle body according to various programs. For example, the body system control unit 12020 functions as a control device for a keyless entry system, a smart key system, a power window system, or various lamps such as headlights, reverse lights, brake lights, turn signals, or fog lights. In this case, the body system control unit 12020 may receive radio waves transmitted from a portable device that replaces a key or signals from various switches. The body system control unit 12020 receives these radio waves or signals and controls the vehicle's door lock system, power window system, lamps, etc. 【0102】The external information detection unit 12030 detects information from outside the vehicle equipped with the vehicle control system 12000. For example, an imaging unit 12031 is connected to the external information detection unit 12030. The external information detection unit 12030 causes the imaging unit 12031 to capture images of the outside of the vehicle and receives the captured images. Based on the received images, the external information detection unit 12030 may perform object detection processing such as detecting people, cars, obstacles, signs, or characters on the road surface, or distance detection processing. 【0103】 The imaging unit 12031 is a light sensor that receives light and outputs an electrical signal corresponding to the amount of light received. The imaging unit 12031 can output the electrical signal as an image or as distance measurement information. The light received by the imaging unit 12031 may be visible light or invisible light such as infrared light. 【0104】 The in-vehicle information detection unit 12040 detects information inside the vehicle. The in-vehicle information detection unit 12040 is connected to, for example, a driver status detection unit 12041 that detects the driver's state. The driver status detection unit 12041 includes, for example, a camera that captures images of the driver, and the in-vehicle information detection unit 12040 may calculate the driver's level of fatigue or concentration, or determine whether the driver is drowsy, based on the detection information input from the driver status detection unit 12041. 【0105】 The microcomputer 12051 can calculate control target values ​​for the drive force generator, steering mechanism, or braking device based on information inside and outside the vehicle acquired by the external information detection unit 12030 or the internal information detection unit 12040, and output control commands to the drive system control unit 12010. For example, the microcomputer 12051 can perform cooperative control aimed at realizing ADAS (Advanced Driver Assistance System) functions, including collision avoidance or impact mitigation, following driving based on distance between vehicles, maintaining vehicle speed, vehicle collision warning, or vehicle lane departure warning. 【0106】Furthermore, the microcomputer 12051 can perform cooperative control for purposes such as autonomous driving, where the vehicle drives autonomously without driver intervention, by controlling the drive force generating device, steering mechanism, or braking device, etc., based on information about the vehicle's surroundings acquired by the external information detection unit 12030 or the internal information detection unit 12040. 【0107】 Furthermore, the microcomputer 12051 can output control commands to the body system control unit 12020 based on external information acquired by the external information detection unit 12030. For example, the microcomputer 12051 can control the headlights according to the position of a preceding or oncoming vehicle detected by the external information detection unit 12030, and perform coordinated control aimed at reducing glare, such as switching from high beams to low beams. 【0108】 The audio-image output unit 12052 transmits at least one of audio and image output signals to an output device capable of visually or audibly notifying information to the vehicle's occupants or to those outside the vehicle. In the example shown in Figure 15, the output devices include an audio speaker 12061, a display unit 12062, and an instrument panel 12063. The display unit 12062 may include, for example, at least one of an onboard display and a head-up display. 【0109】 Figure 17 shows an example of the installation position of the imaging unit 12031. 【0110】 In Figure 17, the imaging unit 12031 includes imaging units 12101, 12102, 12103, 12104, and 12105. 【0111】The imaging units 12101, 12102, 12103, 12104, and 12105 are installed, for example, on the front nose, side mirrors, rear bumper, back door, and the upper part of the windshield inside the vehicle 12100. The imaging unit 12101 installed on the front nose and the imaging unit 12105 installed on the upper part of the windshield inside the vehicle mainly acquire images of the front of the vehicle 12100. The imaging units 12102 and 12103 installed on the side mirrors mainly acquire images of the sides of the vehicle 12100. The imaging unit 12104 installed on the rear bumper or back door mainly acquires images of the rear of the vehicle 12100. The imaging unit 12105 installed on the upper part of the windshield inside the vehicle is mainly used for detecting preceding vehicles, pedestrians, obstacles, traffic lights, traffic signs, or lanes. 【0112】 Figure 17 shows an example of the imaging range of imaging units 12101 to 12104. Imaging range 12111 indicates the imaging range of imaging unit 12101 located on the front nose, imaging ranges 12112 and 12113 indicate the imaging ranges of imaging units 12102 and 12103 located on the side mirrors, respectively, and imaging range 12114 indicates the imaging range of imaging unit 12104 located on the rear bumper or back door. For example, by superimposing the image data captured by imaging units 12101 to 12104, an overhead view image of the vehicle 12100 can be obtained. 【0113】 At least one of the imaging units 12101 to 12104 may have a function for acquiring distance information. For example, at least one of the imaging units 12101 to 12104 may be a stereo camera consisting of multiple image sensors, or an image sensor having pixels for phase difference detection. 【0114】For example, the microcomputer 12051, based on distance information obtained from the imaging units 12101 to 12104, can determine the distance to each object within the imaging range 12111 to 12114 and the temporal change of this distance (relative speed to the vehicle 12100). In particular, it can extract the closest object on the vehicle 12100's path that is traveling in approximately the same direction as the vehicle 12100 at a predetermined speed (e.g., 0 km / h or more) as the preceding vehicle. Furthermore, the microcomputer 12051 can set a predetermined distance to be maintained before the preceding vehicle and perform automatic braking control (including follow-and-stop control) and automatic acceleration control (including follow-and-start control), etc. In this way, cooperative control aimed at autonomous driving, where the vehicle drives autonomously without driver intervention, can be performed. 【0115】 For example, the microcomputer 12051 can use distance information obtained from imaging units 12101 to 12104 to classify and extract three-dimensional object data related to three-dimensional objects, such as motorcycles, passenger cars, large vehicles, pedestrians, utility poles, and other three-dimensional objects, and use this data for automatic obstacle avoidance. For example, the microcomputer 12051 identifies obstacles around the vehicle 12100 into obstacles that are visible to the driver of the vehicle 12100 and obstacles that are difficult to see. The microcomputer 12051 then determines the collision risk, which indicates the degree of risk of collision with each obstacle. If the collision risk is above a set value and there is a possibility of collision, the microcomputer 12051 can provide driving assistance to avoid collisions by outputting a warning to the driver via the audio speaker 12061 or the display unit 12062, or by performing forced deceleration or evasive steering via the drive system control unit 12010. 【0116】At least one of the imaging units 12101 to 12104 may be an infrared camera that detects infrared light. For example, the microcomputer 12051 can recognize pedestrians by determining whether or not pedestrians are present in the images captured by the imaging units 12101 to 12104. Such pedestrian recognition is performed, for example, by a procedure to extract feature points from the images captured by the imaging units 12101 to 12104 as infrared cameras, and a procedure to perform pattern matching on a series of feature points that indicate the contour of an object to determine whether or not it is a pedestrian. When the microcomputer 12051 determines that a pedestrian is present in the images captured by the imaging units 12101 to 12104 and recognizes a pedestrian, the audio-image output unit 12052 controls the display unit 12062 to superimpose a rectangular contour line for emphasis on the recognized pedestrian. The audio-image output unit 12052 may also control the display unit 12062 to display an icon indicating a pedestrian at a desired position. 【0117】 The above describes an example of a vehicle control system to which the technology relating to this disclosure may be applied. The technology relating to this disclosure can be applied to the external information detection unit 12030 of the configuration described above. Specifically, the information processing device 120 in Figure 6 can be applied to the external information detection unit 12030, and the radar can be applied to the imaging unit 12031. 【0118】 [About this Disclosure] The effects described in this disclosure are merely examples and not limiting, and other effects may also occur. The description of multiple effects above does not necessarily mean that they will occur simultaneously. It means that at least one of the effects described above can be obtained depending on the conditions, and it is also possible that effects not described in this disclosure may occur. Furthermore, it is possible to combine at least two of the feature elements described in this disclosure. 【0119】 Furthermore, this technology can also be configured as follows. 【0120】(1) An information processing device comprising: a control unit that transmits a transmission wave, which is an electromagnetic wave, from a transmitting antenna toward the surrounding environment of a moving object; a processing unit that generates point cloud data based on reflected waves reflected by objects present in the surrounding environment of the moving object and received by a receiving antenna; a determination unit that determines a driving scene based on the generated point cloud data; and a map generation unit that generates a map having regions with different accuracy of object detection rate based on the determination result of the determination unit. (2) An information processing device according to (1) above, further comprising a detection unit that detects the object based on the point cloud data, wherein the map generation unit detects the object in a region of interest which is a predetermined range of the object with a first accuracy, and detects the object in regions other than the region of interest with a second accuracy lower than the first accuracy. (3) An information processing device according to (1) or (2) above, wherein the map generation unit generates the map by calculating an index that indicates the likelihood of whether the object is present in a region with a high accuracy of object detection rate. (4) A tactile presentation device according to any one of (1) to (3) above, wherein the map generation unit divides the surrounding environment space into a grid in a region where the detection rate of the object is highly accurate and generates an occupied grid map that describes the probability of the object's occupation in each grid. (5) A tactile presentation device according to any one of (1) to (4) above, further comprising a calculation unit that calculates the speed of the moving object based on the transmitted wave and the reflected wave, wherein the map generation unit generates the map based on the calculation result of the calculation unit. (6) A tactile presentation device according to any one of (1) to (5) above, wherein the tactile presentation device is a device attached to the user's arm, wherein the actuator is attached to the back of the user's wrist, the expansion unit is attached to the palm side of the user's wrist, and the flow channel unit is attached to the side of the user's wrist.(7) An information processing device for a tactile presentation device as described in (6) above, wherein the calculation unit calculates the speed of the moving object using the RANSAC (Random Sample Consensus) method. (8) A radar device comprising: a transmitting antenna that transmits a transmitting wave, which is an electromagnetic wave, toward the surrounding environment of a moving object; a receiving antenna that receives a reflected wave reflected by an object present in the surrounding environment of the moving object; a processing unit that generates point cloud data based on the reflected wave received by the receiving antenna; a determination unit that determines a driving scene based on the generated point cloud data; and a map generation unit that generates a map showing the probability of existence of an object and having regions with different accuracy of detection rate of the object based on the determination result of the determination unit. (9) An information processing method that transmits a transmitting wave, which is an electromagnetic wave, from a transmitting antenna toward the surrounding environment of a moving object; generates point cloud data based on a reflected wave reflected by an object present in the surrounding environment of the moving object received by a receiving antenna; determines a driving scene based on the generated point cloud data; and generates a map showing the probability of existence of an object and having regions with different accuracy of detection rate of the object based on the determined driving scene. 【0121】 100...Radar device 110...Radar 120...Information processing device 121...Radar control unit 122...Radar acquisition unit 123...Radar data processing unit 124...Object detection unit 125...Speed ​​calculation unit 126...Situation determination unit 127...Map generation unit

Claims

1. An information processing device comprising: a control unit that transmits electromagnetic waves from a transmitting antenna toward the surrounding environment of a moving object; a processing unit that generates point cloud data based on reflected waves reflected by objects present in the surrounding environment of the moving object and received by a receiving antenna; a determination unit that determines a driving scene based on the generated point cloud data; and a map generation unit that generates a map having regions with different accuracy levels for detecting the objects based on the determination result of the determination unit.

2. An information processing device according to claim 1, further comprising a detection unit for detecting the object based on the point cloud data, wherein the map generation unit detects the object in a region of interest which is a predetermined range of the object based on the detection result of the detection unit with a first accuracy, and detects the object in a region other than the region of interest with a second accuracy lower than the first accuracy.

3. An information processing device according to claim 1, wherein the map generation unit generates the map by calculating an index indicating the likelihood of whether the object is present in a region with high accuracy in detecting the object.

4. An information processing device according to claim 3, wherein the map generation unit divides the surrounding environment into a grid in areas where the detection rate of the object is highly accurate, and generates an occupancy grid map that describes the occupancy probability of the object in each grid.

5. An information processing device according to claim 1, wherein the map generation unit generates a region with low accuracy in detecting the object by integrating the point cloud data.

6. An information processing apparatus according to claim 1, further comprising a calculation unit that calculates the speed of the moving object based on the transmitted wave and the reflected wave, wherein the map generation unit generates the map based on the calculation result of the calculation unit.

7. An information processing device according to claim 6, wherein the calculation unit calculates the speed of the moving object using the RANSAC (Random Sample Consensus) method.

8. A radar device comprising: a transmitting antenna that transmits electromagnetic waves toward the surrounding environment of a moving object and a receiving antenna that receives reflected waves reflected by objects present in the surrounding environment of the moving object; a processing unit that generates point cloud data based on the reflected waves received by the receiving antenna; a determination unit that determines a driving scene based on the generated point cloud data; and a map generation unit that generates a map indicating the probability of the existence of the object and having regions with different accuracy of detection rate of the object based on the determination result of the determination unit.

9. An information processing method comprising: transmitting electromagnetic waves from a transmitting antenna toward the surrounding environment of a moving object; generating point cloud data based on reflected waves reflected by objects present in the surrounding environment of the moving object and received by a receiving antenna; determining a driving scene based on the generated point cloud data; and generating a map based on the determined driving scene, indicating the probability of the existence of the object and having regions with different accuracy of detection rate for the object.

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