Method and device for improving resolution of lidar, lidar

Abstract

The application discloses a method and device for improving resolution of a laser radar, and the laser radar has a plurality of actual channels, wherein one actual channel corresponds to one transmitting unit of a transmitting end and one detecting unit of a detecting end, the method comprises the following steps: determining at least one to-be-generated interpolation channel; for each to-be-generated interpolation channel, determining one or more associated channels in the plurality of actual channels which are related to the to-be-generated interpolation channel; determining the weight of the one or more associated channels relative to the to-be-generated interpolation channel; generating the waveform of the interpolation channel according to the waveform information of the one or more associated channels and the weight, and obtaining the point cloud data corresponding to the laser radar according to the waveform information of each actual channel and each interpolation channel. The application can effectively improve the resolution of the laser radar without increasing the hardware load of the existing laser radar.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, specifically to a method and apparatus for improving the resolution of a lidar, and also to a lidar. Background Technology

[0002] A lidar system is a radar system that uses laser beams to detect the position, velocity, and other characteristics of a target. Its working principle involves emitting a detection signal (laser beam) towards the target, then comparing the received signal (echo pulse signal) reflected back from the target with the emitted signal. After appropriate processing, information about the target can be obtained, such as its distance, azimuth, altitude, velocity, attitude, and even shape, thereby enabling target detection, tracking, and identification.

[0003] With the development of lidar technology, the requirements for its resolution are becoming increasingly stringent. Whether it's mechanically rotating lidar, MEMS (Micro-Electro-Mechanical System) lidar, flash array lidar, or OPA (Optical Parametric Amplification) lidar, achieving higher resolution is a crucial indicator for improving lidar performance. Currently, there are generally two ways to improve resolution. One is through hardware configuration, such as adding transceiver pairs and corresponding ADC (analog-to-digital converter) / TDC (time-to-digital converter) channels to meet the high-resolution requirement. This method not only consumes significant computing resources but also greatly increases device power consumption. Furthermore, adding transceiver pairs increases the possibility of crosstalk between channels, leading to reduced detection accuracy. The other method is to process the point cloud information output by the lidar using techniques such as deep convolutional neural networks to calculate new point clouds at certain locations, thereby improving resolution.

[0004] However, the problem with directly processing neural networks based on point cloud information is that the new point cloud obtained from point cloud computing does not have a direct echo pulse signal to rely on, so its accuracy is not high enough. Summary of the Invention

[0005] This application provides a method and apparatus for improving the resolution of a lidar, which effectively improves the resolution of the lidar without increasing the hardware load of the existing lidar.

[0006] One embodiment of this application provides a lidar that can have higher resolution compared to lidars with the same hardware architecture.

[0007] Therefore, the embodiments of the present invention provide the following technical solutions:

[0008] A method for improving the resolution of a lidar, wherein the lidar has multiple actual channels, wherein each actual channel corresponds to a transmitting unit at a transmitting end and a detecting unit at a detecting end, the method comprising:

[0009] Identify at least one interpolation channel to be generated;

[0010] For each interpolation channel to be generated, one or more associated channels related to the interpolation channel to be generated are determined from among the plurality of actual channels;

[0011] Determine the weights of the one or more associated channels relative to the interpolation channels to be generated;

[0012] The waveform of the interpolation channel is generated based on the waveform information and weights of the one or more associated channels, so as to obtain point cloud data corresponding to the lidar based on the obtained waveform information of each actual channel and each interpolation channel.

[0013] Optionally, the step of determining at least one interpolation channel to be generated further includes: determining at least one interpolation channel to be generated based on the required interpolation field of view range.

[0014] Optionally, at least one interpolation channel is distributed among all or some of the actual channels.

[0015] Optionally, the step of determining one or more associated channels among the plurality of actual channels that are related to the interpolation channel to be generated further includes: taking the actual channels whose distance from the interpolation channel is within a set range as the associated channels of the interpolation channel.

[0016] Optionally, the weights of the associated channels are determined according to any one or more of the following:

[0017] - The distance between the associated channel and the interpolation channel;

[0018] - Signal quality of the associated channel;

[0019] - The field of view corresponding to the associated channel.

[0020] Optionally, the transmitting unit and its corresponding receiving unit of the lidar are arranged in a two-dimensional layout.

[0021] Optionally, among the multiple associated channels corresponding to the interpolation channel to be generated, at least two actual channels are vertically adjacent, and at least two actual channels are horizontally adjacent.

[0022] Optionally, when the lidar uses multi-pulse coding, generating the waveform of the interpolation channel based on the waveform information and weight of the associated channel includes: generating the waveform of the interpolation channel based on the waveform information and weight of the first pulse received by the associated channel.

[0023] Optionally, the lidar emits signal light multiple times within one cycle; the method further includes: after each emission of the signal light, determining the point cloud data corresponding to each waveform information for this emission based on the waveform information of each actual channel and each interpolation channel; and determining a frame of point cloud data of the lidar based on all the point cloud data obtained within one cycle.

[0024] A device for improving the resolution of a lidar, the lidar having multiple practical channels, wherein each practical channel corresponds to a transmitting unit at a transmitting end and a detecting unit at a detecting end, the device comprising:

[0025] Interpolation channel determination module, used to determine at least one interpolation channel to be generated;

[0026] The associated channel determination module is used to determine one or more associated channels among the plurality of actual channels that are related to the interpolation channel to be generated for each interpolation channel to be generated;

[0027] The weight determination module is used to determine the weights of the one or more associated channels relative to the interpolation channels to be generated;

[0028] The interpolation channel generation module is used to generate the waveform of the interpolation channel based on the waveform information and weights of the one or more associated channels, so as to obtain point cloud data corresponding to the lidar based on the waveform information of each actual channel and each interpolation channel.

[0029] Optionally, the interpolation channel determination module is specifically used to determine at least one interpolation channel to be generated based on the required interpolation field of view range.

[0030] Optionally, at least one interpolation channel is distributed among all or some of the actual channels.

[0031] Optionally, the associated channel determination module is specifically used to use the actual channel whose distance from the interpolation channel is within a set range as the associated channel of the interpolation channel.

[0032] Optionally, the associated channel determination module determines the weight of the associated channel based on any one or more of the following:

[0033] - The distance between the associated channel and the interpolation channel;

[0034] - Signal quality of the associated channel;

[0035] - The field of view corresponding to the associated channel.

[0036] Optionally, the transmitting unit and its corresponding receiving unit of the lidar are arranged in a two-dimensional layout.

[0037] Optionally, among the multiple associated channels corresponding to the interpolation channel to be generated, at least two actual channels are vertically adjacent, and at least two actual channels are horizontally adjacent.

[0038] Optionally, the lidar employs multi-pulse coding; the interpolation channel generation module is specifically used to generate the waveform of the interpolation channel based on the waveform information of the first pulse received by the associated channel and its weight.

[0039] Optionally, the lidar emits signal light multiple times within one cycle; the device further includes: a first data determination module, used to determine the point cloud data corresponding to each waveform information for this emission based on the waveform information of each actual channel and each interpolation channel obtained after each emission of the signal light; and a second data determination module, used to determine one frame of point cloud data of the lidar based on all the point cloud data obtained within one cycle.

[0040] A lidar includes the aforementioned means for improving lidar resolution.

[0041] The method and apparatus for improving the resolution of a lidar provided in this invention are based on a hardware structure where one actual channel of the lidar corresponds to one transmitting unit at the transmitting end and one detecting unit at the detecting end. Without changing the hardware structure, interpolation is performed on the actual channels to generate interpolated channels. During interpolation, the interpolated channels are generated based on the waveform information and weights of one or more associated channels related to the interpolated channel to be generated from multiple actual channels. Thus, based on the obtained waveform information of each actual channel and each interpolated channel, point cloud data corresponding to the lidar is obtained. This effectively improves the resolution of the lidar without increasing the hardware load on existing lidars. In other words, a lidar including this apparatus can have a higher resolution compared to lidars with the same hardware architecture. Attached Figure Description

[0042] Figure 1 This is a flowchart of a method for improving lidar resolution according to an embodiment of the present invention;

[0043] Figure 2 This is an example of an interpolation channel in an embodiment of the present invention;

[0044] Figure 3This is another example of an interpolation channel in the embodiments of the present invention;

[0045] Figure 4 This is another example of an interpolation channel in the embodiments of the present invention;

[0046] Figure 5 This is another example of an interpolation channel in the embodiments of the present invention;

[0047] Figure 6 This is an example of a waveform for generating an interpolation channel in an embodiment of the present invention;

[0048] Figure 7 This is another example of generating the waveform of the interpolation channel in an embodiment of the present invention;

[0049] Figure 8 This is a schematic diagram of the interpolation channel in a two-dimensionally arranged lidar system according to an embodiment of the present invention;

[0050] Figure 9 This is another flowchart of a method for improving lidar resolution according to an embodiment of the present invention;

[0051] Figure 10 This is a structural block diagram of a device for improving the resolution of a lidar according to an embodiment of the present invention;

[0052] Figure 11 This is another structural block diagram of the device for improving lidar resolution according to an embodiment of the present invention. Detailed Implementation

[0053] To make the above-mentioned objectives, features and beneficial effects of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0054] To address the issues of increased hardware load and power consumption associated with adding hardware channels (i.e., increasing transceiver pairs and other hardware configurations within each channel) in existing technologies that require high resolution, this invention provides a method and apparatus for improving the resolution of a lidar system. Based on a hardware structure where one actual lidar channel corresponds to one transmitting unit at the transmitting end and one detecting unit at the detecting end, the method interpolates the actual channels to generate interpolated channels without altering the hardware structure. Furthermore, during interpolation, the interpolated channels are generated based on the waveform information and weights of one or more associated channels related to the interpolated channel from among the multiple actual channels. This effectively improves the resolution of the lidar system without increasing its hardware load.

[0055] In this embodiment of the invention, the lidar has multiple actual channels, wherein each actual channel corresponds to a transmitting unit at the transmitting end and a detecting unit at the detecting end.

[0056] like Figure 1 The diagram shown is a flowchart of a method for improving the resolution of a lidar system according to an embodiment of the present invention, including the following steps:

[0057] Step 101: Determine at least one interpolation channel to be generated.

[0058] Specifically, based on the required interpolation field of view range, multiple actual channels for generating at least one interpolation channel to be generated can be determined, and based on the resolution level to be improved, the number of interpolation channels between every two adjacent actual channels can be determined.

[0059] A lidar system has a horizontal field of view and a vertical field of view. The horizontal and vertical field of view angles indicate the scanning range of the lidar in the horizontal and vertical directions, respectively. For example, in a mechanically rotating lidar, where both the transmitting and receiving modules are driven by a rotating mechanism, the horizontal field of view is typically a full circle, i.e., 360 degrees. The vertical field of view is usually determined by the transmitting unit within the lidar's transmitting module. The vertical field of view is the sum of the upward and downward scanning angles. For example, a 64-line lidar has an upward scanning angle of 15° and a downward scanning angle of 25°, resulting in a vertical field of view of 40°. Conversely, for lidar with fixed transmitting and receiving modules and a scanning module for scanning the field of view, the horizontal and vertical field of view angles are typically determined by the scanning range of the scanning module.

[0060] That is, when performing interpolation according to the present invention, the portion or the entire field of view that needs to be expanded is first determined. For example, when interpolation is required for the entire field of view and the resolution is to be doubled, it can be determined that there is an interpolation channel to be generated between every two adjacent actual channels; or, for example, when the requirement includes increasing the resolution of the field of view within ±5° of the vertical field of view to three times, it is determined that two interpolation channels will be uniformly added between every two adjacent actual channels within that field of view.

[0061] Of course, those skilled in the art will understand that a certain range within the vertical field of view can be selected as the required interpolation field of view range based on information such as the size and height of the target to be detected, and at least one interpolation channel to be generated can be determined within this field of view range.

[0062] In addition, one or more interpolation channels may be distributed among all or some of the actual channels, as needed.

[0063] Continuing with the 64-line LiDAR example mentioned earlier, ideally, assuming a uniform laser beam distribution, the angular resolution of this 64-line LiDAR would be 40° / 64 = 0.625°. However, in some applications, the LiDAR beam is not vertically uniformly distributed. For example, in autonomous driving applications using LiDAR for ground vehicle detection, to both detect obstacles and focus the laser beam on the vehicle of interest, the beam distribution is typically denser in the center and sparser on both sides.

[0064] Therefore, in practical applications, multiple interpolation channels can be determined within the required interpolation field of view. These interpolation channels can be uniformly distributed among the actual channels or non-uniformly distributed among the actual channels. Moreover, there may be no interpolation channels or one or more interpolation channels between two actual channels. This embodiment of the invention does not limit this.

[0065] The following example illustrates how to determine the interpolation channel.

[0066] For example, when an interpolation channel is interpolated between every two actual channels, such as... Figure 2 As shown, interpolation channel I_CH1 is generated between actual channel CH1 and actual channel CH2, interpolation channel I_CH2 is generated between actual channel CH2 and actual channel CH3, and so on. If there are N actual channels, the total number of channels after interpolation (i.e., the number of actual channels + the number of interpolated channels) is 2N-1, which is basically twice the original number of actual channels.

[0067] For example, two interpolated channels can be generated between two actual channels. For instance... Figure 3 As shown, interpolation channels I_CH1 and I_CH2 are generated between actual channels CH1 and CH2; interpolation channels I_CH3 and I_CH4 are generated between actual channels CH2 and CH3; interpolation channels I_CH5 and I_CH6 are generated between actual channels CH3 and CH4, and so on. If there are N actual channels, the total number of channels after interpolation is 3N-2, which is basically three times the original number of actual channels.

[0068] For example, one or more interpolated channels can be interpolated between two actual channels. For instance... Figure 4 As shown, interpolation channel I_CH1 is generated between actual channel CH1 and actual channel CH2; interpolation channel I_CH2 is generated between actual channel CH2 and actual channel CH3; and interpolation channels I_CH3 and I_CH4 are generated between actual channel CH3 and actual channel CH4.

[0069] For example, interpolation can also be performed only near certain actual channels, such as... Figure 5 As shown, interpolation is performed only on the actual channels within a 5° range above and below the center of the vertical field of view to improve the resolution of this field of view area.

[0070] Step 102: For each interpolation channel to be generated, determine one or more associated channels among the plurality of actual channels that are related to the interpolation channel to be generated.

[0071] Specifically, for each interpolation channel to be generated, all actual channels can be used as associated channels of that interpolation channel. Of course, to reduce the computational load during subsequent interpolation, only actual channels whose distance from the interpolation channel is within a set range can be used as associated channels of the interpolation channel; this embodiment of the invention does not limit this.

[0072] Step 103: Determine the weights of the one or more associated channels relative to the interpolation channels to be generated.

[0073] As mentioned earlier, actual channels within a set distance from the interpolation channel can be considered as associated channels of the interpolation channel. Since different actual channels will have different effects on the interpolation channel, these effects need to be considered when performing interpolation calculations. To facilitate subsequent calculations, these effects can be represented as weights of the associated channels; that is, a corresponding weight is set for each associated channel of the interpolation channel.

[0074] In practical applications, the weights of the associated channels can be determined based on, but not limited to, any one or more of the following:

[0075] - The distance between the associated channel and the interpolation channel, for example, the closer the distance, the greater the distance weight;

[0076] - The signal quality of the associated channel, for example, the better the signal quality, the greater the signal weight;

[0077] - The field of view corresponding to the associated channel, such as whether the field of view is within the region of interest (ROI). When the field of view is within the ROI, its field of view weight is larger, and vice versa.

[0078] For example, when interpolating an interpolation channel between two actual channels CH1 and CH2, these two adjacent actual channels are used as associated channels of the interpolation channel, and the weight of each associated channel is 0.5.

[0079] When interpolating multiple interpolation channels between two actual channels, the weights of each interpolation channel can be adjusted according to its position relative to the two actual channels on either side. For example, if interpolation channels I_CH1 and I_CH2 need to be interpolated between actual channels CH1 and CH2, assuming that the two interpolation channels I_CH1 and I_CH2 are evenly distributed between actual channels CH1 and CH2, and that actual channels CH1 and CH2 are used as associated channels of interpolation channels I_CH1 and I_CH2, then: for interpolation channel I_CH1, the weight of its associated channel I_CH1 is 2 / 3, and the weight of its associated channel I_CH2 is 1 / 3; while for interpolation channel I_CH2, the weight of its associated channel I_CH1 is 1 / 3, and the weight of its associated channel I_CH2 is 2 / 3.

[0080] When interpolating multiple interpolated channels between two actual channels, the weights of each interpolated channel can be determined based on its position relative to the actual channels on both sides and the signal quality of the actual channels. For example, the channel with the best signal quality can be assigned a weight of 1, its directly adjacent channel 0.9, its second adjacent channel 0.8, and so on.

[0081] When using multiple types of weights to determine the total weight of each associated channel, the proportion of each type of weight in the total weight can be determined as needed, and then the total weight of each associated channel relative to the interpolation channel can be determined.

[0082] For example, when considering the aforementioned distance weight, signal weight, and field-of-view weight, each of these three types of weights can account for 1 / 3 of the total weight; as another example, when only distance weight and signal weight are considered, each of these two types of weights can account for 1 / 2 of the total weight; and as yet another example, when more consideration needs to be given to the impact of signal quality on the interpolation channel, the distance weight can be set to 1 / 3 of the total weight, and the signal weight to 2 / 3, and so on. Those skilled in the art can set the proportion of each category of weight in the total weight according to the actual situation and needs to obtain the interpolation channel with optimal quality, which will not be elaborated further here.

[0083] Step 104: Generate the waveform of the interpolation channel based on the waveform information and weights of the one or more associated channels, so as to obtain point cloud data corresponding to the lidar based on the obtained waveform information of each actual channel and each interpolation channel.

[0084] For the existing N actual channels, the signal of each channel is defined as Wave(N). Wave(N) is used to represent the waveform information obtained by the actual channel. Specifically, it can include the following different types of information:

[0085] 1) The specific sampling waveform; wherein, the sampling waveform can be characterized by multiple sampling points, or by a curve obtained by fitting the sampling points.

[0086] 2) Commonly used waveform pulse related information, such as: leading edge point, pulse width, peak value, etc.

[0087] When performing interpolation, the waveform of the interpolation channel is obtained by combining the waveform information of the associated channels related to the interpolation channel with the weights of each associated channel.

[0088] Let In_Wave(M) represent the Mth interpolation channel. As mentioned earlier, for each interpolation channel to be generated, all actual channels can be used as associated channels of that interpolation channel. Therefore, the waveform of the interpolation channel can be obtained according to the following general signal synthesis formula:

[0089] In_Wave(M) = A M，1 ×Wave(1)+A M，2 ×Wave(2)+……+A M,N ×Wave(N);

[0090] Among them, A M，i (i = 1, 2, 3, ..., N) represents the weight information of each actual channel, used to characterize the influence of each actual detection channel relative to In_Wave(M), A M，1 +A M，2 +……+A M,N =1.

[0091] According to this general formula, the weight of the actual channel that is not associated with the interpolation channel, i.e., the non-associated channel of the interpolation channel, can be set to 0.

[0092] Of course, during the calculation, only the waveform information of the associated channel of the interpolation channel and the weight of the associated channel can be selected for calculation, and this embodiment of the invention does not limit this.

[0093] for example, Figure 6 The interpolation method shown is used to obtain the waveform signal of channel CH1.5, i.e., interpolated channel 1_CH1, based on the waveform information of actual channels CH1 and CH2. The calculation formula is as follows:

[0094] Wave(CH1.5)=A 1.5,1 ×Wave(CH1)+A 1.5,2 ×Wave(CH2);

[0095] When channel 1.5 is located between channels CH1 and CH2, we can choose A. 1.5,1 =A 1.5,2 =0.5.

[0096] For example, the one mentioned earlier Figure 3 The interpolation method shown requires interpolating interpolation channels I_CH1 and I_CH2 between actual channels CH1 and CH2. The interpolation channels I_CH1 and I_CH2 are obtained based on the waveform information of actual channels CH1 and CH2, calculated using the following formula:

[0097] In_Wave(I_CH1)=2 / 3*Wave(CH1)+1 / 3*Wave(CH2);

[0098] In_Wave(I_CH2)=1 / 3*Wave(CH1)+2 / 3*Wave(CH2).

[0099] For example, Figure 7 The interpolation method shown requires interpolation to be performed near the actual channel P, with five interpolation channels extended in each of the two adjacent directions. The waveform calculation for each interpolation channel is as follows:

[0100] In_Wave(P-5)=A P-5,1 *Wave(P-5)+A N+1,2 *Wave(P-4);

[0101] In_Wave(P-4)=A P-4,1 *Wave(P-4)+A N+2,2 *Wave(P-3);

[0102] ...

[0103] In_Wave(P+5)=A P+4,1 *Wave(P+4)+A P+5,2 *Wave(P+5).

[0104] For example, suppose the signal weights of the actual channels (wl and wr) on both sides of the interpolation channel Wx are 0.8 and 0.7 respectively, and the distances between the interpolation channel Wx and the two actual channels are 1 / 3 and 1 / 3 respectively; where the distance weight accounts for 1 / 2 of the total weight, and the signal weight accounts for 1 / 2 of the total weight. Taking the actual channels wl and wr as the associated channels of the interpolation channel Wx, then: for the interpolation channel Wx, the weight of its associated channel wl is 2 / 3, and the weight of its associated channel I_CH2 is 1 / 3; while for the interpolation channel I_CH2, the weight of its associated channel I_CH1 is 1 / 3, and the weight of its associated channel I_CH2 is 2 / 3. The waveform of the interpolation channel Wx is then calculated as follows:

[0105] It should be noted that, when considering multiple types of weights, the calculation of the interpolation channel waveform based on the waveform information and weights of the associated channel can refer to the calculation method of the interpolation channel Wx mentioned above, and will not be illustrated in detail here.

[0106] The method for improving lidar resolution provided in this invention is based on a hardware structure where one actual channel of the lidar corresponds to one transmitting unit at the transmitting end and one detecting unit at the detecting end. Without altering the hardware structure, interpolation is performed on the actual channels to generate interpolated channels. During interpolation, the interpolated channels are generated based on the waveform information and weights of one or more associated channels related to the interpolated channel from among the multiple actual channels. Thus, based on the obtained waveform information of each actual channel and each interpolated channel, point cloud data corresponding to the lidar is obtained. This effectively improves the resolution of the lidar without increasing the hardware load, meaning that the lidar including this device can have a higher resolution compared to lidars with the same hardware architecture.

[0107] It should be noted that in practical applications, some lidar systems have different gating times for different detection channels (i.e., actual channels). In such cases, when determining the associated channels and their weights for each interpolation channel, the adjacent channels of the interpolation channel can be adjusted accordingly based on the gating time of each actual channel. That is, when the gating times of the multiple actual channels are different, for the interpolation channel to be generated, different associated channels are selected at different gating times to generate the interpolation channel. For example, to generate an interpolation channel corresponding to a certain field of view, in gating mode 1, the waveform of the interpolation channel can be generated from the waveform information of actual channels CH5 and CH7; in gating mode 2, the waveform of the interpolation channel can be generated from the waveform information of actual channels CH4 and CH6, and so on. Furthermore, the actual channels in the two modes may use different weight values.

[0108] Furthermore, in some lidar systems, the laser signal may employ multi-pulse coding. In the case of multi-pulse coding, since the timing of the arrival of the second pulse is not easily aligned, the waveform of the interpolation channel can also be generated based on the waveform information of the first pulse received by the associated channel and its weight.

[0109] Furthermore, in some lidar systems, both the transmitting unit and its corresponding receiving unit are arranged in a two-dimensional layout. For example... Figure 8 As shown, in this case, interpolation can be performed on the two-dimensional receiving channel. Among the multiple associated channels corresponding to the interpolation channel to be generated, at least two actual channels are vertically adjacent, and at least two actual channels are horizontally adjacent. Figure 8The interpolation channels in the example are I_CH12, I_CH22, I_CH13, and I_CH23.

[0110] For this type of two-dimensional channel, its interpolation channel can be obtained according to the following formula:

[0111] In_Wave(i,j)=A i,j-1 *Wave(i,j-1)+A i+1,j-1 *Wave(i+1,j-1)+A i+1,j *Wave(i+1,j)+A i+1,j *Wave(i+1,j);

[0112] Where i and j represent the horizontal and vertical arrangement numbers of the actual channels, respectively.

[0113] like Figure 9 The diagram shown is another flowchart of a method for improving lidar resolution according to an embodiment of the present invention.

[0114] In this embodiment, the lidar emits signal light multiple times within one cycle, and the method includes the following steps:

[0115] Step 901: Determine at least one interpolation channel to be generated.

[0116] Step 902: For each interpolation channel to be generated, determine one or more associated channels among the plurality of actual channels that are related to the interpolation channel to be generated.

[0117] Step 903: Determine the weights of the one or more associated channels relative to the interpolation channels to be generated.

[0118] Step 904: Generate the waveform of the interpolation channel based on the waveform information and weights of the one or more associated channels.

[0119] Steps 901 to 904 above are the same as those mentioned earlier. Figure 1 Steps 101 to 104 are the same and will not be repeated here.

[0120] Step 905: After each transmission of signal light, determine the point cloud data corresponding to each transmission based on the waveform information of each actual channel and each interpolation channel.

[0121] Step 906: Based on all the point cloud data obtained within one cycle, determine one frame of point cloud data for the lidar.

[0122] The point cloud data can be used as the output of the lidar. Compared with point cloud data that only outputs the actual channels, point cloud data based on interpolated channels and actual channel outputs can give the lidar higher resolution and effectively improve lidar performance without increasing hardware load.

[0123] Accordingly, embodiments of the present invention also provide a device for improving the resolution of lidar, such as... Figure 10 The diagram shown is a structural block diagram of the device.

[0124] In this embodiment, the device includes the following modules:

[0125] Interpolation channel determination module 11 is used to determine at least one interpolation channel to be generated;

[0126] The associated channel determination module 12 is used to determine one or more associated channels among the plurality of actual channels that are related to the interpolation channel to be generated for each interpolation channel to be generated;

[0127] The weight determination module 13 is used to determine the weight of the one or more associated channels relative to the interpolation channels to be generated;

[0128] The interpolation channel generation module 14 is used to generate the waveform information of the interpolation channel based on the waveform information and weights of the one or more associated channels, so as to obtain point cloud data corresponding to the lidar based on the obtained waveform information of each actual channel and each interpolation channel.

[0129] Specifically, the interpolation channel determination module 11 can determine at least one interpolation channel to be generated based on the required interpolation field of view range. Furthermore, at least one interpolation channel can be distributed among all or some of the actual channels.

[0130] Specifically, the associated channel determination module 12 can use actual channels whose distance from the interpolation channel is within a set range as the associated channels of the interpolation channel. Of course, there can be various factors influencing the weight of the associated channel; for example, the weight of the associated channel can be determined based on any one or more of the following:

[0131] - The distance between the associated channel and the interpolation channel;

[0132] - Signal quality of the associated channel;

[0133] - The field of view corresponding to the associated channel.

[0134] The specific calculation method for the interpolation channel generation module 14 to generate the waveform of the interpolation channel based on the waveform information and weights of one or more associated channels has been described in detail in the preceding description of the method of the present invention, and will not be repeated here.

[0135] The device for improving lidar resolution provided in this invention is based on a hardware structure where one actual channel of the lidar corresponds to one transmitting unit at the transmitting end and one detecting unit at the detecting end. Without altering the hardware structure, it interpolates the actual channels to generate interpolated channels. During interpolation, it generates interpolated channels based on waveform information and weights of one or more associated channels related to the interpolated channel from among the multiple actual channels. Thus, based on the obtained waveform information of each actual channel and each interpolated channel, point cloud data corresponding to the lidar is obtained. This effectively improves the resolution of the lidar without increasing the hardware load, meaning that a lidar including this device can have a higher resolution compared to lidars with the same hardware architecture.

[0136] It should be noted that in some lidar systems, the lidar transmitting unit and its corresponding receiving unit can be arranged in a two-dimensional configuration. Accordingly, among the multiple associated channels corresponding to the interpolation channel to be generated, at least two actual channels are vertically adjacent, and at least two actual channels are horizontally adjacent.

[0137] In some non-limiting examples, the lidar may employ multi-pulse coding. In the case of multi-pulse coding, since the timing of the arrival of the second pulse is difficult to align, the interpolation channel generation module 14 may also generate the waveform of the interpolation channel based on the waveform information of the first pulse received by the associated channel and its weight.

[0138] In some non-limiting examples, the lidar can emit signal light multiple times within one cycle. Accordingly, such as Figure 11 The diagram shows another structural block diagram of a device for improving lidar resolution according to an embodiment of the present invention.

[0139] and Figure 10 The difference in the illustrated embodiment is that, in this embodiment, the device further includes the following modules:

[0140] The first data determination module 15 is used to determine the point cloud data corresponding to each waveform information for this transmission based on the waveform information of each actual channel and each interpolation channel obtained after each transmission of the signal light.

[0141] The second data determination module 16 is used to determine a frame of point cloud data of the lidar based on all point cloud data obtained within a cycle.

[0142] It should be noted that the point cloud data can be used as the output of the lidar. Compared with point cloud data that only has actual channel output, point cloud data based on interpolated channels and actual channel output can enable the lidar to have higher resolution, effectively improving lidar performance without increasing hardware load.

[0143] A lidar equipped with the aforementioned device for improving lidar resolution can achieve higher resolution and scanning performance compared to existing lidars with the same number of channels.

[0144] It should be noted that the lidar mentioned in the embodiments of the present invention can be lidar of any structural type, such as mechanical rotating lidar, MEMS (Micro-Electro-Mechanical System) lidar, flash area array lidar, or OPA (Optical Parametric Amplification) lidar, etc. The embodiments of the present invention do not limit this.

[0145] In specific implementation, the modules / units included in the various devices and products described in the above embodiments can be software modules / units, hardware modules / units, or a combination of both.

[0146] For example, for various devices and products applied to or integrated into a chip, each module / unit can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs that run on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits; for various devices and products applied to or integrated into a chip module, each module / unit can be implemented using hardware methods such as circuits, and different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The components can be implemented using software programs that run on the processor integrated within the chip module. The remaining (if any) modules / units can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into the terminal, each of its components / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or in different components within the terminal. Alternatively, at least some modules / units can be implemented using software programs that run on the processor integrated within the terminal, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits.

[0147] This invention also provides a computer-readable storage medium, which is a non-volatile or non-transient storage medium, storing a computer program thereon. The computer program is executed by a processor. Figure 1 or Figure 9 The steps of the method provided in the corresponding embodiment.

[0148] This invention also provides another device for improving the resolution of lidar, including a memory and a processor. The memory stores a computer program that can run on the processor, and the processor executes the above-described... Figure 1 or Figure 9 The steps of the method provided in the corresponding embodiment.

[0149] This invention also provides an electronic device, including a memory and a processor. The memory stores a computer program that can run on the processor, and when the processor runs the computer program, it performs the above-described... Figure 1 or Figure 9 The steps of the method provided in the corresponding embodiment.

[0150] In this embodiment of the invention, the processor can be a central processing unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0151] It should also be understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0152] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article indicates that the preceding and following related objects have an "or" relationship.

[0153] In the embodiments of this application, "multiple" refers to two or more.

[0154] The descriptions of "first," "second," etc., appearing in the embodiments of this application are for illustrative purposes and to distinguish the objects being described. They have no order and do not indicate any special limitation on the number of devices in the embodiments of this application, nor do they constitute any limitation on the embodiments of this application.

[0155] In this application, the term "connection" refers to various connection methods, such as direct connection or indirect connection, to achieve communication between devices. This application does not impose any limitations on this.

[0156] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A method for improving the resolution of a lidar, wherein the lidar has multiple actual channels, A physical channel corresponds to a transmitting unit at the transmitting end and a detecting unit at the detecting end, characterized in that the method includes: Identify at least one interpolation channel to be generated; For each interpolation channel to be generated, one or more associated channels related to the interpolation channel to be generated are determined from among the plurality of actual channels; Determine the weights of the one or more associated channels relative to the interpolation channels to be generated; The waveform of the interpolation channel is generated based on the waveform information and weights of the one or more associated channels, so as to obtain point cloud data corresponding to the lidar based on the obtained waveform information of each actual channel and each interpolation channel.

2. The method according to claim 1, characterized in that, The step of determining at least one interpolation channel to be generated further includes: Determine at least one interpolation channel to be generated based on the required interpolation field of view range.

3. The method according to claim 1, characterized in that, At least one interpolation channel is distributed among all or some of the actual channels.

4. The method according to claim 1, characterized in that, The step of determining one or more associated channels among the plurality of actual channels that are related to the interpolation channel to be generated further includes: The actual channel whose distance from the interpolation channel is within a set range is used as the associated channel of the interpolation channel.

5. The method according to claim 1, characterized in that, The weights of the associated channels are determined according to one or more of the following: - The distance between the associated channel and the interpolation channel; - Signal quality of the associated channel; - The field of view corresponding to the associated channel.

6. The method according to claim 1, characterized in that, The transmitting unit and its corresponding receiving unit of the lidar are both arranged in a two-dimensional layout.

7. The method according to claim 6, characterized in that, Among the multiple associated channels corresponding to the interpolation channel to be generated, at least two actual channels are vertically adjacent, and at least two actual channels are horizontally adjacent.

8. The method according to any one of claims 1 to 6, characterized in that, When the lidar employs multi-pulse coding, generating the waveform of the interpolation channel based on the waveform information and weights of the associated channel includes: The waveform of the interpolation channel is generated based on the first pulse waveform information received by the associated channel and its weight.

9. The method according to any one of claims 1 to 6, characterized in that, The lidar emits signal light multiple times within one cycle; the method further includes: After each transmission of the signal light, the point cloud data corresponding to this transmission is determined based on the waveform information of each actual channel and each interpolation channel. Based on all point cloud data obtained within a cycle, determine a frame of point cloud data for the lidar.

10. An apparatus for improving the resolution of a lidar, wherein the lidar has multiple actual channels, A physical channel corresponds to a transmitting unit at the transmitting end and a detecting unit at the detecting end, characterized in that the device comprises: Interpolation channel determination module, used to determine at least one interpolation channel to be generated; The associated channel determination module is used to determine one or more associated channels among the plurality of actual channels that are related to the interpolation channel to be generated for each interpolation channel to be generated; The weight determination module is used to determine the weights of the one or more associated channels relative to the interpolation channels to be generated; The interpolation channel generation module is used to generate the waveform of the interpolation channel based on the waveform information and weights of the one or more associated channels, so as to obtain point cloud data corresponding to the lidar based on the waveform information of each actual channel and each interpolation channel.

11. The apparatus according to claim 10, characterized in that, The interpolation channel determination module is specifically used to determine at least one interpolation channel to be generated based on the required interpolation field of view range.

12. The apparatus according to claim 10, characterized in that, At least one interpolation channel is distributed among all or some of the actual channels.

13. The apparatus according to claim 10, characterized in that, The associated channel determination module is specifically used to identify actual channels whose distance from the interpolation channel is within a set range as associated channels of the interpolation channel.

14. The apparatus according to claim 10, characterized in that, The associated channel determination module determines the weight of the associated channel based on any one or more of the following: - The distance between the associated channel and the interpolation channel; - Signal quality of the associated channel; - The field of view corresponding to the associated channel.

15. The apparatus according to claim 10, characterized in that, The transmitting unit and its corresponding receiving unit of the lidar are both arranged in a two-dimensional layout.

16. The apparatus according to claim 15, characterized in that, Among the multiple associated channels corresponding to the interpolation channel to be generated, at least two actual channels are vertically adjacent, and at least two actual channels are horizontally adjacent.

17. The apparatus according to any one of claims 10 to 16, characterized in that, The lidar uses multi-pulse coding; The interpolation channel generation module is specifically used to generate the waveform of the interpolation channel based on the first pulse waveform information received by the associated channel and its weight.

18. The apparatus according to any one of claims 10 to 16, characterized in that, The lidar emits signal light multiple times within one cycle; the device also includes: The first data determination module is used to determine the point cloud data corresponding to each waveform information for this transmission based on the waveform information of each actual channel and each interpolation channel obtained after each transmission of the signal light. The second data determination module is used to determine a frame of point cloud data for the lidar based on all point cloud data obtained within a cycle.

19. A lidar, comprising means for improving lidar resolution as described in any one of claims 10 to 18.

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